{"BioData Catalyst":[{"open_access-1000Genomes":{"gen3_discovery":{"authz":"/programs/open_access/projects/1000Genomes","tags":[{"name":"Genotype","category":"Data Type"},{"name":"Clinical Phenotype","category":"Data Type"}],"_unique_id":"open_access-1000Genomes","study_id":"open_access-1000Genomes","study_description":"high_coverage_2019_Public","full_name":"","short_name":"","commons":"BioData Catalyst","study_url":"https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=..","_subjects_count":3202,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs000007.v31.p12.c1":{"gen3_discovery":{"authz":null,"tags":null,"_unique_id":"phs000007.v31.p12.c1","study_id":"phs000007.v31.p12.c1","study_description":null,"full_name":null,"short_name":null,"commons":"BioData Catalyst","study_url":null,"_subjects_count":0,"__manifest":null,"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs000007.v31.p12.c2":{"gen3_discovery":{"authz":null,"tags":null,"_unique_id":"phs000007.v31.p12.c2","study_id":"phs000007.v31.p12.c2","study_description":null,"full_name":null,"short_name":null,"commons":"BioData Catalyst","study_url":null,"_subjects_count":0,"__manifest":null,"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs000007.v34.p15.c1":{"gen3_discovery":{"authz":null,"tags":null,"_unique_id":"phs000007.v34.p15.c1","study_id":"phs000007.v34.p15.c1","study_description":null,"full_name":null,"short_name":null,"commons":"BioData Catalyst","study_url":null,"_subjects_count":0,"__manifest":null,"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs000007.v34.p15.c2":{"gen3_discovery":{"authz":null,"tags":null,"_unique_id":"phs000007.v34.p15.c2","study_id":"phs000007.v34.p15.c2","study_description":null,"full_name":null,"short_name":null,"commons":"BioData Catalyst","study_url":null,"_subjects_count":0,"__manifest":null,"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs000007.v35.p16.c1":{"gen3_discovery":{"authz":"/programs/parent/projects/FHS_HMB-IRB-MDS_","tags":[],"_unique_id":"phs000007.v35.p16.c1","study_id":"phs000007.v35.p16.c1","study_description":"See Grouping of Framingham Phenotype Datasets Startup of Framingham Heart Study. Cardiovascular disease (CVD) is the leading cause of death and serious illness in the United States. In 1948, the Framingham Heart Study (FHS) -- under the direction of the National Heart Institute (now known as the National Heart, Lung, and Blood Institute, NHLBI) -- embarked on a novel and ambitious project in health research. At the time, little was known about the general causes of heart disease and stroke, but the death rates for CVD had been increasing steadily since the beginning of the century and had become an American epidemic. The objective of the FHS was to identify the common factors or characteristics that contribute to CVD by following its development over a long period of time in a large group of participants who had not yet developed overt symptoms of CVD or suffered a heart attack or stroke. Design of Framingham Heart Study. In 1948, the researchers recruited 5,209 men and women between the ages of 30 and 62 from the town of Framingham, Massachusetts, and began the first round of extensive physical examinations and lifestyle interviews that they would later analyze for common patterns related to CVD development. Since 1948, the subjects have returned to the study every two years for an examination consisting of a detailed medical history, physical examination, and laboratory tests, and in 1971, the study enrolled a second-generation cohort -- 5,124 of the original participants' adult children and their spouses -- to participate in similar examinations. The second examination of the Offspring cohort occurred eight years after the first examination, and subsequent examinations have occurred approximately every four years thereafter. In April 2002 the Study entered a new phase: the enrollment of a third generation of participants, the grandchildren of the original cohort. The first examination of the Third Generation Study was completed in July 2005 and involved 4,095 participants. Thus, the FHS has evolved into a prospective, community-based, three generation family study. The FHS is a joint project of the National Heart, Lung and Blood Institute and Boston University. Research Areas in the Framingham Heart Study. Over the years, careful monitoring of the FHS population has led to the identification of the major CVD risk factors -- high blood pressure, high blood cholesterol, smoking, obesity, diabetes, and physical inactivity -- as well as a great deal of valuable information on the effects of related factors such as blood triglyceride and HDL cholesterol levels, age, gender, and psychosocial issues. Risk factors have been identified for the major components of CVD, including coronary heart disease, stroke, intermittent claudication, and heart failure. It is also clear from research in the FHS and other studies that substantial subclinical vascular disease occurs in the blood vessels, heart and brain that precedes clinical CVD. With recent advances in technology, the FHS has enhanced its research capabilities and capitalized on its inherent resources by the conduct of high resolution imaging to detect and quantify subclinical vascular disease in the major blood vessels, heart and brain. These studies have included ultrasound studies of the heart (echocardiography) and carotid arteries, computed tomography studies of the heart and aorta, and magnetic resonance imaging studies of the brain, heart, and aorta. Although the Framingham cohort is primarily white, the importance of the major CVD risk factors identified in this group have been shown in other studies to apply almost universally among racial and ethnic groups, even though the patterns of distribution may vary from group to group. In the past half century, the Study has produced approximately 1,200 articles in leading medical journals. The concept of CVD risk factors has become an integral part of the modern medical curriculum and has led to the development of effective treatment and preventive strategies in clinical practice. In addition to research studies focused on risk factors, subclinical CVD and clinically apparent CVD, Framingham investigators have also collaborated with leading researchers from around the country and throughout the world on projects involving some of the major chronic illnesses in men and women, including dementia, osteoporosis and arthritis, nutritional deficiencies, eye diseases, hearing disorders, and chronic obstructive lung diseases. Genetic Research in the Framingham Heart Study. While pursuing the Study's established research goals, the NHLBI and the Framingham investigators has expanded its research mission into the study of genetic factors underlying CVD and other disorders. Over the past two decades, DNA has been collected from blood samples and from immortalized cell lines obtained from Original Cohort participants, members of the Offspring Cohort and the Third Generation Cohort. Several large-scale genotyping projects have been conducted in the past decade. Genome-wide linkage analysis has been conducted using genotypes of approximately 400 microsatellite markers that have been completed in over 9,300 subjects in all three generations. Analyses using microsatellite markers completed in the original cohort and offspring cohorts have resulted in over 100 publications, including many publications from the Genetics Analysis Workshop 13. Several other recent collaborative projects have completed thousands of SNP genotypes for candidate gene regions in subsets of FHS subjects with available DNA. These projects include the Cardiogenomics Program of the NHLBI's Programs for Genomics Applications, the genotyping of ~3000 SNPs in inflammation genes, and the completion of a genome-wide scan of 100,000 SNPs using the Affymetrix 100K Genechip. Framingham Cohort Phenotype Data. The phenotype database contains a vast array of phenotype information available in all three generations. These will include the quantitative measures of the major risk factors such as systolic blood pressure, total and HDL cholesterol, fasting glucose, and cigarette use, as well as anthropomorphic measures such as body mass index, biomarkers such as fibrinogen and CRP, and electrocardiography measures such as the QT interval. Many of these measures have been collected repeatedly in the original and offspring cohorts. Also included in the SHARe database will be an array of recently collected biomarkers, subclinical disease imaging measures, clinical CVD outcomes as well as an array of ancillary studies. The phenotype data is located here in the top-level study phs000007 Framingham Cohort. To view the phenotype variables collected from the Framingham Cohort, please click on the \"Variables\" tab above. The Framingham Cohort is utilized in the following dbGaP substudies. To view genotypes, analysis, expression data, other molecular data, and derived variables collected in these substudies, please click on the following substudies below or in the \"Substudies\" section of this top-level study page phs000007 Framingham Cohort. phs000342 Framingham SHARe phs000282 Framingham CARe phs000363 Framingham SABRe phs000307 Framingham Medical Resequencing phs000401 Framingham ESP Heart-GO phs000651 Framingham CHARGE-S phs000724 Framingham DNA Methylation phs001610 Framingham T2D-GENES phs002558 Framingham ADSP phs002559 Framingham BRIDGET phs002560 Framingham Cholesterol phs002611 Framingham Post-Mortem Brain Tissue phs002938 Framingham Molecular QTL The unflagging commitment of the research participants in the NHLBI FHS has made more than a half century of research success possible. For decades, the FHS has made its data and DNA widely available to qualified investigators throughout the world through the Limited Access Datasets and the FHS DNA Committee, and the SHARe database will continue that tradition by allowing access to qualified investigators who agree to the requirements of data access. With the SHARe database, we continue with an ambitious research agenda and look forward to new discoveries in the decades to come. Study Weblinks: The Framingham Heart Study NHLBI Framingham Heart Study Study Design: Prospective Longitudinal Cohort Study Type: Longitudinal Total number of consented subjects: 15089 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Framingham Cohort","short_name":"FHS_HMB-IRB-MDS_","commons":"BioData Catalyst","study_url":"","_subjects_count":13139,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs000007.v35.p16.c2":{"gen3_discovery":{"authz":"/programs/parent/projects/FHS_HMB-IRB-NPU-MDS_","tags":[],"_unique_id":"phs000007.v35.p16.c2","study_id":"phs000007.v35.p16.c2","study_description":"See Grouping of Framingham Phenotype Datasets Startup of Framingham Heart Study. Cardiovascular disease (CVD) is the leading cause of death and serious illness in the United States. In 1948, the Framingham Heart Study (FHS) -- under the direction of the National Heart Institute (now known as the National Heart, Lung, and Blood Institute, NHLBI) -- embarked on a novel and ambitious project in health research. At the time, little was known about the general causes of heart disease and stroke, but the death rates for CVD had been increasing steadily since the beginning of the century and had become an American epidemic. The objective of the FHS was to identify the common factors or characteristics that contribute to CVD by following its development over a long period of time in a large group of participants who had not yet developed overt symptoms of CVD or suffered a heart attack or stroke. Design of Framingham Heart Study. In 1948, the researchers recruited 5,209 men and women between the ages of 30 and 62 from the town of Framingham, Massachusetts, and began the first round of extensive physical examinations and lifestyle interviews that they would later analyze for common patterns related to CVD development. Since 1948, the subjects have returned to the study every two years for an examination consisting of a detailed medical history, physical examination, and laboratory tests, and in 1971, the study enrolled a second-generation cohort -- 5,124 of the original participants' adult children and their spouses -- to participate in similar examinations. The second examination of the Offspring cohort occurred eight years after the first examination, and subsequent examinations have occurred approximately every four years thereafter. In April 2002 the Study entered a new phase: the enrollment of a third generation of participants, the grandchildren of the original cohort. The first examination of the Third Generation Study was completed in July 2005 and involved 4,095 participants. Thus, the FHS has evolved into a prospective, community-based, three generation family study. The FHS is a joint project of the National Heart, Lung and Blood Institute and Boston University. Research Areas in the Framingham Heart Study. Over the years, careful monitoring of the FHS population has led to the identification of the major CVD risk factors -- high blood pressure, high blood cholesterol, smoking, obesity, diabetes, and physical inactivity -- as well as a great deal of valuable information on the effects of related factors such as blood triglyceride and HDL cholesterol levels, age, gender, and psychosocial issues. Risk factors have been identified for the major components of CVD, including coronary heart disease, stroke, intermittent claudication, and heart failure. It is also clear from research in the FHS and other studies that substantial subclinical vascular disease occurs in the blood vessels, heart and brain that precedes clinical CVD. With recent advances in technology, the FHS has enhanced its research capabilities and capitalized on its inherent resources by the conduct of high resolution imaging to detect and quantify subclinical vascular disease in the major blood vessels, heart and brain. These studies have included ultrasound studies of the heart (echocardiography) and carotid arteries, computed tomography studies of the heart and aorta, and magnetic resonance imaging studies of the brain, heart, and aorta. Although the Framingham cohort is primarily white, the importance of the major CVD risk factors identified in this group have been shown in other studies to apply almost universally among racial and ethnic groups, even though the patterns of distribution may vary from group to group. In the past half century, the Study has produced approximately 1,200 articles in leading medical journals. The concept of CVD risk factors has become an integral part of the modern medical curriculum and has led to the development of effective treatment and preventive strategies in clinical practice. In addition to research studies focused on risk factors, subclinical CVD and clinically apparent CVD, Framingham investigators have also collaborated with leading researchers from around the country and throughout the world on projects involving some of the major chronic illnesses in men and women, including dementia, osteoporosis and arthritis, nutritional deficiencies, eye diseases, hearing disorders, and chronic obstructive lung diseases. Genetic Research in the Framingham Heart Study. While pursuing the Study's established research goals, the NHLBI and the Framingham investigators has expanded its research mission into the study of genetic factors underlying CVD and other disorders. Over the past two decades, DNA has been collected from blood samples and from immortalized cell lines obtained from Original Cohort participants, members of the Offspring Cohort and the Third Generation Cohort. Several large-scale genotyping projects have been conducted in the past decade. Genome-wide linkage analysis has been conducted using genotypes of approximately 400 microsatellite markers that have been completed in over 9,300 subjects in all three generations. Analyses using microsatellite markers completed in the original cohort and offspring cohorts have resulted in over 100 publications, including many publications from the Genetics Analysis Workshop 13. Several other recent collaborative projects have completed thousands of SNP genotypes for candidate gene regions in subsets of FHS subjects with available DNA. These projects include the Cardiogenomics Program of the NHLBI's Programs for Genomics Applications, the genotyping of ~3000 SNPs in inflammation genes, and the completion of a genome-wide scan of 100,000 SNPs using the Affymetrix 100K Genechip. Framingham Cohort Phenotype Data. The phenotype database contains a vast array of phenotype information available in all three generations. These will include the quantitative measures of the major risk factors such as systolic blood pressure, total and HDL cholesterol, fasting glucose, and cigarette use, as well as anthropomorphic measures such as body mass index, biomarkers such as fibrinogen and CRP, and electrocardiography measures such as the QT interval. Many of these measures have been collected repeatedly in the original and offspring cohorts. Also included in the SHARe database will be an array of recently collected biomarkers, subclinical disease imaging measures, clinical CVD outcomes as well as an array of ancillary studies. The phenotype data is located here in the top-level study phs000007 Framingham Cohort. To view the phenotype variables collected from the Framingham Cohort, please click on the \"Variables\" tab above. The Framingham Cohort is utilized in the following dbGaP substudies. To view genotypes, analysis, expression data, other molecular data, and derived variables collected in these substudies, please click on the following substudies below or in the \"Substudies\" section of this top-level study page phs000007 Framingham Cohort. phs000342 Framingham SHARe phs000282 Framingham CARe phs000363 Framingham SABRe phs000307 Framingham Medical Resequencing phs000401 Framingham ESP Heart-GO phs000651 Framingham CHARGE-S phs000724 Framingham DNA Methylation phs001610 Framingham T2D-GENES phs002558 Framingham ADSP phs002559 Framingham BRIDGET phs002560 Framingham Cholesterol phs002611 Framingham Post-Mortem Brain Tissue phs002938 Framingham Molecular QTL The unflagging commitment of the research participants in the NHLBI FHS has made more than a half century of research success possible. For decades, the FHS has made its data and DNA widely available to qualified investigators throughout the world through the Limited Access Datasets and the FHS DNA Committee, and the SHARe database will continue that tradition by allowing access to qualified investigators who agree to the requirements of data access. With the SHARe database, we continue with an ambitious research agenda and look forward to new discoveries in the decades to come. Study Weblinks: The Framingham Heart Study NHLBI Framingham Heart Study Study Design: Prospective Longitudinal Cohort Study Type: Longitudinal Total number of consented subjects: 15089 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Framingham Cohort","short_name":"FHS_HMB-IRB-NPU-MDS_","commons":"BioData Catalyst","study_url":"","_subjects_count":1926,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs000166.v2.p1.c1":{"gen3_discovery":{"authz":"/programs/parent/projects/SHARP_ARR_","tags":[{"name":"Parent","category":"Program"},{"name":"Clinical Phenotype","category":"Data Type"},{"name":"dbGaP","category":"Study Registration"}],"_unique_id":"phs000166.v2.p1.c1","study_id":"phs000166.v2.p1.c1","study_description":"SNP Health Association Resource (SHARe) Asthma Resource project (SHARP) is conducting a genome-wide analysis in adults and children who have participated in National Heart, Lung, and Blood Institute's clinical research trials on asthma. This includes 1041 children with asthma who participated in the Childhood Asthma Management Program (CAMP), 994 children who participated in one or five clinical trials conducted by the Childhood Asthma Research and Education (CARE) network, and 701 adults who participated in one of six clinical trials conducted by the Asthma Clinical Research Network (ACRN). There are three study types. The longitudinal clinical trials can be subsetted for population-based and/or case-control analyses. Each of the childhood asthma studies has a majority of children participating as part of a parent-child trio. The ACRN (adult) studies are probands alone. Control genotypes will be provided for case-control analyses. Study Weblinks: CAMP CARE ACRN Study Design: Cross-Sectional Study Type: Longitudinal Parent-Offspring Trios Case-Control Total number of consented subjects: 4046 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"National Heart, Lung, and Blood Institute SNP Health Association Asthma Resource Project (SHARP)","short_name":"SHARP_ARR_","commons":"BioData Catalyst","study_url":"https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000166.v2.p1","_subjects_count":4046,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs000179.v6.p2.c1":{"gen3_discovery":{"authz":"/programs/parent/projects/COPDGene_HMB_","tags":[{"name":"Parent","category":"Program"},{"name":"DCC Harmonized","category":"Data Type"},{"name":"Clinical Phenotype","category":"Data Type"},{"name":"dbGaP","category":"Study Registration"}],"_unique_id":"phs000179.v6.p2.c1","study_id":"phs000179.v6.p2.c1","study_description":"Chronic obstructive pulmonary disease (COPD) is the fourth leading cause of death in the United States and the only leading cause of death that is steadily increasing in frequency. This project will establish a racially diverse cohort that is sufficiently large and appropriately designed for genome-wide association analysis of COPD. A total of 10,000 subjects will be recruited, including control smokers, definite COPD cases (GOLD Stage 2 to 4), and subjects not included in either group (GOLD 1 or GOLD-Unclassified). This cohort will be used for cross-sectional analysis, although long-term longitudinal follow-up will be a future goal. The primary focus of the study will be genome-wide association analysis to identify the genetic risk factors that determine susceptibility for COPD and COPD-related phenotypes. Detailed phenotyping of both cases and controls, including chest CT scan assessment of emphysema and airway disease, will allow identification of genetic determinants for the heterogeneous components of the COPD syndrome. The hypotheses to be studied are: 1) Precise phenotypic characterization of COPD subjects using computed tomography, as well as clinical and physiological measures, will provide data that will enable the broad COPD syndrome to be decomposed into clinically significant subtypes. 2) Genome-wide association studies will identify genetic determinants for COPD susceptibility that will provide insight into clinically relevant COPD subtypes. 3) Distinct genetic determinants influence the development of emphysema and airway disease. The initial phase of genome-wide association analysis included 500 COPD cases and 500 control subjects (all non-Hispanic White) genotyped with the Illumina Omni-1 chip. The second phase genotyped the entire study cohort using the Illumina Omni-Express chip. Unique aspects of the study include: 1) Inclusion of large numbers of African American subjects (approximately 1/3 of the cohort); 2) Obtaining chest CT scans (including inspiratory and expiratory images); and 3) Inclusion of the full range of disease severity. The COPDGene_v6 Cohort is utilized in the following dbGaP sub-studies. To view genotypes, other molecular data, and derived variables collected in these sub-studies, please click on the following sub-studies below or in the \"Sub-studies\" section of this top-level study page phs000179 COPDGene_v6 Cohort. phs000296 ESP LungGO COPDGene phs000765 COPDGene_Geno Study Weblinks: COPDGene Study Design: Case-Control Study Type: Case-Control dbGaP estimated ancestry using GRAF-pop Total number of consented subjects: 10371 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Genetic Epidemiology of COPD (COPDGene) Funded by the National Heart, Lung, and Blood Institute","short_name":"COPDGene_HMB_","commons":"BioData Catalyst","study_url":"https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000179.v6.p2","_subjects_count":10099,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs000179.v6.p2.c2":{"gen3_discovery":{"authz":"/programs/parent/projects/COPDGene_DS-CS_","tags":[{"name":"Parent","category":"Program"},{"name":"DCC Harmonized","category":"Data Type"},{"name":"Clinical Phenotype","category":"Data Type"},{"name":"dbGaP","category":"Study Registration"}],"_unique_id":"phs000179.v6.p2.c2","study_id":"phs000179.v6.p2.c2","study_description":"Chronic obstructive pulmonary disease (COPD) is the fourth leading cause of death in the United States and the only leading cause of death that is steadily increasing in frequency. This project will establish a racially diverse cohort that is sufficiently large and appropriately designed for genome-wide association analysis of COPD. A total of 10,000 subjects will be recruited, including control smokers, definite COPD cases (GOLD Stage 2 to 4), and subjects not included in either group (GOLD 1 or GOLD-Unclassified). This cohort will be used for cross-sectional analysis, although long-term longitudinal follow-up will be a future goal. The primary focus of the study will be genome-wide association analysis to identify the genetic risk factors that determine susceptibility for COPD and COPD-related phenotypes. Detailed phenotyping of both cases and controls, including chest CT scan assessment of emphysema and airway disease, will allow identification of genetic determinants for the heterogeneous components of the COPD syndrome. The hypotheses to be studied are: 1) Precise phenotypic characterization of COPD subjects using computed tomography, as well as clinical and physiological measures, will provide data that will enable the broad COPD syndrome to be decomposed into clinically significant subtypes. 2) Genome-wide association studies will identify genetic determinants for COPD susceptibility that will provide insight into clinically relevant COPD subtypes. 3) Distinct genetic determinants influence the development of emphysema and airway disease. The initial phase of genome-wide association analysis included 500 COPD cases and 500 control subjects (all non-Hispanic White) genotyped with the Illumina Omni-1 chip. The second phase genotyped the entire study cohort using the Illumina Omni-Express chip. Unique aspects of the study include: 1) Inclusion of large numbers of African American subjects (approximately 1/3 of the cohort); 2) Obtaining chest CT scans (including inspiratory and expiratory images); and 3) Inclusion of the full range of disease severity. The COPDGene_v6 Cohort is utilized in the following dbGaP sub-studies. To view genotypes, other molecular data, and derived variables collected in these sub-studies, please click on the following sub-studies below or in the \"Sub-studies\" section of this top-level study page phs000179 COPDGene_v6 Cohort. phs000296 ESP LungGO COPDGene phs000765 COPDGene_Geno Study Weblinks: COPDGene Study Design: Case-Control Study Type: Case-Control dbGaP estimated ancestry using GRAF-pop Total number of consented subjects: 10371 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Genetic Epidemiology of COPD (COPDGene) Funded by the National Heart, Lung, and Blood Institute","short_name":"COPDGene_DS-CS_","commons":"BioData Catalyst","study_url":"https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000179.v6.p2","_subjects_count":272,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs000200.v12.p3.c1":{"gen3_discovery":{"authz":"/programs/parent/projects/WHI_HMB-IRB_","tags":[{"name":"Parent","category":"Program"},{"name":"DCC Harmonized","category":"Data Type"},{"name":"Clinical Phenotype","category":"Data Type"},{"name":"dbGaP","category":"Study Registration"}],"_unique_id":"phs000200.v12.p3.c1","study_id":"phs000200.v12.p3.c1","study_description":"The Women's Health Initiative (WHI) is a long-term national health study that has focused on strategies for preventing heart disease, breast and colorectal cancer, and osteoporotic fractures in postmenopausal women. The original WHI study included 161,808 postmenopausal women enrolled between 1993 and 1998. The Fred Hutchinson Cancer Research Center in Seattle, WA serves as the WHI Clinical Coordinating Center for data collection, management, and analysis of the WHI. The WHI has two major parts: a partial factorial randomized Clinical Trial (CT) and an Observational Study (OS); both were conducted at 40 Clinical Centers nationwide. The CT enrolled 68,132 postmenopausal women between the ages of 50-79 into trials testing three prevention strategies. If eligible, women could choose to enroll in one, two, or all three of the trial components. The components are: Hormone Therapy Trials (HT): This double-blind component examined the effects of combined hormones or estrogen alone on the prevention of coronary heart disease and osteoporotic fractures, and associated risk for breast cancer. Women participating in this component with an intact uterus were randomized to estrogen plus progestin (conjugated equine estrogens [CEE], 0.625 mg/d plus medroxyprogesterone acetate [MPA] 2.5 mg/d] or a matching placebo. Women with prior hysterectomy were randomized to CEE or placebo. Both trials were stopped early, in July 2002 and March 2004, respectively, based on adverse effects. All HT participants continued to be followed without intervention until close-out. Dietary Modification Trial (DM): The Dietary Modification component evaluated the effect of a low-fat and high fruit, vegetable and grain diet on the prevention of breast and colorectal cancers and coronary heart disease. Study participants were randomized to either their usual eating pattern or a low-fat dietary pattern. Calcium/Vitamin D Trial (CaD): This double-blind component began 1 to 2 years after a woman joined one or both of the other clinical trial components. It evaluated the effect of calcium and vitamin D supplementation on the prevention of osteoporotic fractures and colorectal cancer. Women in this component were randomized to calcium (1000 mg/d) and vitamin D (400 IU/d) supplements or a matching placebo. The Observational Study (OS) examines the relationship between lifestyle, environmental, medical and molecular risk factors and specific measures of health or disease outcomes. This component involves tracking the medical history and health habits of 93,676 women not participating in the CT. Recruitment for the observational study was completed in 1998 and participants were followed annually for 8 to 12 years. Extension Studies: The original protocol allowed for follow-up until March 2005, after which participants were invited to enroll in the first WHI Extension Study for follow-up through 2010. Participants were invited again to participate in the second WHI Extension Study with continued follow up from 2010 to at least 2015. As of March 31, 2011 there were 93,122 women enrolled in the second extension. In Extension Study 2, the overall WHI study population was divided into two new subsamples, the Medical Records Cohort (MRC) and the Self-Report Cohort (SRC). The MRC consists of all former hormone trial participants and all African American and Hispanic participants from all study components. The SRC consists of the remaining participants. The extent of outcome information collected differs between the two cohorts, with more extensive outcomes information collection on the MRC. As part of Extension Study 2, selected older WHI participants were invited to participate in an In Person Visit (a.k.a., Long Life Study) at their homes during which additional blood samples were collected and various measurements were taken (such as blood pressure, height, weight, waist circumference, grip strength, etc.). In October 2015, Extension Study 2 was renewed with continued follow-up planned through October 2020, pending annual contract review and renewal. Additional Information: The WHI website, https://www.whi.org/about/SitePages/About%20WHI.aspx has much more information about the study. For WHI data collection forms used over the years, please see https://www.whi.org/researchers/studydoc/SitePages/Forms.aspx. For additional dataset documentation, see https://www.whi.org/researchers/data/Pages/Available%20Data.aspx. For data preparation and use, please refer to 'WHI dbGaP Cohort Data Release Data Preparation Guide May 2018' for additional details about the WHI data. The WHI Cohort is utilized in the following dbGaP substudies. To view genotypes, analysis, expression data, other molecular data, and derived variables collected in these substudies, please click on the following substudies below or in the \"Substudies\" section of this top-level study page phs000200 WHI Cohort. phs000386 WHI SHARe phs000281 GO-ESP WHISP phs000315 WHI GARNET phs000503 WHISE phs000227 PAGE WHI phs000675 WHIMS+ phs000746 WHI Harmonized and Imputed GWAS phs001334 WHI Metabolomics of CHD phs001335 WHI BA23 phs001614 WHI LLS Phase III GWAS Study Weblinks: Scientific Resources Website: Women's Health Initiative NHLBI Women's Health Initiative Study Design: Prospective Longitudinal Cohort Study Type: Partial Factorial Randomized Double-Blind Placebo-Controlled Cohort Longitudinal dbGaP estimated ancestry using GRAF-pop Total number of consented subjects: 143213 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Women's Health Initiative Clinical Trial and Observational Study","short_name":"WHI_HMB-IRB_","commons":"BioData Catalyst","study_url":"https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000200.v12.p3","_subjects_count":117675,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs000200.v12.p3.c2":{"gen3_discovery":{"authz":"/programs/parent/projects/WHI_HMB-IRB-NPU_","tags":[{"name":"Parent","category":"Program"},{"name":"DCC Harmonized","category":"Data Type"},{"name":"Clinical Phenotype","category":"Data Type"},{"name":"dbGaP","category":"Study Registration"}],"_unique_id":"phs000200.v12.p3.c2","study_id":"phs000200.v12.p3.c2","study_description":"The Women's Health Initiative (WHI) is a long-term national health study that has focused on strategies for preventing heart disease, breast and colorectal cancer, and osteoporotic fractures in postmenopausal women. The original WHI study included 161,808 postmenopausal women enrolled between 1993 and 1998. The Fred Hutchinson Cancer Research Center in Seattle, WA serves as the WHI Clinical Coordinating Center for data collection, management, and analysis of the WHI. The WHI has two major parts: a partial factorial randomized Clinical Trial (CT) and an Observational Study (OS); both were conducted at 40 Clinical Centers nationwide. The CT enrolled 68,132 postmenopausal women between the ages of 50-79 into trials testing three prevention strategies. If eligible, women could choose to enroll in one, two, or all three of the trial components. The components are: Hormone Therapy Trials (HT): This double-blind component examined the effects of combined hormones or estrogen alone on the prevention of coronary heart disease and osteoporotic fractures, and associated risk for breast cancer. Women participating in this component with an intact uterus were randomized to estrogen plus progestin (conjugated equine estrogens [CEE], 0.625 mg/d plus medroxyprogesterone acetate [MPA] 2.5 mg/d] or a matching placebo. Women with prior hysterectomy were randomized to CEE or placebo. Both trials were stopped early, in July 2002 and March 2004, respectively, based on adverse effects. All HT participants continued to be followed without intervention until close-out. Dietary Modification Trial (DM): The Dietary Modification component evaluated the effect of a low-fat and high fruit, vegetable and grain diet on the prevention of breast and colorectal cancers and coronary heart disease. Study participants were randomized to either their usual eating pattern or a low-fat dietary pattern. Calcium/Vitamin D Trial (CaD): This double-blind component began 1 to 2 years after a woman joined one or both of the other clinical trial components. It evaluated the effect of calcium and vitamin D supplementation on the prevention of osteoporotic fractures and colorectal cancer. Women in this component were randomized to calcium (1000 mg/d) and vitamin D (400 IU/d) supplements or a matching placebo. The Observational Study (OS) examines the relationship between lifestyle, environmental, medical and molecular risk factors and specific measures of health or disease outcomes. This component involves tracking the medical history and health habits of 93,676 women not participating in the CT. Recruitment for the observational study was completed in 1998 and participants were followed annually for 8 to 12 years. Extension Studies: The original protocol allowed for follow-up until March 2005, after which participants were invited to enroll in the first WHI Extension Study for follow-up through 2010. Participants were invited again to participate in the second WHI Extension Study with continued follow up from 2010 to at least 2015. As of March 31, 2011 there were 93,122 women enrolled in the second extension. In Extension Study 2, the overall WHI study population was divided into two new subsamples, the Medical Records Cohort (MRC) and the Self-Report Cohort (SRC). The MRC consists of all former hormone trial participants and all African American and Hispanic participants from all study components. The SRC consists of the remaining participants. The extent of outcome information collected differs between the two cohorts, with more extensive outcomes information collection on the MRC. As part of Extension Study 2, selected older WHI participants were invited to participate in an In Person Visit (a.k.a., Long Life Study) at their homes during which additional blood samples were collected and various measurements were taken (such as blood pressure, height, weight, waist circumference, grip strength, etc.). In October 2015, Extension Study 2 was renewed with continued follow-up planned through October 2020, pending annual contract review and renewal. Additional Information: The WHI website, https://www.whi.org/about/SitePages/About%20WHI.aspx has much more information about the study. For WHI data collection forms used over the years, please see https://www.whi.org/researchers/studydoc/SitePages/Forms.aspx. For additional dataset documentation, see https://www.whi.org/researchers/data/Pages/Available%20Data.aspx. For data preparation and use, please refer to 'WHI dbGaP Cohort Data Release Data Preparation Guide May 2018' for additional details about the WHI data. The WHI Cohort is utilized in the following dbGaP substudies. To view genotypes, analysis, expression data, other molecular data, and derived variables collected in these substudies, please click on the following substudies below or in the \"Substudies\" section of this top-level study page phs000200 WHI Cohort. phs000386 WHI SHARe phs000281 GO-ESP WHISP phs000315 WHI GARNET phs000503 WHISE phs000227 PAGE WHI phs000675 WHIMS+ phs000746 WHI Harmonized and Imputed GWAS phs001334 WHI Metabolomics of CHD phs001335 WHI BA23 phs001614 WHI LLS Phase III GWAS Study Weblinks: Scientific Resources Website: Women's Health Initiative NHLBI Women's Health Initiative Study Design: Prospective Longitudinal Cohort Study Type: Partial Factorial Randomized Double-Blind Placebo-Controlled Cohort Longitudinal dbGaP estimated ancestry using GRAF-pop Total number of consented subjects: 143213 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Women's Health Initiative Clinical Trial and Observational Study","short_name":"WHI_HMB-IRB-NPU_","commons":"BioData Catalyst","study_url":"https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000200.v12.p3","_subjects_count":25538,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs000204.v1.p1.c1":{"gen3_discovery":{"authz":"/programs/heartfailure/projects/LMD-FSS_GRU","tags":[],"_unique_id":"phs000204.v1.p1.c1","study_id":"phs000204.v1.p1.c1","study_description":"The overall goal of this project is to investigate the etiology and pathogenesis of malformations (i.e., birth defects) of the limb, concentrating on abnormalities of limb patterning such as limb deficiency/duplications and multiple congenital contractures. The exome sequences of four unrelated individuals were obtained by massively parallel DNA sequencing. The three individuals were affected with Freeman Sheldon syndrome (OMIM: 193700). Study Design: Mendelian Study Type: Exome Sequencing Total number of consented subjects: 3 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Genetic Analysis of Limb Malformation Disorders: Freeman Sheldon Syndrome Exome Sequencing Study (LMD-FSS)","short_name":"LMD-FSS_GRU","commons":"BioData Catalyst","study_url":"","_subjects_count":3,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs000209.v13.p3.c1":{"gen3_discovery":{"authz":"/programs/parent/projects/MESA_HMB_","tags":[{"name":"Parent","category":"Program"},{"name":"DCC Harmonized","category":"Data Type"},{"name":"Clinical Phenotype","category":"Data Type"},{"name":"dbGaP","category":"Study Registration"}],"_unique_id":"phs000209.v13.p3.c1","study_id":"phs000209.v13.p3.c1","study_description":"MESA The Multi-Ethnic Study of Atherosclerosis (MESA) is a study of the characteristics of subclinical cardiovascular disease (disease detected non-invasively before it has produced clinical signs and symptoms) and the risk factors that predict progression to clinically overt cardiovascular disease or progression of the subclinical disease. MESA researchers study a diverse, population-based sample of 6,814 asymptomatic men and women aged 45-84. Thirty-eight percent of the recruited participants are white, 28 percent African-American, 22 percent Hispanic, and 12 percent Asian, predominantly of Chinese descent. Participants were recruited from six field centers across the United States: Wake Forest University, Columbia University, Johns Hopkins University, University of Minnesota, Northwestern University and University of California - Los Angeles. Each participant received an extensive physical exam and determination of coronary calcification, ventricular mass and function, flow-mediated endothelial vasodilation, carotid intimal-medial wall thickness and presence of echogenic lucencies in the carotid artery, lower extremity vascular insufficiency, arterial wave forms, electrocardiographic (ECG) measures, standard coronary risk factors, sociodemographic factors, lifestyle factors, and psychosocial factors. Selected repetition of subclinical disease measures and risk factors at follow-up visits allows study of the progression of disease. Blood samples have been assayed for putative biochemical risk factors and stored for case-control studies. DNA has been extracted and lymphocytes cryopreserved (for possible immortalization) for study of candidate genes and possibly, genome-wide scanning, expression, and other genetic techniques. Participants are being followed for identification and characterization of cardiovascular disease events, including acute myocardial infarction and other forms of coronary heart disease (CHD), stroke, and congestive heart failure; for cardiovascular disease interventions; and for mortality. In addition to the six Field Centers, MESA involves a Coordinating Center, a Central Laboratory, and Central Reading Centers for Computed Tomography (CT), Magnetic Resonance Imaging (MRI), Ultrasound, and Electrocardiography (ECG). Protocol development, staff training, and pilot testing were performed in the first 18 months of the study. The first examination took place over two years, from July 2000 - July 2002. It was followed by four examination periods that were 17-20 months in length. Participants have been contacted every 9 to 12 months throughout the study to assess clinical morbidity and mortality. MESA Family The general goal of the MESA Family Study, an ancillary study to MESA funded by a grant from NHLBI, is to apply modern genetic analysis and genotyping methodologies to delineate the genetic determinants of early atherosclerosis. This is being accomplished by utilizing all the current organizational structures of the Multi-Ethnic Study of Atherosclerosis (MESA) and Genetic Centers at Cedars-Sinai Medical Center and University of Virginia. In the MESA Family Study, the goal is to locate and identify genes contributing to the genetic risk for cardiovascular disease (CVD), by looking at the early changes of atherosclerosis within families (mainly siblings). 2128 individuals from 594 families, yielding 3,026 sibpairs divided between African Americans and Hispanic-Americans, were recruited by utilizing the existing framework of MESA. MESA Family studied siblings of index subjects from the MESA study and from new sibpair families (with the same demographic characteristics) and is determining the extent of genetic contribution to the variation in coronary calcium (obtained via CT Scan) and carotid artery wall thickness (B-mode ultrasound) in the two largest non-majority U.S. populations. In a small proportion of subjects, parents of MESA index subjects participating in MESA Family were studied but only to have blood drawn for genotyping. The MESA Family cohort was recruited from the six MESA Field Centers. MESA Family participants underwent the same examination as MESA participants during May 2004 - May 2007. DNA was extracted and lymphocytes immortalized for study of candidate genes, genome-wide linkage scanning, and analyzed for linkage with these subclinical cardiovascular traits. While linkage analysis is the primary approach being used, an additional aspect of the MESA Family Study takes advantage of the existing MESA study population for testing a variety of candidate genes for association with the same subclinical traits. Genotyping and data analysis will occur throughout the study. MESA Air The general goal of the Multi-Ethnic Study of Atherosclerosis and Air Pollution ('MESA Air') is to prospectively examine the relation between an individual level assessment of long-term ambient air pollution exposures (including PM2.5 and the progression of subclinical cardiovascular disease in a multi-city, multi-ethnic cohort. MESA Air will also prospectively examine the relationship between an individual level assessment of long-term ambient air pollution exposures and the incidence of cardiovascular disease, including myocardial infarction and cardiovascular death. MESA AIR is funded by a grant from the United States Environmental Protection Agency to the University of Washington and subcontracts from the UW to other participating institutions. MESA Air will assess if ambient air pollution is associated with changes over time in subclinical measures of atherosclerosis and plasma markers of inflammation, oxidative damage, and endothelial activation in a longitudinal data model, adjusting for age, race/ethnicity, socioeconomic status, and specific cardiovascular risk factors (such as diabetes, hypertension, smoking, and diet). The study will similarly assess if the incidence of cardiovascular events is associated with long-term exposure to ambient air pollution, using a proportional hazards model. The study includes refinement of statistical tools, and explores joint/independent effects of acute and long-term pollutant exposure in the occurrence of cardiovascular disease. The MESA Air study is built on the foundation of the ongoing MESA study. The parent MESA Study cohort is located in six geographic areas ('Field Centers') that capture tremendous exposure heterogeneity, comparable to or greater than the variability in locations of prior U.S. cohort studies. In addition to the six Field Centers, the study involves a Coordinating Center, a Central Laboratory, and Reading Centers for Computed Tomography (CT), ultrasound and air pollution data. The cohort for the MESA Air study currently includes 6226 subjects: 5479 enrolled in the parent MESA study; 257 recruited specifically for this study, and 490 recruited from the MESA Family study. The entire MESA Air cohort will be followed over a 10-year project period for the occurrence of cardiovascular disease events. On two occasions over the ten-year study period, 3600 subjects from the MESA Air cohort, residing in nine locales, will undergo computed tomography scanning to assess presence and extent of coronary artery calcification (CAC), and ultrasound of the carotid artery to determine intima-media thickness (IMT). We will also repeatedly assess plasma markers of inflammation, oxidative damage, and endothelial function in 720 subjects. MESA Air adds state-of-the-art air pollution exposure assessment information to the MESA cohort study, and introduces new subjects and outcome measures to achieve our aims. The study will assess long-term individual-level exposure to ambient air pollutants for each subject using community-scale monitoring, outdoor spatial variation, subject proximity to pollution sources, pollutants' infiltration efficiency, and personal time-activity information. The exposure models will be validated using detailed monitoring in a subset of subjects. The MESA Cohort is utilized in the following dbGaP substudies. To view genotypes, analysis, expression data, other molecular data, and derived variables collected in these substudies, please click on the following substudies below or in the \"Substudies\" section of this top-level study page phs000209 MESA Cohort. phs000420 MESA SHARe phs000283 MESA CARe phs000403 MESA ESP Heart-GO Study Weblinks: MESA MESA Air Study Design: Prospective Longitudinal Cohort Study Type: Longitudinal Family Total number of consented subjects: 8296 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Multi-Ethnic Study of Atherosclerosis (MESA) Cohort","short_name":"MESA_HMB_","commons":"BioData Catalyst","study_url":"https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000209.v13.p3","_subjects_count":7440,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs000209.v13.p3.c2":{"gen3_discovery":{"authz":"/programs/parent/projects/MESA_HMB-NPU_","tags":[{"name":"Parent","category":"Program"},{"name":"DCC Harmonized","category":"Data Type"},{"name":"Clinical Phenotype","category":"Data Type"},{"name":"dbGaP","category":"Study Registration"}],"_unique_id":"phs000209.v13.p3.c2","study_id":"phs000209.v13.p3.c2","study_description":"MESA The Multi-Ethnic Study of Atherosclerosis (MESA) is a study of the characteristics of subclinical cardiovascular disease (disease detected non-invasively before it has produced clinical signs and symptoms) and the risk factors that predict progression to clinically overt cardiovascular disease or progression of the subclinical disease. MESA researchers study a diverse, population-based sample of 6,814 asymptomatic men and women aged 45-84. Thirty-eight percent of the recruited participants are white, 28 percent African-American, 22 percent Hispanic, and 12 percent Asian, predominantly of Chinese descent. Participants were recruited from six field centers across the United States: Wake Forest University, Columbia University, Johns Hopkins University, University of Minnesota, Northwestern University and University of California - Los Angeles. Each participant received an extensive physical exam and determination of coronary calcification, ventricular mass and function, flow-mediated endothelial vasodilation, carotid intimal-medial wall thickness and presence of echogenic lucencies in the carotid artery, lower extremity vascular insufficiency, arterial wave forms, electrocardiographic (ECG) measures, standard coronary risk factors, sociodemographic factors, lifestyle factors, and psychosocial factors. Selected repetition of subclinical disease measures and risk factors at follow-up visits allows study of the progression of disease. Blood samples have been assayed for putative biochemical risk factors and stored for case-control studies. DNA has been extracted and lymphocytes cryopreserved (for possible immortalization) for study of candidate genes and possibly, genome-wide scanning, expression, and other genetic techniques. Participants are being followed for identification and characterization of cardiovascular disease events, including acute myocardial infarction and other forms of coronary heart disease (CHD), stroke, and congestive heart failure; for cardiovascular disease interventions; and for mortality. In addition to the six Field Centers, MESA involves a Coordinating Center, a Central Laboratory, and Central Reading Centers for Computed Tomography (CT), Magnetic Resonance Imaging (MRI), Ultrasound, and Electrocardiography (ECG). Protocol development, staff training, and pilot testing were performed in the first 18 months of the study. The first examination took place over two years, from July 2000 - July 2002. It was followed by four examination periods that were 17-20 months in length. Participants have been contacted every 9 to 12 months throughout the study to assess clinical morbidity and mortality. MESA Family The general goal of the MESA Family Study, an ancillary study to MESA funded by a grant from NHLBI, is to apply modern genetic analysis and genotyping methodologies to delineate the genetic determinants of early atherosclerosis. This is being accomplished by utilizing all the current organizational structures of the Multi-Ethnic Study of Atherosclerosis (MESA) and Genetic Centers at Cedars-Sinai Medical Center and University of Virginia. In the MESA Family Study, the goal is to locate and identify genes contributing to the genetic risk for cardiovascular disease (CVD), by looking at the early changes of atherosclerosis within families (mainly siblings). 2128 individuals from 594 families, yielding 3,026 sibpairs divided between African Americans and Hispanic-Americans, were recruited by utilizing the existing framework of MESA. MESA Family studied siblings of index subjects from the MESA study and from new sibpair families (with the same demographic characteristics) and is determining the extent of genetic contribution to the variation in coronary calcium (obtained via CT Scan) and carotid artery wall thickness (B-mode ultrasound) in the two largest non-majority U.S. populations. In a small proportion of subjects, parents of MESA index subjects participating in MESA Family were studied but only to have blood drawn for genotyping. The MESA Family cohort was recruited from the six MESA Field Centers. MESA Family participants underwent the same examination as MESA participants during May 2004 - May 2007. DNA was extracted and lymphocytes immortalized for study of candidate genes, genome-wide linkage scanning, and analyzed for linkage with these subclinical cardiovascular traits. While linkage analysis is the primary approach being used, an additional aspect of the MESA Family Study takes advantage of the existing MESA study population for testing a variety of candidate genes for association with the same subclinical traits. Genotyping and data analysis will occur throughout the study. MESA Air The general goal of the Multi-Ethnic Study of Atherosclerosis and Air Pollution ('MESA Air') is to prospectively examine the relation between an individual level assessment of long-term ambient air pollution exposures (including PM2.5 and the progression of subclinical cardiovascular disease in a multi-city, multi-ethnic cohort. MESA Air will also prospectively examine the relationship between an individual level assessment of long-term ambient air pollution exposures and the incidence of cardiovascular disease, including myocardial infarction and cardiovascular death. MESA AIR is funded by a grant from the United States Environmental Protection Agency to the University of Washington and subcontracts from the UW to other participating institutions. MESA Air will assess if ambient air pollution is associated with changes over time in subclinical measures of atherosclerosis and plasma markers of inflammation, oxidative damage, and endothelial activation in a longitudinal data model, adjusting for age, race/ethnicity, socioeconomic status, and specific cardiovascular risk factors (such as diabetes, hypertension, smoking, and diet). The study will similarly assess if the incidence of cardiovascular events is associated with long-term exposure to ambient air pollution, using a proportional hazards model. The study includes refinement of statistical tools, and explores joint/independent effects of acute and long-term pollutant exposure in the occurrence of cardiovascular disease. The MESA Air study is built on the foundation of the ongoing MESA study. The parent MESA Study cohort is located in six geographic areas ('Field Centers') that capture tremendous exposure heterogeneity, comparable to or greater than the variability in locations of prior U.S. cohort studies. In addition to the six Field Centers, the study involves a Coordinating Center, a Central Laboratory, and Reading Centers for Computed Tomography (CT), ultrasound and air pollution data. The cohort for the MESA Air study currently includes 6226 subjects: 5479 enrolled in the parent MESA study; 257 recruited specifically for this study, and 490 recruited from the MESA Family study. The entire MESA Air cohort will be followed over a 10-year project period for the occurrence of cardiovascular disease events. On two occasions over the ten-year study period, 3600 subjects from the MESA Air cohort, residing in nine locales, will undergo computed tomography scanning to assess presence and extent of coronary artery calcification (CAC), and ultrasound of the carotid artery to determine intima-media thickness (IMT). We will also repeatedly assess plasma markers of inflammation, oxidative damage, and endothelial function in 720 subjects. MESA Air adds state-of-the-art air pollution exposure assessment information to the MESA cohort study, and introduces new subjects and outcome measures to achieve our aims. The study will assess long-term individual-level exposure to ambient air pollutants for each subject using community-scale monitoring, outdoor spatial variation, subject proximity to pollution sources, pollutants' infiltration efficiency, and personal time-activity information. The exposure models will be validated using detailed monitoring in a subset of subjects. The MESA Cohort is utilized in the following dbGaP substudies. To view genotypes, analysis, expression data, other molecular data, and derived variables collected in these substudies, please click on the following substudies below or in the \"Substudies\" section of this top-level study page phs000209 MESA Cohort. phs000420 MESA SHARe phs000283 MESA CARe phs000403 MESA ESP Heart-GO Study Weblinks: MESA MESA Air Study Design: Prospective Longitudinal Cohort Study Type: Longitudinal Family Total number of consented subjects: 8296 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Multi-Ethnic Study of Atherosclerosis (MESA) Cohort","short_name":"MESA_HMB-NPU_","commons":"BioData Catalyst","study_url":"https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000209.v13.p3","_subjects_count":856,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs000221.v1.p1.c1":{"gen3_discovery":{"authz":"/programs/heartfailure/projects/FamHS_GRU","tags":[],"_unique_id":"phs000221.v1.p1.c1","study_id":"phs000221.v1.p1.c1","study_description":"The Family Heart Study (FamHS) was funded by the National Heart, Lung, and Blood Institute (NHLBI). It was begun in 1992 with the ascertainment of 1,200 families, half randomly sampled, and half selected because of an excess of coronary heart disease (CHD) or risk factor abnormalities as compared with age- and sex-specific population rates (Higgins et al. 1996). The families, with approximately 6,000 individuals, were sampled on the basis of information on probands from four population-based parent studies: the Framingham Heart Study, the Utah Family Tree Study, and two Atherosclerosis Risk in Communities (ARIC) centers (Minneapolis, and Forsyth County, NC). A broad range of phenotypes were assessed at a clinic examination in broad domains of CHD, atherosclerosis, cardiac and vascular function, inflammation and hemostasis, lipids and lipoproteins, blood pressure, diabetes and insulin resistance, pulmonary function, and anthropometry (FamHS Visit 1). Approximately 8 years later, study participants belonging to the largest pedigrees were invited for a second clinical exam (FamHS Visit 2). A total of 2,756 Caucasian subjects in 508 extended families were examined. A two-phase design was adopted for the genome wide association (GWA) study. In phase-1, 1007 subjects were chosen, equally distributed between the upper and lower quartile of age- and sex-adjusted values for coronary artery calcification, assessed by CT scan in Visit 2. These subjects were chosen to be largely unrelated; 34% of the subjects were from unique families, while 200 other subjects had 1 or more siblings selected into the sample, yielding a sample of 465 unrelated subjects. The remaining family members (N=1749) were genotyped in the phase-2 for replication of the top hits from the phase-1. The results presented here represent those for the analysis of the phase-1 case-control sample for variables assessed in FamHS Visit 1 (from 1992 to 1995) and for the variables assessed in FamHS Visit 2 (from 2002 to 2003). All subjects were typed on the Illumina HumMap 550 chip (Phase 1 genotype). Of these, 33 (3.3%) were excluded due to technical errors, call rates below 98%, and discrepancies between reported sex and sex-diagnostic markers. The final sample of 974 subjects have Visit 2 phenotypes, approximately 100 of these do not have Visit 1 phenotypes. There was no significant plate-to-plate variation in allele frequencies. The covariate adjustments were performed separately by sex using cubic polynomial age and clinical centers, and retaining the terms in the stepwise regression analysis that were significant at the 5% level. Extreme outliers (>4 SD from the mean) were set aside, temporarily, for the adjustments. The final phenotypes were computed for all individuals using the best mean regression models and standardizing to 0 mean and unit variance. The FamHS has contributed GWA results in many phenotype domains (antropometric and adiposity, atherosclerosis and coronary heart disease, lipid profile, diabetes and glicemic traits, metabolic syndrome etc) to meta-analyses and various consortia, including Heard-Costa et al. 2009, Köttgen et al. 2010, Teslovich et al. 2010, Nettleton et al. 2010, Lango et al. 2010, Heid et al. 2010, Speliotes et al. 2010, Dupuis et al. 2010, Kraja et al. 2011. Study Weblinks: The NHLBI Family Heart Study FHS SCAN Study Design: Prospective Longitudinal Cohort Study Type: Family Longitudinal NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"NHLBI Family Heart Study (FamHS-Visit1 and FamHS-Visit2)","short_name":"FamHS_GRU","commons":"BioData Catalyst","study_url":"","_subjects_count":0,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs000223.v8.p2.c1":{"gen3_discovery":{"authz":"/programs/dbGaP/projects/PAGE_CALiCo_ARIC_HMB-IRB","tags":[],"_unique_id":"phs000223.v8.p2.c1","study_id":"phs000223.v8.p2.c1","study_description":"This sub-study phs000223 PAGE CALiCo ARIC contains genotype data and selected phenotype of subjects available from the phs000223. Summary level phenotypes for the NHLBI ARIC Cohort study participants can be viewed at the top-level study page phs000280 ARIC Cohort. Individual level phenotype data and molecular data for all ARIC Cohort top-level study and sub-study are available by requesting Authorized Access to the NHLBI ARIC Cohort phs000280 study. CALiCo ARIC The Atherosclerosis Risk in Communities Study (ARIC), sponsored by the National Heart, Lung and Blood Institute (NHLBI), is a prospective epidemiologic study conducted in four U.S. communities. ARIC is designed to investigate the etiology and natural history of atherosclerosis, the etiology of clinical atherosclerotic diseases, and variation in cardiovascular risk factors, medical care and disease by race, gender, location, and date. ARIC includes a Cohort Component and a Community Surveillance Component. Cohort enrollment began in 1987. Each ARIC field center randomly selected and recruited a sample of approximately 4,000 individuals aged 45-64 from a defined population in their community. A total of 15,792 participants received an extensive examination, including medical, social, and demographic data. These participants were reexamined every three years with the first screen (baseline) occurring in 1987-89, the second in 1990-92, the third in 1993-95, and the fourth and last exam wastook place in 1996-98. Follow-up occurs yearly byA fifth cohort examination is underway (2011-2013). Yearly telephone tointerviews maintain contact with participants and to assess health status of the cohort. In the Community Surveillance Component, currently ongoing, these four communities are investigated to determine the community-wide occurrence of hospitalized myocardial infarction and coronary heart disease deaths in men and women aged 35-84 years. Hospitalized stroke is investigated in cohort participants only. The study conducts community surveillance of inpatient heart failure (ages 55 years and older) and cohort surveillance outpatient heart failure events beginning in 2005. This study is part of the Population Architecture using Genomics and Epidemiology (PAGE) study phs000356. Study Weblinks: Population Architecture using Genomics and Epidemiology (PAGE) ARIC Study Design: Prospective Longitudinal Cohort Study Type: Longitudinal dbGaP estimated ancestry using GRAF-pop Total number of consented subjects: 3516 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Population Architecture using Genomics and Epidemiology (PAGE): Causal Variants Across the Life Course (CALiCo): Atherosclerosis Risk in Communities (ARIC)","short_name":"PAGE_CALiCo_ARIC_HMB-IRB","commons":"BioData Catalyst","study_url":"","_subjects_count":3301,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs000223.v8.p2.c2":{"gen3_discovery":{"authz":"/programs/dbGaP/projects/PAGE_CALiCo_ARIC_DS-CVD-IRB","tags":[],"_unique_id":"phs000223.v8.p2.c2","study_id":"phs000223.v8.p2.c2","study_description":"This sub-study phs000223 PAGE CALiCo ARIC contains genotype data and selected phenotype of subjects available from the phs000223. Summary level phenotypes for the NHLBI ARIC Cohort study participants can be viewed at the top-level study page phs000280 ARIC Cohort. Individual level phenotype data and molecular data for all ARIC Cohort top-level study and sub-study are available by requesting Authorized Access to the NHLBI ARIC Cohort phs000280 study. CALiCo ARIC The Atherosclerosis Risk in Communities Study (ARIC), sponsored by the National Heart, Lung and Blood Institute (NHLBI), is a prospective epidemiologic study conducted in four U.S. communities. ARIC is designed to investigate the etiology and natural history of atherosclerosis, the etiology of clinical atherosclerotic diseases, and variation in cardiovascular risk factors, medical care and disease by race, gender, location, and date. ARIC includes a Cohort Component and a Community Surveillance Component. Cohort enrollment began in 1987. Each ARIC field center randomly selected and recruited a sample of approximately 4,000 individuals aged 45-64 from a defined population in their community. A total of 15,792 participants received an extensive examination, including medical, social, and demographic data. These participants were reexamined every three years with the first screen (baseline) occurring in 1987-89, the second in 1990-92, the third in 1993-95, and the fourth and last exam wastook place in 1996-98. Follow-up occurs yearly byA fifth cohort examination is underway (2011-2013). Yearly telephone tointerviews maintain contact with participants and to assess health status of the cohort. In the Community Surveillance Component, currently ongoing, these four communities are investigated to determine the community-wide occurrence of hospitalized myocardial infarction and coronary heart disease deaths in men and women aged 35-84 years. Hospitalized stroke is investigated in cohort participants only. The study conducts community surveillance of inpatient heart failure (ages 55 years and older) and cohort surveillance outpatient heart failure events beginning in 2005. This study is part of the Population Architecture using Genomics and Epidemiology (PAGE) study phs000356. Study Weblinks: Population Architecture using Genomics and Epidemiology (PAGE) ARIC Study Design: Prospective Longitudinal Cohort Study Type: Longitudinal dbGaP estimated ancestry using GRAF-pop Total number of consented subjects: 3516 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Population Architecture using Genomics and Epidemiology (PAGE): Causal Variants Across the Life Course (CALiCo): Atherosclerosis Risk in Communities (ARIC)","short_name":"PAGE_CALiCo_ARIC_DS-CVD-IRB","commons":"BioData Catalyst","study_url":"","_subjects_count":215,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs000244.v1.p1.c1":{"gen3_discovery":{"authz":"/programs/heartfailure/projects/LMD-MS_GRU","tags":[],"_unique_id":"phs000244.v1.p1.c1","study_id":"phs000244.v1.p1.c1","study_description":"The overall goal of this project is to investigate the etiology and pathogenesis of malformations (i.e., birth defects) of the limb, concentrating on abnormalities of limb patterning such as limb deficiency/duplications and multiple congenital contractures. The exome sequences of two siblings and two unrelated individuals were obtained by massively parallel DNA sequencing. The four individuals were affected with Miller syndrome (OMIM: 263750). Additionally, the whole-genome sequences of a family of four were obtained with the method of Complete Genomics Incorporated (CGI). The two offspring were both affected with Miller syndrome and is the same sibling pair mentioned previously from whom exome sequences were also obtained. Study Design: Mendelian Study Type: Exome Sequencing Pedigree Whole Genome Sequencing Total number of consented subjects: 6 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Genetic Analysis of Limb Malformation Disorders: Miller Syndrome Sequencing Study (LMD-MS)","short_name":"LMD-MS_GRU","commons":"BioData Catalyst","study_url":"","_subjects_count":6,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs000253.v1.p1.c1":{"gen3_discovery":{"authz":"/programs/heartfailure/projects/HLC_GRU","tags":[{"name":"dbGaP","category":"Study Registration"}],"_unique_id":"phs000253.v1.p1.c1","study_id":"phs000253.v1.p1.c1","study_description":"The Human Liver Cohort (HLC) study aimed to characterize the genetic architecture of gene expression in human liver using genotyping, gene expression profiling, and enzyme activity measurements of Cytochrom P450. The HLC was assembled from a total of 780 liver samples screened. DNA samples were genotyped on the Affymetrix 500K SNP and Illumina 650Y SNP genotyping arrays. Only data from those samples which were collected postmortem are accessible through this submission. These 228 samples represent a subset of the 427 samples included in the Human Liver Cohort Publication (Schadt, Molony et al. 2008, PMID: 18462017). RNA samples were profiled on a custom Agilent 44,000 feature microarray composed of 39,280 oligonucleotide probes targeting transcripts representing 34,266 known and predicted genes, including high-confidence, noncoding RNA sequences. Gene Expression data for the samples from which it could be obtained is available in GEO under accession number GSE9588. Results and networks will be made available for download from Sage Bionetworks. Study Design: Cross-Sectional Study Type: Population Total number of consented subjects: 228 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Human Liver Cohort (HLC)","short_name":"HLC_GRU","commons":"BioData Catalyst","study_url":"https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000253.v1.p1","_subjects_count":228,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs000279.v2.p1.c1":{"gen3_discovery":{"authz":"/programs/heartfailure/projects/BroadEOMI_DS-CVD","tags":[],"_unique_id":"phs000279.v2.p1.c1","study_id":"phs000279.v2.p1.c1","study_description":"The NHLBI \"Grand Opportunity\" Exome Sequencing Project (GO-ESP), a signature project of the NHLBI Recovery Act investment, was designed to identify genetic variants in coding regions (exons) of the human genome (the \"exome\") that are associated with heart, lung and blood diseases. These and related diseases that are of high impact to public health and individuals from diverse racial and ethnic groups will be studied. These data may help researchers understand the causes of disease, contributing to better ways to prevent, diagnose, and treat diseases, as well as determine whether to tailor prevention and treatments to specific populations. This could lead to more effective treatments and reduce the likelihood of side effects. GO-ESP is comprised of five collaborative components: 3 cohort consortia - HeartGO, LungGO, and WHISP - and 2 sequencing centers - BroadGO and SeattleGO. In the Grand Opportunities Exome Sequencing Program Early MI Project (GO ESP - EOMI), we are sequencing cases with extremely early-onset MI drawn from 8 cohorts. These cohorts include five hospital or community-based studies that ascertained individuals based on MI status. These include PennCATH, Cleveland Clinic Genebank, Massachusetts General Hospital Premature Coronary Artery Disease Study (MGH-PCAD), Heart Attack Risk in Puget Sound (HARPS), and Translational Research Investigating Underlying Disparities in Myocardial Infarction Patients' Health Status (TRIUMPH). Cases were selected based on MI occurring in men aged ≤50 years and women aged ≤60 years. In addition, early-MI cases are being drawn from three population-cohort studies including the Framingham Heart Study, the Women's Health Initiative, and the Atherosclerosis Risk in Communities Study. MI-free controls are being drawn from five population-based cohort studies including the Framingham Heart Study, the Women's Health Initiative, Atherosclerosis Risk in Communities Study, Cardiovascular Health Study, and the Jackson Heart Study. Controls were selected based on two factors: (1) highest predicted risk for MI based on Framingham risk score; and (2) absence of prevalent or incident MI despite a high predicted risk. Study Weblinks: NHLBI GO ESP Project Study Design: Prospective Longitudinal Cohort Study Type: Longitudinal Case-Control Exome Sequencing Total number of consented subjects: 736 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"NHLBI GO-ESP: Early-Onset Myocardial Infarction (Broad EOMI)","short_name":"BroadEOMI_DS-CVD","commons":"BioData Catalyst","study_url":"","_subjects_count":736,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs000280.v8.p2.c1":{"gen3_discovery":{"authz":"/programs/parent/projects/ARIC_HMB-IRB_","tags":[],"_unique_id":"phs000280.v8.p2.c1","study_id":"phs000280.v8.p2.c1","study_description":"The Atherosclerosis Risk in Communities (ARIC) Study, sponsored by the National Heart, Lung and Blood Institute (NHLBI), is a prospective epidemiologic study conducted in four U.S. communities. The four communities are Forsyth County, NC; Jackson, MS; the northwest suburbs of Minneapolis, MN; and Washington County, MD. ARIC is designed to investigate the etiology and natural history of atherosclerosis, the etiology of clinical atherosclerotic diseases, and variation in cardiovascular risk factors, medical care and disease by race, gender, location, and date. ARIC includes two parts: the Cohort Component and the Community Surveillance Component. The Cohort Component began in 1987, and each ARIC field center randomly selected and recruited a cohort sample of approximately 4,000 individuals aged 45-64 from a defined population in their community. A total of 15,792 participants received an extensive examination, including medical, social, and demographic data. These participants were examined with the baseline visit occurring in 1987-89, the second visit in 1990-92, the third visit in 1993-95, the fourth visit in 1996-98, the fifth visit in 2011-13, the sixth visit 2016-17 and the seventh visit 2018-19. Follow-up occurs yearly by telephone to maintain contact with participants and to assess health status of the cohort. In the Community Surveillance Component, these four communities were investigated to determine the community-wide occurrence of hospitalized myocardial infarction and coronary heart disease deaths in men and women aged 35-84 years. Hospitalized stroke is investigated in cohort participants only. Starting in 2006, the study conducted community surveillance of inpatient (ages 55 years and older) and outpatient heart failure (ages 65 years and older) for heart failure events beginning in 2005. Community Surveillance for non-cohorts ended in event year 2014. ARIC is currently funded through 2028. The ARIC Cohort is utilized in the following dbGaP sub-studies. To view genotypes, other molecular data, and derived variables collected in these sub-studies, please click on the following sub-studies below or in the \"Sub-studies\" section of this top-level study page phs000280 ARIC Cohort. phs000557 ARIC_CARe phs000090 GENEVA_ARIC phs000223 PAGE_CALiCo_ARIC phs000398 GO-ESP: HeartGo_ARIC phs000668 CHARGE_ARIC phs000860 MICORTEX phs001536 CCDG_ARIC Study Weblinks: ARIC Atherosclerosis Risk in Communities Study Study Design: Prospective Longitudinal Cohort Study Type: Cohort Longitudinal Total number of consented subjects: 15158 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Atherosclerosis Risk in Communities (ARIC) Cohort","short_name":"ARIC_HMB-IRB_","commons":"BioData Catalyst","study_url":"","_subjects_count":0,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs000280.v8.p2.c2":{"gen3_discovery":{"authz":"/programs/parent/projects/ARIC_DS-CVD-IRB_","tags":[],"_unique_id":"phs000280.v8.p2.c2","study_id":"phs000280.v8.p2.c2","study_description":"The Atherosclerosis Risk in Communities (ARIC) Study, sponsored by the National Heart, Lung and Blood Institute (NHLBI), is a prospective epidemiologic study conducted in four U.S. communities. The four communities are Forsyth County, NC; Jackson, MS; the northwest suburbs of Minneapolis, MN; and Washington County, MD. ARIC is designed to investigate the etiology and natural history of atherosclerosis, the etiology of clinical atherosclerotic diseases, and variation in cardiovascular risk factors, medical care and disease by race, gender, location, and date. ARIC includes two parts: the Cohort Component and the Community Surveillance Component. The Cohort Component began in 1987, and each ARIC field center randomly selected and recruited a cohort sample of approximately 4,000 individuals aged 45-64 from a defined population in their community. A total of 15,792 participants received an extensive examination, including medical, social, and demographic data. These participants were examined with the baseline visit occurring in 1987-89, the second visit in 1990-92, the third visit in 1993-95, the fourth visit in 1996-98, the fifth visit in 2011-13, the sixth visit 2016-17 and the seventh visit 2018-19. Follow-up occurs yearly by telephone to maintain contact with participants and to assess health status of the cohort. In the Community Surveillance Component, these four communities were investigated to determine the community-wide occurrence of hospitalized myocardial infarction and coronary heart disease deaths in men and women aged 35-84 years. Hospitalized stroke is investigated in cohort participants only. Starting in 2006, the study conducted community surveillance of inpatient (ages 55 years and older) and outpatient heart failure (ages 65 years and older) for heart failure events beginning in 2005. Community Surveillance for non-cohorts ended in event year 2014. ARIC is currently funded through 2028. The ARIC Cohort is utilized in the following dbGaP sub-studies. To view genotypes, other molecular data, and derived variables collected in these sub-studies, please click on the following sub-studies below or in the \"Sub-studies\" section of this top-level study page phs000280 ARIC Cohort. phs000557 ARIC_CARe phs000090 GENEVA_ARIC phs000223 PAGE_CALiCo_ARIC phs000398 GO-ESP: HeartGo_ARIC phs000668 CHARGE_ARIC phs000860 MICORTEX phs001536 CCDG_ARIC Study Weblinks: ARIC Atherosclerosis Risk in Communities Study Study Design: Prospective Longitudinal Cohort Study Type: Cohort Longitudinal Total number of consented subjects: 15158 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Atherosclerosis Risk in Communities (ARIC) Cohort","short_name":"ARIC_DS-CVD-IRB_","commons":"BioData Catalyst","study_url":"","_subjects_count":0,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs000284.v2.p1.c1":{"gen3_discovery":{"authz":"/programs/parent/projects/CFS_DS-HLBS-IRB-NPU_","tags":[{"name":"Parent","category":"Program"},{"name":"DCC Harmonized","category":"Data Type"},{"name":"Clinical Phenotype","category":"Data Type"},{"name":"dbGaP","category":"Study Registration"}],"_unique_id":"phs000284.v2.p1.c1","study_id":"phs000284.v2.p1.c1","study_description":"The Cleveland Family Study is the largest family-based study of sleep apnea world-wide, consisting of 2284 individuals (46% African American) from 361 families studied on up to 4 occasions over a period of 16 years. The study was begun in 1990 with the initial aims of quantifying the familial aggregation of sleep apnea. NIH renewals provided expansion of the original cohort (including increased minority recruitment) and longitudinal follow-up, with the last exam occurring in February 2006. Index probands (n=275) were recruited from 3 area hospital sleep labs if they had a confirmed diagnosis of sleep apnea and at least 2 first-degree relatives available to be studied. In the first 5 years of the study, neighborhood control probands (n=87) with at least 2 living relatives available for study were selected at random from a list provided by the index family and also studied. All available first degree relatives and spouses of the case and control probands also were recruited. Second-degree relatives, including half-sibs, aunts, uncles and grandparents, were also included if they lived near the first degree relatives (cases or controls), or if the family had been found to have two or more relatives with sleep apnea. Blood was sampled and DNA isolated for participants seen in the last two exam cycles (n=1447). The sample, which is enriched with individuals with sleep apnea, also contains a high prevalence of individuals with sleep apnea-related traits, including: obesity, impaired glucose tolerance, and HTN. Phenotyping data have been collected over 4 exam cycles, each occurring ~every 4 years. The last three exams targeted all subjects who had been studied at earlier exams, as well as new minority families and family members of previously studied probands who had been unavailable at prior exams. Data from one, two, three and four visits are available for 412, 630, 329 and 67, participants, respectively. In the first 3 exams, participants underwent overnight in-home sleep studies, allowing determination of the number and duration of hypopneas and apneas, sleep period, heart rate, and oxygen saturation levels; anthropometry (weight, height, and waist, hip, and neck circumferences); resting blood pressure; spirometry; standardized questionnaire evaluation of symptoms, medications, sleep patterns, quality of life, daytime sleepiness measures and health history; venipuncture and measurement of total and HDL cholesterol. The 4th exam (2001-2006) was designed to collect more detailed measurements of sleep, metabolic and CVD phenotypes and included measurement of state-of-the-art polysomnography, with both collection of blood and measurement of blood pressure before and after sleep, and anthropometry, upper airway assessments, spirometry, exhaled nitric oxide, and ECG performed the morning after the sleep study. Data have been collected by trained research assistants or GCRC nurses following written Manuals of Procedures who were certified following standard approaches for each study procedure. Ongoing data quality, with assessment of within or between individual drift, has been monitored on an ongoing basis, using statistical techniques as well as regular re-certification procedures. Between and within scorer reliabilities for key sleep apnea indices have been excellent, with intra-class correlation coefficients (ICCs) exceeding 0.92 for the apnea-hypopnea index (AHI). Sleep staging, assessed with epoch specific comparisons, also demonstrate excellent reliability for stage identification (kappas>0.82). There has been no evidence of significant time trends-between or within scorers- for the AHI variables. We also have evaluated the night-to-night variability of the AHI and other sleep variables in 91 subjects, with each measurement made 1-3 months apart. There is high night to night consistency for the AHI (ICC: 0.80), the arousal index (0.76), and the % sleep time in slow-wave sleep (0.73). We have demonstrated the comparability of the apnea estimates (AHI) determined from limited channel studies obtained at in-home settings with in full in-laboratory polysomnography. In addition to our published validation study, we more recently compared the AHI in 169 Cleveland Family Study participants undergoing both assessments (in-home and in-laboratory) within one week apart. These showed excellent levels of agreement (ICC=0.83), demonstrating the feasibility of examining data from either in-home or in-laboratory studies for apnea phenotyping. Data collected in the GCRC were obtained, when possible, with comparable, if not identical techniques, as were the same measures collected at prior exams performed in the participants' homes. To address the comparability of data collected over different exams, we calculated the crude age-adjusted correlations ~3 year within individual correlations between measures made in the most recent GCRC exam with measures made in a prior exam and demonstrated excellent levels of agreement for BMI (r=.91); waist circumference (0.91); FVC (0.88); and FEV1 (0.86). As expected due to higher biological and measurement variability, 149 somewhat lower 3-year correlations were demonstrated for SBP (0.56); Diastolic BP (0.48); AHI (0.62); and nocturnal oxygen desaturation (0.60). NHLBI Candidate-gene Association Resource. The NHLBI initiated the Candidate gene Association Resource (CARe) to create a shared genotype/phenotype resource for analyses of the association of genotypes with phenotypes relevant to the mission of the NHLBI. The resource comprises nine cohort studies funded by the NHLBI: Atherosclerosis Risk in Communities (ARIC), Cardiovascular Health Study (CHS), Cleveland Family Study (CFS), Coronary Artery Risk Development in Young Adults (CARDIA), Cooperative Study of Sickle Cell Disease (CSSCD), Framingham Heart Study (FHS), Jackson Heart Study (JHS), Multi-Ethnic Study of Atherosclerosis (MESA), and the Sleep Heart Health Study (SHHS). A database of genotype and phenotype data will be created that includes records for approximately 50,000 study participants with approximately 50,000 SNPs from more than 1,200 selected candidate genes. In addition, a genome wide association study using a 1,000K SNP Chip will be conducted on approximately 9,500 African American participants drawn from the 50,000 participants in the nine cohorts. Some relevant CARe publications CARe Study: PMID 20400780 CVD Chip Design: PMID 18974833 Study Weblinks: Cleveland Family Study Study Design: Prospective Longitudinal Cohort Study Type: Longitudinal dbGaP estimated ancestry using GRAF-pop Total number of consented subjects: 1473 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"NHLBI Cleveland Family Study (CFS) Candidate Gene Association Resource (CARe)","short_name":"CFS_DS-HLBS-IRB-NPU_","commons":"BioData Catalyst","study_url":"https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000284.v2.p1","_subjects_count":1473,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs000285.v3.p2.c1":{"gen3_discovery":{"authz":"/programs/parent/projects/CARDIA_HMB-IRB_","tags":[],"_unique_id":"phs000285.v3.p2.c1","study_id":"phs000285.v3.p2.c1","study_description":"CARDIA is a study examining the etiology and natural history of cardiovascular disease beginning in young adulthood. In 1985-1986, a cohort of 5115 healthy black and white men and women aged 18-30 years were selected to have approximately the same number of people in subgroups of age (18-24 and 25-30), sex, race, and education (high school or less and more than high school) within each of four US Field Centers. These same participants were asked to participate in follow-up examinations during 1987-1988 (Year 2), 1990-1991 (Year 5), 1992-1993 (Year 7), 1995-1996 (Year 10), 2000-2001 (Year 15), 2005-2006 (Year 20), and 2010-2011 (Year 25); the proportions of the surviving cohort that have returned for the seven follow-up examinations were 90%, 86%, 81%, 79%, 74%, 72%, and 72%, respectively. In addition to the follow-up examinations, participants are contacted regularly for the ascertainment of information on out-patient procedures and hospitalizations experienced between contacts. Within the past five years, 95% of the original surviving cohort has been contacted. While the specifics of each examination has differed somewhat, data have been collected on a variety of factors believed to be related to heart disease. These include conditions with clear links to heart disease such as blood pressure, cholesterol and other lipids. Data have also been collected on physical measurements such as weight and skinfold fat as well as lifestyle factors such as substance use (tobacco and alcohol), dietary and exercise patterns, behavioral and psychological variables, medical and family history, and other chemistries (e.g., insulin and glucose). In addition, subclinical atherosclerosis was measured via echocardiography during Years 5, 10, and 25, computed tomography during Years 15 and 20, and carotid ultrasound during Year 20. The CARDIA Cohort is utilized in the following dbGaP sub-studies. To view genotypes, other molecular data, and derived variables collected in these sub-studies, please click on the following sub-studies below or in the \"Sub-studies\" box located on the right hand side of this top-level study page phs000285 CARDIA Cohort. phs000236 PAGE_CALiCo_CARDIA phs000309 GENEVA_CARDIA phs000399 GO-ESP HeartGO_CARDIA phs000613 CARDIA_CARe Study Weblinks: CARDIA Study Design: Prospective Longitudinal Cohort Study Type: Longitudinal dbGaP estimated ancestry using GRAF-pop Total number of consented subjects: 3622 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Coronary Artery Risk Development in Young Adults (CARDIA) Study - Cohort","short_name":"CARDIA_HMB-IRB_","commons":"BioData Catalyst","study_url":"","_subjects_count":0,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs000285.v3.p2.c2":{"gen3_discovery":{"authz":"/programs/parent/projects/CARDIA_HMB-IRB-NPU_","tags":[],"_unique_id":"phs000285.v3.p2.c2","study_id":"phs000285.v3.p2.c2","study_description":"CARDIA is a study examining the etiology and natural history of cardiovascular disease beginning in young adulthood. In 1985-1986, a cohort of 5115 healthy black and white men and women aged 18-30 years were selected to have approximately the same number of people in subgroups of age (18-24 and 25-30), sex, race, and education (high school or less and more than high school) within each of four US Field Centers. These same participants were asked to participate in follow-up examinations during 1987-1988 (Year 2), 1990-1991 (Year 5), 1992-1993 (Year 7), 1995-1996 (Year 10), 2000-2001 (Year 15), 2005-2006 (Year 20), and 2010-2011 (Year 25); the proportions of the surviving cohort that have returned for the seven follow-up examinations were 90%, 86%, 81%, 79%, 74%, 72%, and 72%, respectively. In addition to the follow-up examinations, participants are contacted regularly for the ascertainment of information on out-patient procedures and hospitalizations experienced between contacts. Within the past five years, 95% of the original surviving cohort has been contacted. While the specifics of each examination has differed somewhat, data have been collected on a variety of factors believed to be related to heart disease. These include conditions with clear links to heart disease such as blood pressure, cholesterol and other lipids. Data have also been collected on physical measurements such as weight and skinfold fat as well as lifestyle factors such as substance use (tobacco and alcohol), dietary and exercise patterns, behavioral and psychological variables, medical and family history, and other chemistries (e.g., insulin and glucose). In addition, subclinical atherosclerosis was measured via echocardiography during Years 5, 10, and 25, computed tomography during Years 15 and 20, and carotid ultrasound during Year 20. The CARDIA Cohort is utilized in the following dbGaP sub-studies. To view genotypes, other molecular data, and derived variables collected in these sub-studies, please click on the following sub-studies below or in the \"Sub-studies\" box located on the right hand side of this top-level study page phs000285 CARDIA Cohort. phs000236 PAGE_CALiCo_CARDIA phs000309 GENEVA_CARDIA phs000399 GO-ESP HeartGO_CARDIA phs000613 CARDIA_CARe Study Weblinks: CARDIA Study Design: Prospective Longitudinal Cohort Study Type: Longitudinal dbGaP estimated ancestry using GRAF-pop Total number of consented subjects: 3622 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Coronary Artery Risk Development in Young Adults (CARDIA) Study - Cohort","short_name":"CARDIA_HMB-IRB-NPU_","commons":"BioData Catalyst","study_url":"","_subjects_count":0,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs000286.v7.p2.c1":{"gen3_discovery":{"authz":"/programs/parent/projects/JHS_HMB-IRB-NPU_","tags":[],"_unique_id":"phs000286.v7.p2.c1","study_id":"phs000286.v7.p2.c1","study_description":"The Jackson Heart Study (JHS) is a large, community-based, observational study whose participants were recruited from urban and rural areas of the three counties (Hinds, Madison and Rankin) that make up the Jackson, MS metropolitan statistical area (MSA). Participants were enrolled from each of 4 recruitment pools: (1) random, 17%, (2) volunteer, 30%, (3) currently enrolled in the Atherosclerosis Risk in Communities (ARIC) Study, 31%, and (4) secondary family members, 22%. The final cohort of 5,306 participants included 6.59% of all African American Jackson MSA residents, aged 35-84, during the baseline exam (N-76,426, US Census 2000). Among these, approximately 3,600 gave consent that allows genetic research and deposition of data into dbGaP. Major components of three clinic examinations (see study history) include medical history, physical examination, blood/urine analytes, and interview questions on areas such as physical activity, stress, coping and spirituality, racism and discrimination, socioeconomic position, and access to health care. Extensive clinical phenotyping includes anthropometrics, electrocardiography, carotid ultrasound, ankle-brachial blood pressure index, echocardiography, CT chest and abdomen for coronary and aortic calcification, liver fat, and subcutaneous and visceral fat measurements, and cardiac MRI. At 12-month intervals after the baseline clinic visit (Exam 1), participants have been contacted by telephone to update information, confirm vital statistics, document interim medical events, hospitalizations and functional status, and obtain additional sociocultural information. Questions about medical events, symptoms of cardiovascular disease and functional status are repeated annually. Ongoing cohort surveillance includes abstraction of medical records and death certificates for relevant International Classification of Diseases (ICD) codes and adjudication of nonfatal events and deaths. CMS data are currently being incorporated into the dataset. Note: Regarding date variables warehoused in the Jackson Heart Study (JHS) Cohort on dbGaP, the coordinating center has developed an algorithm that will systematically review and de-identify any of the (nearly 100) date-related variable types stored in the data package. To simultaneously minimize (i) de-identifiability of the data and (ii) impact on analyses utilizing sensitive data elements, a participant-level random number was generated to avoid the necessity of sharing any potentially sensitive data. The coordinating center maintains an archived linkage of these data in their raw form and regularly reviews ad hoc requests to utilize the raw data on a project-by-project basis. The JHS Cohort is utilized in the following dbGaP substudies. To view genotypes, other molecular data, and derived variables collected in these substudies, please click on the following substudies below or in the \"Substudies\" section of this top-level study page phs000286 JHS Cohort. phs000402 ESP Heart GO JHS phs000498 JHS Allelic Spectrum Seq phs000499 JHS CARephs001069 MI Gen JHS phs001098 T2D GENES Exome Seq phs001356 Exome Chip phs002256 Cardiometabolic Renal Proteomics phs002369 Metabolomics Insulin Resistance Study Weblinks: Jackson Heart Study JHS Publications Study Design: Prospective Longitudinal Cohort Study Type: Cohort Total number of consented subjects: 3889 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Jackson Heart Study (JHS) Cohort","short_name":"JHS_HMB-IRB-NPU_","commons":"BioData Catalyst","study_url":"","_subjects_count":0,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs000286.v7.p2.c2":{"gen3_discovery":{"authz":"/programs/parent/projects/JHS_DS-FDO-IRB-NPU_","tags":[],"_unique_id":"phs000286.v7.p2.c2","study_id":"phs000286.v7.p2.c2","study_description":"The Jackson Heart Study (JHS) is a large, community-based, observational study whose participants were recruited from urban and rural areas of the three counties (Hinds, Madison and Rankin) that make up the Jackson, MS metropolitan statistical area (MSA). Participants were enrolled from each of 4 recruitment pools: (1) random, 17%, (2) volunteer, 30%, (3) currently enrolled in the Atherosclerosis Risk in Communities (ARIC) Study, 31%, and (4) secondary family members, 22%. The final cohort of 5,306 participants included 6.59% of all African American Jackson MSA residents, aged 35-84, during the baseline exam (N-76,426, US Census 2000). Among these, approximately 3,600 gave consent that allows genetic research and deposition of data into dbGaP. Major components of three clinic examinations (see study history) include medical history, physical examination, blood/urine analytes, and interview questions on areas such as physical activity, stress, coping and spirituality, racism and discrimination, socioeconomic position, and access to health care. Extensive clinical phenotyping includes anthropometrics, electrocardiography, carotid ultrasound, ankle-brachial blood pressure index, echocardiography, CT chest and abdomen for coronary and aortic calcification, liver fat, and subcutaneous and visceral fat measurements, and cardiac MRI. At 12-month intervals after the baseline clinic visit (Exam 1), participants have been contacted by telephone to update information, confirm vital statistics, document interim medical events, hospitalizations and functional status, and obtain additional sociocultural information. Questions about medical events, symptoms of cardiovascular disease and functional status are repeated annually. Ongoing cohort surveillance includes abstraction of medical records and death certificates for relevant International Classification of Diseases (ICD) codes and adjudication of nonfatal events and deaths. CMS data are currently being incorporated into the dataset. Note: Regarding date variables warehoused in the Jackson Heart Study (JHS) Cohort on dbGaP, the coordinating center has developed an algorithm that will systematically review and de-identify any of the (nearly 100) date-related variable types stored in the data package. To simultaneously minimize (i) de-identifiability of the data and (ii) impact on analyses utilizing sensitive data elements, a participant-level random number was generated to avoid the necessity of sharing any potentially sensitive data. The coordinating center maintains an archived linkage of these data in their raw form and regularly reviews ad hoc requests to utilize the raw data on a project-by-project basis. The JHS Cohort is utilized in the following dbGaP substudies. To view genotypes, other molecular data, and derived variables collected in these substudies, please click on the following substudies below or in the \"Substudies\" section of this top-level study page phs000286 JHS Cohort. phs000402 ESP Heart GO JHS phs000498 JHS Allelic Spectrum Seq phs000499 JHS CARephs001069 MI Gen JHS phs001098 T2D GENES Exome Seq phs001356 Exome Chip phs002256 Cardiometabolic Renal Proteomics phs002369 Metabolomics Insulin Resistance Study Weblinks: Jackson Heart Study JHS Publications Study Design: Prospective Longitudinal Cohort Study Type: Cohort Total number of consented subjects: 3889 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Jackson Heart Study (JHS) Cohort","short_name":"JHS_DS-FDO-IRB-NPU_","commons":"BioData Catalyst","study_url":"","_subjects_count":0,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs000286.v7.p2.c3":{"gen3_discovery":{"authz":"/programs/parent/projects/JHS_HMB-IRB_","tags":[],"_unique_id":"phs000286.v7.p2.c3","study_id":"phs000286.v7.p2.c3","study_description":"The Jackson Heart Study (JHS) is a large, community-based, observational study whose participants were recruited from urban and rural areas of the three counties (Hinds, Madison and Rankin) that make up the Jackson, MS metropolitan statistical area (MSA). Participants were enrolled from each of 4 recruitment pools: (1) random, 17%, (2) volunteer, 30%, (3) currently enrolled in the Atherosclerosis Risk in Communities (ARIC) Study, 31%, and (4) secondary family members, 22%. The final cohort of 5,306 participants included 6.59% of all African American Jackson MSA residents, aged 35-84, during the baseline exam (N-76,426, US Census 2000). Among these, approximately 3,600 gave consent that allows genetic research and deposition of data into dbGaP. Major components of three clinic examinations (see study history) include medical history, physical examination, blood/urine analytes, and interview questions on areas such as physical activity, stress, coping and spirituality, racism and discrimination, socioeconomic position, and access to health care. Extensive clinical phenotyping includes anthropometrics, electrocardiography, carotid ultrasound, ankle-brachial blood pressure index, echocardiography, CT chest and abdomen for coronary and aortic calcification, liver fat, and subcutaneous and visceral fat measurements, and cardiac MRI. At 12-month intervals after the baseline clinic visit (Exam 1), participants have been contacted by telephone to update information, confirm vital statistics, document interim medical events, hospitalizations and functional status, and obtain additional sociocultural information. Questions about medical events, symptoms of cardiovascular disease and functional status are repeated annually. Ongoing cohort surveillance includes abstraction of medical records and death certificates for relevant International Classification of Diseases (ICD) codes and adjudication of nonfatal events and deaths. CMS data are currently being incorporated into the dataset. Note: Regarding date variables warehoused in the Jackson Heart Study (JHS) Cohort on dbGaP, the coordinating center has developed an algorithm that will systematically review and de-identify any of the (nearly 100) date-related variable types stored in the data package. To simultaneously minimize (i) de-identifiability of the data and (ii) impact on analyses utilizing sensitive data elements, a participant-level random number was generated to avoid the necessity of sharing any potentially sensitive data. The coordinating center maintains an archived linkage of these data in their raw form and regularly reviews ad hoc requests to utilize the raw data on a project-by-project basis. The JHS Cohort is utilized in the following dbGaP substudies. To view genotypes, other molecular data, and derived variables collected in these substudies, please click on the following substudies below or in the \"Substudies\" section of this top-level study page phs000286 JHS Cohort. phs000402 ESP Heart GO JHS phs000498 JHS Allelic Spectrum Seq phs000499 JHS CARephs001069 MI Gen JHS phs001098 T2D GENES Exome Seq phs001356 Exome Chip phs002256 Cardiometabolic Renal Proteomics phs002369 Metabolomics Insulin Resistance Study Weblinks: Jackson Heart Study JHS Publications Study Design: Prospective Longitudinal Cohort Study Type: Cohort Total number of consented subjects: 3889 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Jackson Heart Study (JHS) Cohort","short_name":"JHS_HMB-IRB_","commons":"BioData Catalyst","study_url":"","_subjects_count":0,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs000286.v7.p2.c4":{"gen3_discovery":{"authz":"/programs/parent/projects/JHS_DS-FDO-IRB_","tags":[],"_unique_id":"phs000286.v7.p2.c4","study_id":"phs000286.v7.p2.c4","study_description":"The Jackson Heart Study (JHS) is a large, community-based, observational study whose participants were recruited from urban and rural areas of the three counties (Hinds, Madison and Rankin) that make up the Jackson, MS metropolitan statistical area (MSA). Participants were enrolled from each of 4 recruitment pools: (1) random, 17%, (2) volunteer, 30%, (3) currently enrolled in the Atherosclerosis Risk in Communities (ARIC) Study, 31%, and (4) secondary family members, 22%. The final cohort of 5,306 participants included 6.59% of all African American Jackson MSA residents, aged 35-84, during the baseline exam (N-76,426, US Census 2000). Among these, approximately 3,600 gave consent that allows genetic research and deposition of data into dbGaP. Major components of three clinic examinations (see study history) include medical history, physical examination, blood/urine analytes, and interview questions on areas such as physical activity, stress, coping and spirituality, racism and discrimination, socioeconomic position, and access to health care. Extensive clinical phenotyping includes anthropometrics, electrocardiography, carotid ultrasound, ankle-brachial blood pressure index, echocardiography, CT chest and abdomen for coronary and aortic calcification, liver fat, and subcutaneous and visceral fat measurements, and cardiac MRI. At 12-month intervals after the baseline clinic visit (Exam 1), participants have been contacted by telephone to update information, confirm vital statistics, document interim medical events, hospitalizations and functional status, and obtain additional sociocultural information. Questions about medical events, symptoms of cardiovascular disease and functional status are repeated annually. Ongoing cohort surveillance includes abstraction of medical records and death certificates for relevant International Classification of Diseases (ICD) codes and adjudication of nonfatal events and deaths. CMS data are currently being incorporated into the dataset. Note: Regarding date variables warehoused in the Jackson Heart Study (JHS) Cohort on dbGaP, the coordinating center has developed an algorithm that will systematically review and de-identify any of the (nearly 100) date-related variable types stored in the data package. To simultaneously minimize (i) de-identifiability of the data and (ii) impact on analyses utilizing sensitive data elements, a participant-level random number was generated to avoid the necessity of sharing any potentially sensitive data. The coordinating center maintains an archived linkage of these data in their raw form and regularly reviews ad hoc requests to utilize the raw data on a project-by-project basis. The JHS Cohort is utilized in the following dbGaP substudies. To view genotypes, other molecular data, and derived variables collected in these substudies, please click on the following substudies below or in the \"Substudies\" section of this top-level study page phs000286 JHS Cohort. phs000402 ESP Heart GO JHS phs000498 JHS Allelic Spectrum Seq phs000499 JHS CARephs001069 MI Gen JHS phs001098 T2D GENES Exome Seq phs001356 Exome Chip phs002256 Cardiometabolic Renal Proteomics phs002369 Metabolomics Insulin Resistance Study Weblinks: Jackson Heart Study JHS Publications Study Design: Prospective Longitudinal Cohort Study Type: Cohort Total number of consented subjects: 3889 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Jackson Heart Study (JHS) Cohort","short_name":"JHS_DS-FDO-IRB_","commons":"BioData Catalyst","study_url":"","_subjects_count":0,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs000287.v7.p1.c1":{"gen3_discovery":{"authz":"/programs/parent/projects/CHS_HMB-MDS_","tags":[{"name":"Parent","category":"Program"},{"name":"DCC Harmonized","category":"Data Type"},{"name":"Clinical Phenotype","category":"Data Type"},{"name":"dbGaP","category":"Study Registration"}],"_unique_id":"phs000287.v7.p1.c1","study_id":"phs000287.v7.p1.c1","study_description":"The Cardiovascular Health Study (CHS) is a prospective study of risk factors for development and progression of CHD and stroke in people aged 65 years and older. The 5,888 study participants were recruited from four U.S. communities and have undergone extensive clinic examinations for evaluation of markers of subclinical cardiovascular disease. The original cohort, enrolled in 1989-90, totaled 5,201 participants. A supplemental cohort of 687 predominantly African-American participants was enrolled in 1992-93. Clinic examinations were performed at study baseline and at annual visits through 1998-1999, and again in 2005-2006. Examination components included medical and personal history, medication inventory, ECG, blood pressure, anthropometry, assessment of physical and cognitive function, and depression screening. Other components done less frequently included phlebotomy, spirometry, echocardiography, carotid ultrasound, cerebral magnetic resonance imaging, measurement of ankle-brachial index and retinal exam. Participants were contacted by telephone annually between exams to collect information about hospitalizations and potential cardiovascular events. Since 1999, participants have been contacted every six months by phone, primarily to identify cardiovascular events and to assess physical and cognitive health. Standard protocols for the identification and adjudication of events were implemented during follow-up. The adjudicated events are myocardial infarction, angina, heart failure (HF), stroke, transient ischemic attack (TIA), claudication and mortality.The Cardiovascular Health Study Cohort is utilized in the following dbGaP substudies. To view genotypes, analysis, expression data, other molecular data, and derived variables collected in these substudies, please click on the following substudies below or in the \"Substudies\" section of this top-level study page phs000287 Cardiovascular Health Study (CHS) Cohort: an NHLBI-funded observational study of risk factors for cardiovascular disease in adults 65 years or older. phs000226 STAMPEED: Cardiovascular Health Study (CHS) phs000301 PAGE: CaLiCo: Cardiovascular Health Study (CHS) phs000377 CARe: Candidate Gene Association Resource (CARe) phs000400 GO-ESP: Heart Cohorts Exome Sequencing Project (CHS) phs000667 CHARGE: Cardiovascular Health Study (CHS) Study Weblinks: CHS Study Design: Prospective Longitudinal Cohort Study Type: Longitudinal Total number of consented subjects: 5609 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Cardiovascular Health Study (CHS) Cohort: an NHLBI-funded observational study of risk factors for cardiovascular disease in adults 65 years or older","short_name":"CHS_HMB-MDS_","commons":"BioData Catalyst","study_url":"https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000287.v7.p1","_subjects_count":5382,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs000287.v7.p1.c2":{"gen3_discovery":{"authz":"/programs/parent/projects/CHS_HMB-NPU-MDS_","tags":[{"name":"Parent","category":"Program"},{"name":"DCC Harmonized","category":"Data Type"},{"name":"Clinical Phenotype","category":"Data Type"},{"name":"dbGaP","category":"Study Registration"}],"_unique_id":"phs000287.v7.p1.c2","study_id":"phs000287.v7.p1.c2","study_description":"The Cardiovascular Health Study (CHS) is a prospective study of risk factors for development and progression of CHD and stroke in people aged 65 years and older. The 5,888 study participants were recruited from four U.S. communities and have undergone extensive clinic examinations for evaluation of markers of subclinical cardiovascular disease. The original cohort, enrolled in 1989-90, totaled 5,201 participants. A supplemental cohort of 687 predominantly African-American participants was enrolled in 1992-93. Clinic examinations were performed at study baseline and at annual visits through 1998-1999, and again in 2005-2006. Examination components included medical and personal history, medication inventory, ECG, blood pressure, anthropometry, assessment of physical and cognitive function, and depression screening. Other components done less frequently included phlebotomy, spirometry, echocardiography, carotid ultrasound, cerebral magnetic resonance imaging, measurement of ankle-brachial index and retinal exam. Participants were contacted by telephone annually between exams to collect information about hospitalizations and potential cardiovascular events. Since 1999, participants have been contacted every six months by phone, primarily to identify cardiovascular events and to assess physical and cognitive health. Standard protocols for the identification and adjudication of events were implemented during follow-up. The adjudicated events are myocardial infarction, angina, heart failure (HF), stroke, transient ischemic attack (TIA), claudication and mortality.The Cardiovascular Health Study Cohort is utilized in the following dbGaP substudies. To view genotypes, analysis, expression data, other molecular data, and derived variables collected in these substudies, please click on the following substudies below or in the \"Substudies\" section of this top-level study page phs000287 Cardiovascular Health Study (CHS) Cohort: an NHLBI-funded observational study of risk factors for cardiovascular disease in adults 65 years or older. phs000226 STAMPEED: Cardiovascular Health Study (CHS) phs000301 PAGE: CaLiCo: Cardiovascular Health Study (CHS) phs000377 CARe: Candidate Gene Association Resource (CARe) phs000400 GO-ESP: Heart Cohorts Exome Sequencing Project (CHS) phs000667 CHARGE: Cardiovascular Health Study (CHS) Study Weblinks: CHS Study Design: Prospective Longitudinal Cohort Study Type: Longitudinal Total number of consented subjects: 5609 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Cardiovascular Health Study (CHS) Cohort: an NHLBI-funded observational study of risk factors for cardiovascular disease in adults 65 years or older","short_name":"CHS_HMB-NPU-MDS_","commons":"BioData Catalyst","study_url":"https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000287.v7.p1","_subjects_count":217,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs000287.v7.p1.c3":{"gen3_discovery":{"authz":"/programs/parent/projects/CHS_DS-CVD-MDS_","tags":[{"name":"Parent","category":"Program"},{"name":"DCC Harmonized","category":"Data Type"},{"name":"Clinical Phenotype","category":"Data Type"},{"name":"dbGaP","category":"Study Registration"}],"_unique_id":"phs000287.v7.p1.c3","study_id":"phs000287.v7.p1.c3","study_description":"The Cardiovascular Health Study (CHS) is a prospective study of risk factors for development and progression of CHD and stroke in people aged 65 years and older. The 5,888 study participants were recruited from four U.S. communities and have undergone extensive clinic examinations for evaluation of markers of subclinical cardiovascular disease. The original cohort, enrolled in 1989-90, totaled 5,201 participants. A supplemental cohort of 687 predominantly African-American participants was enrolled in 1992-93. Clinic examinations were performed at study baseline and at annual visits through 1998-1999, and again in 2005-2006. Examination components included medical and personal history, medication inventory, ECG, blood pressure, anthropometry, assessment of physical and cognitive function, and depression screening. Other components done less frequently included phlebotomy, spirometry, echocardiography, carotid ultrasound, cerebral magnetic resonance imaging, measurement of ankle-brachial index and retinal exam. Participants were contacted by telephone annually between exams to collect information about hospitalizations and potential cardiovascular events. Since 1999, participants have been contacted every six months by phone, primarily to identify cardiovascular events and to assess physical and cognitive health. Standard protocols for the identification and adjudication of events were implemented during follow-up. The adjudicated events are myocardial infarction, angina, heart failure (HF), stroke, transient ischemic attack (TIA), claudication and mortality.The Cardiovascular Health Study Cohort is utilized in the following dbGaP substudies. To view genotypes, analysis, expression data, other molecular data, and derived variables collected in these substudies, please click on the following substudies below or in the \"Substudies\" section of this top-level study page phs000287 Cardiovascular Health Study (CHS) Cohort: an NHLBI-funded observational study of risk factors for cardiovascular disease in adults 65 years or older. phs000226 STAMPEED: Cardiovascular Health Study (CHS) phs000301 PAGE: CaLiCo: Cardiovascular Health Study (CHS) phs000377 CARe: Candidate Gene Association Resource (CARe) phs000400 GO-ESP: Heart Cohorts Exome Sequencing Project (CHS) phs000667 CHARGE: Cardiovascular Health Study (CHS) Study Weblinks: CHS Study Design: Prospective Longitudinal Cohort Study Type: Longitudinal Total number of consented subjects: 5609 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Cardiovascular Health Study (CHS) Cohort: an NHLBI-funded observational study of risk factors for cardiovascular disease in adults 65 years or older","short_name":"CHS_DS-CVD-MDS_","commons":"BioData Catalyst","study_url":"https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000287.v7.p1","_subjects_count":2,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs000287.v7.p1.c4":{"gen3_discovery":{"authz":"/programs/parent/projects/CHS_DS-CVD-NPU-MDS_","tags":[{"name":"Parent","category":"Program"},{"name":"DCC Harmonized","category":"Data Type"},{"name":"Clinical Phenotype","category":"Data Type"},{"name":"dbGaP","category":"Study Registration"}],"_unique_id":"phs000287.v7.p1.c4","study_id":"phs000287.v7.p1.c4","study_description":"The Cardiovascular Health Study (CHS) is a prospective study of risk factors for development and progression of CHD and stroke in people aged 65 years and older. The 5,888 study participants were recruited from four U.S. communities and have undergone extensive clinic examinations for evaluation of markers of subclinical cardiovascular disease. The original cohort, enrolled in 1989-90, totaled 5,201 participants. A supplemental cohort of 687 predominantly African-American participants was enrolled in 1992-93. Clinic examinations were performed at study baseline and at annual visits through 1998-1999, and again in 2005-2006. Examination components included medical and personal history, medication inventory, ECG, blood pressure, anthropometry, assessment of physical and cognitive function, and depression screening. Other components done less frequently included phlebotomy, spirometry, echocardiography, carotid ultrasound, cerebral magnetic resonance imaging, measurement of ankle-brachial index and retinal exam. Participants were contacted by telephone annually between exams to collect information about hospitalizations and potential cardiovascular events. Since 1999, participants have been contacted every six months by phone, primarily to identify cardiovascular events and to assess physical and cognitive health. Standard protocols for the identification and adjudication of events were implemented during follow-up. The adjudicated events are myocardial infarction, angina, heart failure (HF), stroke, transient ischemic attack (TIA), claudication and mortality.The Cardiovascular Health Study Cohort is utilized in the following dbGaP substudies. To view genotypes, analysis, expression data, other molecular data, and derived variables collected in these substudies, please click on the following substudies below or in the \"Substudies\" section of this top-level study page phs000287 Cardiovascular Health Study (CHS) Cohort: an NHLBI-funded observational study of risk factors for cardiovascular disease in adults 65 years or older. phs000226 STAMPEED: Cardiovascular Health Study (CHS) phs000301 PAGE: CaLiCo: Cardiovascular Health Study (CHS) phs000377 CARe: Candidate Gene Association Resource (CARe) phs000400 GO-ESP: Heart Cohorts Exome Sequencing Project (CHS) phs000667 CHARGE: Cardiovascular Health Study (CHS) Study Weblinks: CHS Study Design: Prospective Longitudinal Cohort Study Type: Longitudinal Total number of consented subjects: 5609 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Cardiovascular Health Study (CHS) Cohort: an NHLBI-funded observational study of risk factors for cardiovascular disease in adults 65 years or older","short_name":"CHS_DS-CVD-NPU-MDS_","commons":"BioData Catalyst","study_url":"https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000287.v7.p1","_subjects_count":8,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs000289.v2.p1.c1":{"gen3_discovery":{"authz":"/programs/parent/projects/Mayo_VTE_GRU_","tags":[{"name":"Parent","category":"Program"},{"name":"DCC Harmonized","category":"Data Type"},{"name":"Clinical Phenotype","category":"Data Type"},{"name":"dbGaP","category":"Study Registration"}],"_unique_id":"phs000289.v2.p1.c1","study_id":"phs000289.v2.p1.c1","study_description":"Overview: Our overall long-term goal is to determine risk factors for the complex (multifactorial) disease, venous thromboembolism (VTE), that will allow physicians to stratify individual patient risk and target VTE prophylaxis to those who would benefit most. In this genome-wide association case-control study (1300 cases and 1300 controls) we hope to identify susceptibility variants for VTE. Mutations within genes encoding for important components of the anticoagulant, procoagulant, fibrinolytic, and innate immunity pathways are risk factors for VTE. We hypothesize that other genes within these four pathways or within other pathways also are VTE disease-susceptibility genes. Therefore, we performed a genome wide association (GWA) screen and analysis using the Illumina 660W platform to identify SNPs within 1,300 clinic-based, non-cancer VTE cases primarily from Minnesota and the upper Midwest USA, and 1300 clinic-based, unrelated controls frequency-matched on patient age, gender, myocardial infarction/stroke status and state of residence. This is a subset of a slightly larger candidate gene study using 1500 case-control pairs to identify haplotype-tagging SNPs (ht-SNPs) in a large set of candidate genes (n~750) within the anticoagulant, procoagulant, fibrinolytic, and innate immunity pathways. Study Populations. Cases. VTE cases were consecutive Mayo Clinic outpatients with objectively-diagnosed deep vein thrombosis (DVT) and/or pulmonary embolism (PE) residing in the upper Midwest and referred by Mayo Clinic physician to the Mayo Clinic Special Coagulation Laboratory for clinical diagnostic testing to evaluate for an acquired or inherited thrombophilia, or to the Mayo Clinic Thrombophilia Center. Any person contacted to be a control but discovered to have had a VTE was evaluated for inclusion as a case. Cases were primarily residents from Minnesota, Wisconsin, Iowa, Michigan, Illinois, North or South Dakota, Nebraska, Kansas, Missouri and Indiana. A DVT or PE was categorized as objectively diagnosed when (a) confirmed by venography or pulmonary angiography, or pathology examination of thrombus removed at surgery, or (b) if at least one non-invasive test (compression duplex ultrasonography, lung scan, computed tomography scan, magnetic resonance imaging) was positive. A VTE was defined as: Proximal leg deep vein thrombosis (DVT), which includes the common iliac, internal iliac, external iliac, common femoral, superficial [now termed \"femoral\"] femoral, deep femoral [sometimes referred to as \"profunda\" femoral] and/or popliteal veins. (Note: greater and lesser saphenous veins, or other superficial or perforator veins, were not included as proximal or distal leg DVT). Distal leg DVT (or \"isolated calf DVT\"), which includes the anterior tibial, posterior tibial and/or peroneal veins. (Note: gastrocnemius, soleal and/or sural [e.g., \"deep muscular veins\" of the calf] vein thrombosis was not included as distal leg DVT). Arm DVT, which includes the axillary, subclavian and/or innominate (brachiocephalic) veins. (Note: jugular [internal or external], cephalic and brachial vein thrombosis was not included in \"arm DVT\"). Hepatic, portal, splenic, superior or inferior mesenteric, and/or renal vein thrombosis. (Note: ovarian, testicular, peri-prostatic and/or pelvic vein thrombosis was not included). Cerebral vein thrombosis (includes cerebral or dural sinus or vein, saggital sinus or vein, and/or transverse sinus or vein thrombosis). Inferior vena cava (IVC) thrombosis Superior vena cava (SVC) thrombosis Pulmonary embolism Patients with VTE related to active cancer, antiphospholipid syndrome, inflammatory bowel disease, vasculitis, a rheumatoid or other autoimmune disorder, a vascular anomaly (e.g., Klippel-Trénaunay syndrome, etc.), heparin-induced thrombocytopenia, or a mechanical cause for DVT (e.g., arm DVT or SVC thrombosis related to a central venous catheter or transvenous pacemaker, portal and/or splenic vein thrombosis related to liver cirrhosis, IVC thrombosis related to retroperitoneal fibrosis, etc.), with hemodialysis arteriovenous fistula thrombosis, or with prior liver or bone marrow transplantation were excluded. Controls. A Mayo Clinic outpatient control group was prospectively recruited for this study. Controls were frequency-matched on the age group (18-29, 30-39, 40-49, 50-59, 60-69, 70-79, and 80+ years), sex, myocardial infarction/stroke status, and state of residence distribution of the cases. We selected clinic-based controls using a controls' database of persons undergoing general medical examinations in the Mayo Clinic Departments of General Internal Medicine or Primary Care Internal Medicine. Additionally persons undergoing evaluation at the Mayo Clinic Sports Medicine Center, and the Department of Family Medicine were screened for inclusion as controls. This study is part of the Gene Environment Association Studies initiative (GENEVA, http://www.genevastudy.org) funded by the trans-NIH Genes, Environment, and Health Initiative (GEI). The overarching goal is to identify novel genetic factors that contribute to venous thrombosis through large-scale genome-wide association studies of 1,300 clinic-based, VTE cases and 1300 clinic-based, unrelated controls. Genotyping was performed at the Johns Hopkins University Center for Inherited Disease Research (CIDR). Data cleaning and harmonization were done at the GEI-funded GENEVA Coordinating Center at the University of Washington. Study Design: Case-Control Study Type: Case-Control dbGaP estimated ancestry using GRAF-pop Total number of consented subjects: 2597 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"National Human Genome Research Institute (NHGRI) GENEVA Genome-Wide Association Study of Venous Thrombosis (GWAS of VTE)","short_name":"Mayo_VTE_GRU_","commons":"BioData Catalyst","study_url":"https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000289.v2.p1","_subjects_count":2597,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs000290.v1.p1.c1":{"gen3_discovery":{"authz":"/programs/heartfailure/projects/LungExome_PAH_GRU","tags":[],"_unique_id":"phs000290.v1.p1.c1","study_id":"phs000290.v1.p1.c1","study_description":"The NHLBI \"Grand Opportunity\" Exome Sequencing Project (GO-ESP), a signature project of the NHLBI Recovery Act investment, was designed to identify genetic variants in coding regions (exons) of the human genome (the \"exome\") that are associated with heart, lung and blood diseases. These and related diseases that are of high impact to public health and individuals from diverse racial and ethnic groups will be studied. These data may help researchers understand the causes of disease, contributing to better ways to prevent, diagnose, and treat diseases, as well as determine whether to tailor prevention and treatments to specific populations. This could lead to more effective treatments and reduce the likelihood of side effects. GO-ESP is comprised of five collaborative components: 3 cohort consortia - HeartGO, LungGO, and WHISP - and 2 sequencing centers - BroadGO and SeattleGO. The syndrome of pulmonary hypertension (PH) is a pulmonary disease that carries very high morbidity and mortality. Pulmonary arterial hypertension (PAH) is a category of PH (WHO Group 1) that includes several entities (idiopathic or heritable PAH, and PAH associated with other diseases such as connective tissue diseases including scleroderma-associated PAH) and carries a dismal prognosis, in particular when it relates to scleroderma-associated PAH (median survival of about 4 years). It is believed that the severity of structural changes involving the pulmonary vasculature and right ventricular failure are genetically determined. The 'Genomics and Genetics of Pulmonary Arterial Hypertension' study at Johns Hopkins University aims to identify genetic determinants associated with risk of PAH in a cohort of European American and African American participants with and without PAH. The study also focuses on patients with scleroderma, who are further stratified according to those who have or do not have PAH. The broad goals of the Lung GO/ESP-GO falls into two general categories: (i) discovery of all variants (i.e., common and rare) in all protein-coding regions of the human genome (i.e., the exome) conferring risk to complex pulmonary diseases including PAH. The Johns Hopkins University PAH cohort offers a unique opportunity to elucidate genetic variants that cause PAH. Study Weblinks: NHLBI GO ESP Project Study Design: Case-Control Study Type: Case-Control Exome Sequencing dbGaP estimated ancestry using GRAF-pop Total number of consented subjects: 96 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"NHLBI GO-ESP: Lung Cohorts Exome Sequencing Project (Pulmonary Arterial Hypertension)","short_name":"LungExome_PAH_GRU","commons":"BioData Catalyst","study_url":"","_subjects_count":96,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs000291.v2.p1.c1":{"gen3_discovery":{"authz":"/programs/heartfailure/projects/LHS-COPD_GRU","tags":[],"_unique_id":"phs000291.v2.p1.c1","study_id":"phs000291.v2.p1.c1","study_description":"The NHLBI \"Grand Opportunity\" Exome Sequencing Project (GO-ESP), a signature project of the NHLBI Recovery Act investment, was designed to identify genetic variants in coding regions (exons) of the human genome (the \"exome\") that are associated with heart, lung and blood diseases. These and related diseases that are of high impact to public health and individuals from diverse racial and ethnic groups will be studied. These data may help researchers understand the causes of disease, contributing to better ways to prevent, diagnose, and treat diseases, as well as determine whether to tailor prevention and treatments to specific populations. This could lead to more effective treatments and reduce the likelihood of side effects. GO-ESP is comprised of five collaborative components: 3 cohort consortia - HeartGO, LungGO, and WHISP - and 2 sequencing centers - BroadGO and SeattleGO. The Lung Health Study I was a randomized multicenter clinical trial with 5887 participants carried out from October 1986 to April 1994, designed to test the effectiveness of smoking cessation and bronchodilator administration in smokers aged 35 to 60 with mild lung function impairment. Participants were randomly assigned to one of three groups: usual care, who received no intervention smoking intervention with the inhaled bronchodilator ipratroprium bromide smoking intervention with an inhaled placebo The effect of intervention was evaluated by the rate of decline of forced expiratory volume in one second (FEV1). Study Weblinks: Lung Health Study NHLBI GO ESP Project Study Design: Prospective Longitudinal Cohort Study Type: Longitudinal Exome Sequencing dbGaP estimated ancestry using GRAF-pop Total number of consented subjects: 337 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"NHLBI GO-ESP: Lung Cohorts Exome Sequencing Project (Lung Health Study of Chronic Obstructive Pulmonary Disease)","short_name":"LHS-COPD_GRU","commons":"BioData Catalyst","study_url":"","_subjects_count":337,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs000294.v1.p1.c1":{"gen3_discovery":{"authz":"/programs/heartfailure/projects/STAMPEED_MIGen_GRU","tags":[],"_unique_id":"phs000294.v1.p1.c1","study_id":"phs000294.v1.p1.c1","study_description":"Myocardial infarction (MI) is a common complex disease and the leading cause of death and disability worldwide. The genetic basis of this disease is largely unknown. It has been thought that early-onset MI events would have a substantially greater heritability, thus making DNA collections with younger individuals desirable. More recently, genome-wide association studies have become feasible through the development of whole genome arrays and a large catalogue of common variants reported in the International HapMap database. This study aims to use Affymetrix genotyping platform to do a whole genome scan in 3000 early-onset MI cases and 3000 matched controls from 6 study collection sites. Study Design: Case-Control Study Type: Case-Control dbGaP estimated ancestry using GRAF-pop Total number of consented subjects: 6042 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"STAMPEED: Myocardial Infarction Genetics Consortium (MIGen)","short_name":"STAMPEED_MIGen_GRU","commons":"BioData Catalyst","study_url":"","_subjects_count":6042,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs000296.v5.p2.c1":{"gen3_discovery":{"authz":"/programs/dbGaP/projects/GO_ESP_COPDGene_HMB","tags":[],"_unique_id":"phs000296.v5.p2.c1","study_id":"phs000296.v5.p2.c1","study_description":"This sub-study phs000296 ESP LungGO COPDGene contains genotype derived from sequence data and selected phenotype of subjects available from the phs000179 COPDGene_v6 study. Summary level phenotypes for the NHLBI COPDGene Cohort study participants can be viewed at the top-level study page eric.austin@Vanderbilt.Edu COPDGene Cohort. Individual level phenotype data and molecular data for all COPDGene Cohort top-level study and sub-study are available by requesting Authorized Access to the NHLBI COPDGene Cohort phs000179 COPDGene_v6 study. The NHLBI \"Grand Opportunity\" Exome Sequencing Project (GO-ESP), a signature project of the NHLBI Recovery Act investment, was designed to identify genetic variants in coding regions (exons) of the human genome (the \"exome\") that are associated with heart, lung and blood diseases. These and related diseases that are of high impact to public health and individuals from diverse racial and ethnic groups will be studied. These data may help researchers understand the causes of disease, contributing to better ways to prevent, diagnose, and treat diseases, as well as determine whether to tailor prevention and treatments to specific populations. This could lead to more effective treatments and reduce the likelihood of side effects. GO-ESP is comprised of five collaborative components: 3 cohort consortia - HeartGO, LungGO, and WHISP - and 2 sequencing centers - BroadGO and SeattleGO. Chronic obstructive pulmonary disease (COPD) is the fourth leading cause of death in the United States and the only leading cause of death that is steadily increasing in frequency. This project will establish a racially diverse cohort that is sufficiently large and appropriately designed for genome-wide association analysis of COPD. A total of 10,000 subjects will be recruited, including control smokers, definite COPD cases (GOLD Stage 2 to 4), and subjects not included in either group (GOLD 1 or GOLD-Unclassified). This cohort will be used for cross-sectional analysis, although long-term longitudinal follow-up will be a future goal. The primary focus of the study will be genome-wide association analysis to identify the genetic risk factors that determine susceptibility for COPD and COPD-related phenotypes. Detailed phenotyping of both cases and controls, including chest CT scan assessment of emphysema and airway disease, will allow identification of genetic determinants for the heterogeneous components of the COPD syndrome. The hypotheses to be studied are: 1) Precise phenotypic characterization of COPD subjects using computed tomography, as well as clinical and physiological measures, will provide data that will enable the broad COPD syndrome to be decomposed into clinically significant subtypes. 2) Genome-wide association studies will identify genetic determinants for COPD susceptibility that will provide insight into clinically relevant COPD subtypes. 3) Distinct genetic determinants influence the development of emphysema and airway disease. The initial phase of genome-wide association analysis included 500 COPD cases and 500 control subjects (all non-Hispanic White) genotyped with the Illumina Omni-1 chip, but plans are being developed to obtain genome-wide association analysis on the entire study cohort (using the Illumina Omni-Express chip). Unique aspects of the study include: 1) Inclusion of large numbers of African American subjects (approximately 1/3 of the cohort); 2) Obtaining chest CT scans (including inspiratory and expiratory images); and 3) Inclusion of the full range of disease severity. Study Weblinks: COPDGene NHLBI GO ESP Project Study Design: Case-Control Study Type: Case-Control Exome Sequencing dbGaP estimated ancestry using GRAF-pop Total number of consented subjects: 289 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"NHLBI GO-ESP: Lung Cohorts Exome Sequencing Project (COPDGene)","short_name":"GO_ESP_COPDGene_HMB","commons":"BioData Catalyst","study_url":"","_subjects_count":289,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs000296.v5.p2.c2":{"gen3_discovery":{"authz":"/programs/dbGaP/projects/GO_ESP_COPDGene_DS-CS","tags":[],"_unique_id":"phs000296.v5.p2.c2","study_id":"phs000296.v5.p2.c2","study_description":"This sub-study phs000296 ESP LungGO COPDGene contains genotype derived from sequence data and selected phenotype of subjects available from the phs000179 COPDGene_v6 study. Summary level phenotypes for the NHLBI COPDGene Cohort study participants can be viewed at the top-level study page eric.austin@Vanderbilt.Edu COPDGene Cohort. Individual level phenotype data and molecular data for all COPDGene Cohort top-level study and sub-study are available by requesting Authorized Access to the NHLBI COPDGene Cohort phs000179 COPDGene_v6 study. The NHLBI \"Grand Opportunity\" Exome Sequencing Project (GO-ESP), a signature project of the NHLBI Recovery Act investment, was designed to identify genetic variants in coding regions (exons) of the human genome (the \"exome\") that are associated with heart, lung and blood diseases. These and related diseases that are of high impact to public health and individuals from diverse racial and ethnic groups will be studied. These data may help researchers understand the causes of disease, contributing to better ways to prevent, diagnose, and treat diseases, as well as determine whether to tailor prevention and treatments to specific populations. This could lead to more effective treatments and reduce the likelihood of side effects. GO-ESP is comprised of five collaborative components: 3 cohort consortia - HeartGO, LungGO, and WHISP - and 2 sequencing centers - BroadGO and SeattleGO. Chronic obstructive pulmonary disease (COPD) is the fourth leading cause of death in the United States and the only leading cause of death that is steadily increasing in frequency. This project will establish a racially diverse cohort that is sufficiently large and appropriately designed for genome-wide association analysis of COPD. A total of 10,000 subjects will be recruited, including control smokers, definite COPD cases (GOLD Stage 2 to 4), and subjects not included in either group (GOLD 1 or GOLD-Unclassified). This cohort will be used for cross-sectional analysis, although long-term longitudinal follow-up will be a future goal. The primary focus of the study will be genome-wide association analysis to identify the genetic risk factors that determine susceptibility for COPD and COPD-related phenotypes. Detailed phenotyping of both cases and controls, including chest CT scan assessment of emphysema and airway disease, will allow identification of genetic determinants for the heterogeneous components of the COPD syndrome. The hypotheses to be studied are: 1) Precise phenotypic characterization of COPD subjects using computed tomography, as well as clinical and physiological measures, will provide data that will enable the broad COPD syndrome to be decomposed into clinically significant subtypes. 2) Genome-wide association studies will identify genetic determinants for COPD susceptibility that will provide insight into clinically relevant COPD subtypes. 3) Distinct genetic determinants influence the development of emphysema and airway disease. The initial phase of genome-wide association analysis included 500 COPD cases and 500 control subjects (all non-Hispanic White) genotyped with the Illumina Omni-1 chip, but plans are being developed to obtain genome-wide association analysis on the entire study cohort (using the Illumina Omni-Express chip). Unique aspects of the study include: 1) Inclusion of large numbers of African American subjects (approximately 1/3 of the cohort); 2) Obtaining chest CT scans (including inspiratory and expiratory images); and 3) Inclusion of the full range of disease severity. Study Weblinks: COPDGene NHLBI GO ESP Project Study Design: Case-Control Study Type: Case-Control Exome Sequencing dbGaP estimated ancestry using GRAF-pop Total number of consented subjects: 289 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"NHLBI GO-ESP: Lung Cohorts Exome Sequencing Project (COPDGene)","short_name":"GO_ESP_COPDGene_DS-CS","commons":"BioData Catalyst","study_url":"","_subjects_count":0,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs000307.v20.p16.c1":{"gen3_discovery":{"authz":"/programs/dbGaP/projects/Allelic_Spectrum_FHS_HMB-IRB-MDS","tags":[],"_unique_id":"phs000307.v20.p16.c1","study_id":"phs000307.v20.p16.c1","study_description":"This substudy phs000307 Framingham Allelic Spectrum Project includes the generation of deep coverage targeted re-sequencing and variant identification for 216 genes in the Framingham Heart Study (FHS) sample collection, produced as part of NHLBI's Medical Resequencing projects. Summary level phenotypes for the Framingham Cohort study participants can be viewed at the top-level study page phs000007 Framingham Cohort. Individual level phenotype data and molecular data for all Framingham top-level study and substudies are available by requesting Authorized Access to the Framingham Cohort study phs000007. Cardiovascular disease (CVD) is the leading cause of death in the US, affecting 64 million Americans and costing over 368 billion dollars annually. To elucidate causes of CVD, NIH established the Framingham Heart Study (FHS) in 1948. In 1971, 5000 adult children and spouses of original FHS participants expanded the initial population-based cohort. The FHS Offspring cohort has now been followed for a decade beyond their 6th cardiovascular examination, providing incidence and prevalence data for CVD. These data indicate that diabetes mellitus, hyperlipidemia, hypertension, left ventricular hypertrophy, cigarette smoking, obesity, sedentary life style, and family history are major risk factors for development of atherosclerosis, coronary artery disease, myocardial infarction, heart failure, and stroke. The role of genetic variation is documented by substantial heritability to cardiovascular disease risk factors, left ventricular hypertrophy and subclinical atherosclerosis, as well as evidence for familial aggregation of common forms of cardiovascular disease such as coronary heart disease, heart failure and sudden cardiac death. Molecular genetic studies of Mendelian disorders (and, to a much more limited degree, association studies of common variants) have led to the identification of human gene mutations that influence important CVD phenotypes. Hundreds of mutations in over 100 genes are known to produce major effects on serum cholesterol, lipoprotein and glucose levels, blood pressure via renal handling of salt and water, myocardial contractile function and ventricular morphology, and cardiac electrophysiologic properties. The phenotypes produced by single gene defects (hypercholesterolemia, diabetes, hypertension, cardiac hypertrophy, and cardiac arrhythmias) are remarkably similar to the common cardiovascular disease risk factors found broadly within the general population, raising the hypothesis that the full allelic spectrum of CVD genes may, in sum, contribute substantially to overall CVD prevalence. To provide a comprehensive assessment of the frequency and distribution of rare and common allelic variation in previously defined cardiovascular genes in general populations with defined incident cardiovascular risks and disease, we have assembled a collaborative group that includes investigators with considerable expertise in the study of CVD genes and leading investigators in the FHS. Study Design: Prospective Longitudinal Cohort Study Type: Cohort Total number of consented subjects: 1623 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Framingham Heart Study Allelic Spectrum Project","short_name":"Allelic_Spectrum_FHS_HMB-IRB-MDS","commons":"BioData Catalyst","study_url":"","_subjects_count":1260,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs000307.v20.p16.c2":{"gen3_discovery":{"authz":"/programs/dbGaP/projects/Allelic_Spectrum_FHS_HMB-IRB-NPU-MDS","tags":[],"_unique_id":"phs000307.v20.p16.c2","study_id":"phs000307.v20.p16.c2","study_description":"This substudy phs000307 Framingham Allelic Spectrum Project includes the generation of deep coverage targeted re-sequencing and variant identification for 216 genes in the Framingham Heart Study (FHS) sample collection, produced as part of NHLBI's Medical Resequencing projects. Summary level phenotypes for the Framingham Cohort study participants can be viewed at the top-level study page phs000007 Framingham Cohort. Individual level phenotype data and molecular data for all Framingham top-level study and substudies are available by requesting Authorized Access to the Framingham Cohort study phs000007. Cardiovascular disease (CVD) is the leading cause of death in the US, affecting 64 million Americans and costing over 368 billion dollars annually. To elucidate causes of CVD, NIH established the Framingham Heart Study (FHS) in 1948. In 1971, 5000 adult children and spouses of original FHS participants expanded the initial population-based cohort. The FHS Offspring cohort has now been followed for a decade beyond their 6th cardiovascular examination, providing incidence and prevalence data for CVD. These data indicate that diabetes mellitus, hyperlipidemia, hypertension, left ventricular hypertrophy, cigarette smoking, obesity, sedentary life style, and family history are major risk factors for development of atherosclerosis, coronary artery disease, myocardial infarction, heart failure, and stroke. The role of genetic variation is documented by substantial heritability to cardiovascular disease risk factors, left ventricular hypertrophy and subclinical atherosclerosis, as well as evidence for familial aggregation of common forms of cardiovascular disease such as coronary heart disease, heart failure and sudden cardiac death. Molecular genetic studies of Mendelian disorders (and, to a much more limited degree, association studies of common variants) have led to the identification of human gene mutations that influence important CVD phenotypes. Hundreds of mutations in over 100 genes are known to produce major effects on serum cholesterol, lipoprotein and glucose levels, blood pressure via renal handling of salt and water, myocardial contractile function and ventricular morphology, and cardiac electrophysiologic properties. The phenotypes produced by single gene defects (hypercholesterolemia, diabetes, hypertension, cardiac hypertrophy, and cardiac arrhythmias) are remarkably similar to the common cardiovascular disease risk factors found broadly within the general population, raising the hypothesis that the full allelic spectrum of CVD genes may, in sum, contribute substantially to overall CVD prevalence. To provide a comprehensive assessment of the frequency and distribution of rare and common allelic variation in previously defined cardiovascular genes in general populations with defined incident cardiovascular risks and disease, we have assembled a collaborative group that includes investigators with considerable expertise in the study of CVD genes and leading investigators in the FHS. Study Design: Prospective Longitudinal Cohort Study Type: Cohort Total number of consented subjects: 1623 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Framingham Heart Study Allelic Spectrum Project","short_name":"Allelic_Spectrum_FHS_HMB-IRB-NPU-MDS","commons":"BioData Catalyst","study_url":"","_subjects_count":363,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs000349.v1.p1.c1":{"gen3_discovery":{"authz":"/programs/heartfailure/projects/SEA_GRU","tags":[],"_unique_id":"phs000349.v1.p1.c1","study_id":"phs000349.v1.p1.c1","study_description":"The SEA study is a genome-wide association study to identify genetic variants associated with premature atherosclerosis in subjects included in the Pathobiological Determinants of Atherosclerosis in Youth (PDAY) repository - a unique NHLBI resource including data, DNA and arterial specimens from over 3000 multi-ethnic subjects 15-34 years of age who died of non-atherosclerotic causes (mostly trauma). All PDAY subjects had post-mortem quantitative assessment of raised atherosclerotic lesions in their aorta and coronary arteries - making this the largest and most carefully phenotyped cohort for premature atherosclerosis in the world. The goal of the current project was to use the quantitative measure of raised atherosclerotic lesions in the PDAY cohort as the target phenotype for a genome-wide association study and to use quantitative measures of subclinical atherosclerosis (coronary calcium and carotid IMT) in the Multi-Ethnic Study of Atherosclerosis (MESA) to confirm or refute candidate loci identified from the PDAY analysis. Identifying genetic factors that predispose individuals to premature atherosclerosis could lead to more effective screening and early treatment of high risk individuals and suggest novel molecular targets for treatment and prevention interventions. Study Weblinks: SEA Study Design: Case-Control Study Type: Cross-Sectional Total number of consented subjects: 1068 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"SNPs and Extent of Atherosclerosis (SEA) Study","short_name":"SEA_GRU","commons":"BioData Catalyst","study_url":"","_subjects_count":1068,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs000354.v1.p1.c1":{"gen3_discovery":{"authz":"/programs/heartfailure/projects/Fam_PAH_GRU","tags":[],"_unique_id":"phs000354.v1.p1.c1","study_id":"phs000354.v1.p1.c1","study_description":"The NHLBI \"Grand Opportunity\" Exome Sequencing Project (GO-ESP), a signature project of the NHLBI Recovery Act investment, was designed to identify genetic variants in coding regions (exons) of the human genome (the \"exome\") that are associated with heart, lung and blood diseases. These and related diseases that are of high impact to public health and individuals from diverse racial and ethnic groups will be studied. These data may help researchers understand the causes of disease, contributing to better ways to prevent, diagnose, and treat diseases, as well as determine whether to tailor prevention and treatments to specific populations. This could lead to more effective treatments and reduce the likelihood of side effects. GO-ESP is comprised of five collaborative components: 3 cohort consortia - HeartGO, LungGO, and WHISP - and 2 sequencing centers - BroadGO and SeattleGO. Pulmonary arterial hypertension (PAH) is a progressive disease characterized by widespread occlusion of the smallest arteries of the lungs. Pulmonary vascular obstruction leads to increased pulmonary vascular resistance, which subsequently causes heart failure with mean survival of 3 years. PAH occurs at all ages and affects women more than twice as frequently as men. Sporadic Idiopathic pulmonary arterial hypertension (IPAH), comprises 94% of what was formerly known as primary pulmonary hypertension, and is clinically and pathologically indistinguishable from familial PAH (FPAH). Most FPAH is due to mutation in BMPR2, including more than 120 families in the US. Our goal here is to find other genes that are a basis for FPAH, so we selected for exome sequencing 5 families among 40 who do not have mutation in BMPR2, or other known genes (ACVRL1, SMAD8, ENG) that rarely are the basis for FPAH. Study Weblinks: NHLBI GO ESP Project: Family Studies Study Design: Prospective Longitudinal Cohort Study Type: Longitudinal Family Exome Sequencing dbGaP estimated ancestry using GRAF-pop Total number of consented subjects: 12 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"NHLBI GO-ESP Family Studies: Pulmonary Arterial Hypertension","short_name":"Fam_PAH_GRU","commons":"BioData Catalyst","study_url":"","_subjects_count":12,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs000362.v1.p1.c1":{"gen3_discovery":{"authz":"/programs/heartfailure/projects/Fam_FAF_HMB","tags":[],"_unique_id":"phs000362.v1.p1.c1","study_id":"phs000362.v1.p1.c1","study_description":"The NHLBI \"Grand Opportunity\" Exome Sequencing Project (GO-ESP), a signature project of the NHLBI Recovery Act investment, was designed to identify genetic variants in coding regions (exons) of the human genome (the \"exome\") that are associated with heart, lung and blood diseases. These and related diseases that are of high impact to public health and individuals from diverse racial and ethnic groups will be studied. These data may help researchers understand the causes of disease, contributing to better ways to prevent, diagnose, and treat diseases, as well as determine whether to tailor prevention and treatments to specific populations. This could lead to more effective treatments and reduce the likelihood of side effects. GO-ESP is comprised of five collaborative components: 3 cohort consortia - HeartGO, LungGO, and WHISP - and 2 sequencing centers - BroadGO and SeattleGO. Large epidemiological studies have demonstrated a significant heritable component in atrial fibrillation (AF), especially the Lone forms, suggesting a monogenic syndrome. Although substantial genetic contribution has been made to the etiology of AF, the specific genes have not yet been identified. The familial form of this disease remains poorly characterized and largely undetermined. Here we seek to identify, characterize and determine the natural course of AF in our clinical practice. We identified four large multi-generation families (FAF 1-4). In FAF 1-2, most family members have symptomatic paroxysmal Atrial Fibrillation (AF) and were adequately treated with a combination of rate and rhythm therapies. By contrast, the AF substrate in FAF 3 and 4 was resistant to anti-arrhythmic drugs and ablation therapies. Study Weblinks: NHLBI Grand Opportunity Exome Sequencing Project (ESP) Study Design: Family/Twin/Trios Study Type: Cohort Total number of consented subjects: 12 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"NHLBI GO-ESP: Family Studies (Familial Atrial Fibrillation)","short_name":"Fam_FAF_HMB","commons":"BioData Catalyst","study_url":"","_subjects_count":12,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs000363.v22.p16.c1":{"gen3_discovery":{"authz":"/programs/dbGaP/projects/SABRe_CVD_HMB-IRB-MDS","tags":[],"_unique_id":"phs000363.v22.p16.c1","study_id":"phs000363.v22.p16.c1","study_description":"This substudy phs000363 Framingham SABRe contains immunoassays, gene expression profiling, and microRNA data. Summary level phenotypes for the Framingham Cohort study participants can be viewed at the top-level study page phs000007 Framingham Cohort. Individual level phenotype data and molecular data for all Framingham top-level study and substudies are available by requesting Authorized Access to the Framingham Cohort study phs000007. Systems Approach to Biomarker Research in Cardiovascular Disease in the NHLBI's Framingham Heart Study: The SABRe CVD Initiative The NHLBI's Framingham Heart Study (FHS), one of the world's preeminent observational study settings, is devoted to increasing scientific knowledge by establishing a public resource of data and samples. For nearly 60 years, the people of Framingham have generously volunteered their time to this high-profile study and remain deeply committed to its success. The Systems Approach to Biomarker Research in Cardiovascular Disease Initiative (SABRe CVD Initiative) will generate extensive biomarker data from 7000 FHS participants using multiple high throughput platforms including immunoassays, proteomics, metabolomics/lipomics, and gene expression and microRNA profiling. SABRe will generate thousands of new biomarkers from each participant, with data deposited with the NCBI and linked to the extensive phenotype and genotype data already in an NCBI data repository (as part of the NHLBI SHARe Genome-wide Association Project). All data from the SABRe, SHARe, and the nearly 60 years of phenotypic data from the FHS will be integrated into a massive resource that will be accessible to the outside scientific community in a manner consistent with the informed consent preferences of the Framingham participants. SABRe CVD Projects Project 1: Discovery proteomics and metabolomics/lipomics in case-control studies of subclinical atherosclerosis, metabolic syndrome (300 cases, 300 controls), and predicting new cardiovascular events using samples obtained prior to event (150 cases, 300 controls). Project 2: Immunoassays of 180 circulating protein biomarkers of atherosclerosis and metabolic syndrome in 7400 FHS participants. Project 3: Gene expression profiling of WBC derived RNA to characterize the genomic signatures of atherosclerosis and metabolic syndrome in 5000-7000 FHS participants (lab work to take place at NHLBI Core Microarray Lab). Project 4: MicroRNA profiling of WBC derived RNA to characterize microRNA regulation of gene expression and the relations of microRNA to clinical traits and diseases. microRNA profiling will be conducted in 5000-7000 FHS participants. The SABRe Initiative is a state-of-the-art research enterprise to advance personalized medicine through biomarker discovery and validation. This project holds great promise for identifying mechanisms of disease and promoting the development of new diagnostics and therapeutics for diseases of high impact. The specific aims for SABRe CVD are as follows: 1. To identify the biomarker signatures of atherosclerosis as determined by: a) aortic and coronary calcification on CT (data available in 3500 people), b) aortic plaque burden by MRI (n=2000), c) carotid intimal-medial thickness by ultrasound (n=3500), d) clinical atherosclerotic CVD (n=500), and e) the dynamic balance between arterial calcification and bone demineralization (n=3500). 2. To identify the biomarker signatures of metabolic risk factors related to cardiovascular risk: a) systolic and diastolic blood pressure (n=7000), b) body mass index (n=7000) and visceral adiposity by CT (n=3500), c) dyslipidemia (lipid levels, n=7000), and d) impaired fasting glucose, diabetes, and insulin resistance (glucose and insulin levels, n=7000). 3. To identify genomic convergence (convergence of signals from genetic variation and gene expression) with SABRe biomarker levels and clinical traits and diseases. Available Data sets Currently we have the following data SABRe CVD data sets available in the 'Authorized Access' area of dbGaP. Project 1: We have 2 Px data sets posted: iTRAQ Px data set of 135 case/control pairs Targeted MRM Px of 33 targets measured in the CVD study of 658 samples. Next release will have 2 additional data sets: LCMS Lipids from Metabolic Syndrome study GCMS Mx from Metabolic Syndrome study Project 2: Immunoassay Panels ~5000 Framingham samples from Offspring Exam 7 and Gen III Exam 1. The full methods, target protein list, QC and related information can be found in the publication: J Am Heart Assoc. 2018 Jul 17; 7(14): e008108. Published online 2018 Jul 13. doi:10.1161/JAHA.117.008108 PMCID: PMC6064847 PMID: 30006491Individual Data sets are listed below: SABRe_Project_2_Immunoassays_l_mpimn01_2005_m_0692sSABRe_Project_2_Immunoassays_l_mpimn02_2005_m_0693sSABRe_Project_2_Immunoassays_l_mpimn03_2005_m_0694sSABRe_Project_2_Immunoassays_l_mpimn04_2005_m_0757sSABRe_Project_2_Immunoassays_l_mpimn05_2005_m_0758sSABRe_Project_2_Immunoassays_l_mpimn06_2005_m_0792sSABRe_Project_2_Immunoassays_l_mpimn07_2005_m_0802sSABRe_Project_2_Immunoassays_l_mpimn08_2005_m_0836sSABRe_Project_2_Immunoassays_l_mpimn09_2005_m_0850sSABRe_Project_2_Immunoassays_l_mpimn10_2005_m_0854sSABRe_Project_2_Immunoassays_l_mpimn11_2005_m_0855sSABRe_Project_2_Immunoassays_l_mpimn12_2005_m_0932sSABRe_Project_2_Immunoassays_l_mpimn13_2005_m_0931sSABRe_Project_2_Immunoassays_l_mpimn14_2005_m_0856sSABRe_Project_2_Immunoassays_l_mpimn15_2005_m_0974sSABRe_Project_2_Immunoassays_l_mpimn16_2005_m_0976sSABRe_Project_2_Immunoassays_l_mpimn17_2005_m_0977sProject 3: Expression dataset (phe000002) is updated with Generation III (GENIII) exam 2 expression data and is repacked in accordance with new consent information. Please note that subject IDs were revised for 7 previously released FHS_OFFs samples. This data set includes Offspring exam 8 case-control, Offspring exam 8 cohort and GEN III expression data and reflects the completion of the gene expression data generation. Project 4: miRNA dataset SABRe_Project_4_miRNA_I_mrna_2011_m_0797s includes Offspring exam 8, case-control and Offspring exam 8 and Gen III miRNA data as a combined data set with variables to indicate case/control status as well as cohort status to differentiate the combined data set. Study Weblinks: The Framingham Heart Study NHLBI Framingham Heart Study Study Design: Prospective Longitudinal Cohort Study Type: Cohort Total number of consented subjects: 7496 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"SABRe CVD","short_name":"SABRe_CVD_HMB-IRB-MDS","commons":"BioData Catalyst","study_url":"","_subjects_count":6616,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs000363.v22.p16.c2":{"gen3_discovery":{"authz":"/programs/dbGaP/projects/SABRe_CVD_HMB-IRB-NPU-MDS","tags":[],"_unique_id":"phs000363.v22.p16.c2","study_id":"phs000363.v22.p16.c2","study_description":"This substudy phs000363 Framingham SABRe contains immunoassays, gene expression profiling, and microRNA data. Summary level phenotypes for the Framingham Cohort study participants can be viewed at the top-level study page phs000007 Framingham Cohort. Individual level phenotype data and molecular data for all Framingham top-level study and substudies are available by requesting Authorized Access to the Framingham Cohort study phs000007. Systems Approach to Biomarker Research in Cardiovascular Disease in the NHLBI's Framingham Heart Study: The SABRe CVD Initiative The NHLBI's Framingham Heart Study (FHS), one of the world's preeminent observational study settings, is devoted to increasing scientific knowledge by establishing a public resource of data and samples. For nearly 60 years, the people of Framingham have generously volunteered their time to this high-profile study and remain deeply committed to its success. The Systems Approach to Biomarker Research in Cardiovascular Disease Initiative (SABRe CVD Initiative) will generate extensive biomarker data from 7000 FHS participants using multiple high throughput platforms including immunoassays, proteomics, metabolomics/lipomics, and gene expression and microRNA profiling. SABRe will generate thousands of new biomarkers from each participant, with data deposited with the NCBI and linked to the extensive phenotype and genotype data already in an NCBI data repository (as part of the NHLBI SHARe Genome-wide Association Project). All data from the SABRe, SHARe, and the nearly 60 years of phenotypic data from the FHS will be integrated into a massive resource that will be accessible to the outside scientific community in a manner consistent with the informed consent preferences of the Framingham participants. SABRe CVD Projects Project 1: Discovery proteomics and metabolomics/lipomics in case-control studies of subclinical atherosclerosis, metabolic syndrome (300 cases, 300 controls), and predicting new cardiovascular events using samples obtained prior to event (150 cases, 300 controls). Project 2: Immunoassays of 180 circulating protein biomarkers of atherosclerosis and metabolic syndrome in 7400 FHS participants. Project 3: Gene expression profiling of WBC derived RNA to characterize the genomic signatures of atherosclerosis and metabolic syndrome in 5000-7000 FHS participants (lab work to take place at NHLBI Core Microarray Lab). Project 4: MicroRNA profiling of WBC derived RNA to characterize microRNA regulation of gene expression and the relations of microRNA to clinical traits and diseases. microRNA profiling will be conducted in 5000-7000 FHS participants. The SABRe Initiative is a state-of-the-art research enterprise to advance personalized medicine through biomarker discovery and validation. This project holds great promise for identifying mechanisms of disease and promoting the development of new diagnostics and therapeutics for diseases of high impact. The specific aims for SABRe CVD are as follows: 1. To identify the biomarker signatures of atherosclerosis as determined by: a) aortic and coronary calcification on CT (data available in 3500 people), b) aortic plaque burden by MRI (n=2000), c) carotid intimal-medial thickness by ultrasound (n=3500), d) clinical atherosclerotic CVD (n=500), and e) the dynamic balance between arterial calcification and bone demineralization (n=3500). 2. To identify the biomarker signatures of metabolic risk factors related to cardiovascular risk: a) systolic and diastolic blood pressure (n=7000), b) body mass index (n=7000) and visceral adiposity by CT (n=3500), c) dyslipidemia (lipid levels, n=7000), and d) impaired fasting glucose, diabetes, and insulin resistance (glucose and insulin levels, n=7000). 3. To identify genomic convergence (convergence of signals from genetic variation and gene expression) with SABRe biomarker levels and clinical traits and diseases. Available Data sets Currently we have the following data SABRe CVD data sets available in the 'Authorized Access' area of dbGaP. Project 1: We have 2 Px data sets posted: iTRAQ Px data set of 135 case/control pairs Targeted MRM Px of 33 targets measured in the CVD study of 658 samples. Next release will have 2 additional data sets: LCMS Lipids from Metabolic Syndrome study GCMS Mx from Metabolic Syndrome study Project 2: Immunoassay Panels ~5000 Framingham samples from Offspring Exam 7 and Gen III Exam 1. The full methods, target protein list, QC and related information can be found in the publication: J Am Heart Assoc. 2018 Jul 17; 7(14): e008108. Published online 2018 Jul 13. doi:10.1161/JAHA.117.008108 PMCID: PMC6064847 PMID: 30006491Individual Data sets are listed below: SABRe_Project_2_Immunoassays_l_mpimn01_2005_m_0692sSABRe_Project_2_Immunoassays_l_mpimn02_2005_m_0693sSABRe_Project_2_Immunoassays_l_mpimn03_2005_m_0694sSABRe_Project_2_Immunoassays_l_mpimn04_2005_m_0757sSABRe_Project_2_Immunoassays_l_mpimn05_2005_m_0758sSABRe_Project_2_Immunoassays_l_mpimn06_2005_m_0792sSABRe_Project_2_Immunoassays_l_mpimn07_2005_m_0802sSABRe_Project_2_Immunoassays_l_mpimn08_2005_m_0836sSABRe_Project_2_Immunoassays_l_mpimn09_2005_m_0850sSABRe_Project_2_Immunoassays_l_mpimn10_2005_m_0854sSABRe_Project_2_Immunoassays_l_mpimn11_2005_m_0855sSABRe_Project_2_Immunoassays_l_mpimn12_2005_m_0932sSABRe_Project_2_Immunoassays_l_mpimn13_2005_m_0931sSABRe_Project_2_Immunoassays_l_mpimn14_2005_m_0856sSABRe_Project_2_Immunoassays_l_mpimn15_2005_m_0974sSABRe_Project_2_Immunoassays_l_mpimn16_2005_m_0976sSABRe_Project_2_Immunoassays_l_mpimn17_2005_m_0977sProject 3: Expression dataset (phe000002) is updated with Generation III (GENIII) exam 2 expression data and is repacked in accordance with new consent information. Please note that subject IDs were revised for 7 previously released FHS_OFFs samples. This data set includes Offspring exam 8 case-control, Offspring exam 8 cohort and GEN III expression data and reflects the completion of the gene expression data generation. Project 4: miRNA dataset SABRe_Project_4_miRNA_I_mrna_2011_m_0797s includes Offspring exam 8, case-control and Offspring exam 8 and Gen III miRNA data as a combined data set with variables to indicate case/control status as well as cohort status to differentiate the combined data set. Study Weblinks: The Framingham Heart Study NHLBI Framingham Heart Study Study Design: Prospective Longitudinal Cohort Study Type: Cohort Total number of consented subjects: 7496 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"SABRe CVD","short_name":"SABRe_CVD_HMB-IRB-NPU-MDS","commons":"BioData Catalyst","study_url":"","_subjects_count":880,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs000366.v1.p1.c1":{"gen3_discovery":{"authz":"/programs/dbGaP/projects/GM_CSSCD_GRU","tags":[],"_unique_id":"phs000366.v1.p1.c1","study_id":"phs000366.v1.p1.c1","study_description":"Phenotypic heterogeneity is characteristic of sickle cell anemia, a Mendelian disorder caused by homozygosity for the sickle HBB gene (glu6val). Patients have different rates of hemolysis/vasculopathy and viscosity/vasoocclusion-related complications. These complications account for a substantial reduction in life expectancy. In 1994, the median life expectancy for men and women with sickle cell anemia was 42 and 48 years, respectively, and despite many advances in care, the annual mortality still approaches 4%. Fetal hemoglobin (HbF) is one of the most studied markers of severity of sickle cell anemia, and detailed longitudinal measurements were taken on subjects enrolled in the Cooperative Study of Sickle Cell Disease (CSSCD). Cubic root transformation of the median values from follow-up in 848 African American subjects is the phenotype data used in the GWAS of fetal hemoglobin. The analysis was adjusted by sex. Details are in Solovieff et al., Blood 2010 [PMID: 20018918]. To integrate individual disease complications into a comprehensive measure of severity, we developed a model of the associations among clinical and laboratory variables that scored disease severity as the risk of death within 5 years. This network was developed using data obtained from more than 3,400 subjects from the CSSCD, and its accuracy was validated in two unrelated sets of sickle cell patients. Recently, the network was also validated in a small European cohort of patients with sickle cell anemia. We used extreme values of disease severity as cases and control in the GWAS of severity of sickle cell anemia. We conducted the GWAS in 1,265 patients with either \"severe\" (177) or \"mild\" disease (1088) based on a network model of disease severity. Details are in Sebastiani et al. Am J Hematol, 2010 [PMID: 20029952]. Study Weblinks: Cooperative Study of Sickle Cell Disease (CSSCD) Study Design: Prospective Longitudinal Cohort Study Type: Longitudinal NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"NHLBI: Genetic modifiers of sickle cell anemia severity and fetal hemoglobin expression in the Cooperative Study of Sickle Cell Disease (CSSCD)","short_name":"GM_CSSCD_GRU","commons":"BioData Catalyst","study_url":"","_subjects_count":0,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs000379.v1.p1.c1":{"gen3_discovery":{"authz":"/programs/heartfailure/projects/GENOA_GRU","tags":[],"_unique_id":"phs000379.v1.p1.c1","study_id":"phs000379.v1.p1.c1","study_description":"The Genetic Epidemiology Network of Arteriopathy (GENOA): GENOA is one of four research networks that form the NHLBI Family Blood Pressure Program (FBPP). From its inception in 1995, GENOA's long-term objective was to elucidate the genetics of hypertension and its arteriosclerotic target-organ damage, including both atherosclerotic (macrovascular) and arteriolosclerotic (microvascular) complications involving the heart, brain, kidneys, and peripheral arteries. Two GENOA cohorts were originally ascertained (1995-2000) through sibships in which at least 2 siblings had essential hypertension diagnosed prior to age 60 years. All siblings in the sibship were invited to participate, both normotensive and hypertensive. These include non-Hispanic White Americans from Rochester, MN (n =1583 at the 1st exam) and African Americans from Jackson, MS (N=1854 at the 1st exam). During the second exam (2000-2005), approximately 80% of participants were re-recruited. The GENOA data consists of biological samples (DNA, serum, urine) as well as demographic, anthropometric, environmental, clinical, biochemical, physiological, and genetic data for understanding the genetic predictors of diseases of the heart, brain, kidney, and peripheral arteries. Family Blood Pressure Program (FBPP): GENOA's parent program, the FBPP, is an unprecedented collaboration to identify genes influencing blood pressure (BP) levels, hypertension, and its target-organ damage. This program has conducted over 21,000 physical examinations, assembled a shared database of several hundred BP and hypertension-related phenotypic measurements, completed genome-wide linkage analyses for BP, hypertension, and hypertension associated risk factors and complications, and published over 130 manuscripts on program findings. The FBPP emerged from what was initially funded as four independent networks of investigators (HyperGEN, GenNet, SAPPHIRe and GENOA) competing to identify genetic determinants of hypertension in multiple ethnic groups. Realizing the greater likelihood of success through collaboration, the investigators began working together during the first funding cycle (1995-2000) and formalized this arrangement in the second cycle (2000-2005), creating a single confederation with program-wide and network-specific goals. Study Design: Family/Twin/Trios Study Type: Sibling Cohort NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Genetic Epidemiology Network of Arteriopathy (GENOA)","short_name":"GENOA_GRU","commons":"BioData Catalyst","study_url":"","_subjects_count":0,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs000398.v8.p2.c1":{"gen3_discovery":{"authz":"/programs/dbGaP/projects/GO_ESP_ARIC_HMB-IRB","tags":[],"_unique_id":"phs000398.v8.p2.c1","study_id":"phs000398.v8.p2.c1","study_description":"This sub-study phs000398 HeartGO_ARIC contains genotype derived from sequence data and selected phenotype of subjects available from the phs000398 study. Summary level phenotypes for the NHLBI ARIC Cohort study participants can be viewed at the top-level study page phs000280 ARIC Cohort. Individual level phenotype data and molecular data for all ARIC Cohort top-level study and sub-study are available by requesting Authorized Access to the NHLBI ARIC Cohort phs000280 study. The NHLBI \"Grand Opportunity\" Exome Sequencing Project (GO-ESP), a signature project of the NHLBI Recovery Act investment, was designed to identify genetic variants in coding regions (exons) of the human genome (the \"exome\") that are associated with heart, lung and blood diseases. These and related diseases that are of high impact to public health and individuals from diverse racial and ethnic groups will be studied. These data may help researchers understand the causes of disease, contributing to better ways to prevent, diagnose, and treat diseases, as well as determine whether to tailor prevention and treatments to specific populations. This could lead to more effective treatments and reduce the likelihood of side effects. GO-ESP is comprised of five collaborative components: 3 cohort consortia - HeartGO, LungGO, and WHISP - and 2 sequencing centers - BroadGO and SeattleGO. HeartGO is a consortium of six well-phenotyped NHLBI cohorts: Atherosclerosis Risk in Communities (ARIC) study, the Coronary Artery Risk Development in Young Adults (CARDIA) study, the Cardiovascular Health Study (CHS), the Framingham Heart Study (FHS), the Jackson Heart Study (JHS), and the Multi-Ethnic Study of Atherosclerosis (MESA). Together, for the GO-ESP, these cohorts have provided DNA and phenotype datasets from a diverse cohort of individuals of African and Caucasian ancestry to be made available for use by qualified investigators in dbGaP. HeartGO investigators will conduct genotype-phenotype analyses for phenotypes related not only to heart disease but with other variables that will be contributed to dbGaP. The HeartGO dataset provides investigators with genotype-phenotype analytic opportunities for traits not only related to heart disease but also associated with ancillary variables that will be contributed to dbGaP, including disease endpoints, risk factors, biomarkers, and subclinical disease measures. The phenotypes planned for investigation as part of the GO-ESP HeartGO project include five primary phenotypes for which initial ascertainment of samples for exome sequencing were made (early-onset myocardial infarction (EOMI), low density lipoprotein (LDL) cholesterol, body mass index/type 2 diabetes (BMI/T2D), blood pressure and ischemic stroke) and a randomly ascertained common comparison group with extensive phenotyping (deeply phenotyped reference, DPR). Additional phenotypes available on these selected samples permitted a large array of additional analyses to be performed. These secondary phenotypes account for ~80 outcomes from both qualitative and quantitative traits. Results of the proposed analyses as well as relevant replication/follow-up analyses will be reported in peer-reviewed journals. Study Weblinks: ARIC NHLBI GO-ESP Study Design: Case-Control Study Type: Case-Control Cohort Total number of consented subjects: 808 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"National Heart Lung and Blood Institute (NHLBI) GO-ESP: Heart Cohorts Component of the Exome Sequencing Project (ARIC)","short_name":"GO_ESP_ARIC_HMB-IRB","commons":"BioData Catalyst","study_url":"","_subjects_count":789,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs000398.v8.p2.c2":{"gen3_discovery":{"authz":"/programs/dbGaP/projects/GO_ESP_ARIC_DS-CVD-IRB","tags":[],"_unique_id":"phs000398.v8.p2.c2","study_id":"phs000398.v8.p2.c2","study_description":"This sub-study phs000398 HeartGO_ARIC contains genotype derived from sequence data and selected phenotype of subjects available from the phs000398 study. Summary level phenotypes for the NHLBI ARIC Cohort study participants can be viewed at the top-level study page phs000280 ARIC Cohort. Individual level phenotype data and molecular data for all ARIC Cohort top-level study and sub-study are available by requesting Authorized Access to the NHLBI ARIC Cohort phs000280 study. The NHLBI \"Grand Opportunity\" Exome Sequencing Project (GO-ESP), a signature project of the NHLBI Recovery Act investment, was designed to identify genetic variants in coding regions (exons) of the human genome (the \"exome\") that are associated with heart, lung and blood diseases. These and related diseases that are of high impact to public health and individuals from diverse racial and ethnic groups will be studied. These data may help researchers understand the causes of disease, contributing to better ways to prevent, diagnose, and treat diseases, as well as determine whether to tailor prevention and treatments to specific populations. This could lead to more effective treatments and reduce the likelihood of side effects. GO-ESP is comprised of five collaborative components: 3 cohort consortia - HeartGO, LungGO, and WHISP - and 2 sequencing centers - BroadGO and SeattleGO. HeartGO is a consortium of six well-phenotyped NHLBI cohorts: Atherosclerosis Risk in Communities (ARIC) study, the Coronary Artery Risk Development in Young Adults (CARDIA) study, the Cardiovascular Health Study (CHS), the Framingham Heart Study (FHS), the Jackson Heart Study (JHS), and the Multi-Ethnic Study of Atherosclerosis (MESA). Together, for the GO-ESP, these cohorts have provided DNA and phenotype datasets from a diverse cohort of individuals of African and Caucasian ancestry to be made available for use by qualified investigators in dbGaP. HeartGO investigators will conduct genotype-phenotype analyses for phenotypes related not only to heart disease but with other variables that will be contributed to dbGaP. The HeartGO dataset provides investigators with genotype-phenotype analytic opportunities for traits not only related to heart disease but also associated with ancillary variables that will be contributed to dbGaP, including disease endpoints, risk factors, biomarkers, and subclinical disease measures. The phenotypes planned for investigation as part of the GO-ESP HeartGO project include five primary phenotypes for which initial ascertainment of samples for exome sequencing were made (early-onset myocardial infarction (EOMI), low density lipoprotein (LDL) cholesterol, body mass index/type 2 diabetes (BMI/T2D), blood pressure and ischemic stroke) and a randomly ascertained common comparison group with extensive phenotyping (deeply phenotyped reference, DPR). Additional phenotypes available on these selected samples permitted a large array of additional analyses to be performed. These secondary phenotypes account for ~80 outcomes from both qualitative and quantitative traits. Results of the proposed analyses as well as relevant replication/follow-up analyses will be reported in peer-reviewed journals. Study Weblinks: ARIC NHLBI GO-ESP Study Design: Case-Control Study Type: Case-Control Cohort Total number of consented subjects: 808 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"National Heart Lung and Blood Institute (NHLBI) GO-ESP: Heart Cohorts Component of the Exome Sequencing Project (ARIC)","short_name":"GO_ESP_ARIC_DS-CVD-IRB","commons":"BioData Catalyst","study_url":"","_subjects_count":19,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs000401.v18.p16.c1":{"gen3_discovery":{"authz":"/programs/dbGaP/projects/GO_ESP_FHS_HMB-IRB-MDS","tags":[],"_unique_id":"phs000401.v18.p16.c1","study_id":"phs000401.v18.p16.c1","study_description":"This substudy phs000401 Framingham ESP Heart-GO contains exome sequence data and harmonized phenotype variables, produced as part of NHLBI's GO-ESP project. Summary level phenotypes for the Framingham Cohort study participants can be viewed at the top-level study page phs000007 Framingham Cohort. Individual level phenotype data and molecular data for all Framingham top-level study and substudies are available by requesting Authorized Access to the Framingham Cohort study phs000007. The NHLBI \"Grand Opportunity\" Exome Sequencing Project (GO-ESP), a signature project of the NHLBI Recovery Act investment, was designed to identify genetic variants in coding regions (exons) of the human genome (the \"exome\") that are associated with heart, lung and blood diseases. These and related diseases that are of high impact to public health and individuals from diverse racial and ethnic groups will be studied. These data may help researchers understand the causes of disease, contributing to better ways to prevent, diagnose, and treat diseases, as well as determine whether to tailor prevention and treatments to specific populations. This could lead to more effective treatments and reduce the likelihood of side effects. GO-ESP is comprised of five collaborative components: 3 cohort consortia - HeartGO, LungGO, and WHISP - and 2 sequencing centers - BroadGO and SeattleGO. HeartGO is a consortium of six well-phenotyped NHLBI cohorts: Atherosclerosis Risk in Communities (ARIC) study, the Coronary Artery Risk Development in Young Adults (CARDIA) study, the Cardiovascular Health Study (CHS), the Framingham Heart Study (FHS), the Jackson Heart Study (JHS), and the Multi-Ethnic Study of Atherosclerosis (MESA). Together, for the GO-ESP, these cohorts have provided DNA and phenotype datasets from a diverse cohort of individuals of African and Caucasian ancestry to be made available for use by qualified investigators in dbGaP. HeartGO investigators will conduct genotype-phenotype analyses for phenotypes related not only to heart disease but with other variables that will be contributed to dbGaP. The HeartGO dataset provides investigators with genotype-phenotype analytic opportunities for traits not only related to heart disease but also associated with ancillary variables that will be contributed to dbGaP, including disease endpoints, risk factors, biomarkers, and subclinical disease measures. The phenotypes planned for investigation as part of the GO-ESP HeartGO project include five primary phenotypes for which initial ascertainment of samples for exome sequencing were made (early-onset myocardial infarction (EOMI), low density lipoprotein (LDL) cholesterol, body mass index/type 2 diabetes (BMI/T2D), blood pressure and ischemic stroke) and a randomly ascertained common comparison group with extensive phenotyping (deeply phenotyped reference, DPR). Additional phenotypes available on these selected samples permitted a large array of additional analyses to be performed. These secondary phenotypes account for ~80 outcomes from both qualitative and quantitative traits. Results of the proposed analyses as well as relevant replication/follow-up analyses will be reported in peer-reviewed journals. This study phs000401 contains the Framingham Heart Study (FHS) subset of GO-ESP/Heart-GO. Additional GO-ESP data is also available via dbGaP. Study Weblinks: NHLBI GO-ESP Study Design: Prospective Longitudinal Cohort Study Type: Affected Sib Pairs Case-Cohort Case-Control Cohort Exome Sequencing dbGaP estimated ancestry using GRAF-pop Total number of consented subjects: 459 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"National Heart Lung and Blood Institute (NHLBI) GO-ESP: Heart Cohorts Component of the Exome Sequencing Project (FHS)","short_name":"GO_ESP_FHS_HMB-IRB-MDS","commons":"BioData Catalyst","study_url":"","_subjects_count":374,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs000401.v18.p16.c2":{"gen3_discovery":{"authz":"/programs/dbGaP/projects/GO_ESP_FHS_HMB-IRB-NPU-MDS","tags":[],"_unique_id":"phs000401.v18.p16.c2","study_id":"phs000401.v18.p16.c2","study_description":"This substudy phs000401 Framingham ESP Heart-GO contains exome sequence data and harmonized phenotype variables, produced as part of NHLBI's GO-ESP project. Summary level phenotypes for the Framingham Cohort study participants can be viewed at the top-level study page phs000007 Framingham Cohort. Individual level phenotype data and molecular data for all Framingham top-level study and substudies are available by requesting Authorized Access to the Framingham Cohort study phs000007. The NHLBI \"Grand Opportunity\" Exome Sequencing Project (GO-ESP), a signature project of the NHLBI Recovery Act investment, was designed to identify genetic variants in coding regions (exons) of the human genome (the \"exome\") that are associated with heart, lung and blood diseases. These and related diseases that are of high impact to public health and individuals from diverse racial and ethnic groups will be studied. These data may help researchers understand the causes of disease, contributing to better ways to prevent, diagnose, and treat diseases, as well as determine whether to tailor prevention and treatments to specific populations. This could lead to more effective treatments and reduce the likelihood of side effects. GO-ESP is comprised of five collaborative components: 3 cohort consortia - HeartGO, LungGO, and WHISP - and 2 sequencing centers - BroadGO and SeattleGO. HeartGO is a consortium of six well-phenotyped NHLBI cohorts: Atherosclerosis Risk in Communities (ARIC) study, the Coronary Artery Risk Development in Young Adults (CARDIA) study, the Cardiovascular Health Study (CHS), the Framingham Heart Study (FHS), the Jackson Heart Study (JHS), and the Multi-Ethnic Study of Atherosclerosis (MESA). Together, for the GO-ESP, these cohorts have provided DNA and phenotype datasets from a diverse cohort of individuals of African and Caucasian ancestry to be made available for use by qualified investigators in dbGaP. HeartGO investigators will conduct genotype-phenotype analyses for phenotypes related not only to heart disease but with other variables that will be contributed to dbGaP. The HeartGO dataset provides investigators with genotype-phenotype analytic opportunities for traits not only related to heart disease but also associated with ancillary variables that will be contributed to dbGaP, including disease endpoints, risk factors, biomarkers, and subclinical disease measures. The phenotypes planned for investigation as part of the GO-ESP HeartGO project include five primary phenotypes for which initial ascertainment of samples for exome sequencing were made (early-onset myocardial infarction (EOMI), low density lipoprotein (LDL) cholesterol, body mass index/type 2 diabetes (BMI/T2D), blood pressure and ischemic stroke) and a randomly ascertained common comparison group with extensive phenotyping (deeply phenotyped reference, DPR). Additional phenotypes available on these selected samples permitted a large array of additional analyses to be performed. These secondary phenotypes account for ~80 outcomes from both qualitative and quantitative traits. Results of the proposed analyses as well as relevant replication/follow-up analyses will be reported in peer-reviewed journals. This study phs000401 contains the Framingham Heart Study (FHS) subset of GO-ESP/Heart-GO. Additional GO-ESP data is also available via dbGaP. Study Weblinks: NHLBI GO-ESP Study Design: Prospective Longitudinal Cohort Study Type: Affected Sib Pairs Case-Cohort Case-Control Cohort Exome Sequencing dbGaP estimated ancestry using GRAF-pop Total number of consented subjects: 459 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"National Heart Lung and Blood Institute (NHLBI) GO-ESP: Heart Cohorts Component of the Exome Sequencing Project (FHS)","short_name":"GO_ESP_FHS_HMB-IRB-NPU-MDS","commons":"BioData Catalyst","study_url":"","_subjects_count":85,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs000402.v5.p2.c1":{"gen3_discovery":{"authz":"/programs/dbGaP/projects/GO_ESP_JHS_HMB-IRB-NPU","tags":[],"_unique_id":"phs000402.v5.p2.c1","study_id":"phs000402.v5.p2.c1","study_description":"This sub-study phs000402 HeartGO JHS contains genotype derived from sequence data and selected phenotype of subjects available from the phs000402 study. Summary level phenotypes for the NHLBI JHS Cohort study participants can be viewed at the top-level study page phs000286 JHS Cohort. Individual level phenotype data and molecular data for all JHS Cohort top-level study and sub-study are available by requesting Authorized Access to the NHLBI JHS Cohort phs000286 study. The NHLBI \"Grand Opportunity\" Exome Sequencing Project (GO-ESP), a signature project of the NHLBI Recovery Act investment, was designed to identify genetic variants in coding regions (exons) of the human genome that are associated with heart, lung and blood diseases. These diseases and related diseases that are of high impact to public health and individuals from diverse racial and ethnic groups will be studied. These data may help researchers understand the causes of disease, contributing to better ways to prevent, diagnose, and treat diseases, as well as determine whether to tailor prevention and treatments to specific populations. This could lead to more effective treatments and reduce the likelihood of side effects. The GO-ESP is comprised of five collaborative components, including 3 cohort consortia: HeartGO, LungGO, and WHISP, and 2 sequencing centers: BroadGO and SeattleGO. The HeartGO is a consortium of six well-phenotyped NHLBI cohorts: Atherosclerosis Risk in Communities (ARIC) Study, Coronary Artery Risk Development in Young Adults Study (CARDIA), Cardiovascular Health Study (CHS), Framingham Heart Study (FHS), Jackson Heart Study (JHS), and Multi-Ethnic Study of Atherosclerosis (MESA). Together, for the GO-ESP, these cohorts have provided DNA and phenotype datasets from a diverse cohort of individuals of African and Caucasian ancestry and the datasets have been made available for the authorized investigators to access in dbGaP. The HeartGO dataset provides investigators with genotype-phenotype analytic opportunities for traits not only related to heart disease but also associated with ancillary variables that will be contributed to dbGaP, including disease endpoints, risk factors, biomarkers, and subclinical disease measures. The phenotypes planned for investigation as part of the GO-ESP HeartGO project include five primary phenotypes [early-onset myocardial infarction (EOMI), low density lipoprotein (LDL) cholesterol, body mass index/type 2 diabetes (BMI/T2D), blood pressure (BP), and ischemic stroke], for which initial ascertainment of samples for exome sequencing were made, and a randomly ascertained common comparison group with extensive phenotyping (deeply phenotyped reference, DPR). Additional phenotypes available on these selected samples permitted to perform a large array of additional analyses. These secondary phenotypes account for ~80 outcomes from both qualitative and quantitative traits. Results of the proposed analyses as well as relevant replication/follow-up analyses will be reported in peer-reviewed journals. Study Weblinks: NHLBI GO-ESP Study Design: Case-Control Study Type: Case-Cohort Case-Control Cohort Total number of consented subjects: 402 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"National Heart Lung and Blood Institute (NHLBI) GO-ESP: Heart Cohorts Component of the Exome Sequencing Project (JHS)","short_name":"GO_ESP_JHS_HMB-IRB-NPU","commons":"BioData Catalyst","study_url":"","_subjects_count":62,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs000402.v5.p2.c2":{"gen3_discovery":{"authz":"/programs/dbGaP/projects/GO_ESP_JHS_DS-FDO-IRB-NPU","tags":[],"_unique_id":"phs000402.v5.p2.c2","study_id":"phs000402.v5.p2.c2","study_description":"This sub-study phs000402 HeartGO JHS contains genotype derived from sequence data and selected phenotype of subjects available from the phs000402 study. Summary level phenotypes for the NHLBI JHS Cohort study participants can be viewed at the top-level study page phs000286 JHS Cohort. Individual level phenotype data and molecular data for all JHS Cohort top-level study and sub-study are available by requesting Authorized Access to the NHLBI JHS Cohort phs000286 study. The NHLBI \"Grand Opportunity\" Exome Sequencing Project (GO-ESP), a signature project of the NHLBI Recovery Act investment, was designed to identify genetic variants in coding regions (exons) of the human genome that are associated with heart, lung and blood diseases. These diseases and related diseases that are of high impact to public health and individuals from diverse racial and ethnic groups will be studied. These data may help researchers understand the causes of disease, contributing to better ways to prevent, diagnose, and treat diseases, as well as determine whether to tailor prevention and treatments to specific populations. This could lead to more effective treatments and reduce the likelihood of side effects. The GO-ESP is comprised of five collaborative components, including 3 cohort consortia: HeartGO, LungGO, and WHISP, and 2 sequencing centers: BroadGO and SeattleGO. The HeartGO is a consortium of six well-phenotyped NHLBI cohorts: Atherosclerosis Risk in Communities (ARIC) Study, Coronary Artery Risk Development in Young Adults Study (CARDIA), Cardiovascular Health Study (CHS), Framingham Heart Study (FHS), Jackson Heart Study (JHS), and Multi-Ethnic Study of Atherosclerosis (MESA). Together, for the GO-ESP, these cohorts have provided DNA and phenotype datasets from a diverse cohort of individuals of African and Caucasian ancestry and the datasets have been made available for the authorized investigators to access in dbGaP. The HeartGO dataset provides investigators with genotype-phenotype analytic opportunities for traits not only related to heart disease but also associated with ancillary variables that will be contributed to dbGaP, including disease endpoints, risk factors, biomarkers, and subclinical disease measures. The phenotypes planned for investigation as part of the GO-ESP HeartGO project include five primary phenotypes [early-onset myocardial infarction (EOMI), low density lipoprotein (LDL) cholesterol, body mass index/type 2 diabetes (BMI/T2D), blood pressure (BP), and ischemic stroke], for which initial ascertainment of samples for exome sequencing were made, and a randomly ascertained common comparison group with extensive phenotyping (deeply phenotyped reference, DPR). Additional phenotypes available on these selected samples permitted to perform a large array of additional analyses. These secondary phenotypes account for ~80 outcomes from both qualitative and quantitative traits. Results of the proposed analyses as well as relevant replication/follow-up analyses will be reported in peer-reviewed journals. Study Weblinks: NHLBI GO-ESP Study Design: Case-Control Study Type: Case-Cohort Case-Control Cohort Total number of consented subjects: 402 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"National Heart Lung and Blood Institute (NHLBI) GO-ESP: Heart Cohorts Component of the Exome Sequencing Project (JHS)","short_name":"GO_ESP_JHS_DS-FDO-IRB-NPU","commons":"BioData Catalyst","study_url":"","_subjects_count":22,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs000402.v5.p2.c3":{"gen3_discovery":{"authz":"/programs/dbGaP/projects/GO_ESP_JHS_HMB-IRB","tags":[],"_unique_id":"phs000402.v5.p2.c3","study_id":"phs000402.v5.p2.c3","study_description":"This sub-study phs000402 HeartGO JHS contains genotype derived from sequence data and selected phenotype of subjects available from the phs000402 study. Summary level phenotypes for the NHLBI JHS Cohort study participants can be viewed at the top-level study page phs000286 JHS Cohort. Individual level phenotype data and molecular data for all JHS Cohort top-level study and sub-study are available by requesting Authorized Access to the NHLBI JHS Cohort phs000286 study. The NHLBI \"Grand Opportunity\" Exome Sequencing Project (GO-ESP), a signature project of the NHLBI Recovery Act investment, was designed to identify genetic variants in coding regions (exons) of the human genome that are associated with heart, lung and blood diseases. These diseases and related diseases that are of high impact to public health and individuals from diverse racial and ethnic groups will be studied. These data may help researchers understand the causes of disease, contributing to better ways to prevent, diagnose, and treat diseases, as well as determine whether to tailor prevention and treatments to specific populations. This could lead to more effective treatments and reduce the likelihood of side effects. The GO-ESP is comprised of five collaborative components, including 3 cohort consortia: HeartGO, LungGO, and WHISP, and 2 sequencing centers: BroadGO and SeattleGO. The HeartGO is a consortium of six well-phenotyped NHLBI cohorts: Atherosclerosis Risk in Communities (ARIC) Study, Coronary Artery Risk Development in Young Adults Study (CARDIA), Cardiovascular Health Study (CHS), Framingham Heart Study (FHS), Jackson Heart Study (JHS), and Multi-Ethnic Study of Atherosclerosis (MESA). Together, for the GO-ESP, these cohorts have provided DNA and phenotype datasets from a diverse cohort of individuals of African and Caucasian ancestry and the datasets have been made available for the authorized investigators to access in dbGaP. The HeartGO dataset provides investigators with genotype-phenotype analytic opportunities for traits not only related to heart disease but also associated with ancillary variables that will be contributed to dbGaP, including disease endpoints, risk factors, biomarkers, and subclinical disease measures. The phenotypes planned for investigation as part of the GO-ESP HeartGO project include five primary phenotypes [early-onset myocardial infarction (EOMI), low density lipoprotein (LDL) cholesterol, body mass index/type 2 diabetes (BMI/T2D), blood pressure (BP), and ischemic stroke], for which initial ascertainment of samples for exome sequencing were made, and a randomly ascertained common comparison group with extensive phenotyping (deeply phenotyped reference, DPR). Additional phenotypes available on these selected samples permitted to perform a large array of additional analyses. These secondary phenotypes account for ~80 outcomes from both qualitative and quantitative traits. Results of the proposed analyses as well as relevant replication/follow-up analyses will be reported in peer-reviewed journals. Study Weblinks: NHLBI GO-ESP Study Design: Case-Control Study Type: Case-Cohort Case-Control Cohort Total number of consented subjects: 402 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"National Heart Lung and Blood Institute (NHLBI) GO-ESP: Heart Cohorts Component of the Exome Sequencing Project (JHS)","short_name":"GO_ESP_JHS_HMB-IRB","commons":"BioData Catalyst","study_url":"","_subjects_count":268,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs000402.v5.p2.c4":{"gen3_discovery":{"authz":"/programs/dbGaP/projects/GO_ESP_JHS_DS-FDO-IRB","tags":[],"_unique_id":"phs000402.v5.p2.c4","study_id":"phs000402.v5.p2.c4","study_description":"This sub-study phs000402 HeartGO JHS contains genotype derived from sequence data and selected phenotype of subjects available from the phs000402 study. Summary level phenotypes for the NHLBI JHS Cohort study participants can be viewed at the top-level study page phs000286 JHS Cohort. Individual level phenotype data and molecular data for all JHS Cohort top-level study and sub-study are available by requesting Authorized Access to the NHLBI JHS Cohort phs000286 study. The NHLBI \"Grand Opportunity\" Exome Sequencing Project (GO-ESP), a signature project of the NHLBI Recovery Act investment, was designed to identify genetic variants in coding regions (exons) of the human genome that are associated with heart, lung and blood diseases. These diseases and related diseases that are of high impact to public health and individuals from diverse racial and ethnic groups will be studied. These data may help researchers understand the causes of disease, contributing to better ways to prevent, diagnose, and treat diseases, as well as determine whether to tailor prevention and treatments to specific populations. This could lead to more effective treatments and reduce the likelihood of side effects. The GO-ESP is comprised of five collaborative components, including 3 cohort consortia: HeartGO, LungGO, and WHISP, and 2 sequencing centers: BroadGO and SeattleGO. The HeartGO is a consortium of six well-phenotyped NHLBI cohorts: Atherosclerosis Risk in Communities (ARIC) Study, Coronary Artery Risk Development in Young Adults Study (CARDIA), Cardiovascular Health Study (CHS), Framingham Heart Study (FHS), Jackson Heart Study (JHS), and Multi-Ethnic Study of Atherosclerosis (MESA). Together, for the GO-ESP, these cohorts have provided DNA and phenotype datasets from a diverse cohort of individuals of African and Caucasian ancestry and the datasets have been made available for the authorized investigators to access in dbGaP. The HeartGO dataset provides investigators with genotype-phenotype analytic opportunities for traits not only related to heart disease but also associated with ancillary variables that will be contributed to dbGaP, including disease endpoints, risk factors, biomarkers, and subclinical disease measures. The phenotypes planned for investigation as part of the GO-ESP HeartGO project include five primary phenotypes [early-onset myocardial infarction (EOMI), low density lipoprotein (LDL) cholesterol, body mass index/type 2 diabetes (BMI/T2D), blood pressure (BP), and ischemic stroke], for which initial ascertainment of samples for exome sequencing were made, and a randomly ascertained common comparison group with extensive phenotyping (deeply phenotyped reference, DPR). Additional phenotypes available on these selected samples permitted to perform a large array of additional analyses. These secondary phenotypes account for ~80 outcomes from both qualitative and quantitative traits. Results of the proposed analyses as well as relevant replication/follow-up analyses will be reported in peer-reviewed journals. Study Weblinks: NHLBI GO-ESP Study Design: Case-Control Study Type: Case-Cohort Case-Control Cohort Total number of consented subjects: 402 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"National Heart Lung and Blood Institute (NHLBI) GO-ESP: Heart Cohorts Component of the Exome Sequencing Project (JHS)","short_name":"GO_ESP_JHS_DS-FDO-IRB","commons":"BioData Catalyst","study_url":"","_subjects_count":50,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs000422.v1.p1.c1":{"gen3_discovery":{"authz":"/programs/parent/projects/Asthma_GRU_","tags":[{"name":"Parent","category":"Program"},{"name":"Clinical Phenotype","category":"Data Type"},{"name":"dbGaP","category":"Study Registration"}],"_unique_id":"phs000422.v1.p1.c1","study_id":"phs000422.v1.p1.c1","study_description":"The NHLBI \"Grand Opportunity\" Exome Sequencing Project (GO-ESP), a signature project of the NHLBI Recovery Act investment, was designed to identify genetic variants in coding regions (exons) of the human genome (the \"exome\") that are associated with heart, lung and blood diseases. These and related diseases that are of high impact to public health and individuals from diverse racial and ethnic groups will be studied. These data may help researchers understand the causes of disease, contributing to better ways to prevent, diagnose, and treat diseases, as well as determine whether to tailor prevention and treatments to specific populations. This could lead to more effective treatments and reduce the likelihood of side effects. GO-ESP is comprised of five collaborative components: 3 cohort consortia - HeartGO, LungGO, and WHISP - and 2 sequencing centers - BroadGO and SeattleGO. The exome sequencing asthma project includes 200 African-Americans with asthma from the NHLBI multicenter Severe Asthma Research Program (SARP). SARP participants were recruited at the NHLBI SARP sites with an emphasis on recruiting severe asthmatics (Moore et al., Am J Respir Crit Care Med, 2010. PMID: 19892860). Asthma status was based on both a physician's diagnosis and either bronchodilator reversibility or hyper-responsiveness to methacholine as well as less than 5 pack years of smoking. All subjects were carefully characterized using the standardized SARP protocol which included spirometry (medication withheld), maximum bronchodilator reversibility, hyper-responsiveness to methacholine (not performed in subjects with low baseline FEV1), skin-tests to common allergens, questionnaires on health care utilization and medication use and sputum, lung imaging and bronchoscopy in a subset. In addition GWAS data are available (phs000355, Illumina platform). Study Design: Case Set Study Type: Case Set Total number of consented subjects: 191 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"NHLBI GO-ESP: Lung Cohorts Exome Sequencing Project (Asthma): Genetic variants affecting susceptibility and severity","short_name":"Asthma_GRU_","commons":"BioData Catalyst","study_url":"https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000422.v1.p1","_subjects_count":191,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs000438.v1.p1.c1":{"gen3_discovery":{"authz":"/programs/heartfailure/projects/PGRN_ACE_HMB","tags":[],"_unique_id":"phs000438.v1.p1.c1","study_id":"phs000438.v1.p1.c1","study_description":"The purpose of this study is to identify genetic predictors of ACE inhibitor-associated angioedema. In addition to preventing the formation of the pressor angiotensin II, ACE inhibitors prevent the carboxyl-terminal degradation of the vasoactive substances bradykinin and substance P. Angioedema is hypothesized to result from defective amino-terminal degradation of bradykinin or substance P in patients in whom ACE is inhibited. For example, activity of dipeptidyl peptidase IV (DPP-IV), the enzyme responsible for the inactivation of substance P when ACE is inhibited, is decreased in patients with angioedema. In preliminary studies, we have identified SNPs in the DPP4 gene that associate with DPP-IV activity and, in blacks, with risk of angioedema. This project will use genome-wide genotyping to compare 250 cases and 568 ACE inhibitor-exposed control subjects (131 cases and 288 controls ascertained at Vanderbilt and 70 cases and 280 controls ascertained at the Marshfield Clinic). We plan a 2-stage analysis of associations between SNPs and angioedema - first, we will study DPP4 SNPs for association with angioedema and, second, we will explore associations using the full GWAS data set. Depending on the platform, additional DPP4 SNPs will be used to fully tag common genetic variants in both African American and European American samples. Based on the HapMap data, there are 14 tagging SNPs in people of European descent and 34 in Yoruba (selection criteria MAF>0.05 and r2>0.8). Cases were defined as having ACE inhibitor-associated angioedema if they had had swelling of the lips, throat, tongue or face while taking an ACE inhibitor but had never had angioedema while not taking an ACE inhibitor. For simplicity, intestinal edema was excluded. Control subjects were treated for at least 6 months with an ACE inhibitor without angioedema. Because black Americans are known to be overrepresented among patients with ACE inhibitor-associated angioedema, control subjects were prespecified to be 50% black American, 50% white American, and 50% female. At Vanderbilt, the medical history, including the history of angioedema, was confirmed by a research nurse or physician using a detailed case report form. Characteristics of Vanderbilt cases appear in the Table. At Marshfield, medical history will be confirmed by chart review. The Marshfield cohort is 98% white American and 57% female with a mean age of 47.2 years. Study Design: Case-Control Study Type: Case-Control dbGaP estimated ancestry using GRAF-pop Total number of consented subjects: 721 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"A Genome-Wide Association Analysis in Angiotensin-Converting Enzyme (ACE) Inhibitor-Associated Angioedema and ACE Inhibitor-Exposed Controls; A Collaboration between the NIH Pharmacogenomics Research Network and the RIKEN Yokohama Center for Genomic Medicine","short_name":"PGRN_ACE_HMB","commons":"BioData Catalyst","study_url":"","_subjects_count":721,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs000439.v1.p1.c1":{"gen3_discovery":{"authz":"/programs/heartfailure/projects/PGRN_Afib_HMB","tags":[],"_unique_id":"phs000439.v1.p1.c1","study_id":"phs000439.v1.p1.c1","study_description":"The goal of this study was to identify genetic predictors of response to rate control therapy in patients with AF. We conducted a genome-wide association study (GWAS) focusing on subjects with a history of atrial fibrillation. Rate control therapy for AF uses a range of drugs (beta-adrenergic receptor blockers, calcium channel blockers, and digitalis) to depress conduction through the AV node, thereby preventing rapid rates and minimizing symptoms. In large groups of patients, such as the Vanderbilt AF Registry (a clinical and genetic repository with over 1200 patients with ECG-confirmed AF) from which these study subjects were drawn, approximately 5% display failure of aggressive AV nodal-blocking therapy to control ventricular rate. In these patients, interruption of the AV node by ablation and pacemaker implantation are necessary for adequate rate control. Study cases were individuals who underwent AV node ablation and pacemaker implantation after combined therapy with 3 AV nodal-blocking agents was ineffective in rate control. Controls for this study were individuals who met standardized rate-control efficacy criteria (as described in AFFIRM study, Wyse et al, NEJM 2002; PMID: 12466506) for optimal rate control with 2 or fewer AV nodal-blocking agents. Two additional groups were genotyped by RIKEN: An additional group of patients with AF as well as subjects undergoing cardiac surgery in whom AF did not occur post-operatively. All study participants were recruited and treated/evaluated at Vanderbilt University Medical Center. This study was conducted by the Pharmacogenomics of Arrhythmia Therapy subgroup of the Pharmacogenetics Research Network, a nationwide collaboration of scientists studying the genetic contributions to drug response variability. Genotyping was performed by the RIKEN research institute in Japan using the Illumina 610 Quad Beadchip platform. Study Design: Case-Control Study Type: Case-Control dbGaP estimated ancestry using GRAF-pop Total number of consented subjects: 1888 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"A Genome-Wide Association Comparative Analysis of Response of AF Patients to Rate Control Therapy; A Collaboration between the NIH Pharmacogenomics Research Network and the RIKEN Yokohama Institute Center for Genomic Medicine","short_name":"PGRN_Afib_HMB","commons":"BioData Catalyst","study_url":"","_subjects_count":1888,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs000442.v1.p1.c1":{"gen3_discovery":{"authz":"/programs/heartfailure/projects/DrugRes_HTN_GRU","tags":[],"_unique_id":"phs000442.v1.p1.c1","study_id":"phs000442.v1.p1.c1","study_description":"Resistant hypertension is defined as blood pressure that remains above goal in spite of the concurrent use of 3 antihypertensive agents of different classes or the concurrent use of 4 or more antihypertensive agents regardless of control. Its diagnosis is important for the identification of patients who are at high risk of having reversible causes of hypertension and/or patients who, because of persistently high blood pressure levels, may benefit from special diagnostic and therapeutic considerations. Resistant hypertension represents an extreme phenotype, thus, it has been predicted that genetic factors could play a larger role than for the general hypertensive population. Genetic assessments of patients with resistant hypertension have been limited. The current study assayed the exome of 91 African American patients with treatment resistant hypertension. Study Design: Case-Control Study Type: Longitudinal Case Set Exome Sequencing dbGaP estimated ancestry using GRAF-pop Total number of consented subjects: 91 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Drug Resistant Hypertension in African Americans' Exome","short_name":"DrugRes_HTN_GRU","commons":"BioData Catalyst","study_url":"","_subjects_count":91,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs000479.v1.p1.c1":{"gen3_discovery":{"authz":"/programs/heartfailure/projects/Exome_SCID_GRU","tags":[{"name":"dbGaP","category":"Study Registration"}],"_unique_id":"phs000479.v1.p1.c1","study_id":"phs000479.v1.p1.c1","study_description":"Analysis of the molecular etiologies of severe combined immunodeficiency (SCID) has led to important insights into the control of immune cell development. Most cases of SCID result from either X-linked or autosomal recessive inheritance of mutations in a known causative gene. However, in some cases, the molecular etiology remains unclear. To identify the cause of SCID in a patient known to lack the protein tyrosine phosphatase CD45, we utilized single nucleotide polymorphisms (SNP) arrays and whole exome sequencing. The patient's mother was heterozygous for an inactivating mutation in CD45, while the paternal alleles lacked mutations. The patient exhibited a single CD45 mutation identical to the maternal allele. Patient SNP array analysis revealed no change in copy number but loss of heterozygosity for the entire length of chromosome 1 (Chr1), indicating that disease was caused by uniparental disomy (UPD) with isodisomy of the entire maternal Chr1 bearing the CD45 mutation. Non-lymphoid blood cells and other mesoderm and ectoderm-derived tissues retained UPD of the entire maternal Chr1 in this patient who had undergone successful bone marrow transplantation. Exome sequencing revealed mutations in 7 additional genes bearing nonsynonymous SNPs predicted to have deleterious effects. These findings represent the first reported case of SCID caused by UPD and suggest UPD should be considered in SCID and other recessive disorders, especially when the patient appears homozygous for an abnormal gene found in only one parent. Evaluation for alterations in other genes affected by UPD should also be considered in such cases. Study Design: Family/Twin/Trios Study Type: Parent-Offspring Trios Total number of consented subjects: 3 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"National Heart Lung and Blood Institute Exome sequencing in SCID","short_name":"Exome_SCID_GRU","commons":"BioData Catalyst","study_url":"https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000479.v1.p1","_subjects_count":3,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs000481.v3.p2.c1":{"gen3_discovery":{"authz":"/programs/heartfailure/projects/CAP_GRU","tags":[],"_unique_id":"phs000481.v3.p2.c1","study_id":"phs000481.v3.p2.c1","study_description":"The Cholesterol and Pharmacogenetics Study was a 6-week open label, non-randomized study of 40mg/day simvastatin treatment in 335 black and 609 white (944 total) men and women. Plasma lipids and lipoproteins were measured on two occasions prior to treatment and at 4 and 6 weeks of treatment. The study was designed to test for genetic associations with baseline measurements and changes in response to simvastatin treatment. Whole genome genotyping was performed on 592 white CAP study participants in two stages. In Stage 1, 304 were genotyped for 314,621 SNPs to tag for common genomic variation. In Stage 2, 290 participants were genotyped, including 280 who were genotyped for 620,901 SNPs. Two samples were excluded due to gender discrepancies. More recently, CAP self-reported black participants were genotyped on Illumina Omni2.5Exome chips. PolyA-selected strand-specific RNA-seq libraries were generated in several batches from lymphoblastoid cell lines (LCLs) derived from 268 white and 165 black CAP participants. The LCLs were exposed to sham buffer (control) or 2 uM activated simvastatin for 24 hours, producing a total of 866 100/101 bp paired end RNA-seq libraries sequenced on Illumina HiSeq 2000 machines. Study Weblinks: Cholesterol and Pharmacogenetic Study (CAP) Study Design: Clinical Trial Study Type: Clinical Trial dbGaP estimated ancestry using GRAF-pop Total number of consented subjects: 762 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Cholesterol and Pharmacogenetics (CAP) Study","short_name":"CAP_GRU","commons":"BioData Catalyst","study_url":"","_subjects_count":762,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs000498.v5.p2.c1":{"gen3_discovery":{"authz":"/programs/dbGaP/projects/Allelic_Spectrum_JHS_HMB-IRB-NPU","tags":[],"_unique_id":"phs000498.v5.p2.c1","study_id":"phs000498.v5.p2.c1","study_description":"This sub-study phs000498 JHS Allelic Spectrum Seq contains genotype derived from sequence data and selected phenotype of subjects available from the phs000498 study. Summary level phenotypes for the NHLBI JHS Cohort study participants can be viewed at the top-level study page phs000286 JHS Cohort. Individual level phenotype data and molecular data for all JHS Cohort top-level study and sub-study are available by requesting Authorized Access to the NHLBI JHS Cohort phs000286 study. Cardiovascular disease (CVD) is the leading cause of death in the US, affecting 64 million Americans and costing over 368 billion dollars annually. To elucidate causes of CVD, NIH established the Framingham Heart Study (FHS) in 1948. In 1971, 5000 adult children and spouses of original FHS participants expanded the initial population-based cohort. The FHS Offspring cohort has now been followed for a decade beyond their 6th cardiovascular examination, providing incidence and prevalence data for CVD. These data indicate that diabetes mellitus, hyperlipidemia, hypertension, left ventricular hypertrophy, cigarette smoking, obesity, sedentary life style, and family history are major risk factors for development of atherosclerosis, coronary artery disease, myocardial infarction, heart failure, and stroke. With these discoveries came the unanticipated realization of considerable gender and ethnic disparities in the prevalence of cardiovascular risk factors, clinically overt CVD, and CVD-related mortality. White women scored lowest in each of these categories, and black men scored highest. To understand and address these disparities, additional cohorts were designed with specified ethnic and racial demographics. One of these, the Jackson Heart Study (JHS), extends and expands a minority cohort living in Jackson, MS and initially identified within an earlier population-based study (The Atherosclerosis Risk in Communities; ARIC). Between 2000-2004 the JHS has enrolled and conducted clinical examinations to determine the prevalence of cardiovascular risk factors and disease in over 5300 subjects. The JHS cohort resembles the recent FHS Offspring examination 6 cohort (JHS: 1907 men, 3395 women; mean age 55 years; FHS Offspring: 1647 men, 1866 women; mean age 59 years), however the FHS cohort contains predominantly white Americans (›95%) of European ancestry while the JHS cohort contains 100% African Americans. The role of genetic variation is documented by substantial heritability to cardiovascular disease risk factors, left ventricular hypertrophy and subclinical atherosclerosis, as well as evidence for familial aggregation of common forms of cardiovascular disease such as coronary heart disease, heart failure and sudden cardiac death. Molecular genetic studies of Mendelian disorders and, to a much more limited degree, association studies of common variants have led to the identification of human gene mutations that influence important CVD phenotypes. Hundreds of mutations in over 100 genes are known to produce major effects on serum cholesterol, lipoprotein and glucose levels, blood pressure via renal handling of salt and water, myocardial contractile function and ventricular morphology, and cardiac electrophysiologic properties. The phenotypes produced by single gene defects (hypercholesterolemia, diabetes, hypertension, cardiac hypertrophy, and cardiac arrhythmias) are remarkably similar to the common cardiovascular disease risk factors found broadly within the general population, raising the hypothesis that the full allelic spectrum of CVD genes may, in sum, contribute substantially to overall CVD prevalence. To provide a comprehensive assessment of the frequency and distribution of rare and common allelic variation in previously defined cardiovascular genes in general populations with defined incident cardiovascular risks and disease, we have assembled a collaborative group that includes investigators with considerable expertise in the study of CVD genes and leading investigators in the JHS. This study includes the generation of deep coverage targeted re-sequencing and variant identification for 219 genes in the Jackson Heart Study sample collection. Study Design: Prospective Longitudinal Cohort Study Type: Cohort Total number of consented subjects: 1983 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"JHS Allelic Spectrum Project","short_name":"Allelic_Spectrum_JHS_HMB-IRB-NPU","commons":"BioData Catalyst","study_url":"","_subjects_count":501,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs000498.v5.p2.c2":{"gen3_discovery":{"authz":"/programs/dbGaP/projects/Allelic_Spectrum_JHS_DS-FDO-IRB-NPU","tags":[],"_unique_id":"phs000498.v5.p2.c2","study_id":"phs000498.v5.p2.c2","study_description":"This sub-study phs000498 JHS Allelic Spectrum Seq contains genotype derived from sequence data and selected phenotype of subjects available from the phs000498 study. Summary level phenotypes for the NHLBI JHS Cohort study participants can be viewed at the top-level study page phs000286 JHS Cohort. Individual level phenotype data and molecular data for all JHS Cohort top-level study and sub-study are available by requesting Authorized Access to the NHLBI JHS Cohort phs000286 study. Cardiovascular disease (CVD) is the leading cause of death in the US, affecting 64 million Americans and costing over 368 billion dollars annually. To elucidate causes of CVD, NIH established the Framingham Heart Study (FHS) in 1948. In 1971, 5000 adult children and spouses of original FHS participants expanded the initial population-based cohort. The FHS Offspring cohort has now been followed for a decade beyond their 6th cardiovascular examination, providing incidence and prevalence data for CVD. These data indicate that diabetes mellitus, hyperlipidemia, hypertension, left ventricular hypertrophy, cigarette smoking, obesity, sedentary life style, and family history are major risk factors for development of atherosclerosis, coronary artery disease, myocardial infarction, heart failure, and stroke. With these discoveries came the unanticipated realization of considerable gender and ethnic disparities in the prevalence of cardiovascular risk factors, clinically overt CVD, and CVD-related mortality. White women scored lowest in each of these categories, and black men scored highest. To understand and address these disparities, additional cohorts were designed with specified ethnic and racial demographics. One of these, the Jackson Heart Study (JHS), extends and expands a minority cohort living in Jackson, MS and initially identified within an earlier population-based study (The Atherosclerosis Risk in Communities; ARIC). Between 2000-2004 the JHS has enrolled and conducted clinical examinations to determine the prevalence of cardiovascular risk factors and disease in over 5300 subjects. The JHS cohort resembles the recent FHS Offspring examination 6 cohort (JHS: 1907 men, 3395 women; mean age 55 years; FHS Offspring: 1647 men, 1866 women; mean age 59 years), however the FHS cohort contains predominantly white Americans (›95%) of European ancestry while the JHS cohort contains 100% African Americans. The role of genetic variation is documented by substantial heritability to cardiovascular disease risk factors, left ventricular hypertrophy and subclinical atherosclerosis, as well as evidence for familial aggregation of common forms of cardiovascular disease such as coronary heart disease, heart failure and sudden cardiac death. Molecular genetic studies of Mendelian disorders and, to a much more limited degree, association studies of common variants have led to the identification of human gene mutations that influence important CVD phenotypes. Hundreds of mutations in over 100 genes are known to produce major effects on serum cholesterol, lipoprotein and glucose levels, blood pressure via renal handling of salt and water, myocardial contractile function and ventricular morphology, and cardiac electrophysiologic properties. The phenotypes produced by single gene defects (hypercholesterolemia, diabetes, hypertension, cardiac hypertrophy, and cardiac arrhythmias) are remarkably similar to the common cardiovascular disease risk factors found broadly within the general population, raising the hypothesis that the full allelic spectrum of CVD genes may, in sum, contribute substantially to overall CVD prevalence. To provide a comprehensive assessment of the frequency and distribution of rare and common allelic variation in previously defined cardiovascular genes in general populations with defined incident cardiovascular risks and disease, we have assembled a collaborative group that includes investigators with considerable expertise in the study of CVD genes and leading investigators in the JHS. This study includes the generation of deep coverage targeted re-sequencing and variant identification for 219 genes in the Jackson Heart Study sample collection. Study Design: Prospective Longitudinal Cohort Study Type: Cohort Total number of consented subjects: 1983 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"JHS Allelic Spectrum Project","short_name":"Allelic_Spectrum_JHS_DS-FDO-IRB-NPU","commons":"BioData Catalyst","study_url":"","_subjects_count":94,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs000498.v5.p2.c3":{"gen3_discovery":{"authz":"/programs/dbGaP/projects/Allelic_Spectrum_JHS_HMB-IRB","tags":[],"_unique_id":"phs000498.v5.p2.c3","study_id":"phs000498.v5.p2.c3","study_description":"This sub-study phs000498 JHS Allelic Spectrum Seq contains genotype derived from sequence data and selected phenotype of subjects available from the phs000498 study. Summary level phenotypes for the NHLBI JHS Cohort study participants can be viewed at the top-level study page phs000286 JHS Cohort. Individual level phenotype data and molecular data for all JHS Cohort top-level study and sub-study are available by requesting Authorized Access to the NHLBI JHS Cohort phs000286 study. Cardiovascular disease (CVD) is the leading cause of death in the US, affecting 64 million Americans and costing over 368 billion dollars annually. To elucidate causes of CVD, NIH established the Framingham Heart Study (FHS) in 1948. In 1971, 5000 adult children and spouses of original FHS participants expanded the initial population-based cohort. The FHS Offspring cohort has now been followed for a decade beyond their 6th cardiovascular examination, providing incidence and prevalence data for CVD. These data indicate that diabetes mellitus, hyperlipidemia, hypertension, left ventricular hypertrophy, cigarette smoking, obesity, sedentary life style, and family history are major risk factors for development of atherosclerosis, coronary artery disease, myocardial infarction, heart failure, and stroke. With these discoveries came the unanticipated realization of considerable gender and ethnic disparities in the prevalence of cardiovascular risk factors, clinically overt CVD, and CVD-related mortality. White women scored lowest in each of these categories, and black men scored highest. To understand and address these disparities, additional cohorts were designed with specified ethnic and racial demographics. One of these, the Jackson Heart Study (JHS), extends and expands a minority cohort living in Jackson, MS and initially identified within an earlier population-based study (The Atherosclerosis Risk in Communities; ARIC). Between 2000-2004 the JHS has enrolled and conducted clinical examinations to determine the prevalence of cardiovascular risk factors and disease in over 5300 subjects. The JHS cohort resembles the recent FHS Offspring examination 6 cohort (JHS: 1907 men, 3395 women; mean age 55 years; FHS Offspring: 1647 men, 1866 women; mean age 59 years), however the FHS cohort contains predominantly white Americans (›95%) of European ancestry while the JHS cohort contains 100% African Americans. The role of genetic variation is documented by substantial heritability to cardiovascular disease risk factors, left ventricular hypertrophy and subclinical atherosclerosis, as well as evidence for familial aggregation of common forms of cardiovascular disease such as coronary heart disease, heart failure and sudden cardiac death. Molecular genetic studies of Mendelian disorders and, to a much more limited degree, association studies of common variants have led to the identification of human gene mutations that influence important CVD phenotypes. Hundreds of mutations in over 100 genes are known to produce major effects on serum cholesterol, lipoprotein and glucose levels, blood pressure via renal handling of salt and water, myocardial contractile function and ventricular morphology, and cardiac electrophysiologic properties. The phenotypes produced by single gene defects (hypercholesterolemia, diabetes, hypertension, cardiac hypertrophy, and cardiac arrhythmias) are remarkably similar to the common cardiovascular disease risk factors found broadly within the general population, raising the hypothesis that the full allelic spectrum of CVD genes may, in sum, contribute substantially to overall CVD prevalence. To provide a comprehensive assessment of the frequency and distribution of rare and common allelic variation in previously defined cardiovascular genes in general populations with defined incident cardiovascular risks and disease, we have assembled a collaborative group that includes investigators with considerable expertise in the study of CVD genes and leading investigators in the JHS. This study includes the generation of deep coverage targeted re-sequencing and variant identification for 219 genes in the Jackson Heart Study sample collection. Study Design: Prospective Longitudinal Cohort Study Type: Cohort Total number of consented subjects: 1983 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"JHS Allelic Spectrum Project","short_name":"Allelic_Spectrum_JHS_HMB-IRB","commons":"BioData Catalyst","study_url":"","_subjects_count":1138,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs000498.v5.p2.c4":{"gen3_discovery":{"authz":"/programs/dbGaP/projects/Allelic_Spectrum_JHS_DS-FDO-IRB","tags":[],"_unique_id":"phs000498.v5.p2.c4","study_id":"phs000498.v5.p2.c4","study_description":"This sub-study phs000498 JHS Allelic Spectrum Seq contains genotype derived from sequence data and selected phenotype of subjects available from the phs000498 study. Summary level phenotypes for the NHLBI JHS Cohort study participants can be viewed at the top-level study page phs000286 JHS Cohort. Individual level phenotype data and molecular data for all JHS Cohort top-level study and sub-study are available by requesting Authorized Access to the NHLBI JHS Cohort phs000286 study. Cardiovascular disease (CVD) is the leading cause of death in the US, affecting 64 million Americans and costing over 368 billion dollars annually. To elucidate causes of CVD, NIH established the Framingham Heart Study (FHS) in 1948. In 1971, 5000 adult children and spouses of original FHS participants expanded the initial population-based cohort. The FHS Offspring cohort has now been followed for a decade beyond their 6th cardiovascular examination, providing incidence and prevalence data for CVD. These data indicate that diabetes mellitus, hyperlipidemia, hypertension, left ventricular hypertrophy, cigarette smoking, obesity, sedentary life style, and family history are major risk factors for development of atherosclerosis, coronary artery disease, myocardial infarction, heart failure, and stroke. With these discoveries came the unanticipated realization of considerable gender and ethnic disparities in the prevalence of cardiovascular risk factors, clinically overt CVD, and CVD-related mortality. White women scored lowest in each of these categories, and black men scored highest. To understand and address these disparities, additional cohorts were designed with specified ethnic and racial demographics. One of these, the Jackson Heart Study (JHS), extends and expands a minority cohort living in Jackson, MS and initially identified within an earlier population-based study (The Atherosclerosis Risk in Communities; ARIC). Between 2000-2004 the JHS has enrolled and conducted clinical examinations to determine the prevalence of cardiovascular risk factors and disease in over 5300 subjects. The JHS cohort resembles the recent FHS Offspring examination 6 cohort (JHS: 1907 men, 3395 women; mean age 55 years; FHS Offspring: 1647 men, 1866 women; mean age 59 years), however the FHS cohort contains predominantly white Americans (›95%) of European ancestry while the JHS cohort contains 100% African Americans. The role of genetic variation is documented by substantial heritability to cardiovascular disease risk factors, left ventricular hypertrophy and subclinical atherosclerosis, as well as evidence for familial aggregation of common forms of cardiovascular disease such as coronary heart disease, heart failure and sudden cardiac death. Molecular genetic studies of Mendelian disorders and, to a much more limited degree, association studies of common variants have led to the identification of human gene mutations that influence important CVD phenotypes. Hundreds of mutations in over 100 genes are known to produce major effects on serum cholesterol, lipoprotein and glucose levels, blood pressure via renal handling of salt and water, myocardial contractile function and ventricular morphology, and cardiac electrophysiologic properties. The phenotypes produced by single gene defects (hypercholesterolemia, diabetes, hypertension, cardiac hypertrophy, and cardiac arrhythmias) are remarkably similar to the common cardiovascular disease risk factors found broadly within the general population, raising the hypothesis that the full allelic spectrum of CVD genes may, in sum, contribute substantially to overall CVD prevalence. To provide a comprehensive assessment of the frequency and distribution of rare and common allelic variation in previously defined cardiovascular genes in general populations with defined incident cardiovascular risks and disease, we have assembled a collaborative group that includes investigators with considerable expertise in the study of CVD genes and leading investigators in the JHS. This study includes the generation of deep coverage targeted re-sequencing and variant identification for 219 genes in the Jackson Heart Study sample collection. Study Design: Prospective Longitudinal Cohort Study Type: Cohort Total number of consented subjects: 1983 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"JHS Allelic Spectrum Project","short_name":"Allelic_Spectrum_JHS_DS-FDO-IRB","commons":"BioData Catalyst","study_url":"","_subjects_count":250,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs000499.v5.p2.c1":{"gen3_discovery":{"authz":"/programs/dbGaP/projects/CARe_JHS_HMB-IRB-NPU","tags":[],"_unique_id":"phs000499.v5.p2.c1","study_id":"phs000499.v5.p2.c1","study_description":"This sub-study phs000499 JHS CARe contains genotype data of subjects available from the phs000499 study. Summary level phenotypes for the NHLBI JHS Cohort study participants can be viewed at the top-level study page phs000286 JHS Cohort. Individual level phenotype data and molecular data for all JHS Cohort top-level study and substudies are available by requesting Authorized Access to the NHLBI JHS Cohort phs000286 study. The Jackson Heart Study (JHS) is a large, community-based, observational study whose participants were recruited from urban and rural areas of the three counties (Hinds, Madison and Rankin) that make up the Jackson, Mississippi, metropolitan statistical area (MSA). Participants were enrolled from each of 4 recruitment pools: random, 17%; volunteer, 30%; currently enrolled in the Atherosclerosis Risk in Communities (ARIC) Study, 22% and secondary family members, 31%. Recruitment was limited to non-institutionalized adult African Americans 35-84 years old, except in the family cohort where those 21 to 34 years of age were eligible. The final cohort of 5,301 participants includes 6.59% of all African American Jackson MSA residents aged 35-84 (N-76,426, US Census 2000). Major components of each exam include medical history, physical examination, blood/urine analytes and interview questions on areas such as: physical activity; stress, coping and spirituality; racism and discrimination; socioeconomic position; and access to health care. At 12-month intervals after the baseline clinic visit (Exam 1), participants are contacted by telephone to: update information; confirm vital statistics; document interim medical events, hospitalizations, and functional status; and obtain additional sociocultural information. Questions about medical events, symptoms of cardiovascular disease and functional status are repeated annually. Ongoing cohort surveillance includes abstraction of medical records and death certificates for relevant International Classification of Diseases (ICD) codes and adjudication of nonfatal events and deaths. NHLBI Candidate-gene Association Resource. The NHLBI initiated the Candidate gene Association Resource (CARe) to create a shared genotype/phenotype resource for analyses of the association of genotypes with phenotypes relevant to the mission of the NHLBI. The resource comprises nine cohort studies funded by the NHLBI including: Atherosclerosis Risk in Communities (ARIC), Cardiovascular Health Study (CHS), Cleveland Family Study (CFS), Coronary Artery Risk Development in Young Adults (CARDIA), Framingham Heart Study (FHS), Jackson Heart Study (JHS), Multi-Ethnic Study of Atherosclerosis (MESA), and the Sleep Heart Health Study (SHHS). A database of genotype and phenotype data was created that includes records for approximately 41,000 study participants with approximately 50,000 SNPs from more than 2,000 selected candidate genes. In addition, a genome wide association study (GWAS) using a 1,000K SNP Chip was conducted on approximately 8,900 African American participants drawn from five CARe cohorts: ARIC, CARDIA, CFS, JHS, and MESA. Data from individual cohorts is available to approved investigators through dbGaP. Study Weblinks: Jackson Heart Study Study Design: Prospective Longitudinal Cohort Study Type: Cohort dbGaP estimated ancestry using GRAF-pop Total number of consented subjects: 3352 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"NHLBI Jackson Heart Study Candidate Gene Association Resource (CARe)","short_name":"CARe_JHS_HMB-IRB-NPU","commons":"BioData Catalyst","study_url":"","_subjects_count":757,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs000499.v5.p2.c2":{"gen3_discovery":{"authz":"/programs/dbGaP/projects/CARe_JHS_DS-FDO-IRB-NPU","tags":[],"_unique_id":"phs000499.v5.p2.c2","study_id":"phs000499.v5.p2.c2","study_description":"This sub-study phs000499 JHS CARe contains genotype data of subjects available from the phs000499 study. Summary level phenotypes for the NHLBI JHS Cohort study participants can be viewed at the top-level study page phs000286 JHS Cohort. Individual level phenotype data and molecular data for all JHS Cohort top-level study and substudies are available by requesting Authorized Access to the NHLBI JHS Cohort phs000286 study. The Jackson Heart Study (JHS) is a large, community-based, observational study whose participants were recruited from urban and rural areas of the three counties (Hinds, Madison and Rankin) that make up the Jackson, Mississippi, metropolitan statistical area (MSA). Participants were enrolled from each of 4 recruitment pools: random, 17%; volunteer, 30%; currently enrolled in the Atherosclerosis Risk in Communities (ARIC) Study, 22% and secondary family members, 31%. Recruitment was limited to non-institutionalized adult African Americans 35-84 years old, except in the family cohort where those 21 to 34 years of age were eligible. The final cohort of 5,301 participants includes 6.59% of all African American Jackson MSA residents aged 35-84 (N-76,426, US Census 2000). Major components of each exam include medical history, physical examination, blood/urine analytes and interview questions on areas such as: physical activity; stress, coping and spirituality; racism and discrimination; socioeconomic position; and access to health care. At 12-month intervals after the baseline clinic visit (Exam 1), participants are contacted by telephone to: update information; confirm vital statistics; document interim medical events, hospitalizations, and functional status; and obtain additional sociocultural information. Questions about medical events, symptoms of cardiovascular disease and functional status are repeated annually. Ongoing cohort surveillance includes abstraction of medical records and death certificates for relevant International Classification of Diseases (ICD) codes and adjudication of nonfatal events and deaths. NHLBI Candidate-gene Association Resource. The NHLBI initiated the Candidate gene Association Resource (CARe) to create a shared genotype/phenotype resource for analyses of the association of genotypes with phenotypes relevant to the mission of the NHLBI. The resource comprises nine cohort studies funded by the NHLBI including: Atherosclerosis Risk in Communities (ARIC), Cardiovascular Health Study (CHS), Cleveland Family Study (CFS), Coronary Artery Risk Development in Young Adults (CARDIA), Framingham Heart Study (FHS), Jackson Heart Study (JHS), Multi-Ethnic Study of Atherosclerosis (MESA), and the Sleep Heart Health Study (SHHS). A database of genotype and phenotype data was created that includes records for approximately 41,000 study participants with approximately 50,000 SNPs from more than 2,000 selected candidate genes. In addition, a genome wide association study (GWAS) using a 1,000K SNP Chip was conducted on approximately 8,900 African American participants drawn from five CARe cohorts: ARIC, CARDIA, CFS, JHS, and MESA. Data from individual cohorts is available to approved investigators through dbGaP. Study Weblinks: Jackson Heart Study Study Design: Prospective Longitudinal Cohort Study Type: Cohort dbGaP estimated ancestry using GRAF-pop Total number of consented subjects: 3352 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"NHLBI Jackson Heart Study Candidate Gene Association Resource (CARe)","short_name":"CARe_JHS_DS-FDO-IRB-NPU","commons":"BioData Catalyst","study_url":"","_subjects_count":165,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs000499.v5.p2.c3":{"gen3_discovery":{"authz":"/programs/dbGaP/projects/CARe_JHS_HMB-IRB","tags":[],"_unique_id":"phs000499.v5.p2.c3","study_id":"phs000499.v5.p2.c3","study_description":"This sub-study phs000499 JHS CARe contains genotype data of subjects available from the phs000499 study. Summary level phenotypes for the NHLBI JHS Cohort study participants can be viewed at the top-level study page phs000286 JHS Cohort. Individual level phenotype data and molecular data for all JHS Cohort top-level study and substudies are available by requesting Authorized Access to the NHLBI JHS Cohort phs000286 study. The Jackson Heart Study (JHS) is a large, community-based, observational study whose participants were recruited from urban and rural areas of the three counties (Hinds, Madison and Rankin) that make up the Jackson, Mississippi, metropolitan statistical area (MSA). Participants were enrolled from each of 4 recruitment pools: random, 17%; volunteer, 30%; currently enrolled in the Atherosclerosis Risk in Communities (ARIC) Study, 22% and secondary family members, 31%. Recruitment was limited to non-institutionalized adult African Americans 35-84 years old, except in the family cohort where those 21 to 34 years of age were eligible. The final cohort of 5,301 participants includes 6.59% of all African American Jackson MSA residents aged 35-84 (N-76,426, US Census 2000). Major components of each exam include medical history, physical examination, blood/urine analytes and interview questions on areas such as: physical activity; stress, coping and spirituality; racism and discrimination; socioeconomic position; and access to health care. At 12-month intervals after the baseline clinic visit (Exam 1), participants are contacted by telephone to: update information; confirm vital statistics; document interim medical events, hospitalizations, and functional status; and obtain additional sociocultural information. Questions about medical events, symptoms of cardiovascular disease and functional status are repeated annually. Ongoing cohort surveillance includes abstraction of medical records and death certificates for relevant International Classification of Diseases (ICD) codes and adjudication of nonfatal events and deaths. NHLBI Candidate-gene Association Resource. The NHLBI initiated the Candidate gene Association Resource (CARe) to create a shared genotype/phenotype resource for analyses of the association of genotypes with phenotypes relevant to the mission of the NHLBI. The resource comprises nine cohort studies funded by the NHLBI including: Atherosclerosis Risk in Communities (ARIC), Cardiovascular Health Study (CHS), Cleveland Family Study (CFS), Coronary Artery Risk Development in Young Adults (CARDIA), Framingham Heart Study (FHS), Jackson Heart Study (JHS), Multi-Ethnic Study of Atherosclerosis (MESA), and the Sleep Heart Health Study (SHHS). A database of genotype and phenotype data was created that includes records for approximately 41,000 study participants with approximately 50,000 SNPs from more than 2,000 selected candidate genes. In addition, a genome wide association study (GWAS) using a 1,000K SNP Chip was conducted on approximately 8,900 African American participants drawn from five CARe cohorts: ARIC, CARDIA, CFS, JHS, and MESA. Data from individual cohorts is available to approved investigators through dbGaP. Study Weblinks: Jackson Heart Study Study Design: Prospective Longitudinal Cohort Study Type: Cohort dbGaP estimated ancestry using GRAF-pop Total number of consented subjects: 3352 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"NHLBI Jackson Heart Study Candidate Gene Association Resource (CARe)","short_name":"CARe_JHS_HMB-IRB","commons":"BioData Catalyst","study_url":"","_subjects_count":1984,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs000499.v5.p2.c4":{"gen3_discovery":{"authz":"/programs/dbGaP/projects/CARe_JHS_DS-FDO-IRB","tags":[],"_unique_id":"phs000499.v5.p2.c4","study_id":"phs000499.v5.p2.c4","study_description":"This sub-study phs000499 JHS CARe contains genotype data of subjects available from the phs000499 study. Summary level phenotypes for the NHLBI JHS Cohort study participants can be viewed at the top-level study page phs000286 JHS Cohort. Individual level phenotype data and molecular data for all JHS Cohort top-level study and substudies are available by requesting Authorized Access to the NHLBI JHS Cohort phs000286 study. The Jackson Heart Study (JHS) is a large, community-based, observational study whose participants were recruited from urban and rural areas of the three counties (Hinds, Madison and Rankin) that make up the Jackson, Mississippi, metropolitan statistical area (MSA). Participants were enrolled from each of 4 recruitment pools: random, 17%; volunteer, 30%; currently enrolled in the Atherosclerosis Risk in Communities (ARIC) Study, 22% and secondary family members, 31%. Recruitment was limited to non-institutionalized adult African Americans 35-84 years old, except in the family cohort where those 21 to 34 years of age were eligible. The final cohort of 5,301 participants includes 6.59% of all African American Jackson MSA residents aged 35-84 (N-76,426, US Census 2000). Major components of each exam include medical history, physical examination, blood/urine analytes and interview questions on areas such as: physical activity; stress, coping and spirituality; racism and discrimination; socioeconomic position; and access to health care. At 12-month intervals after the baseline clinic visit (Exam 1), participants are contacted by telephone to: update information; confirm vital statistics; document interim medical events, hospitalizations, and functional status; and obtain additional sociocultural information. Questions about medical events, symptoms of cardiovascular disease and functional status are repeated annually. Ongoing cohort surveillance includes abstraction of medical records and death certificates for relevant International Classification of Diseases (ICD) codes and adjudication of nonfatal events and deaths. NHLBI Candidate-gene Association Resource. The NHLBI initiated the Candidate gene Association Resource (CARe) to create a shared genotype/phenotype resource for analyses of the association of genotypes with phenotypes relevant to the mission of the NHLBI. The resource comprises nine cohort studies funded by the NHLBI including: Atherosclerosis Risk in Communities (ARIC), Cardiovascular Health Study (CHS), Cleveland Family Study (CFS), Coronary Artery Risk Development in Young Adults (CARDIA), Framingham Heart Study (FHS), Jackson Heart Study (JHS), Multi-Ethnic Study of Atherosclerosis (MESA), and the Sleep Heart Health Study (SHHS). A database of genotype and phenotype data was created that includes records for approximately 41,000 study participants with approximately 50,000 SNPs from more than 2,000 selected candidate genes. In addition, a genome wide association study (GWAS) using a 1,000K SNP Chip was conducted on approximately 8,900 African American participants drawn from five CARe cohorts: ARIC, CARDIA, CFS, JHS, and MESA. Data from individual cohorts is available to approved investigators through dbGaP. Study Weblinks: Jackson Heart Study Study Design: Prospective Longitudinal Cohort Study Type: Cohort dbGaP estimated ancestry using GRAF-pop Total number of consented subjects: 3352 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"NHLBI Jackson Heart Study Candidate Gene Association Resource (CARe)","short_name":"CARe_JHS_DS-FDO-IRB","commons":"BioData Catalyst","study_url":"","_subjects_count":446,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs000507.v2.p2.c1":{"gen3_discovery":{"authz":"/programs/heartfailure/projects/BEN_HMB","tags":[],"_unique_id":"phs000507.v2.p2.c1","study_id":"phs000507.v2.p2.c1","study_description":"Benign ethnic neutropenia (BEN) is a clinical condition more commonly observed in African-Americans. It is characterized by a relative reduction in neutrophil count by about 1000 cells per microliter, leading to a decrease in total leukocyte count by similar decrement. Previous reports of this condition showed that there was neither higher frequency nor increased severity of infections in affected individuals. Bone marrow examinations showed normal white cell maturation; and ex vivo culture of marrow cells showed low normal or slightly reduced number of myeloid colonies. Under physiologic stress, the increases in neutrophil and leukocyte counts of BEN individuals are slightly lower, compared to normal African-Americans or Caucasians. These clinical observations suggest that BEN results from a lower 'set point' for cell number in the marrow. Additionally, case reports of familial BEN, the persistence of BEN over many decades in the US, UK, and Africa, and the recent report of Duffy antigen and chemokine receptor (DARC) being associated with neutropenia, all suggest a strong genetic association to neutropenia/leukopenia. Our initial look into microarray analyses in a pilot trial of subjects showed that there were no significant differences in mRNA signals between BEN and normal subjects. Therefore, we are now proposing a larger study, utilizing Illumina Omni Express chips, to look for genetic associations. We have partnered with the Reasons for Geographic and Racial Differences in Stroke study (REGARDS), where nearly half of the cohort are African-Americans. This will be one of the few GWAS being performed in only African-Americans, and will provide valuable genetic information to link with neutropenia and possibly other conditions/diseases. Genotyping was performed by the Johns Hopkins University Center for Inherited Disease Research (CIDR). Quality control of the genotypic and phenotypic data was performed through a collaboration between CIDR and the Genetics Coordinating Center, Department of Biostatistics at the University of Washington, which is funded by a federal contract supported by 14 NIH Institutes (HHSN268200782096C). Study Weblinks: REGARDS Study Design: Case-Control Study Type: Case-Control dbGaP estimated ancestry using GRAF-pop Total number of consented subjects: 1200 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"NHLBI and NIDDK Sponsored GWAS in Benign Ethnic Neutropenia/Leukopenia (BEN) in African-Americans (age >45 yrs old) from the REGARDS","short_name":"BEN_HMB","commons":"BioData Catalyst","study_url":"","_subjects_count":1200,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs000518.v1.p1.c1":{"gen3_discovery":{"authz":"/programs/heartfailure/projects/Fam_IB_GRU","tags":[],"_unique_id":"phs000518.v1.p1.c1","study_id":"phs000518.v1.p1.c1","study_description":"The NHLBI \"Grand Opportunity\" Exome Sequencing Project (GO-ESP), a signature project of the NHLBI Recovery Act investment, was designed to identify genetic variants in coding regions (exons) of the human genome (the \"exome\") that are associated with heart, lung and blood diseases. These and related diseases that are of high impact to public health and individuals from diverse racial and ethnic groups will be studied. These data may help researchers understand the causes of disease, contributing to better ways to prevent, diagnose, and treat diseases, as well as determine whether to tailor prevention and treatments to specific populations. This could lead to more effective treatments and reduce the likelihood of side effects. GO-ESP is comprised of five collaborative components: 3 cohort consortia - HeartGO, LungGO, and WHISP - and 2 sequencing centers - BroadGO and SeattleGO. The major goal of this project is to apply next generation resequencing technology to identify disease-causing variants that cause bronchiectasis of unknown etiology (e.g. non cystic fibrosis (CF), classic primary ciliary dyskinesia (PCD), immune deficiency, or any other known cause of bronchiectasis), i.e., \"idiopathic bronchiectasis.\" As part of our ongoing efforts to define the genetic cause of rare lung diseases, we have also studied families in whom diagnosis of PCD or other known etiologies could not be confirmed. We have systematically collected and stored the DNA and phenotypic data on each of the families in our cohort. The phenotypic data includes age, gender, ethnicity information, clinical data pertaining to the airways disease, including neonatal respiratory distress, otitis media, sinusitis and bronchiectasis, ciliary ultrastructure analysis, and microbial colonization (status of nontuberculosis mycobacterium). During the course of our study, we have acquired 98 unrelated patients in whom bronchiectasis seemed to be of unknown causes. We will be using 11 unrelated patients, 5 unrelated affected sib-pairs, and 3 affected sibs from a family from this cohort, based on 1) development of bronchiectasis in the absence of smoking, 2) a good family pedigree with available DNA, and 3) a family history of bronchiectasis and/or occurrence of airways disease in a sibling. Classic CF, PCD and immune deficiency were ruled out, based on the tests described above. Alpha-1 antiprotease deficiency work up was negative and none of the patients were tobacco users or smokers. Study Weblinks: NHLBI GO-ESP Project Study Design: Prospective Longitudinal Cohort Study Type: Cohort Total number of consented subjects: 24 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"NHLBI GO-ESP Family Studies: Idiopathic Bronchiectasis of unknown etiology that is not related to cystic fibrosis or classic primary ciliary dyskinesia or immune deficiency or any other known causes","short_name":"Fam_IB_GRU","commons":"BioData Catalyst","study_url":"","_subjects_count":24,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs000553.v1.p1.c1":{"gen3_discovery":{"authz":"/programs/heartfailure/projects/FamExome_RarePeds_GRU-MDS","tags":[{"name":"dbGaP","category":"Study Registration"}],"_unique_id":"phs000553.v1.p1.c1","study_id":"phs000553.v1.p1.c1","study_description":"To discover novel candidate genes associated with rare Mendelian phenotypes, we will conduct individual genomic and phenotypic characterization using genome-wide array, pedigree exome sequencing, candidate genotyping, and pertinent clinical testing to define phenotype. Pedigrees included in this submission will have a variety of clinical pathological phenotypes. Study Design: Family/Twin/Trios Study Type: Parent-Offspring Trios dbGaP estimated ancestry using GRAF-pop Total number of consented subjects: 6 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Familial Exome Sequencing in Rare Pediatric Phenotypes","short_name":"FamExome_RarePeds_GRU-MDS","commons":"BioData Catalyst","study_url":"https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000553.v1.p1","_subjects_count":6,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs000555.v2.p2.c1":{"gen3_discovery":{"authz":"/programs/dbGaP/projects/PAGE_CALiCo_HCHS_SOL_HMB-NPU","tags":[],"_unique_id":"phs000555.v2.p2.c1","study_id":"phs000555.v2.p2.c1","study_description":"This sub-study phs000555 PAGE CALiCo SOL contains genotype data and selected phenotype of subjects available from the phs000555. Summary level phenotypes for the NHLBI HCHS SOL Cohort study participants can be viewed at the top-level study page phs000810 HCHS SOL Cohort. Individual level phenotype data and molecular data for all HCHS SOL Cohort top-level study and sub-study are available by requesting Authorized Access to the NHLBI HCHS SOL Cohort phs000810 study. PAGE CALiCo SOL The Hispanic Community Health Study / Study of Latinos (HCHS/SOL) is a multi-center epidemiologic study in Hispanic/Latino populations to determine the role of acculturation in the prevalence and development of disease, and to identify risk factors playing a protective or harmful role in Hispanics/Latinos. The study is sponsored by the National Heart, Lung, and Blood Institute (NHLBI) and six other institutes, centers, and offices of the National Institutes of Health (NIH). The population of 16,000 persons of Hispanic/Latino origin, specifically Cuban, Puerto Rican, Mexican, and Central/South American, was recruited through four Field Centers affiliated with San Diego State University, Northwestern University in Chicago, Albert Einstein College of Medicine in the Bronx area of New York, and the University of Miami. Seven additional academic centers serve as scientific and logistical support centers. Study participants aged 18-74 years completed an extensive clinic exam and assessments to determine baseline risk factors. Annual follow-up interviews are conducted to determine health outcomes of interest. Study results are disseminated through scientific journals and also conveyed to the communities involved in the study in order to improve public health at the local level. This study is part of the Population Architecture using Genomics and Epidemiology (PAGE) study (phs000356). Study Weblinks: Population Architecture using Genomics and Epidemiology (PAGE) Hispanic Community Health Study Study Design: Prospective Longitudinal Cohort Study Type: Cohort Longitudinal dbGaP estimated ancestry using GRAF-pop Total number of consented subjects: 11043 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Population Architecture using Genomics and Epidemiology (PAGE): Causal Variants Across the Life Course (CALiCo): Hispanic Community Health Study / Study of Latinos (HCHS/SOL)","short_name":"PAGE_CALiCo_HCHS_SOL_HMB-NPU","commons":"BioData Catalyst","study_url":"","_subjects_count":2074,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs000555.v2.p2.c2":{"gen3_discovery":{"authz":"/programs/dbGaP/projects/PAGE_CALiCo_HCHS_SOL_HMB","tags":[],"_unique_id":"phs000555.v2.p2.c2","study_id":"phs000555.v2.p2.c2","study_description":"This sub-study phs000555 PAGE CALiCo SOL contains genotype data and selected phenotype of subjects available from the phs000555. Summary level phenotypes for the NHLBI HCHS SOL Cohort study participants can be viewed at the top-level study page phs000810 HCHS SOL Cohort. Individual level phenotype data and molecular data for all HCHS SOL Cohort top-level study and sub-study are available by requesting Authorized Access to the NHLBI HCHS SOL Cohort phs000810 study. PAGE CALiCo SOL The Hispanic Community Health Study / Study of Latinos (HCHS/SOL) is a multi-center epidemiologic study in Hispanic/Latino populations to determine the role of acculturation in the prevalence and development of disease, and to identify risk factors playing a protective or harmful role in Hispanics/Latinos. The study is sponsored by the National Heart, Lung, and Blood Institute (NHLBI) and six other institutes, centers, and offices of the National Institutes of Health (NIH). The population of 16,000 persons of Hispanic/Latino origin, specifically Cuban, Puerto Rican, Mexican, and Central/South American, was recruited through four Field Centers affiliated with San Diego State University, Northwestern University in Chicago, Albert Einstein College of Medicine in the Bronx area of New York, and the University of Miami. Seven additional academic centers serve as scientific and logistical support centers. Study participants aged 18-74 years completed an extensive clinic exam and assessments to determine baseline risk factors. Annual follow-up interviews are conducted to determine health outcomes of interest. Study results are disseminated through scientific journals and also conveyed to the communities involved in the study in order to improve public health at the local level. This study is part of the Population Architecture using Genomics and Epidemiology (PAGE) study (phs000356). Study Weblinks: Population Architecture using Genomics and Epidemiology (PAGE) Hispanic Community Health Study Study Design: Prospective Longitudinal Cohort Study Type: Cohort Longitudinal dbGaP estimated ancestry using GRAF-pop Total number of consented subjects: 11043 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Population Architecture using Genomics and Epidemiology (PAGE): Causal Variants Across the Life Course (CALiCo): Hispanic Community Health Study / Study of Latinos (HCHS/SOL)","short_name":"PAGE_CALiCo_HCHS_SOL_HMB","commons":"BioData Catalyst","study_url":"","_subjects_count":8969,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs000557.v7.p2.c1":{"gen3_discovery":{"authz":"/programs/dbGaP/projects/CARe_ARIC_HMB-IRB","tags":[],"_unique_id":"phs000557.v7.p2.c1","study_id":"phs000557.v7.p2.c1","study_description":"This sub-study phs000557 ARIC_CARe contains genotype derived from sequence data and selected phenotype of subjects available from the phs000557 study. Summary level phenotypes for the NHLBI ARIC Cohort study participants can be viewed at the top-level study page phs000280 ARIC Cohort. Individual level phenotype data and molecular data for all ARIC Cohort top-level study and sub-study are available by requesting Authorized Access to the NHLBI ARIC Cohort phs000280 study. The Atherosclerosis Risk in Communities (ARIC) Study, sponsored by the National Heart, Lung and Blood Institute (NHLBI), is a prospective epidemiologic study conducted in four U.S. communities. The four communities are Forsyth County, NC; Jackson, MS; the northwest suburbs of Minneapolis, MN; and Washington County, MD. ARIC is designed to investigate the etiology and natural history of atherosclerosis, the etiology of clinical atherosclerotic diseases, and variation in cardiovascular risk factors, medical care and disease by race, gender, location, and date. ARIC includes two parts: the Cohort Component and the Community Surveillance Component. The Cohort Component began in 1987, and each ARIC field center randomly selected and recruited a cohort sample of approximately 4,000 individuals aged 45-64 from a defined population in their community. A total of 15,792 participants received an extensive examination, including medical, social, and demographic data. These participants were examined with the baseline visit occurring in 1987-89, the second visit in 1990-92, the third visit in 1993-95, the fourth visit in 1996-98, and the fifth visit in 2011-13 Follow-up occurs yearly by telephone to maintain contact with participants and to assess health status of the cohort. In the Community Surveillance Component, currently ongoing, these four communities are investigated to determine the community-wide occurrence of hospitalized myocardial infarction and coronary heart disease deaths in men and women aged 35-84 years. Hospitalized stroke is investigated in cohort participants only. Starting in 2006, the study conducts community surveillance of inpatient (ages 55 years and older) and outpatient heart failure (ages 65 years and older) for heart failure events beginning in 2005. NHLBI Candidate-gene Association Resource. The NHLBI initiated the Candidate gene Association Resource (CARe) to create a shared genotype/phenotype resource for analyses of the association of genotypes with phenotypes relevant to the mission of the NHLBI. The resource comprises nine cohort studies funded by the NHLBI including: Atherosclerosis Risk in Communities (ARIC), Cardiovascular Health Study (CHS), Cleveland Family Study (CFS), Coronary Artery Risk Development in Young Adults (CARDIA), Framingham Heart Study (FHS), Jackson Heart Study (JHS), Multi-Ethnic Study of Atherosclerosis (MESA), and the Sleep Heart Health Study (SHHS). A database of genotype and phenotype data was created that includes records for approximately 41,000 study participants with approximately 50,000 SNPs from more than 2,000 selected candidate genes. In addition, a genome wide association study using a 1,000K SNP Chip was conducted on approximately 8,900 African American participants drawn from five CARe cohorts: ARIC, CARDIA, CFS, JHS, and MESA. Data from individual cohorts is available to approved investigators through dbGaP. Some relevant CARe publications CARe Study: PMID 20400780 CVD Chip Design: PMID 18974833 Study Weblinks: ARIC Study Design: Case-Control Study Type: Case-Control dbGaP estimated ancestry using GRAF-pop Total number of consented subjects: 13865 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"NHLBI Atherosclerosis Risk in Communities (ARIC) Candidate Gene Association Resource (CARe)","short_name":"CARe_ARIC_HMB-IRB","commons":"BioData Catalyst","study_url":"","_subjects_count":13408,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs000557.v7.p2.c2":{"gen3_discovery":{"authz":"/programs/dbGaP/projects/CARe_ARIC_DS-CVD-IRB","tags":[],"_unique_id":"phs000557.v7.p2.c2","study_id":"phs000557.v7.p2.c2","study_description":"This sub-study phs000557 ARIC_CARe contains genotype derived from sequence data and selected phenotype of subjects available from the phs000557 study. Summary level phenotypes for the NHLBI ARIC Cohort study participants can be viewed at the top-level study page phs000280 ARIC Cohort. Individual level phenotype data and molecular data for all ARIC Cohort top-level study and sub-study are available by requesting Authorized Access to the NHLBI ARIC Cohort phs000280 study. The Atherosclerosis Risk in Communities (ARIC) Study, sponsored by the National Heart, Lung and Blood Institute (NHLBI), is a prospective epidemiologic study conducted in four U.S. communities. The four communities are Forsyth County, NC; Jackson, MS; the northwest suburbs of Minneapolis, MN; and Washington County, MD. ARIC is designed to investigate the etiology and natural history of atherosclerosis, the etiology of clinical atherosclerotic diseases, and variation in cardiovascular risk factors, medical care and disease by race, gender, location, and date. ARIC includes two parts: the Cohort Component and the Community Surveillance Component. The Cohort Component began in 1987, and each ARIC field center randomly selected and recruited a cohort sample of approximately 4,000 individuals aged 45-64 from a defined population in their community. A total of 15,792 participants received an extensive examination, including medical, social, and demographic data. These participants were examined with the baseline visit occurring in 1987-89, the second visit in 1990-92, the third visit in 1993-95, the fourth visit in 1996-98, and the fifth visit in 2011-13 Follow-up occurs yearly by telephone to maintain contact with participants and to assess health status of the cohort. In the Community Surveillance Component, currently ongoing, these four communities are investigated to determine the community-wide occurrence of hospitalized myocardial infarction and coronary heart disease deaths in men and women aged 35-84 years. Hospitalized stroke is investigated in cohort participants only. Starting in 2006, the study conducts community surveillance of inpatient (ages 55 years and older) and outpatient heart failure (ages 65 years and older) for heart failure events beginning in 2005. NHLBI Candidate-gene Association Resource. The NHLBI initiated the Candidate gene Association Resource (CARe) to create a shared genotype/phenotype resource for analyses of the association of genotypes with phenotypes relevant to the mission of the NHLBI. The resource comprises nine cohort studies funded by the NHLBI including: Atherosclerosis Risk in Communities (ARIC), Cardiovascular Health Study (CHS), Cleveland Family Study (CFS), Coronary Artery Risk Development in Young Adults (CARDIA), Framingham Heart Study (FHS), Jackson Heart Study (JHS), Multi-Ethnic Study of Atherosclerosis (MESA), and the Sleep Heart Health Study (SHHS). A database of genotype and phenotype data was created that includes records for approximately 41,000 study participants with approximately 50,000 SNPs from more than 2,000 selected candidate genes. In addition, a genome wide association study using a 1,000K SNP Chip was conducted on approximately 8,900 African American participants drawn from five CARe cohorts: ARIC, CARDIA, CFS, JHS, and MESA. Data from individual cohorts is available to approved investigators through dbGaP. Some relevant CARe publications CARe Study: PMID 20400780 CVD Chip Design: PMID 18974833 Study Weblinks: ARIC Study Design: Case-Control Study Type: Case-Control dbGaP estimated ancestry using GRAF-pop Total number of consented subjects: 13865 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"NHLBI Atherosclerosis Risk in Communities (ARIC) Candidate Gene Association Resource (CARe)","short_name":"CARe_ARIC_DS-CVD-IRB","commons":"BioData Catalyst","study_url":"","_subjects_count":457,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs000571.v6.p2.c1":{"gen3_discovery":{"authz":null,"tags":null,"_unique_id":"phs000571.v6.p2.c1","study_id":"phs000571.v6.p2.c1","study_description":null,"full_name":null,"short_name":null,"commons":"BioData Catalyst","study_url":null,"_subjects_count":0,"__manifest":null,"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs000571.v6.p2.c2":{"gen3_discovery":{"authz":null,"tags":null,"_unique_id":"phs000571.v6.p2.c2","study_id":"phs000571.v6.p2.c2","study_description":null,"full_name":null,"short_name":null,"commons":"BioData Catalyst","study_url":null,"_subjects_count":0,"__manifest":null,"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs000571.v7.p3.c1":{"gen3_discovery":{"authz":"/programs/PCGC/projects/CHD-GENES_HMB","tags":[],"_unique_id":"phs000571.v7.p3.c1","study_id":"phs000571.v7.p3.c1","study_description":"This substudy phs000571 PCGC contains whole exome sequences, targeted sequences, and SNP array data. Summary level phenotypes for the PCGC Cohort study participants can be viewed at the top-level study page phs001194 PCGC Cohort. Individual level phenotype data and molecular data for all PCGC top-level study and substudies are available by requesting Authorized Access to the PCGC Cohort study phs001194. Multi-center, prospective observational cohort study of individuals with congenital heart defects (CHD). Phenotypic data and source DNA derived from 15,000+ probands, parents, and families of interest are being collected to investigate relationships between genetic factors and phenotypic and clinical outcomes in patients with CHD. Study Weblinks: Bench to Bassinet Program Study Design: Prospective Longitudinal Cohort Study Type: Cohort Parent-Offspring Trios dbGaP estimated ancestry using GRAF-pop Total number of consented subjects: 20529 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"National Heart, Lung, and Blood Institute (NHLBI) Bench to Bassinet Program: The Pediatric Cardiac Genetics Consortium (PCGC)","short_name":"CHD-GENES_HMB","commons":"BioData Catalyst","study_url":"","_subjects_count":20416,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs000571.v7.p3.c2":{"gen3_discovery":{"authz":"/programs/PCGC/projects/CHD-GENES_DS-CHD","tags":[],"_unique_id":"phs000571.v7.p3.c2","study_id":"phs000571.v7.p3.c2","study_description":"This substudy phs000571 PCGC contains whole exome sequences, targeted sequences, and SNP array data. Summary level phenotypes for the PCGC Cohort study participants can be viewed at the top-level study page phs001194 PCGC Cohort. Individual level phenotype data and molecular data for all PCGC top-level study and substudies are available by requesting Authorized Access to the PCGC Cohort study phs001194. Multi-center, prospective observational cohort study of individuals with congenital heart defects (CHD). Phenotypic data and source DNA derived from 15,000+ probands, parents, and families of interest are being collected to investigate relationships between genetic factors and phenotypic and clinical outcomes in patients with CHD. Study Weblinks: Bench to Bassinet Program Study Design: Prospective Longitudinal Cohort Study Type: Cohort Parent-Offspring Trios dbGaP estimated ancestry using GRAF-pop Total number of consented subjects: 20529 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"National Heart, Lung, and Blood Institute (NHLBI) Bench to Bassinet Program: The Pediatric Cardiac Genetics Consortium (PCGC)","short_name":"CHD-GENES_DS-CHD","commons":"BioData Catalyst","study_url":"","_subjects_count":113,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs000581.v1.p1.c1":{"gen3_discovery":{"authz":"/programs/heartfailure/projects/Fam_DC_DS-FDC","tags":[],"_unique_id":"phs000581.v1.p1.c1","study_id":"phs000581.v1.p1.c1","study_description":"The NHLBI \"Grand Opportunity\" Exome Sequencing Project (GO-ESP), a signature project of the NHLBI Recovery Act investment, was designed to identify genetic variants in coding regions (exons) of the human genome (the \"exome\") that are associated with heart, lung and blood diseases. These and related diseases that are of high impact to public health and individuals from diverse racial and ethnic groups will be studied. These data may help researchers understand the causes of disease, contributing to better ways to prevent, diagnose, and treat diseases, as well as determine whether to tailor prevention and treatments to specific populations. This could lead to more effective treatments and reduce the likelihood of side effects. GO-ESP is comprised of five collaborative components: 3 cohort consortia - HeartGO, LungGO, and WHISP - and 2 sequencing centers - BroadGO and SeattleGO. The goals for this project are to conduct exome sequencing for novel dilated cardiomyopathy (DCM) gene discovery in families with DCM. These families have already been sequenced for 15 DCM genes, accounting for approximately 75% of known genetic cause, without rare coding variants identified. Study Weblinks: NHLBI Grand Opportunity Exome Sequencing Project (ESP) Study Design: Case Set Study Type: Case Set Total number of consented subjects: 49 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"NHLBI GO-ESP: Family Studies (Dilated Cardiomyopathy)","short_name":"Fam_DC_DS-FDC","commons":"BioData Catalyst","study_url":"","_subjects_count":49,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs000587.v1.p1.c1":{"gen3_discovery":{"authz":"/programs/heartfailure/projects/Fam_MLD_DS-CLA","tags":[{"name":"dbGaP","category":"Study Registration"}],"_unique_id":"phs000587.v1.p1.c1","study_id":"phs000587.v1.p1.c1","study_description":"The NHLBI \"Grand Opportunity\" Exome Sequencing Project (GO-ESP), a signature project of the NHLBI Recovery Act investment, was designed to identify genetic variants in coding regions (exons) of the human genome (the \"exome\") that are associated with heart, lung and blood diseases. These and related diseases that are of high impact to public health and individuals from diverse racial and ethnic groups will be studied. These data may help researchers understand the causes of disease, contributing to better ways to prevent, diagnose, and treat diseases, as well as determine whether to tailor prevention and treatments to specific populations. This could lead to more effective treatments and reduce the likelihood of side effects. GO-ESP is comprised of five collaborative components: 3 cohort consortia - HeartGO, LungGO, and WHISP - and 2 sequencing centers - BroadGO and SeattleGO. In this study, we seek to identify the genetic cause of two monogenic lipid disorders-severe hypercholesterolemia and familial hypoalphalipoproteinemia. Monogenic severe hypercholesterolemia is clinically characterized by elevated total and low-density lipoprotein (LDL) cholesterol levels in plasma. Elevated LDL-cholesterol levels lead to excessive deposition of cholesterol in arterial walls, which eventually results in accelerated atherosclerosis and premature cardiovascular disease (CVD). Monogenic hypercholesterolemia has a prevalence of approximately one in 500 individuals, making it one of the most common inherited disorders. To date, mutations in the LDL receptor (LDLR) ligand-binding domains of APOB and PCSK9 have been shown to cause hypercholesterolemia. While mutations in these genes can explain a large percentage of clinically diagnosed patients, the underlying molecular determinant in a substantial fraction of patients remains unknown. Familial hypoalphalipoproteinemia (low HDL-C) is defined by an HDL-C below the age- and sex- specific 10th percentile. ABCA1, LCAT, and APOA1 are known to cause familial hypoalphalipoproteinemia. We hypothesize that: (1) additional novel genes responsible for Mendelian forms of low HDL-C exist; and (2) the causal gene and mutation(s) in each family may be discovered with exome analysis of just a few affected individuals in each pedigree. Study Weblinks: NHLBI Grand Opportunity Exome Sequencing Project (ESP) Study Design: Case Set Study Type: Case Set dbGaP estimated ancestry using GRAF-pop Total number of consented subjects: 29 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"NHLBI GO-ESP: Family Studies (Mendelian Lipid Disorders)","short_name":"Fam_MLD_DS-CLA","commons":"BioData Catalyst","study_url":"https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000587.v1.p1","_subjects_count":29,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs000617.v1.p1.c1":{"gen3_discovery":{"authz":"/programs/heartfailure/projects/KCNE1_TDP_HMB","tags":[],"_unique_id":"phs000617.v1.p1.c1","study_id":"phs000617.v1.p1.c1","study_description":"The goal of this study was to search for genetic variants that could be responsible for modifying the risk of drug-induced long QT syndrome (diLQTS). diLQTS is a relatively common adverse drug event and has been a leading cause for drug relabeling and withdrawal from the market. Our hypothesis, that variants in genes which regulate electrical properties in the heart modify the risk of diLQTS, was tested by genotyping patients of European descent at 1424 single nucleotide polymorphisms (SNPs) in 18 candidate genes. We found that the SNP KCNE1 D85N was highly predictive of diLQTS with an odds ratio of 9.0 (95% confidence interval: 3.5-22.9). Study Design: Case-Control Study Type: Case-Control Total number of consented subjects: 290 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"PGRN-Leducq: Identification of the KCNE1 D85N Polymorphism as a Possible Modulator of Drug-Induced Torsades de Pointes","short_name":"KCNE1_TDP_HMB","commons":"BioData Catalyst","study_url":"","_subjects_count":290,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs000631.v1.p1.c1":{"gen3_discovery":{"authz":"/programs/heartfailure/projects/ARDSnet_gen_HMB","tags":[],"_unique_id":"phs000631.v1.p1.c1","study_id":"phs000631.v1.p1.c1","study_description":"Acute Respiratory Distress Syndrome (ARDS)/ Acute Lung Injury (ALI) is a syndrome defined by the presence of acute hypoxemic respiratory failure, bilateral pulmonary infiltrates on chest radiograph, a known clinical risk factor (e.g. sepsis, pneumonia, trauma, gastric fluid aspiration, pancreatitis, massive transfusion), and the absence of physiologic or clinical evidence of congestive heart failure. The Identification of SNPs Predisposing to Altered ALI Risk (iSPAAR) study is a multi-institutional cooperative study, funded through the NHLBI Recovery Act, that assembled samples and phenotype information from existing cohorts. The consortium included samples from patients with ARDS from the NIH NHLBI ARDS Clinical Trials Network (ARDSNet). Samples were obtained from 3 interventional treatment trials in patients with ARDS, including the Fluid and Catheter Treatment Trial (FACTT), the Albuterol to Treat Acute Lung Injury (ALTA) trial, and the Omega-3 Fatty Acid/Antioxidant Supplementation for ALI trial (Omega). In addition to ARDSnet samples, samples from the other cohorts included cases of established ARDS but also controls: critically ill patients who were at-risk for ARDS but who did not develop ARDS during their hospital course. These cohorts included the Molecular Epidemiology of Acute Respiratory Distress (MEA) Study enrolled at the Harvard University/Massachusetts General Hospital, the Systemic Inflammatory Immune Response Syndrome (SIRS) Patient Database and ICU Traumatic Injury cohorts from Harborview Medical Center, and cohorts collected from the ALI research programs at the University of Pennsylvania and the University of California, San Francisco. The Cohort is utilized in the following dbGaP sub-studies. To view genotypes, other molecular data, and derived variables collected in these sub-studies, please click on the following sub-studies below or in the \"Sub-studies\" section of this top-level study page phs000631 ARDSnet iSPAAR Consortium. phs000334 ESP_LungGO_ALI phs000686 ALI_GeneticRisk Study Weblinks: NHLBI ARDS Network Study Design: Clinical Trial Study Type: Case-Control Total number of consented subjects: 3033 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"ARDSnet and the iSPAAR Consortium: Genomic Basis of Susceptibility and Outcomes in Patients with the Acute Respiratory Distress Syndrome (ARDS)","short_name":"ARDSnet_gen_HMB","commons":"BioData Catalyst","study_url":"","_subjects_count":3033,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs000647.v1.p1.c1":{"gen3_discovery":{"authz":"/programs/heartfailure/projects/Hypox_Ethiopia_GRU","tags":[],"_unique_id":"phs000647.v1.p1.c1","study_id":"phs000647.v1.p1.c1","study_description":"Although it has long been proposed that genetic factors contribute to adaptation to high altitude, such factors remain largely unverified. Recent advances in high-throughput sequencing have made it feasible to analyze genome-wide patterns of genetic variation in human populations. Since traditionally such studies surveyed only a small fraction of the genome (either exons or a subset of SNPs) or a group of candidate genes, interpretation of the results was limited. We focused our study on Ethiopian highlander populations, which have been found to be well adapted to high altitudes (~3500m). We sequenced and analyze the genomes of 13 high altitude native Ethiopians: 6 individuals of Oromo heritage living on Bale Plateau (labeled \"Oromos\"), and 7 individuals residing on the Chennek field in the Simien Mountains (labeled \"Amhara\"). Our study revealed evolutionarily conserved genes that modulate hypoxia tolerance. Study Design: Cross-Sectional Study Type: Cohort dbGaP estimated ancestry using GRAF-pop Total number of consented subjects: 13 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Study of Adaptation to Hypoxia in Ethiopian Highlanders via Whole Genome Sequencing","short_name":"Hypox_Ethiopia_GRU","commons":"BioData Catalyst","study_url":"","_subjects_count":13,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs000651.v15.p16.c1":{"gen3_discovery":{"authz":"/programs/dbGaP/projects/CHARGE_S_FHS_HMB-IRB-MDS","tags":[],"_unique_id":"phs000651.v15.p16.c1","study_id":"phs000651.v15.p16.c1","study_description":"This substudy phs000651 Framingham CHARGE-S contains whole genome, whole exome, and targeted sequence data, produced as part of NHLBI's CHARGE-S project. Summary level phenotypes for the Framingham Cohort study participants can be viewed at the top-level study page phs000007 Framingham Cohort. Individual level phenotype data and molecular data for all Framingham top-level study and substudies are available by requesting Authorized Access to the Framingham Cohort study phs000007. Genome-wide association studies (GWAS) have successfully localized multiple loci containing common variations influencing coronary heart disease and its risk factors, but in most cases neither the gene underlying disease susceptibility nor the spectrum of candidate functional variants has been identified. Building on GWAS for NHLBI-diseases: the U.S. CHARGE consortium (the CHARGE sequencing (CHARGE-S) consortium) is a collaborative effort to leverage existing population, laboratory and computational resources to identify susceptibility genes underlying genome-wide significance and well-replicated GWAS findings for heart, lung and blood diseases and their risk factors. The U.S. CHARGE consortium consists of multiple large population-based longitudinal cohort studies, including the Atherosclerosis Risk in Communities (ARIC) Study (N=15,792), the Cardiovascular Health Study (CHS) (N=5,888), and the Framingham Heart Study (FHS) (N=14,428). The study has taken a two pronged approach to following-up GWAS. First, regional capture targeted sequencing was performed in genomic regions influencing 15 phenotypes to localize causal variants that are responsible for the GWAS signal. The phenotypes examined were atrial fibrillation, blood pressure, body mass index (BMI), bone mineral density, C-reactive protein (CRP), carotid intima-media thickness (IMT), echocardiography, electrocardiogram PR and QRS interval, fasting insulin, hematocrit, pleiotropy, pulmonary function, retinal venule diameter, and stroke. A case-cohort study design was used in which a common reference sample was selected from all three cohorts at baseline. The cohort random sample included 2,000 individuals composed of 1,000 participants from the ARIC study, 500 participants from FHS, and 500 participants from CHS in a 1:1 gender ratio. The comparison groups were either selected cases for discrete phenotypes, or participants drawn from the top and/or bottom tail of the distribution for quantitative phenotypes. The size of each comparison group was 200 individuals. Approximately 2 Mb of the genome was sequenced for the targeted loci. Second, whole exome capture sequencing and low-pass whole genome sequencing was completed for the cohort random sample and 7 phenotypes for which there were more than 3 GWAS signals in coding regions to detect novel rare and common variants. The phenotypes investigated by whole exome sequencing were age at menopause, electrocardiogram QT interval, fasting blood glucose, fibrinogen level, renal function, Stamler-Kannel-like extremes of risk factors, and waist-to-hip ratio. All sequencing was carried out at the Human Genome Sequencing Center at the Baylor College of Medicine. This study contains the Framingham Heart Study subset of CHARGE-S. Additional data from CHARGE-S are also available via dbGaP. Study Design: Prospective Longitudinal Cohort Study Type: Case-Cohort dbGaP estimated ancestry using GRAF-pop Total number of consented subjects: 2515 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Building on GWAS: the U.S. CHARGE Consortium - Sequencing (CHARGE-S): FHS","short_name":"CHARGE_S_FHS_HMB-IRB-MDS","commons":"BioData Catalyst","study_url":"","_subjects_count":2095,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs000651.v15.p16.c2":{"gen3_discovery":{"authz":"/programs/dbGaP/projects/CHARGE_S_FHS_HMB-IRB-NPU-MDS","tags":[],"_unique_id":"phs000651.v15.p16.c2","study_id":"phs000651.v15.p16.c2","study_description":"This substudy phs000651 Framingham CHARGE-S contains whole genome, whole exome, and targeted sequence data, produced as part of NHLBI's CHARGE-S project. Summary level phenotypes for the Framingham Cohort study participants can be viewed at the top-level study page phs000007 Framingham Cohort. Individual level phenotype data and molecular data for all Framingham top-level study and substudies are available by requesting Authorized Access to the Framingham Cohort study phs000007. Genome-wide association studies (GWAS) have successfully localized multiple loci containing common variations influencing coronary heart disease and its risk factors, but in most cases neither the gene underlying disease susceptibility nor the spectrum of candidate functional variants has been identified. Building on GWAS for NHLBI-diseases: the U.S. CHARGE consortium (the CHARGE sequencing (CHARGE-S) consortium) is a collaborative effort to leverage existing population, laboratory and computational resources to identify susceptibility genes underlying genome-wide significance and well-replicated GWAS findings for heart, lung and blood diseases and their risk factors. The U.S. CHARGE consortium consists of multiple large population-based longitudinal cohort studies, including the Atherosclerosis Risk in Communities (ARIC) Study (N=15,792), the Cardiovascular Health Study (CHS) (N=5,888), and the Framingham Heart Study (FHS) (N=14,428). The study has taken a two pronged approach to following-up GWAS. First, regional capture targeted sequencing was performed in genomic regions influencing 15 phenotypes to localize causal variants that are responsible for the GWAS signal. The phenotypes examined were atrial fibrillation, blood pressure, body mass index (BMI), bone mineral density, C-reactive protein (CRP), carotid intima-media thickness (IMT), echocardiography, electrocardiogram PR and QRS interval, fasting insulin, hematocrit, pleiotropy, pulmonary function, retinal venule diameter, and stroke. A case-cohort study design was used in which a common reference sample was selected from all three cohorts at baseline. The cohort random sample included 2,000 individuals composed of 1,000 participants from the ARIC study, 500 participants from FHS, and 500 participants from CHS in a 1:1 gender ratio. The comparison groups were either selected cases for discrete phenotypes, or participants drawn from the top and/or bottom tail of the distribution for quantitative phenotypes. The size of each comparison group was 200 individuals. Approximately 2 Mb of the genome was sequenced for the targeted loci. Second, whole exome capture sequencing and low-pass whole genome sequencing was completed for the cohort random sample and 7 phenotypes for which there were more than 3 GWAS signals in coding regions to detect novel rare and common variants. The phenotypes investigated by whole exome sequencing were age at menopause, electrocardiogram QT interval, fasting blood glucose, fibrinogen level, renal function, Stamler-Kannel-like extremes of risk factors, and waist-to-hip ratio. All sequencing was carried out at the Human Genome Sequencing Center at the Baylor College of Medicine. This study contains the Framingham Heart Study subset of CHARGE-S. Additional data from CHARGE-S are also available via dbGaP. Study Design: Prospective Longitudinal Cohort Study Type: Case-Cohort dbGaP estimated ancestry using GRAF-pop Total number of consented subjects: 2515 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Building on GWAS: the U.S. CHARGE Consortium - Sequencing (CHARGE-S): FHS","short_name":"CHARGE_S_FHS_HMB-IRB-NPU-MDS","commons":"BioData Catalyst","study_url":"","_subjects_count":420,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs000668.v6.p2.c1":{"gen3_discovery":{"authz":"/programs/substudy/projects/charge_s_aric_HMB-IRB","tags":[],"_unique_id":"phs000668.v6.p2.c1","study_id":"phs000668.v6.p2.c1","study_description":"This sub-study phs000668 CHARGE-S Atherosclerosis Risk in Communities (ARIC) contains whole genome, whole exome, and targeted sequencing data, and exome SNP array data, produced as part of NHLBI's CHARGE-S project for subjects available from the phs000668 study. Summary level phenotypes for the NHLBI ARIC Cohort study participants can be viewed at the top-level study page phs000280 ARIC Cohort. Individual level phenotype data and molecular data for the ARIC Cohort top-level study and sub-studies are available by requesting Authorized Access to the NHLBI ARIC Cohort phs000280 study. Genome-wide association studies (GWAS) have successfully localized multiple loci containing common variations influencing coronary heart disease and its risk factors, but in most cases neither the gene underlying disease susceptibility nor the spectrum of candidate functional variants has been identified. Building on GWAS for NHLBI-diseases: the U.S. CHARGE consortium (the CHARGE sequencing (CHARGE-S) consortium) is a collaborative effort to leverage existing population, laboratory and computational resources to identify susceptibility genes underlying genome-wide significant and well-replicated GWAS findings for heart, lung and blood diseases and their risk factors. The sequencing approach was funded by NHLBI with funds provided by the American Recovery and Reinvestment Act of 2009 (ARRA). The U.S. CHARGE consortium consists of multiple large population-based longitudinal cohort studies, including the Atherosclerosis Risk in Communities (ARIC) Study (N=15,792), the Cardiovascular Health Study (CHS) (N=5,888), and the Framingham Heart Study (FHS) (N=14,428). The study has taken a two pronged approach to following-up GWAS. First, regional capture targeted sequencing was performed in genomic regions influencing 15 phenotypes to localize causal variants that are responsible for the GWAS signal. The phenotypes examined were atrial fibrillation, blood pressure, body mass index (BMI), bone mineral density, C-reactive protein (CRP), carotid intima-media thickness (IMT), echocardiography, electrocardiogram PR and QRS interval, fasting insulin, hematocrit, pleiotropy, pulmonary function, retinal venule diameter, and stroke. A case-cohort study design was used in which a common reference sample was selected from all three cohorts at baseline. The cohort random sample included 2,000 individuals composed of 1,000 participants from the ARIC study, 500 participants from FHS, and 500 participants from CHS in a 1:1 gender ratio. The comparison groups were either selected cases for discrete phenotypes, or participants drawn from the top and/or bottom tail of the distribution for quantitative phenotypes. The size of each comparison group was 200 individuals. Approximately 2 Mb of the genome was sequenced for the targeted loci. Second, whole exome capture sequencing and low-pass whole genome sequencing were completed for the cohort random sample and 7 phenotypes for which there were more than 3 GWAS signals in coding regions to detect novel rare and common variants. The phenotypes investigated by whole exome sequencing were age at menopause, electrocardiogram QT interval, fasting blood glucose, fibrinogen level, renal function, Stamler-Kannel-like extremes of risk factors, and waist-to-hip ratio. Follow-up genotyping using the Illumina HumanExome BeadChip has also been completed. Additional information including variant annotation is available at http://web.chargeconsortium.com/main/exomechip. All sequencing was carried out at the Human Genome Sequencing Center at the Baylor College of Medicine. This study contains the Atherosclerosis Risk in Communities (ARIC) study subset of CHARGE-S. Additional data from CHARGE-S is also available via dbGaP. Study Design: Case Set Study Type: Case-Cohort Cohort dbGaP estimated ancestry using GRAF-pop Total number of consented subjects: 14211 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Building on GWAS: the U.S. CHARGE consortium - Sequencing (CHARGE-S): ARIC","short_name":"charge_s_aric_HMB-IRB","commons":"BioData Catalyst","study_url":"","_subjects_count":13749,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs000668.v6.p2.c2":{"gen3_discovery":{"authz":"/programs/substudy/projects/charge_s_aric_DS-CVD-IRB","tags":[],"_unique_id":"phs000668.v6.p2.c2","study_id":"phs000668.v6.p2.c2","study_description":"This sub-study phs000668 CHARGE-S Atherosclerosis Risk in Communities (ARIC) contains whole genome, whole exome, and targeted sequencing data, and exome SNP array data, produced as part of NHLBI's CHARGE-S project for subjects available from the phs000668 study. Summary level phenotypes for the NHLBI ARIC Cohort study participants can be viewed at the top-level study page phs000280 ARIC Cohort. Individual level phenotype data and molecular data for the ARIC Cohort top-level study and sub-studies are available by requesting Authorized Access to the NHLBI ARIC Cohort phs000280 study. Genome-wide association studies (GWAS) have successfully localized multiple loci containing common variations influencing coronary heart disease and its risk factors, but in most cases neither the gene underlying disease susceptibility nor the spectrum of candidate functional variants has been identified. Building on GWAS for NHLBI-diseases: the U.S. CHARGE consortium (the CHARGE sequencing (CHARGE-S) consortium) is a collaborative effort to leverage existing population, laboratory and computational resources to identify susceptibility genes underlying genome-wide significant and well-replicated GWAS findings for heart, lung and blood diseases and their risk factors. The sequencing approach was funded by NHLBI with funds provided by the American Recovery and Reinvestment Act of 2009 (ARRA). The U.S. CHARGE consortium consists of multiple large population-based longitudinal cohort studies, including the Atherosclerosis Risk in Communities (ARIC) Study (N=15,792), the Cardiovascular Health Study (CHS) (N=5,888), and the Framingham Heart Study (FHS) (N=14,428). The study has taken a two pronged approach to following-up GWAS. First, regional capture targeted sequencing was performed in genomic regions influencing 15 phenotypes to localize causal variants that are responsible for the GWAS signal. The phenotypes examined were atrial fibrillation, blood pressure, body mass index (BMI), bone mineral density, C-reactive protein (CRP), carotid intima-media thickness (IMT), echocardiography, electrocardiogram PR and QRS interval, fasting insulin, hematocrit, pleiotropy, pulmonary function, retinal venule diameter, and stroke. A case-cohort study design was used in which a common reference sample was selected from all three cohorts at baseline. The cohort random sample included 2,000 individuals composed of 1,000 participants from the ARIC study, 500 participants from FHS, and 500 participants from CHS in a 1:1 gender ratio. The comparison groups were either selected cases for discrete phenotypes, or participants drawn from the top and/or bottom tail of the distribution for quantitative phenotypes. The size of each comparison group was 200 individuals. Approximately 2 Mb of the genome was sequenced for the targeted loci. Second, whole exome capture sequencing and low-pass whole genome sequencing were completed for the cohort random sample and 7 phenotypes for which there were more than 3 GWAS signals in coding regions to detect novel rare and common variants. The phenotypes investigated by whole exome sequencing were age at menopause, electrocardiogram QT interval, fasting blood glucose, fibrinogen level, renal function, Stamler-Kannel-like extremes of risk factors, and waist-to-hip ratio. Follow-up genotyping using the Illumina HumanExome BeadChip has also been completed. Additional information including variant annotation is available at http://web.chargeconsortium.com/main/exomechip. All sequencing was carried out at the Human Genome Sequencing Center at the Baylor College of Medicine. This study contains the Atherosclerosis Risk in Communities (ARIC) study subset of CHARGE-S. Additional data from CHARGE-S is also available via dbGaP. Study Design: Case Set Study Type: Case-Cohort Cohort dbGaP estimated ancestry using GRAF-pop Total number of consented subjects: 14211 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Building on GWAS: the U.S. CHARGE consortium - Sequencing (CHARGE-S): ARIC","short_name":"charge_s_aric_DS-CVD-IRB","commons":"BioData Catalyst","study_url":"","_subjects_count":462,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs000703.v1.p1.c1":{"gen3_discovery":{"authz":"/programs/parent/projects/CATHGEN_DS-CVD-IRB_","tags":[{"name":"Parent","category":"Program"},{"name":"Clinical Phenotype","category":"Data Type"},{"name":"dbGaP","category":"Study Registration"}],"_unique_id":"phs000703.v1.p1.c1","study_id":"phs000703.v1.p1.c1","study_description":"The CATHGEN biorepository consists of biological samples collected on 9334 sequential consenting individuals undergoing cardiac catheterization at Duke University Medical Center between 2001 and 2010 inclusive. The Institutional Review Board informed consent allowed for 50 mL of blood to be collected from fasting patients through the femoral arterial sheath during the catheterization procedure. Three 7.5 mL EDTA tubes for DNA extraction are stored at -80°C. The Duke Database for Cardiovascular Disease (DDCD) provides the bulk of the clinical data used for analysis. Follow-up includes mortality information gleaned from the National Death Index and Social Security Death Index plus follow-up phone calls and written questionnaires regarding MI, stroke, re-hospitalization, coronary re-vascularization procedures, smoking, exercise, and medication use. Study Weblinks: CATHGEN Study Design: Cross-Sectional Study Type: Longitudinal Total number of consented subjects: 3304 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"CATHeterization GENetics (CATHGEN)","short_name":"CATHGEN_DS-CVD-IRB_","commons":"BioData Catalyst","study_url":"https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000703.v1.p1","_subjects_count":3304,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs000724.v12.p16.c1":{"gen3_discovery":{"authz":"/programs/dbGaP/projects/DNA_Methylation_FHS_HMB-IRB-MDS","tags":[],"_unique_id":"phs000724.v12.p16.c1","study_id":"phs000724.v12.p16.c1","study_description":"This substudy phs000724 Framingham DNA Methylation contains raw 450K offspring DNA methylation data as well as processed DNA methylation in both offspring and generation3 (Gen3) participants. 850K array DNA methylation data in both offspring and Gen3 can be found under the FHS substudy phs000974 NHLBI TOPMed: The Framingham Heart Study. Summary level phenotypes for the Framingham Cohort study participants can be viewed at the top-level study page phs000007 Framingham Cohort. Individual level phenotype data and molecular data for all Framingham top-level study and substudies are available by requesting Authorized Access to the Framingham Cohort study phs000007. The risk of cardiovascular disease (CVD) is determined by the complex interaction of multiple genetic and environmental factors. Although genome-wide association studies (GWAS) have been highly successful in unraveling genes and pathways involved in multiple complex traits and diseases, common genetic variation only explains a small proportion of the heritability of these traits. It is believed that epigenetic factors (modifications in how our genes work that are not due to changes in DNA sequence) impact greatly on multiple complex traits. Epigenetic modifications, however, are largely unexplored in cardiovascular disease (CVD), where many of the causal genes are known to be regulated by epigenetic mechanisms, including DNA methylation. We seek to characterize DNA methylation in participants from the Framingham Heart Study in order to characterize the contribution of DNA methylation to CVD and other complex traits. This project, when combined with the vast data resources of the Framingham Heart Study (including gene expression and GWAS), will further the knowledge of CVD prevention, prediction, and therapy. For Offspring participants, both raw and processed DNA methylation is available. Offspring DNA methylation from exam 8 was quantified by two labs: 576 samples (CVD case-control study samples) were tested in John Hopkins University and 2270 remaining offspring samples were tested in University of Minnesota. For Gen3 participants, only processed DNA methylation is available. For Gen3 exam 2 sample selection, family study design was emphasized. We selected ~ 1,080 Gen3 participants with both parents having whole genome sequencing (WGS) and DNA methylation data. We also selected ~ 500 Gen3 participants with mother or father having WGS and DNA methylation data. All Gen3 participants were tested by the Illumina lab. For the processed DNA methylation results, lab-specific normalization and quality control (QC) procedures were performed on all samples. QC procedures included multidimensional scaling (MDS) analysis to identify sex mismatch and outliers, call rate checking for samples and DNA probes, consistency checking by comparing SNPs for 65 overlap SNPs by previous genotyping/1000 Genome imputation and by Illumina 450K methylation array, and exclusion of probes that mapped to multiple locations and had SNPs at CpG sites or ≤10 bp of Single Base Extension. After QC procedures, we excluded samples that were MDS outliers, had high missing rate (>1%), or poor matching to SNP genotype. Probes were excluded if they had high missing rate (>20%), mapped to multiple locations, had SNP (MAF>5% in EUR 1000G) at CpG site or ≤10 bp of Single Base Extension. After QC procedures, 2152 samples with 444,098 probes remained for the UMN-lab; 485 samples with 444,055 probes remained for the JHU-lab; 1522 samples with 444046 probes remained for the gen3-lab. The data is packaged separately for each of the labs; each have 444 ‘common' packages with 1000 probes each. The UMN, JHU and gen3 versions with the same package number contain the same DNA methylation probes in the same order. In addition to the 444 common packages, there are lab-specific packages for UMN only (n=98 probes), JHU only (n=55 probes), and gen3 only (n=44 probes). Please note, these 98, 55 and 44 probes are not in common in three labs. But there are overlapping probes between the 98 and 55, 98 and 44, and 55 and 44. Post QC, the total sample size is 4159. Project aims: 1. To assess differences in DNA methylation across the genome, in relation to cardiovascular disease and other phenotypes - leveraging the extensive surveillance for events and comprehensive phenotype characterization in Framingham. 2. To characterize the relations of site specific DNA methylation to transcription levels across the genome at a gene and exon level -- leveraging the genomic resources of the SABRe CVD Initiative. 3. To relate lifestyle and environmental exposures (e.g. diet, smoking, obesity, sleep) and other factors (e.g. sex hormone status) to DNA methylation by investigating the locations, levels and frequency of DNA methylation in relation to these traits -- leveraging the phenotypic resources of Framingham. 4. To relate common genetic variation from GWAS to variable DNA methylation -- leveraging the genetic resources of the Framingham SHARe GWAS. Study Weblinks: The Framingham Heart Study NHLBI Framingham Heart Study Study Design: Prospective Longitudinal Cohort Study Type: Cohort Total number of consented subjects: 4208 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Framingham Offspring Exam 8 and Generation 3 Exam 2 450K Array DNA Methylation Study","short_name":"DNA_Methylation_FHS_HMB-IRB-MDS","commons":"BioData Catalyst","study_url":"","_subjects_count":3929,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs000724.v12.p16.c2":{"gen3_discovery":{"authz":"/programs/dbGaP/projects/DNA_Methylation_FHS_HMB-IRB-NPU-MDS","tags":[],"_unique_id":"phs000724.v12.p16.c2","study_id":"phs000724.v12.p16.c2","study_description":"This substudy phs000724 Framingham DNA Methylation contains raw 450K offspring DNA methylation data as well as processed DNA methylation in both offspring and generation3 (Gen3) participants. 850K array DNA methylation data in both offspring and Gen3 can be found under the FHS substudy phs000974 NHLBI TOPMed: The Framingham Heart Study. Summary level phenotypes for the Framingham Cohort study participants can be viewed at the top-level study page phs000007 Framingham Cohort. Individual level phenotype data and molecular data for all Framingham top-level study and substudies are available by requesting Authorized Access to the Framingham Cohort study phs000007. The risk of cardiovascular disease (CVD) is determined by the complex interaction of multiple genetic and environmental factors. Although genome-wide association studies (GWAS) have been highly successful in unraveling genes and pathways involved in multiple complex traits and diseases, common genetic variation only explains a small proportion of the heritability of these traits. It is believed that epigenetic factors (modifications in how our genes work that are not due to changes in DNA sequence) impact greatly on multiple complex traits. Epigenetic modifications, however, are largely unexplored in cardiovascular disease (CVD), where many of the causal genes are known to be regulated by epigenetic mechanisms, including DNA methylation. We seek to characterize DNA methylation in participants from the Framingham Heart Study in order to characterize the contribution of DNA methylation to CVD and other complex traits. This project, when combined with the vast data resources of the Framingham Heart Study (including gene expression and GWAS), will further the knowledge of CVD prevention, prediction, and therapy. For Offspring participants, both raw and processed DNA methylation is available. Offspring DNA methylation from exam 8 was quantified by two labs: 576 samples (CVD case-control study samples) were tested in John Hopkins University and 2270 remaining offspring samples were tested in University of Minnesota. For Gen3 participants, only processed DNA methylation is available. For Gen3 exam 2 sample selection, family study design was emphasized. We selected ~ 1,080 Gen3 participants with both parents having whole genome sequencing (WGS) and DNA methylation data. We also selected ~ 500 Gen3 participants with mother or father having WGS and DNA methylation data. All Gen3 participants were tested by the Illumina lab. For the processed DNA methylation results, lab-specific normalization and quality control (QC) procedures were performed on all samples. QC procedures included multidimensional scaling (MDS) analysis to identify sex mismatch and outliers, call rate checking for samples and DNA probes, consistency checking by comparing SNPs for 65 overlap SNPs by previous genotyping/1000 Genome imputation and by Illumina 450K methylation array, and exclusion of probes that mapped to multiple locations and had SNPs at CpG sites or ≤10 bp of Single Base Extension. After QC procedures, we excluded samples that were MDS outliers, had high missing rate (>1%), or poor matching to SNP genotype. Probes were excluded if they had high missing rate (>20%), mapped to multiple locations, had SNP (MAF>5% in EUR 1000G) at CpG site or ≤10 bp of Single Base Extension. After QC procedures, 2152 samples with 444,098 probes remained for the UMN-lab; 485 samples with 444,055 probes remained for the JHU-lab; 1522 samples with 444046 probes remained for the gen3-lab. The data is packaged separately for each of the labs; each have 444 ‘common' packages with 1000 probes each. The UMN, JHU and gen3 versions with the same package number contain the same DNA methylation probes in the same order. In addition to the 444 common packages, there are lab-specific packages for UMN only (n=98 probes), JHU only (n=55 probes), and gen3 only (n=44 probes). Please note, these 98, 55 and 44 probes are not in common in three labs. But there are overlapping probes between the 98 and 55, 98 and 44, and 55 and 44. Post QC, the total sample size is 4159. Project aims: 1. To assess differences in DNA methylation across the genome, in relation to cardiovascular disease and other phenotypes - leveraging the extensive surveillance for events and comprehensive phenotype characterization in Framingham. 2. To characterize the relations of site specific DNA methylation to transcription levels across the genome at a gene and exon level -- leveraging the genomic resources of the SABRe CVD Initiative. 3. To relate lifestyle and environmental exposures (e.g. diet, smoking, obesity, sleep) and other factors (e.g. sex hormone status) to DNA methylation by investigating the locations, levels and frequency of DNA methylation in relation to these traits -- leveraging the phenotypic resources of Framingham. 4. To relate common genetic variation from GWAS to variable DNA methylation -- leveraging the genetic resources of the Framingham SHARe GWAS. Study Weblinks: The Framingham Heart Study NHLBI Framingham Heart Study Study Design: Prospective Longitudinal Cohort Study Type: Cohort Total number of consented subjects: 4208 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Framingham Offspring Exam 8 and Generation 3 Exam 2 450K Array DNA Methylation Study","short_name":"DNA_Methylation_FHS_HMB-IRB-NPU-MDS","commons":"BioData Catalyst","study_url":"","_subjects_count":279,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs000758.v1.p1.c1":{"gen3_discovery":{"authz":"/programs/heartfailure/projects/Fam_CHD_HMB","tags":[],"_unique_id":"phs000758.v1.p1.c1","study_id":"phs000758.v1.p1.c1","study_description":"The study identified the causal mutation in a five-generation pedigree harboring a cardiac septal defect. The inheritance pattern is consistent with an autosomal dominant mutation with high penetrance. We performed whole-genome sequencing (Complete Genomics) on 21 individuals in the pedigree, of which 11 individuals are affected. We identified a single gene, GATA4, as primarily responsible for this cardiac phenotype in this pedigree. Study Weblinks: Family Genomics Study Design: Family/Twin/Trios Study Type: Family Total number of consented subjects: 28 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Family Genomics of Congenital Heart Defects","short_name":"Fam_CHD_HMB","commons":"BioData Catalyst","study_url":"","_subjects_count":28,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs000784.v3.p1.c1":{"gen3_discovery":{"authz":"/programs/parent/projects/GenSalt_DS-HCR-IRB_","tags":[{"name":"Parent","category":"Program"},{"name":"Clinical Phenotype","category":"Data Type"},{"name":"dbGaP","category":"Study Registration"}],"_unique_id":"phs000784.v3.p1.c1","study_id":"phs000784.v3.p1.c1","study_description":"The GenSalt study is aimed at identifying novel genes which interact with the effect of dietary sodium and potassium intake or cold pressor on blood pressure. Study Design: Interventional Study Type: Family Interventional dbGaP estimated ancestry using GRAF-pop Total number of consented subjects: 1675 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Genetic Epidemiology Network of Salt Sensitivity (GenSalt)","short_name":"GenSalt_DS-HCR-IRB_","commons":"BioData Catalyst","study_url":"https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000784.v3.p1","_subjects_count":1675,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs000806.v1.p1.c1":{"gen3_discovery":{"authz":"/programs/heartfailure/projects/MiGen_EXS_Ottawa_GRU","tags":[],"_unique_id":"phs000806.v1.p1.c1","study_id":"phs000806.v1.p1.c1","study_description":"The Ottawa Heart Study is a cross-sectional case-control study designed to identify genes that predispose to angiographically defined coronary artery disease. All exome sequencing was performed at the Broad Institute of Harvard and MIT; samples sequence capture was performed using Agilent SureSelect Human All Exon Kit v2 and sequencing was performed on an Illumina HiSeq 2000 or 2500. Study Design: Case-Control Study Type: Case-Control Cross-Sectional dbGaP estimated ancestry using GRAF-pop Total number of consented subjects: 1968 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Myocardial Infarction Genetics Exome Sequencing Consortium: Ottawa Heart Study","short_name":"MiGen_EXS_Ottawa_GRU","commons":"BioData Catalyst","study_url":"","_subjects_count":1968,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs000808.v1.p1.c1":{"gen3_discovery":{"authz":"/programs/heartfailure/projects/PGRN_DILQTS_GRU","tags":[],"_unique_id":"phs000808.v1.p1.c1","study_id":"phs000808.v1.p1.c1","study_description":"The goal of this study was to search for genetic variants that could be responsible for modifying the risk of drug-induced long QT syndrome (diLQTS). diLQTS is a relatively common adverse drug event and has been a leading cause for drug relabeling and withdrawal from the market. Our hypothesis, that variants in genes which regulate electrical properties in the heart modify the risk of diLQTS, was tested by sequencing approximately 225 patients of European descent using next-generation targeted captured or whole exome sequencing. Data from cases and controls (1:2) were analyzed to identify both rare and common genetic variation. Study Design: Case-Control Study Type: Case-Control dbGaP estimated ancestry using GRAF-pop Total number of consented subjects: 250 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"PGRN/PAT: The genomic basis for susceptibility to drug-induced long QT syndrome (diLQTS)","short_name":"PGRN_DILQTS_GRU","commons":"BioData Catalyst","study_url":"","_subjects_count":250,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs000810.v1.p1.c1":{"gen3_discovery":{"authz":null,"tags":null,"_unique_id":"phs000810.v1.p1.c1","study_id":"phs000810.v1.p1.c1","study_description":null,"full_name":null,"short_name":null,"commons":"BioData Catalyst","study_url":null,"_subjects_count":0,"__manifest":null,"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs000810.v1.p1.c2":{"gen3_discovery":{"authz":null,"tags":null,"_unique_id":"phs000810.v1.p1.c2","study_id":"phs000810.v1.p1.c2","study_description":null,"full_name":null,"short_name":null,"commons":"BioData Catalyst","study_url":null,"_subjects_count":0,"__manifest":null,"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs000810.v2.p2.c1":{"gen3_discovery":{"authz":"/programs/parent/projects/HCHS-SOL_HMB-NPU_","tags":[],"_unique_id":"phs000810.v2.p2.c1","study_id":"phs000810.v2.p2.c1","study_description":"The Hispanic Community Health Study / Study of Latinos (HCHS/SOL) is a multi-center epidemiologic study in Hispanic/Latino populations to determine the role of acculturation in the prevalence and development of disease, and to identify risk factors playing a protective or harmful role in Hispanics/Latinos. The study is sponsored by the National Heart, Lung, and Blood Institute (NHLBI) and six other institutes, centers, and offices of the National Institutes of Health (NIH). The goals of the HCHS/SOL include studying the prevalence and development of disease in Hispanics/Latinos, including the role of acculturation, and identifying disease risk factors that play protective or harmful roles in Hispanics/Latinos. A total of 16,415 persons of Cuban, Dominican, Mexican, Puerto Rican, Central American, and South American backgrounds were recruited through four Field Centers affiliated with San Diego State University, Northwestern University in Chicago, Albert Einstein College of Medicine in the Bronx area of New York, and the University of Miami. Seven additional academic centers serve as scientific and logistical support centers. Study participants aged 18-74 years took part in an extensive clinic exam and assessments to ascertain socio-demographic, cultural, environmental and biomedical characteristics. Annual follow-up interviews are conducted to determine a range of health outcomes. The HCHS SOL Cohort is utilized in the following dbGaP substudies. To view genotypes, other molecular data, and derived variables collected in these substudies, please click on the following substudies below or in the \"Substudies\" section of this top-level study page phs000810 HCHS SOL Cohort. phs000555 PAGE CALiCo SOL phs000880 HCHS/SOL Omics in Latinos (Ola)phs003457 NSRR HCHS/SOL - the data for this substudy is temporarily being released as a standalone study under phs003543 Study Weblinks: Hispanic Community Health Study / Study of Latinos Study Design: Prospective Longitudinal Cohort Study Type: Cohort Total number of consented subjects: 12121 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Hispanic Community Health Study /Study of Latinos (HCHS/SOL)","short_name":"HCHS-SOL_HMB-NPU_","commons":"BioData Catalyst","study_url":"","_subjects_count":2304,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs000810.v2.p2.c2":{"gen3_discovery":{"authz":"/programs/parent/projects/HCHS-SOL_HMB_","tags":[],"_unique_id":"phs000810.v2.p2.c2","study_id":"phs000810.v2.p2.c2","study_description":"The Hispanic Community Health Study / Study of Latinos (HCHS/SOL) is a multi-center epidemiologic study in Hispanic/Latino populations to determine the role of acculturation in the prevalence and development of disease, and to identify risk factors playing a protective or harmful role in Hispanics/Latinos. The study is sponsored by the National Heart, Lung, and Blood Institute (NHLBI) and six other institutes, centers, and offices of the National Institutes of Health (NIH). The goals of the HCHS/SOL include studying the prevalence and development of disease in Hispanics/Latinos, including the role of acculturation, and identifying disease risk factors that play protective or harmful roles in Hispanics/Latinos. A total of 16,415 persons of Cuban, Dominican, Mexican, Puerto Rican, Central American, and South American backgrounds were recruited through four Field Centers affiliated with San Diego State University, Northwestern University in Chicago, Albert Einstein College of Medicine in the Bronx area of New York, and the University of Miami. Seven additional academic centers serve as scientific and logistical support centers. Study participants aged 18-74 years took part in an extensive clinic exam and assessments to ascertain socio-demographic, cultural, environmental and biomedical characteristics. Annual follow-up interviews are conducted to determine a range of health outcomes. The HCHS SOL Cohort is utilized in the following dbGaP substudies. To view genotypes, other molecular data, and derived variables collected in these substudies, please click on the following substudies below or in the \"Substudies\" section of this top-level study page phs000810 HCHS SOL Cohort. phs000555 PAGE CALiCo SOL phs000880 HCHS/SOL Omics in Latinos (Ola)phs003457 NSRR HCHS/SOL - the data for this substudy is temporarily being released as a standalone study under phs003543 Study Weblinks: Hispanic Community Health Study / Study of Latinos Study Design: Prospective Longitudinal Cohort Study Type: Cohort Total number of consented subjects: 12121 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Hispanic Community Health Study /Study of Latinos (HCHS/SOL)","short_name":"HCHS-SOL_HMB_","commons":"BioData Catalyst","study_url":"","_subjects_count":9817,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs000814.v1.p1.c1":{"gen3_discovery":{"authz":"/programs/heartfailure/projects/MiGen_EXS_ItalAmer_GRU","tags":[],"_unique_id":"phs000814.v1.p1.c1","study_id":"phs000814.v1.p1.c1","study_description":"Italian Atherosclerosis Thrombosis and Vascular Biology study is a prospective, nationwide, case-control study involving 125 coronary care units in Italy. The cases were patients who were hospitalised for a first MI before the age of 45 years and underwent coronary angiography. Acute MI was defined as resting chest pain lasting more than 30 minutes, accompanied by persistent electrocardiographic changes, and confirmed by an increase in total creatine kinase or in the MB fraction to more than twice the upper normal limits. The controls were healthy subjects without a history of thromboembolic disease who were unrelated to the patients, but individually matched with them by age, gender and geographical origin. They were enrolled from among the blood donors or staff of the same participating hospitals. Recruitment of cases and controls took place between 1994 and 2007. All exome sequencing was performed at the Broad Institute of Harvard and MIT; samples sequence capture was performed using Agilent SureSelect Human All Exon Kit v2 and sequencing was performed on an Illumina HiSeq 2000 or 2500. Study Design: Case-Control Study Type: Case-Control dbGaP estimated ancestry using GRAF-pop Total number of consented subjects: 3592 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Myocardial Infarction Genetics Exome Sequencing Consortium: Italian Atherosclerosis Thrombosis and Vascular Biology","short_name":"MiGen_EXS_ItalAmer_GRU","commons":"BioData Catalyst","study_url":"","_subjects_count":3592,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs000820.v1.p1.c1":{"gen3_discovery":{"authz":null,"tags":null,"_unique_id":"phs000820.v1.p1.c1","study_id":"phs000820.v1.p1.c1","study_description":null,"full_name":null,"short_name":null,"commons":"BioData Catalyst","study_url":null,"_subjects_count":0,"__manifest":null,"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs000820.v2.p1.c1":{"gen3_discovery":{"authz":"/programs/parent/projects/CCAF_GRU-IRB_","tags":[],"_unique_id":"phs000820.v2.p1.c1","study_id":"phs000820.v2.p1.c1","study_description":"Blood samples were taken from patients who have lone atrial fibrillation. DNA samples were processed with Illumina Hap550 and Hap 610 chips. Study Design: Case Set Study Type: Case Set dbGaP estimated ancestry using GRAF-pop Total number of consented subjects: 543 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"The Cleveland Clinic Foundation's (CCF) Lone Atrial Fibrillation (AFIB) GWAS Study","short_name":"CCAF_GRU-IRB_","commons":"BioData Catalyst","study_url":"","_subjects_count":543,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs000860.v6.p2.c1":{"gen3_discovery":{"authz":"/programs/substudy/projects/micortex_aric_HMB-IRB","tags":[],"_unique_id":"phs000860.v6.p2.c1","study_id":"phs000860.v6.p2.c1","study_description":"This sub-study phs000860 MICORTEX contains genotype and selected phenotype of subjects available from the phs000860 study. Summary level phenotypes for the NHLBI ARIC Cohort study participants can be viewed at the top-level study page phs000280 ARIC Cohort. Individual level phenotype data and molecular data for all ARIC Cohort top-level study and sub-study are available by requesting Authorized Access to the NHLBI ARIC Cohort phs000280 study. MICORTEX is a program in systems biology, funded by the National Institute of General Medical Sciences (NIGMS), which focuses on developing resources and non-traditional analytical approaches for answering the primary questions faced by investigators seeking to characterize the impact of DNA sequence variation on human health: Which DNA sequence variations, in which individuals, in which populations and in which environmental contexts within a particular population, predict incidence of coronary heart disease (CHD) and diabetes beyond established risk factors? Study Weblinks: MICORTEX Study Design: Prospective Longitudinal Cohort Study Type: Longitudinal Total number of consented subjects: 6881 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"MIchigan-CORnell-TEXas (MICORTEX) - Estimating the Contribution of the Network of DNA Sequence Variations to the Prediction of CHD and Diabetes","short_name":"micortex_aric_HMB-IRB","commons":"BioData Catalyst","study_url":"","_subjects_count":6615,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs000860.v6.p2.c2":{"gen3_discovery":{"authz":"/programs/substudy/projects/micortex_aric_DS-CVD-IRB","tags":[],"_unique_id":"phs000860.v6.p2.c2","study_id":"phs000860.v6.p2.c2","study_description":"This sub-study phs000860 MICORTEX contains genotype and selected phenotype of subjects available from the phs000860 study. Summary level phenotypes for the NHLBI ARIC Cohort study participants can be viewed at the top-level study page phs000280 ARIC Cohort. Individual level phenotype data and molecular data for all ARIC Cohort top-level study and sub-study are available by requesting Authorized Access to the NHLBI ARIC Cohort phs000280 study. MICORTEX is a program in systems biology, funded by the National Institute of General Medical Sciences (NIGMS), which focuses on developing resources and non-traditional analytical approaches for answering the primary questions faced by investigators seeking to characterize the impact of DNA sequence variation on human health: Which DNA sequence variations, in which individuals, in which populations and in which environmental contexts within a particular population, predict incidence of coronary heart disease (CHD) and diabetes beyond established risk factors? Study Weblinks: MICORTEX Study Design: Prospective Longitudinal Cohort Study Type: Longitudinal Total number of consented subjects: 6881 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"MIchigan-CORnell-TEXas (MICORTEX) - Estimating the Contribution of the Network of DNA Sequence Variations to the Prediction of CHD and Diabetes","short_name":"micortex_aric_DS-CVD-IRB","commons":"BioData Catalyst","study_url":"","_subjects_count":266,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs000873.v1.p1.c1":{"gen3_discovery":{"authz":"/programs/heartfailure/projects/Exome_Thrombo-Leuk_GRU","tags":[],"_unique_id":"phs000873.v1.p1.c1","study_id":"phs000873.v1.p1.c1","study_description":"A family with a history of bleeding, variable thrombocytopenia, red cell macrocytosis and two cases of pre B-cell acute lymphoblastic leukemia was studied in a single visit. The family was assessed for bleeding history using a bleeding questionnaire. Additionally, complete blood counts were measured and whole blood was collected from five affected individuals and three unaffected individuals for DNA extraction and whole exome sequencing. The goal of this study is to determine the genetic cause of thrombocytopenia, red cell macrocytosis, and predisposition to leukemia in a family. It is hoped that the information obtained from this study will help researchers understand the genetic and molecular basis of platelet and red cell production, as well as leukemia predisposition. Study Design: Family/Twin/Trios Study Type: Family dbGaP estimated ancestry using GRAF-pop Total number of consented subjects: 8 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Exome Sequencing of a family with thrombocytopenia, red cell macrocytosis, and lymphoblastic leukemia predisposition","short_name":"Exome_Thrombo-Leuk_GRU","commons":"BioData Catalyst","study_url":"","_subjects_count":8,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs000886.v1.p1.c1":{"gen3_discovery":{"authz":"/programs/heartfailure/projects/Twins_Asthma_GRU","tags":[],"_unique_id":"phs000886.v1.p1.c1","study_id":"phs000886.v1.p1.c1","study_description":"The etiology of asthma involves both genetic and non-genetic factors. We performed whole transcriptome sequencing on monozygotic twins discordant or concordant for asthma (with concordant healthy twins as controls), and identified multiple potential transcriptomic profiles associated with the asthma phenotype. Study Design: Case-Control Study Type: Case-Control Total number of consented subjects: 74 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"An Omics View of Asthma through Monozygotic Twins","short_name":"Twins_Asthma_GRU","commons":"BioData Catalyst","study_url":"","_subjects_count":74,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs000902.v1.p1.c1":{"gen3_discovery":{"authz":"/programs/heartfailure/projects/MiGen_EXS_REGICOR_DS-CVD","tags":[],"_unique_id":"phs000902.v1.p1.c1","study_id":"phs000902.v1.p1.c1","study_description":"The Registre Gironi del Cor (REGICOR) study developed a nested case-control cohort from the Girona province in Spain in order to study genetic factors associated with the development of coronary heart disease. All exome sequencing was performed at the Broad Institute of Harvard and MIT; samples sequence capture was performed using Agilent SureSelect Human All Exon Kit v2 and sequencing was performed on an Illumina HiSeq 2000 or 2500. Study Design: Case-Control Study Type: Case-Control dbGaP estimated ancestry using GRAF-pop Total number of consented subjects: 784 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Myocardial Infarction Genetics Exome Sequencing Consortium: Registre Gironi del Cor","short_name":"MiGen_EXS_REGICOR_DS-CVD","commons":"BioData Catalyst","study_url":"","_subjects_count":784,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs000914.v1.p1.c1":{"gen3_discovery":{"authz":"/programs/parent/projects/SAS_GRU-IRB-PUB-COL-NPU-GSO_","tags":[{"name":"Parent","category":"Program"},{"name":"Clinical Phenotype","category":"Data Type"},{"name":"dbGaP","category":"Study Registration"}],"_unique_id":"phs000914.v1.p1.c1","study_id":"phs000914.v1.p1.c1","study_description":"The research goal of this study is to identify genetic variation that increases susceptibility to obesity and cardiometabolic phenotypes among adult Samoans using genome-wide association (GWAS) methods. DNA from peripheral blood and phenotypic information were collected from 3,119 adult Samoans, 23 to 70 years of age. The participants reside throughout the independent nation of Samoa, which is experiencing economic development and the nutrition transition. Genotyping was performed with the Affymetrix Genome-Wide Human SNP 6.0 Array using a panel of approximately 900,000 SNPs. Anthropometric, fasting blood biomarkers and detailed dietary, physical activity, health and socio-demographic variables were collected. We are replicating the GWAS findings in an independent sample of 2,500 Samoans from earlier studies. After replication of genomic regions and informative SNPs in those regions, we will determine sequences of the important genes, and determine the specific genetic variants in the sequenced genes that are associated with adiposity and related cardiometabolic conditions. We will also identify gene by environment interactions, focusing on dietary intake patterns and nutrients. Study Design: Cross-Sectional Study Type: Cross-Sectional Population dbGaP estimated ancestry using GRAF-pop Total number of consented subjects: 3501 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Genome-Wide Association Study of Adiposity in Samoans","short_name":"SAS_GRU-IRB-PUB-COL-NPU-GSO_","commons":"BioData Catalyst","study_url":"https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000914.v1.p1","_subjects_count":3501,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs000917.v1.p1.c1":{"gen3_discovery":{"authz":"/programs/heartfailure/projects/MiGEN_EXS_PROMIS_GRU","tags":[],"_unique_id":"phs000917.v1.p1.c1","study_id":"phs000917.v1.p1.c1","study_description":"The Pakistan Risk of Myocardial Infarction (PROMIS) study is a retrospective multicenter case-control cohort study of individuals with and without coronary heart disease from Pakistan. Multiple biological samples have been collected from the participants including DNA, plasma, serum, and whole blood. The goal of the study is to recruit 20,000 cases and 20,000 controls of Pakistani descent. All exome sequencing was performed at the Broad Institute of Harvard and MIT; samples sequence capture was performed using either Agilent's SureSelect Human All Exon Kit v2 or Illumina's ICE capture reagent; and sequencing was performed on an Illumina HiSeq 2000 or 2500. Study Design: Case-Control Study Type: Case-Control dbGaP estimated ancestry using GRAF-pop Total number of consented subjects: 7298 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Myocardial Infarction Genetics Exome Sequencing Consortium: Pakistan Risk Of Myocardial Infarction Study","short_name":"MiGEN_EXS_PROMIS_GRU","commons":"BioData Catalyst","study_url":"","_subjects_count":7298,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs000920.v5.p2.c2":{"gen3_discovery":{"authz":"","tags":[],"_unique_id":"phs000920.v5.p2.c2","study_id":"phs000920.v5.p2.c2","study_description":"","full_name":"","short_name":"","commons":"BioData Catalyst","study_url":"","_subjects_count":0,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs000920.v6.p4.c2":{"gen3_discovery":{"authz":"/programs/topmed/projects/GALAII_DS-LD-IRB-COL","tags":[],"_unique_id":"phs000920.v6.p4.c2","study_id":"phs000920.v6.p4.c2","study_description":"This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed) Whole Genome Sequencing Program. TOPMed is part of a broader Precision Medicine Initiative, which aims to provide disease treatments that are tailored to an individual's unique genes and environment. TOPMed will contribute to this initiative through the integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles, protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental, and clinical data. In doing so, this program aims to uncover factors that increase or decrease the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized treatments. Two genotype call sets derived from WGS are now available, Freeze 9b (GRCh38) and Freeze 10b (GRCh38), with largely overlapping sample sets. Information about how to identify other TOPMed WGS accessions for cross-study analysis, as well as descriptions of TOPMed methods of data acquisition, data processing and quality control, are provided in the accompanying documents, \"TOPMed Whole Genome Sequencing Project - Freeze 9b, Phases 1-4\" and \"TOPMed Whole Genome Sequencing Project - Freeze 10b, Phases 1-8\". Please check the study list at the top of each of these methods documents to determine whether it applies to this study accession. This is a case-only pharmacogenetic study of bronchodilator drug response among racially admixed Latino children with asthma. Each participant had two spirometry measurements using the KoKo PFT System. With the first spirometry test, participant was administered with 4 puffs of HFA Albuterol. The second albuterol measurement was based on age, for participants under 16 years of age, additional 2 puffs were administered and for those over 16 years of age, additional 4 puffs were administered. The overall goal is to identify genetic factors which are predictive of drug response in children with asthma. The principal tools include a questionnaire and biological specimen collection. Participants are 8-21 years old at time of recruitment. Children with asthma have physician-diagnosed asthma, symptoms and medications. Comprehensive phenotypic data for GALAII study participants are available through dbGaP phs001180. Study Weblinks: Study Populations and Research Staff Study Design: Case Set Study Type: Case Set dbGaP estimated ancestry using GRAF-pop Total number of consented subjects: 4860 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"NHLBI TOPMed - NHGRI CCDG: Genes-Environments and Admixture in Latino Asthmatics (GALA II)","short_name":"GALAII_DS-LD-IRB-COL","commons":"BioData Catalyst","study_url":"","_subjects_count":4860,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs000921.v4.p1.c2":{"gen3_discovery":{"authz":"","tags":[],"_unique_id":"phs000921.v4.p1.c2","study_id":"phs000921.v4.p1.c2","study_description":"","full_name":"","short_name":"","commons":"BioData Catalyst","study_url":"","_subjects_count":0,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs000921.v5.p2.c2":{"gen3_discovery":{"authz":"/programs/topmed/projects/SAGE_DS-LD-IRB-COL","tags":[],"_unique_id":"phs000921.v5.p2.c2","study_id":"phs000921.v5.p2.c2","study_description":"This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed) Whole Genome Sequencing Program. TOPMed is part of a broader Precision Medicine Initiative, which aims to provide disease treatments that are tailored to an individual's unique genes and environment. TOPMed will contribute to this initiative through the integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles, protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental, and clinical data. In doing so, this program aims to uncover factors that increase or decrease the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized treatments. Two genotype call sets derived from WGS are now available, Freeze 9b (GRCh38) and Freeze 10b (GRCh38), with largely overlapping sample sets. Information about how to identify other TOPMed WGS accessions for cross-study analysis, as well as descriptions of TOPMed methods of data acquisition, data processing and quality control, are provided in the accompanying documents, \"TOPMed Whole Genome Sequencing Project - Freeze 9b, Phases 1-4\" and \"TOPMed Whole Genome Sequencing Project - Freeze 10b, Phases 1-8\". Please check the study list at the top of each of these methods documents to determine whether it applies to this study accession. This is a parallel case-control pharmacogenetic study of bronchodilator drug response among African American children with and without asthma. Each participant had spirometry measured using the KoKo PFT System. Asthmatic participants were administered with 4 puffs of HFA Albuterol. Healthy participants were given a baseline spirometry test. The overall goal is to identify genetic factors which are predictive of drug response in children with asthma. The principal tools include a questionnaire and biological specimen collection. Participants were 8-21 years old at time of recruitment. Children with asthma have physician-diagnosed asthma, symptoms and medications. Study Weblinks: Study Populations and Research Staff Study Design: Case-Control Study Type: Case-Control dbGaP estimated ancestry using GRAF-pop Total number of consented subjects: 1964 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"NHLBI TOPMed: Study of African Americans, Asthma, Genes and Environment (SAGE)","short_name":"SAGE_DS-LD-IRB-COL","commons":"BioData Catalyst","study_url":"","_subjects_count":1964,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs000930.v11.p1.c1":{"gen3_discovery":{"authz":"/programs/heartfailure/projects/CHARGE_GRU","tags":[],"_unique_id":"phs000930.v11.p1.c1","study_id":"phs000930.v11.p1.c1","study_description":"GWAS have successfully identified genetic loci associated with a variety of conditions such as type 2 diabetes and coronary disease. The large number of statistical tests required in GWAS has posed a special challenge because few studies that have DNA and high-quality phenotype data are sufficiently large to provide adequate statistical power for detecting small to modest effect sizes. Even before the era of GWAS, the requirement for large sample sizes and the importance of replication have served as powerful incentives for collaboration. Meta-analyses combining summary data from multiple sources have improved the ability to detect new loci. The Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Consortium was formed to facilitate GWAS meta-analyses and replication among multiple large and well-phenotyped cohort studies. The design of the CHARGE Consortium was formed initially from 5 prospective cohort studies from the United States and Europe: the Age, Gene/Environment Susceptibility (AGES) - Reykjavik Study, the Atherosclerosis Risk in Communities (ARIC) Study, the Cardiovascular Health Study (CHS), the Framingham Heart Study (FHS), and the Rotterdam Study (RS). Additional studies have expanded the CHARGE consortium based upon the phenotypes and willingness to share information across the research community. In order to facilitate investigators across the world to examine relationships between phenotypes and genetic markers within CHARGE published reports, an open site is made available on dbGaP that provides the rsID and the p-value for inspection. Access to detailed summary statistics (including minor allele frequency, odds ratio/effect size) requires approval of a Data Access Request (DAR). Study Weblinks: CHARGE Consortium Study Design: Prospective Longitudinal Cohort Study Type: Cohort Nested Case-Control Family Longitudinal NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"CHARGE (Cohorts for Heart and Aging Research in Genomic Epidemiology) Consortium Summary Results from Genomic Studies","short_name":"CHARGE_GRU","commons":"BioData Catalyst","study_url":"","_subjects_count":0,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs000936.v1.p1.c1":{"gen3_discovery":{"authz":"/programs/heartfailure/projects/BroadEOMI_exome_GRU","tags":[],"_unique_id":"phs000936.v1.p1.c1","study_id":"phs000936.v1.p1.c1","study_description":"The NHLBI \"Grand Opportunity\" Exome Sequencing Project (GO-ESP), a signature project of the NHLBI Recovery Act investment, was designed to identify genetic variants in coding regions (exons) of the human genome (the \"exome\") that are associated with heart, lung and blood diseases. These and related diseases that are of high impact to public health and individuals from diverse racial and ethnic groups will be studied. These data may help researchers understand the causes of disease, contributing to better ways to prevent, diagnose, and treat diseases, as well as determine whether to tailor prevention and treatments to specific populations. This could lead to more effective treatments and reduce the likelihood of side effects. GO-ESP is comprised of five collaborative components: 3 cohort consortia - HeartGO, LungGO, and WHISP - and 2 sequencing centers - BroadGO and SeattleGO. As part of this initiative, the Broad has performed genotyping on several thousand subjects from 4 different cohorts on Illumina's ExomeChip platform as described below: The Duke Study: The Duke study enrolled cases from the Duke University Medical Center with myocardial infarction or coronary artery stenosis > 50%. Controls were individuals who were > 50 years old without coronary stenosis > 30% and without history of myocardial infarction, coronary artery bypass grafting, percutaneous coronary intervention, or heart transplant. The InterMountain Heart Study: The Intermountain Heart Study is an observational registry of individuals with coronary artery disease and healthy controls who received care at participating Intermountain Healthcare facilities. The Ottawa Heart Study: The Ottawa heart study enrolled cases with angiographically confirmed coronary artery disease (> 1 coronary artery with > 50% stenosis) who did not have type 2 diabetes and were ≤ 50 years old for males and ≤ 50 years old for females. Controls were also enrolled who were asymptomatic males > age 65 and females > age 70. PennCATH: PennCATH is a case-control study that recruited individuals undergoing coronary angiography at the University of Pennsylvania Hospital. Cases had angiographically confirmed coronary artery disease (>1 coronary artery with 50% stenosis) and were ≤ 55 years old if male and ≤ 60 years old if female. Controls were men > 40 years old and women > 45 years old with normal coronary angiography. Study Design: Case-Control Study Type: Case-Control dbGaP estimated ancestry using GRAF-pop Total number of consented subjects: 5870 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"NHLBI GO-ESP: Early-Onset Myocardial Infarction Exome Chip (Broad EOMI)","short_name":"BroadEOMI_exome_GRU","commons":"BioData Catalyst","study_url":"","_subjects_count":3278,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs000936.v1.p1.c2":{"gen3_discovery":{"authz":"/programs/heartfailure/projects/BroadEOMI_exome_DS-MI","tags":[],"_unique_id":"phs000936.v1.p1.c2","study_id":"phs000936.v1.p1.c2","study_description":"The NHLBI \"Grand Opportunity\" Exome Sequencing Project (GO-ESP), a signature project of the NHLBI Recovery Act investment, was designed to identify genetic variants in coding regions (exons) of the human genome (the \"exome\") that are associated with heart, lung and blood diseases. These and related diseases that are of high impact to public health and individuals from diverse racial and ethnic groups will be studied. These data may help researchers understand the causes of disease, contributing to better ways to prevent, diagnose, and treat diseases, as well as determine whether to tailor prevention and treatments to specific populations. This could lead to more effective treatments and reduce the likelihood of side effects. GO-ESP is comprised of five collaborative components: 3 cohort consortia - HeartGO, LungGO, and WHISP - and 2 sequencing centers - BroadGO and SeattleGO. As part of this initiative, the Broad has performed genotyping on several thousand subjects from 4 different cohorts on Illumina's ExomeChip platform as described below: The Duke Study: The Duke study enrolled cases from the Duke University Medical Center with myocardial infarction or coronary artery stenosis > 50%. Controls were individuals who were > 50 years old without coronary stenosis > 30% and without history of myocardial infarction, coronary artery bypass grafting, percutaneous coronary intervention, or heart transplant. The InterMountain Heart Study: The Intermountain Heart Study is an observational registry of individuals with coronary artery disease and healthy controls who received care at participating Intermountain Healthcare facilities. The Ottawa Heart Study: The Ottawa heart study enrolled cases with angiographically confirmed coronary artery disease (> 1 coronary artery with > 50% stenosis) who did not have type 2 diabetes and were ≤ 50 years old for males and ≤ 50 years old for females. Controls were also enrolled who were asymptomatic males > age 65 and females > age 70. PennCATH: PennCATH is a case-control study that recruited individuals undergoing coronary angiography at the University of Pennsylvania Hospital. Cases had angiographically confirmed coronary artery disease (>1 coronary artery with 50% stenosis) and were ≤ 55 years old if male and ≤ 60 years old if female. Controls were men > 40 years old and women > 45 years old with normal coronary angiography. Study Design: Case-Control Study Type: Case-Control dbGaP estimated ancestry using GRAF-pop Total number of consented subjects: 5870 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"NHLBI GO-ESP: Early-Onset Myocardial Infarction Exome Chip (Broad EOMI)","short_name":"BroadEOMI_exome_DS-MI","commons":"BioData Catalyst","study_url":"","_subjects_count":577,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs000936.v1.p1.c3":{"gen3_discovery":{"authz":"/programs/heartfailure/projects/BroadEOMI_exome_DS-CVD","tags":[],"_unique_id":"phs000936.v1.p1.c3","study_id":"phs000936.v1.p1.c3","study_description":"The NHLBI \"Grand Opportunity\" Exome Sequencing Project (GO-ESP), a signature project of the NHLBI Recovery Act investment, was designed to identify genetic variants in coding regions (exons) of the human genome (the \"exome\") that are associated with heart, lung and blood diseases. These and related diseases that are of high impact to public health and individuals from diverse racial and ethnic groups will be studied. These data may help researchers understand the causes of disease, contributing to better ways to prevent, diagnose, and treat diseases, as well as determine whether to tailor prevention and treatments to specific populations. This could lead to more effective treatments and reduce the likelihood of side effects. GO-ESP is comprised of five collaborative components: 3 cohort consortia - HeartGO, LungGO, and WHISP - and 2 sequencing centers - BroadGO and SeattleGO. As part of this initiative, the Broad has performed genotyping on several thousand subjects from 4 different cohorts on Illumina's ExomeChip platform as described below: The Duke Study: The Duke study enrolled cases from the Duke University Medical Center with myocardial infarction or coronary artery stenosis > 50%. Controls were individuals who were > 50 years old without coronary stenosis > 30% and without history of myocardial infarction, coronary artery bypass grafting, percutaneous coronary intervention, or heart transplant. The InterMountain Heart Study: The Intermountain Heart Study is an observational registry of individuals with coronary artery disease and healthy controls who received care at participating Intermountain Healthcare facilities. The Ottawa Heart Study: The Ottawa heart study enrolled cases with angiographically confirmed coronary artery disease (> 1 coronary artery with > 50% stenosis) who did not have type 2 diabetes and were ≤ 50 years old for males and ≤ 50 years old for females. Controls were also enrolled who were asymptomatic males > age 65 and females > age 70. PennCATH: PennCATH is a case-control study that recruited individuals undergoing coronary angiography at the University of Pennsylvania Hospital. Cases had angiographically confirmed coronary artery disease (>1 coronary artery with 50% stenosis) and were ≤ 55 years old if male and ≤ 60 years old if female. Controls were men > 40 years old and women > 45 years old with normal coronary angiography. Study Design: Case-Control Study Type: Case-Control dbGaP estimated ancestry using GRAF-pop Total number of consented subjects: 5870 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"NHLBI GO-ESP: Early-Onset Myocardial Infarction Exome Chip (Broad EOMI)","short_name":"BroadEOMI_exome_DS-CVD","commons":"BioData Catalyst","study_url":"","_subjects_count":2015,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs000946.v5.p1.c1":{"gen3_discovery":{"authz":"","tags":[],"_unique_id":"phs000946.v5.p1.c1","study_id":"phs000946.v5.p1.c1","study_description":"","full_name":"","short_name":"","commons":"BioData Catalyst","study_url":"","_subjects_count":0,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs000946.v6.p2.c1":{"gen3_discovery":{"authz":"/programs/topmed/projects/EOCOPD_DS-CS-RD","tags":[{"name":"TOPMed","category":"Program"},{"name":"Genotype","category":"Data Type"},{"name":"dbGaP","category":"Study Registration"}],"_unique_id":"phs000946.v6.p2.c1","study_id":"phs000946.v6.p2.c1","study_description":"This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed) Whole Genome Sequencing Program. TOPMed is part of a broader Precision Medicine Initiative, which aims to provide disease treatments that are tailored to an individual's unique genes and environment. TOPMed will contribute to this initiative through the integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles, protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental, and clinical data. In doing so, this program aims to uncover factors that increase or decrease the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized treatments. Two genotype call sets derived from WGS are now available, Freeze 9b (GRCh38) and Freeze 10b (GRCh38), with largely overlapping sample sets. Information about how to identify other TOPMed WGS accessions for cross-study analysis, as well as descriptions of TOPMed methods of data acquisition, data processing and quality control, are provided in the accompanying documents, \"TOPMed Whole Genome Sequencing Project - Freeze 9b, Phases 1-4\" and \"TOPMed Whole Genome Sequencing Project - Freeze 10b, Phases 1-8\". Please check the study list at the top of each of these methods documents to determine whether it applies to this study accession. Chronic obstructive pulmonary disease (COPD) is the third leading cause of death in the United States and the only leading cause of death that is steadily increasing in frequency. This project collected a set of extended pedigrees ascertained through subjects with severe, early-onset COPD. This study has enrolled subjects with severe COPD (forced expiratory volume in one second (FEV1) < 40% predicted) at an early age (< 53 years) without alpha-1 antitrypsin deficiency (a known Mendelian risk factor for COPD). Extended pedigrees are enrolled, primarily in New England, although some more geographically distant subjects have been included. This study has been used for epidemiological studies, familial aggregation analysis, linkage analysis, and candidate gene association analysis. Approximately 80 of the severe, early-onset COPD probands will undergo whole genome sequencing in this project with sequencing data available through dbGaP. Study Weblinks: Boston COPD Study Design: Family/Twin/Trios Study Type: Probands Whole Genome Sequencing dbGaP estimated ancestry using GRAF-pop Total number of consented subjects: 74 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"NHLBI TOPMed: Boston Early-Onset COPD Study","short_name":"EOCOPD_DS-CS-RD","commons":"BioData Catalyst","study_url":"https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000946.v6.p2","_subjects_count":74,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs000951.v5.p4.c1":{"gen3_discovery":{"authz":"","tags":[],"_unique_id":"phs000951.v5.p4.c1","study_id":"phs000951.v5.p4.c1","study_description":"","full_name":"","short_name":"","commons":"BioData Catalyst","study_url":"","_subjects_count":0,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs000951.v5.p4.c2":{"gen3_discovery":{"authz":"","tags":[],"_unique_id":"phs000951.v5.p4.c2","study_id":"phs000951.v5.p4.c2","study_description":"","full_name":"","short_name":"","commons":"BioData Catalyst","study_url":"","_subjects_count":0,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs000951.v6.p5.c1":{"gen3_discovery":{"authz":"/programs/topmed/projects/COPDGene_HMB","tags":[],"_unique_id":"phs000951.v6.p5.c1","study_id":"phs000951.v6.p5.c1","study_description":"This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed) Whole Genome Sequencing Program. TOPMed is part of a broader Precision Medicine Initiative, which aims to provide disease treatments that are tailored to an individual's unique genes and environment. TOPMed will contribute to this initiative through the integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles, protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental, and clinical data. In doing so, this program aims to uncover factors that increase or decrease the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized treatments. Two genotype call sets derived from WGS are now available, Freeze 9b (GRCh38) and Freeze 10b (GRCh38), with largely overlapping sample sets. Information about how to identify other TOPMed WGS accessions for cross-study analysis, as well as descriptions of TOPMed methods of data acquisition, data processing and quality control, are provided in the accompanying documents, \"TOPMed Whole Genome Sequencing Project - Freeze 9b, Phases 1-4\" and \"TOPMed Whole Genome Sequencing Project - Freeze 10b, Phases 1-8\". Please check the study list at the top of each of these methods documents to determine whether it applies to this study accession. Chronic obstructive pulmonary disease (COPD) is the fourth leading cause of death in the United States, and the only leading cause of death that is steadily increasing in frequency. This project established a racially diverse cohort that is sufficiently large and appropriately designed for genome-wide association analysis of COPD. A total of 10,720 subjects were recruited, including control smokers and nonsmokers, definite COPD cases (GOLD Stage 2 to 4), and subjects not included in either group (GOLD 1 and PRISm). This cohort is being used for cross-sectional analysis, and long-term longitudinal follow-up visits after five years and after ten years are also being performed. The primary focus of the study is to identify the genetic risk factors that determine susceptibility for COPD and COPD-related phenotypes. Detailed phenotyping of both cases and controls, including chest CT scan assessment of emphysema and airway disease, will allow identification of genetic determinants for the heterogeneous components of the COPD syndrome. The aims for this study are: Precise phenotypic characterization of COPD subjects using computed tomography, as well as clinical and physiological measures, that will provide data to enable the broad COPD syndrome to be decomposed into clinically significant subtype; Genome-wide association studies will identify genetic determinants for COPD susceptibility that will provide insight into clinically relevant COPD subtypes; Distinct genetic determinants influence the development of emphysema and airway disease. The TOPMed analysis will include approximately 10,500 subjects with whole genome sequencing after quality control is completed. Comprehensive phenotypic data for COPDGene subjects is available through dbGaP study phs000179. Study Weblinks: COPDGene phs000179 Study Design: Case-Control Study Type: Case-Control dbGaP estimated ancestry using GRAF-pop Total number of consented subjects: 10660 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"NHLBI TOPMed: Genetic Epidemiology of COPD (COPDGene)","short_name":"COPDGene_HMB","commons":"BioData Catalyst","study_url":"","_subjects_count":10367,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs000951.v6.p5.c2":{"gen3_discovery":{"authz":"/programs/topmed/projects/COPDGene_DS-CS-RD","tags":[],"_unique_id":"phs000951.v6.p5.c2","study_id":"phs000951.v6.p5.c2","study_description":"This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed) Whole Genome Sequencing Program. TOPMed is part of a broader Precision Medicine Initiative, which aims to provide disease treatments that are tailored to an individual's unique genes and environment. TOPMed will contribute to this initiative through the integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles, protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental, and clinical data. In doing so, this program aims to uncover factors that increase or decrease the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized treatments. Two genotype call sets derived from WGS are now available, Freeze 9b (GRCh38) and Freeze 10b (GRCh38), with largely overlapping sample sets. Information about how to identify other TOPMed WGS accessions for cross-study analysis, as well as descriptions of TOPMed methods of data acquisition, data processing and quality control, are provided in the accompanying documents, \"TOPMed Whole Genome Sequencing Project - Freeze 9b, Phases 1-4\" and \"TOPMed Whole Genome Sequencing Project - Freeze 10b, Phases 1-8\". Please check the study list at the top of each of these methods documents to determine whether it applies to this study accession. Chronic obstructive pulmonary disease (COPD) is the fourth leading cause of death in the United States, and the only leading cause of death that is steadily increasing in frequency. This project established a racially diverse cohort that is sufficiently large and appropriately designed for genome-wide association analysis of COPD. A total of 10,720 subjects were recruited, including control smokers and nonsmokers, definite COPD cases (GOLD Stage 2 to 4), and subjects not included in either group (GOLD 1 and PRISm). This cohort is being used for cross-sectional analysis, and long-term longitudinal follow-up visits after five years and after ten years are also being performed. The primary focus of the study is to identify the genetic risk factors that determine susceptibility for COPD and COPD-related phenotypes. Detailed phenotyping of both cases and controls, including chest CT scan assessment of emphysema and airway disease, will allow identification of genetic determinants for the heterogeneous components of the COPD syndrome. The aims for this study are: Precise phenotypic characterization of COPD subjects using computed tomography, as well as clinical and physiological measures, that will provide data to enable the broad COPD syndrome to be decomposed into clinically significant subtype; Genome-wide association studies will identify genetic determinants for COPD susceptibility that will provide insight into clinically relevant COPD subtypes; Distinct genetic determinants influence the development of emphysema and airway disease. The TOPMed analysis will include approximately 10,500 subjects with whole genome sequencing after quality control is completed. Comprehensive phenotypic data for COPDGene subjects is available through dbGaP study phs000179. Study Weblinks: COPDGene phs000179 Study Design: Case-Control Study Type: Case-Control dbGaP estimated ancestry using GRAF-pop Total number of consented subjects: 10660 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"NHLBI TOPMed: Genetic Epidemiology of COPD (COPDGene)","short_name":"COPDGene_DS-CS-RD","commons":"BioData Catalyst","study_url":"","_subjects_count":293,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs000954.v4.p2.c1":{"gen3_discovery":{"authz":"/programs/topmed/projects/CFS_DS-HLBS-IRB-NPU","tags":[{"name":"TOPMed","category":"Program"},{"name":"Genotype","category":"Data Type"},{"name":"dbGaP","category":"Study Registration"}],"_unique_id":"phs000954.v4.p2.c1","study_id":"phs000954.v4.p2.c1","study_description":"This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed) Whole Genome Sequencing Program. TOPMed is part of a broader Precision Medicine Initiative, which aims to provide disease treatments that are tailored to an individual's unique genes and environment. TOPMed will contribute to this initiative through the integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles, protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental, and clinical data. In doing so, this program aims to uncover factors that increase or decrease the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized treatments. Two genotype call sets derived from WGS are now available, Freeze 8 (GRCh38) and Freeze 9b (GRCh38), with largely overlapping sample sets. Information about how to identify other TOPMed WGS accessions for cross-study analysis, as well as descriptions of TOPMed methods of data acquisition, data processing and quality control, are provided in the accompanying documents, \"TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4\" and \"TOPMed Whole Genome Sequencing Project - Freeze 9b, Phases 1-4\". Please check the study list at the top of each of these methods documents to determine whether it applies to this study accession. The Cleveland Family Study (CFS) is one cohort involved in the WGS project. The CFS was designed to provide fundamental epidemiological data on genetic and non-genetic risk factors for sleep disordered breathing (SDB). In brief, the CFS is a family-based study that enrolled a total of 2284 individuals from 361 families between 1990 and 2006. The sample was selected by identifying affected probands who had laboratory diagnosed obstructive sleep apnea. All first degree relatives, spouses and available second degree relatives of affected probands were studied. In addition, during the first 5 study years, neighborhood control families were identified through a neighborhood proband, and his/her spouses and first degree relatives. Each exam, occurring at approximately 4 year intervals, included new enrollment as well as follow up exams for previously enrolled subjects. For the first three visits, data, including an overnight sleep study, were collected in the participants' homes while the last visit occurred in a general clinical research center (GCRC). Phenotypic characterization of the entire cohort included overnight sleep apnea studies, blood pressure, spirometry, anthropometry and questionnaires. The GCRC exam (n=735 selected individuals) included more comprehensive phenotype data on a focused subsample of the larger cohort, to permit linking SDB phenotypes with cardio-metabolic phenotypes, with an interest in identifying genetic loci that are associated with these related phenotypes. In this last round of data collection, a subset of 735 individuals was selected based on expected genetic informativity by choosing pedigrees where siblings had extremes of the apnea hypopnea index (AHI). Participants underwent detailed phenotyping including laboratory polysomnography (PSG), ECG, spirometry, nasal and oral acoustic reflectometry, vigilance testing, and blood and urine collection before and after sleep and after an oral glucose tolerance test. A wide range of biochemical measures of inflammation and metabolism were assayed by a Core Laboratory at the University of Vermont. 994 individuals were sequenced as part of TOPMed Phase 1, including 507 African-Americans and 487 European-Americans. Among the sequenced individuals, 156 were probands with diagnosed sleep apnea, an additional 706 were members of families with probands, and 132 were from neighborhood control families. 298 individuals were sequenced as part of TOPMed Phase 3.5, including 169 African-Americans and 129 European-Americans. Among the newly sequenced individuals, 33 were probands with diagnosed sleep apnea, an additional 214 were members of families with probands, and 51 were from neighborhood control families. Please note: Phenotype and pedigree data are available through \"NHLBI Cleveland Family Study (CFS) Candidate Gene Association Resource (CARe)\", phs000284. Study Weblinks: Cleveland Family Study (CFS) Study Design: Prospective Longitudinal Cohort Study Type: Longitudinal dbGaP estimated ancestry using GRAF-pop Total number of consented subjects: 1293 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"NHLBI TOPMed: The Cleveland Family Study (CFS)","short_name":"CFS_DS-HLBS-IRB-NPU","commons":"BioData Catalyst","study_url":"https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000954.v4.p2","_subjects_count":1293,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs000956.v5.p1.c2":{"gen3_discovery":{"authz":"/programs/topmed/projects/Amish_HMB-IRB-MDS","tags":[{"name":"TOPMed","category":"Program"},{"name":"Genotype","category":"Data Type"},{"name":"Clinical Phenotype","category":"Data Type"},{"name":"dbGaP","category":"Study Registration"}],"_unique_id":"phs000956.v5.p1.c2","study_id":"phs000956.v5.p1.c2","study_description":"This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed) Whole Genome Sequencing Program. TOPMed is part of a broader Precision Medicine Initiative, which aims to provide disease treatments that are tailored to an individual's unique genes and environment. TOPMed will contribute to this initiative through the integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles, protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental, and clinical data. In doing so, this program aims to uncover factors that increase or decrease the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized treatments. Two genotype call sets derived from WGS are now available, Freeze 8 (GRCh38) and Freeze 9b (GRCh38), with largely overlapping sample sets. Information about how to identify other TOPMed WGS accessions for cross-study analysis, as well as descriptions of TOPMed methods of data acquisition, data processing and quality control, are provided in the accompanying documents, \"TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4\" and \"TOPMed Whole Genome Sequencing Project - Freeze 9b, Phases 1-4\". Please check the study list at the top of each of these methods documents to determine whether it applies to this study accession. The Amish Complex Disease Research Program includes a set of large community-based studies focused largely on cardiometabolic health carried out in the Old Order Amish (OOA) community of Lancaster, Pennsylvania (http://medschool.umaryland.edu/endocrinology/amish/research-program.asp). The OOA population of Lancaster County, PA immigrated to the Colonies from Western Europe in the early 1700's. There are now over 30,000 OOA individuals in the Lancaster area, nearly all of whom can trace their ancestry back 12-14 generations to approximately 700 founders. Investigators at the University of Maryland School of Medicine have been studying the genetic determinants of cardiometabolic health in this population since 1993. To date, over 7,000 Amish adults have participated in one or more of our studies. Due to their ancestral history, the OOA may be enriched for rare variants that arose in the population from a single founder (or small number of founders) and propagated through genetic drift. Many of these variants have large effect sizes and identifying them can lead to new biological insights about health and disease. The parent study for this WGS project provides one (of multiple) examples. In our parent study, we identified through a genome-wide association analysis a haplotype that was highly enriched in the OOA that is associated with very high LDL-cholesterol levels. At the present time, the identity of the causative SNP - and even the implicated gene - is not known because the associated haplotype contains numerous genes, none of which are obvious lipid candidate genes. A major goal of the WGS that will be obtained through the NHLBI TOPMed Consortium will be to identify functional variants that underlie some of the large effect associations observed in this unique population. Study Weblinks: University of Maryland School of Medicine - Amish Studies Study Design: Family/Twin/Trios Study Type: Family dbGaP estimated ancestry using GRAF-pop Total number of consented subjects: 1123 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"NHLBI TOPMed: Genetics of Cardiometabolic Health in the Amish","short_name":"Amish_HMB-IRB-MDS","commons":"BioData Catalyst","study_url":"https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000956.v5.p1","_subjects_count":1111,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs000963.v1.p1.c1":{"gen3_discovery":{"authz":"/programs/heartfailure/projects/PGRN_Cardio-Stat_HMB","tags":[],"_unique_id":"phs000963.v1.p1.c1","study_id":"phs000963.v1.p1.c1","study_description":"Coronary heart disease (CHD) is an important public health problem in developed countries. Statins are effective in the prevention and treatment of CHD; nevertheless, many patients receiving statins still suffer cardiovascular events (CV) such as heart attack. Identifying genetic variants responsible for differential clinical responses to statins will not only allow individual patients at high residual risk to be targeted for additional therapies, but also will define new biologic pathways contributing to statin response, and thus new targets for future therapies. Accordingly, the goal of this study is to identify genetic variants associated with clinical CV in patients receiving statins. Subjects identified for study are of European descent and include 1718 subjects with CV while on statins (cases) and 4172 subjects without CV while on statins (controls). Key research resources utilized in this effort include VanderbiltD's BioVU DNA databank and associated Synthetic Derivative database of clinical information, and software tools developed to identify drugs and clinical events using Electronic Health Record-derived structured and unstructured (\"free text\") data. Most cases and controls identified include three data types: ICD-9 codes, medication regimens, and medical test results. Genotyping, using IlluminaD's Infinium HumanOmniExpressExome BeadChip (OmniExpressExome), was performed by the RIKEN Integrative Medical Sciences Center (IMS) and supported by the Pharmacogenomics Research Network (PGRN)-RIKEN IMS Global Alliance. Study Design: Case-Control Study Type: Case-Control dbGaP estimated ancestry using GRAF-pop Total number of consented subjects: 5890 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"PGRN-RIKEN: Genetic Determinants of Clinical Cardiovascular Events in Patients Receiving Statins","short_name":"PGRN_Cardio-Stat_HMB","commons":"BioData Catalyst","study_url":"","_subjects_count":5890,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs000964.v5.p1.c1":{"gen3_discovery":{"authz":"/programs/topmed/projects/JHS_HMB-IRB-NPU","tags":[{"name":"TOPMed","category":"Program"},{"name":"Genotype","category":"Data Type"},{"name":"dbGaP","category":"Study Registration"}],"_unique_id":"phs000964.v5.p1.c1","study_id":"phs000964.v5.p1.c1","study_description":"This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed) Whole Genome Sequencing Program. TOPMed is part of a broader Precision Medicine Initiative, which aims to provide disease treatments that are tailored to an individual's unique genes and environment. TOPMed will contribute to this initiative through the integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles, protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental, and clinical data. In doing so, this program aims to uncover factors that increase or decrease the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized treatments. Two genotype call sets derived from WGS are now available, Freeze 8 (GRCh38) and Freeze 9b (GRCh38), with largely overlapping sample sets. Information about how to identify other TOPMed WGS accessions for cross-study analysis, as well as descriptions of TOPMed methods of data acquisition, data processing and quality control, are provided in the accompanying documents, \"TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4\" and \"TOPMed Whole Genome Sequencing Project - Freeze 9b, Phases 1-4\". Please check the study list at the top of each of these methods documents to determine whether it applies to this study accession. Since there is a greater prevalence of cardiovascular disease among African Americans, the purpose of the Jackson Heart Study (JHS) is to explore the reasons for this disparity and to uncover new approaches to reduce it. The JHS is a large, community-based, observational study whose 5306 participants were recruited from among the non-institutionalized African-American adults from urban and rural areas of the three counties (Hinds, Madison, and Rankin) that make up the Jackson, MS, metropolitan statistical area (MSA). Jackson is the capital of Mississippi, the state with the largest percentage (36.3%) of African Americans in the United States. The JHS design included participants from the Jackson ARIC study who had originally been recruited through random selection from a drivers' license registry. Approximately six months before the JHS was to begin, an amendment to the federal Driver's Privacy Protection Act was passed that changed the level of consent for public release of personal information from driver's license lists from an \"opt out\" to an \"opt in\" basis. The Mississippi Highway Patrol was no longer able to release a complete listing of all persons with driver's licenses or state identification cards, which prevented its use in the JHS. New JHS participants were chosen randomly from the Accudata America commercial listing, which provides householder name, address, zip code, phone number (if available), age group in decades, and family components. The Accudata list was deemed to provide the most complete count of households for individuals aged 55 years and older in the Jackson MSA. A structured volunteer sample was also included in which demographic cells for recruitment were designed to mirror the eligible population. Enrollment was opened to volunteers who met census-derived age, sex, and socioeconomic status (SES) eligibility criteria for the Jackson MSA. In addition, a family component was included in the JHS. The sampling frame for the family study was a participant in any one of the ARlC, random, or volunteer samples whose family size met eligibility requirements. Eligibility included having at least two full siblings and four first degree relatives (parents, siblings, children over the age of 21) who lived in the Jackson MSA and who were willing to participate in the study. No upper age limit was placed on the family sample. Known contact information was obtained during the baseline clinic examination from the index family member with a verbal pedigree format to identify name(s), age(s), address (es), and telephone number(s). Recruitment was limited to persons 35-84 years old except in the family cohort, where those 21 years old and above were eligible. Only persons who otherwise met study criteria but were deemed to be physically or mentally incompetent by trained recruiters were excluded from study eligibility.1 1 Wyatt SB, Diekelmann N, Henderson F, Andrew ME, Billingsley G, Felder SH et al. A community-driven model of research participation: the Jackson Heart Study Participant Recruitment and Retention Study. Ethn Dis 2003; 13(4):438-455 (PMID: 14632263). Study Weblinks: Jackson Heart Study Study Design: Prospective Longitudinal Cohort Study Type: Longitudinal Cohort dbGaP estimated ancestry using GRAF-pop Total number of consented subjects: 3596 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"NHLBI TOPMed: The Jackson Heart Study (JHS)","short_name":"JHS_HMB-IRB-NPU","commons":"BioData Catalyst","study_url":"https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000964.v5.p1","_subjects_count":1518,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs000964.v5.p1.c2":{"gen3_discovery":{"authz":"/programs/topmed/projects/JHS_DS-FDO-IRB-NPU","tags":[{"name":"TOPMed","category":"Program"},{"name":"Genotype","category":"Data Type"},{"name":"dbGaP","category":"Study Registration"}],"_unique_id":"phs000964.v5.p1.c2","study_id":"phs000964.v5.p1.c2","study_description":"This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed) Whole Genome Sequencing Program. TOPMed is part of a broader Precision Medicine Initiative, which aims to provide disease treatments that are tailored to an individual's unique genes and environment. TOPMed will contribute to this initiative through the integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles, protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental, and clinical data. In doing so, this program aims to uncover factors that increase or decrease the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized treatments. Two genotype call sets derived from WGS are now available, Freeze 8 (GRCh38) and Freeze 9b (GRCh38), with largely overlapping sample sets. Information about how to identify other TOPMed WGS accessions for cross-study analysis, as well as descriptions of TOPMed methods of data acquisition, data processing and quality control, are provided in the accompanying documents, \"TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4\" and \"TOPMed Whole Genome Sequencing Project - Freeze 9b, Phases 1-4\". Please check the study list at the top of each of these methods documents to determine whether it applies to this study accession. Since there is a greater prevalence of cardiovascular disease among African Americans, the purpose of the Jackson Heart Study (JHS) is to explore the reasons for this disparity and to uncover new approaches to reduce it. The JHS is a large, community-based, observational study whose 5306 participants were recruited from among the non-institutionalized African-American adults from urban and rural areas of the three counties (Hinds, Madison, and Rankin) that make up the Jackson, MS, metropolitan statistical area (MSA). Jackson is the capital of Mississippi, the state with the largest percentage (36.3%) of African Americans in the United States. The JHS design included participants from the Jackson ARIC study who had originally been recruited through random selection from a drivers' license registry. Approximately six months before the JHS was to begin, an amendment to the federal Driver's Privacy Protection Act was passed that changed the level of consent for public release of personal information from driver's license lists from an \"opt out\" to an \"opt in\" basis. The Mississippi Highway Patrol was no longer able to release a complete listing of all persons with driver's licenses or state identification cards, which prevented its use in the JHS. New JHS participants were chosen randomly from the Accudata America commercial listing, which provides householder name, address, zip code, phone number (if available), age group in decades, and family components. The Accudata list was deemed to provide the most complete count of households for individuals aged 55 years and older in the Jackson MSA. A structured volunteer sample was also included in which demographic cells for recruitment were designed to mirror the eligible population. Enrollment was opened to volunteers who met census-derived age, sex, and socioeconomic status (SES) eligibility criteria for the Jackson MSA. In addition, a family component was included in the JHS. The sampling frame for the family study was a participant in any one of the ARlC, random, or volunteer samples whose family size met eligibility requirements. Eligibility included having at least two full siblings and four first degree relatives (parents, siblings, children over the age of 21) who lived in the Jackson MSA and who were willing to participate in the study. No upper age limit was placed on the family sample. Known contact information was obtained during the baseline clinic examination from the index family member with a verbal pedigree format to identify name(s), age(s), address (es), and telephone number(s). Recruitment was limited to persons 35-84 years old except in the family cohort, where those 21 years old and above were eligible. Only persons who otherwise met study criteria but were deemed to be physically or mentally incompetent by trained recruiters were excluded from study eligibility.1 1 Wyatt SB, Diekelmann N, Henderson F, Andrew ME, Billingsley G, Felder SH et al. A community-driven model of research participation: the Jackson Heart Study Participant Recruitment and Retention Study. Ethn Dis 2003; 13(4):438-455 (PMID: 14632263). Study Weblinks: Jackson Heart Study Study Design: Prospective Longitudinal Cohort Study Type: Longitudinal Cohort dbGaP estimated ancestry using GRAF-pop Total number of consented subjects: 3596 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"NHLBI TOPMed: The Jackson Heart Study (JHS)","short_name":"JHS_DS-FDO-IRB-NPU","commons":"BioData Catalyst","study_url":"https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000964.v5.p1","_subjects_count":342,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs000964.v5.p1.c3":{"gen3_discovery":{"authz":"/programs/topmed/projects/JHS_HMB-IRB","tags":[{"name":"TOPMed","category":"Program"},{"name":"Genotype","category":"Data Type"},{"name":"dbGaP","category":"Study Registration"}],"_unique_id":"phs000964.v5.p1.c3","study_id":"phs000964.v5.p1.c3","study_description":"This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed) Whole Genome Sequencing Program. TOPMed is part of a broader Precision Medicine Initiative, which aims to provide disease treatments that are tailored to an individual's unique genes and environment. TOPMed will contribute to this initiative through the integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles, protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental, and clinical data. In doing so, this program aims to uncover factors that increase or decrease the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized treatments. Two genotype call sets derived from WGS are now available, Freeze 8 (GRCh38) and Freeze 9b (GRCh38), with largely overlapping sample sets. Information about how to identify other TOPMed WGS accessions for cross-study analysis, as well as descriptions of TOPMed methods of data acquisition, data processing and quality control, are provided in the accompanying documents, \"TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4\" and \"TOPMed Whole Genome Sequencing Project - Freeze 9b, Phases 1-4\". Please check the study list at the top of each of these methods documents to determine whether it applies to this study accession. Since there is a greater prevalence of cardiovascular disease among African Americans, the purpose of the Jackson Heart Study (JHS) is to explore the reasons for this disparity and to uncover new approaches to reduce it. The JHS is a large, community-based, observational study whose 5306 participants were recruited from among the non-institutionalized African-American adults from urban and rural areas of the three counties (Hinds, Madison, and Rankin) that make up the Jackson, MS, metropolitan statistical area (MSA). Jackson is the capital of Mississippi, the state with the largest percentage (36.3%) of African Americans in the United States. The JHS design included participants from the Jackson ARIC study who had originally been recruited through random selection from a drivers' license registry. Approximately six months before the JHS was to begin, an amendment to the federal Driver's Privacy Protection Act was passed that changed the level of consent for public release of personal information from driver's license lists from an \"opt out\" to an \"opt in\" basis. The Mississippi Highway Patrol was no longer able to release a complete listing of all persons with driver's licenses or state identification cards, which prevented its use in the JHS. New JHS participants were chosen randomly from the Accudata America commercial listing, which provides householder name, address, zip code, phone number (if available), age group in decades, and family components. The Accudata list was deemed to provide the most complete count of households for individuals aged 55 years and older in the Jackson MSA. A structured volunteer sample was also included in which demographic cells for recruitment were designed to mirror the eligible population. Enrollment was opened to volunteers who met census-derived age, sex, and socioeconomic status (SES) eligibility criteria for the Jackson MSA. In addition, a family component was included in the JHS. The sampling frame for the family study was a participant in any one of the ARlC, random, or volunteer samples whose family size met eligibility requirements. Eligibility included having at least two full siblings and four first degree relatives (parents, siblings, children over the age of 21) who lived in the Jackson MSA and who were willing to participate in the study. No upper age limit was placed on the family sample. Known contact information was obtained during the baseline clinic examination from the index family member with a verbal pedigree format to identify name(s), age(s), address (es), and telephone number(s). Recruitment was limited to persons 35-84 years old except in the family cohort, where those 21 years old and above were eligible. Only persons who otherwise met study criteria but were deemed to be physically or mentally incompetent by trained recruiters were excluded from study eligibility.1 1 Wyatt SB, Diekelmann N, Henderson F, Andrew ME, Billingsley G, Felder SH et al. A community-driven model of research participation: the Jackson Heart Study Participant Recruitment and Retention Study. Ethn Dis 2003; 13(4):438-455 (PMID: 14632263). Study Weblinks: Jackson Heart Study Study Design: Prospective Longitudinal Cohort Study Type: Longitudinal Cohort dbGaP estimated ancestry using GRAF-pop Total number of consented subjects: 3596 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"NHLBI TOPMed: The Jackson Heart Study (JHS)","short_name":"JHS_HMB-IRB","commons":"BioData Catalyst","study_url":"https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000964.v5.p1","_subjects_count":4036,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs000964.v5.p1.c4":{"gen3_discovery":{"authz":"/programs/topmed/projects/JHS_DS-FDO-IRB","tags":[{"name":"TOPMed","category":"Program"},{"name":"Genotype","category":"Data Type"},{"name":"dbGaP","category":"Study Registration"}],"_unique_id":"phs000964.v5.p1.c4","study_id":"phs000964.v5.p1.c4","study_description":"This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed) Whole Genome Sequencing Program. TOPMed is part of a broader Precision Medicine Initiative, which aims to provide disease treatments that are tailored to an individual's unique genes and environment. TOPMed will contribute to this initiative through the integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles, protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental, and clinical data. In doing so, this program aims to uncover factors that increase or decrease the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized treatments. Two genotype call sets derived from WGS are now available, Freeze 8 (GRCh38) and Freeze 9b (GRCh38), with largely overlapping sample sets. Information about how to identify other TOPMed WGS accessions for cross-study analysis, as well as descriptions of TOPMed methods of data acquisition, data processing and quality control, are provided in the accompanying documents, \"TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4\" and \"TOPMed Whole Genome Sequencing Project - Freeze 9b, Phases 1-4\". Please check the study list at the top of each of these methods documents to determine whether it applies to this study accession. Since there is a greater prevalence of cardiovascular disease among African Americans, the purpose of the Jackson Heart Study (JHS) is to explore the reasons for this disparity and to uncover new approaches to reduce it. The JHS is a large, community-based, observational study whose 5306 participants were recruited from among the non-institutionalized African-American adults from urban and rural areas of the three counties (Hinds, Madison, and Rankin) that make up the Jackson, MS, metropolitan statistical area (MSA). Jackson is the capital of Mississippi, the state with the largest percentage (36.3%) of African Americans in the United States. The JHS design included participants from the Jackson ARIC study who had originally been recruited through random selection from a drivers' license registry. Approximately six months before the JHS was to begin, an amendment to the federal Driver's Privacy Protection Act was passed that changed the level of consent for public release of personal information from driver's license lists from an \"opt out\" to an \"opt in\" basis. The Mississippi Highway Patrol was no longer able to release a complete listing of all persons with driver's licenses or state identification cards, which prevented its use in the JHS. New JHS participants were chosen randomly from the Accudata America commercial listing, which provides householder name, address, zip code, phone number (if available), age group in decades, and family components. The Accudata list was deemed to provide the most complete count of households for individuals aged 55 years and older in the Jackson MSA. A structured volunteer sample was also included in which demographic cells for recruitment were designed to mirror the eligible population. Enrollment was opened to volunteers who met census-derived age, sex, and socioeconomic status (SES) eligibility criteria for the Jackson MSA. In addition, a family component was included in the JHS. The sampling frame for the family study was a participant in any one of the ARlC, random, or volunteer samples whose family size met eligibility requirements. Eligibility included having at least two full siblings and four first degree relatives (parents, siblings, children over the age of 21) who lived in the Jackson MSA and who were willing to participate in the study. No upper age limit was placed on the family sample. Known contact information was obtained during the baseline clinic examination from the index family member with a verbal pedigree format to identify name(s), age(s), address (es), and telephone number(s). Recruitment was limited to persons 35-84 years old except in the family cohort, where those 21 years old and above were eligible. Only persons who otherwise met study criteria but were deemed to be physically or mentally incompetent by trained recruiters were excluded from study eligibility.1 1 Wyatt SB, Diekelmann N, Henderson F, Andrew ME, Billingsley G, Felder SH et al. A community-driven model of research participation: the Jackson Heart Study Participant Recruitment and Retention Study. Ethn Dis 2003; 13(4):438-455 (PMID: 14632263). Study Weblinks: Jackson Heart Study Study Design: Prospective Longitudinal Cohort Study Type: Longitudinal Cohort dbGaP estimated ancestry using GRAF-pop Total number of consented subjects: 3596 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"NHLBI TOPMed: The Jackson Heart Study (JHS)","short_name":"JHS_DS-FDO-IRB","commons":"BioData Catalyst","study_url":"https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000964.v5.p1","_subjects_count":916,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs000972.v5.p1.c1":{"gen3_discovery":{"authz":"/programs/topmed/projects/SAS_GRU-IRB-PUB-COL-NPU-GSO","tags":[{"name":"TOPMed","category":"Program"},{"name":"Genotype","category":"Data Type"},{"name":"dbGaP","category":"Study Registration"}],"_unique_id":"phs000972.v5.p1.c1","study_id":"phs000972.v5.p1.c1","study_description":"This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed) Whole Genome Sequencing Program. TOPMed is part of a broader Precision Medicine Initiative, which aims to provide disease treatments that are tailored to an individual's unique genes and environment. TOPMed will contribute to this initiative through the integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles, protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental, and clinical data. In doing so, this program aims to uncover factors that increase or decrease the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized treatments. Two genotype call sets derived from WGS are now available, Freeze 8 (GRCh38) and Freeze 9b (GRCh38), with largely overlapping sample sets. Information about how to identify other TOPMed WGS accessions for cross-study analysis, as well as descriptions of TOPMed methods of data acquisition, data processing and quality control, are provided in the accompanying documents, \"TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4\" and \"TOPMed Whole Genome Sequencing Project - Freeze 9b, Phases 1-4\". Please check the study list at the top of each of these methods documents to determine whether it applies to this study accession. The individuals sequenced here represent a small subset of the parent study (described below) and were carefully selected for the purpose of creating a Samoan-specific reference panel for imputation back into the parent study. The INFOSTIP algorithm of Gusev et. al. (2012) (PMID: 22135348) was used to optimally choose the individuals for sequencing. The research goal of the parent study (dbGaP ID phs000914) is to identify genetic variation that increases susceptibility to obesity and cardiometabolic phenotypes among adult Samoans using genome-wide association (GWAS) methods. DNA from peripheral blood and phenotypic information were collected from 3,119 adult Samoans, 23 to 70 years of age. The participants reside throughout the independent nation of Samoa, which is experiencing economic development and the nutrition transition. Genotyping was performed with the Affymetrix Genome-Wide Human SNP 6.0 Array using a panel of approximately 900,000 SNPs. Anthropometric, fasting blood biomarkers and detailed dietary, physical activity, health and socio-demographic variables were collected. We are replicating the GWAS findings in an independent sample of 2,500 Samoans from earlier studies. After replication of genomic regions and informative SNPs in those regions, we will determine sequences of the important genes, and determine the specific genetic variants in the sequenced genes that are associated with adiposity and related cardiometabolic conditions. We will also identify gene by environment interactions, focusing on dietary intake patterns and nutrients. Study Design: Cross-Sectional Study Type: Cross-Sectional Population dbGaP estimated ancestry using GRAF-pop Total number of consented subjects: 1332 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"NHLBI TOPMed: Genome-Wide Association Study of Adiposity in Samoans","short_name":"SAS_GRU-IRB-PUB-COL-NPU-GSO","commons":"BioData Catalyst","study_url":"https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000972.v5.p1","_subjects_count":1285,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs000974.v5.p3.c1":{"gen3_discovery":{"authz":"","tags":[],"_unique_id":"phs000974.v5.p3.c1","study_id":"phs000974.v5.p3.c1","study_description":"","full_name":"","short_name":"","commons":"BioData Catalyst","study_url":"","_subjects_count":0,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs000974.v5.p3.c2":{"gen3_discovery":{"authz":"","tags":[],"_unique_id":"phs000974.v5.p3.c2","study_id":"phs000974.v5.p3.c2","study_description":"","full_name":"","short_name":"","commons":"BioData Catalyst","study_url":"","_subjects_count":0,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs000974.v6.p5.c1":{"gen3_discovery":{"authz":"/programs/topmed/projects/FHS_HMB-IRB-MDS","tags":[],"_unique_id":"phs000974.v6.p5.c1","study_id":"phs000974.v6.p5.c1","study_description":"This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed) Whole Genome Sequencing Program. TOPMed is part of a broader Precision Medicine Initiative, which aims to provide disease treatments that are tailored to an individual's unique genes and environment. TOPMed will contribute to this initiative through the integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles, protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental, and clinical data. In doing so, this program aims to uncover factors that increase or decrease the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized treatments. Two genotype call sets derived from WGS are now available, Freeze 9b (GRCh38) and Freeze 10b (GRCh38), with largely overlapping sample sets. Information about how to identify other TOPMed WGS accessions for cross-study analysis, as well as descriptions of TOPMed methods of data acquisition, data processing and quality control, are provided in the accompanying documents, \"TOPMed Whole Genome Sequencing Project - Freeze 9b, Phases 1-4\" and \"TOPMed Whole Genome Sequencing Project - Freeze 10b, Phases 1-8\". Please check the study list at the top of each of these methods documents to determine whether it applies to this study accession. The Framingham Heart Study (FHS) is a prospective cohort study of 3 generations of subjects who have been followed up to 65 years to evaluate risk factors for cardiovascular disease. Its large sample of ~15,000 men and women who have been extensively phenotyped with repeated examinations make it ideal for the study of genetic associations with cardiovascular disease risk factors and outcomes. DNA samples have been collected and immortalized since the mid-1990s and are available on ~8000 study participants in 1037 families. These samples have been used for collection of GWAS array data and exome chip data in nearly all with DNA samples, and for targeted sequencing, deep exome sequencing and light coverage whole genome sequencing in limited numbers. Additionally, mRNA and miRNA expression data, DNA methylation data, metabolomics and other 'omics data are available on a sizable portion of study participants. This project will focus on deep whole genome sequencing (mean 30X coverage) in ~4100 participants and imputed to all with GWAS array data to more fully understand the genetic contributions to cardiovascular, lung, blood and sleep disorders. Also available are aptamer proteomic profiling, RNAseq and 850K array DNA methylation data that predominantly overlap with participants with WGS data. Comprehensive phenotypic and pedigree data for study participants are available through dbGaP phs000007. Study Weblinks: Framingham Heart Study Study Design: Prospective Longitudinal Cohort Study Type: Cohort dbGaP estimated ancestry using GRAF-pop Total number of consented subjects: 7304 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"NHLBI TOPMed: Genomic Activities such as Whole Genome Sequencing and Related Phenotypes in the Framingham Heart Study","short_name":"FHS_HMB-IRB-MDS","commons":"BioData Catalyst","study_url":"","_subjects_count":6396,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs000974.v6.p5.c2":{"gen3_discovery":{"authz":"/programs/topmed/projects/FHS_HMB-IRB-NPU-MDS","tags":[],"_unique_id":"phs000974.v6.p5.c2","study_id":"phs000974.v6.p5.c2","study_description":"This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed) Whole Genome Sequencing Program. TOPMed is part of a broader Precision Medicine Initiative, which aims to provide disease treatments that are tailored to an individual's unique genes and environment. TOPMed will contribute to this initiative through the integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles, protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental, and clinical data. In doing so, this program aims to uncover factors that increase or decrease the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized treatments. Two genotype call sets derived from WGS are now available, Freeze 9b (GRCh38) and Freeze 10b (GRCh38), with largely overlapping sample sets. Information about how to identify other TOPMed WGS accessions for cross-study analysis, as well as descriptions of TOPMed methods of data acquisition, data processing and quality control, are provided in the accompanying documents, \"TOPMed Whole Genome Sequencing Project - Freeze 9b, Phases 1-4\" and \"TOPMed Whole Genome Sequencing Project - Freeze 10b, Phases 1-8\". Please check the study list at the top of each of these methods documents to determine whether it applies to this study accession. The Framingham Heart Study (FHS) is a prospective cohort study of 3 generations of subjects who have been followed up to 65 years to evaluate risk factors for cardiovascular disease. Its large sample of ~15,000 men and women who have been extensively phenotyped with repeated examinations make it ideal for the study of genetic associations with cardiovascular disease risk factors and outcomes. DNA samples have been collected and immortalized since the mid-1990s and are available on ~8000 study participants in 1037 families. These samples have been used for collection of GWAS array data and exome chip data in nearly all with DNA samples, and for targeted sequencing, deep exome sequencing and light coverage whole genome sequencing in limited numbers. Additionally, mRNA and miRNA expression data, DNA methylation data, metabolomics and other 'omics data are available on a sizable portion of study participants. This project will focus on deep whole genome sequencing (mean 30X coverage) in ~4100 participants and imputed to all with GWAS array data to more fully understand the genetic contributions to cardiovascular, lung, blood and sleep disorders. Also available are aptamer proteomic profiling, RNAseq and 850K array DNA methylation data that predominantly overlap with participants with WGS data. Comprehensive phenotypic and pedigree data for study participants are available through dbGaP phs000007. Study Weblinks: Framingham Heart Study Study Design: Prospective Longitudinal Cohort Study Type: Cohort dbGaP estimated ancestry using GRAF-pop Total number of consented subjects: 7304 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"NHLBI TOPMed: Genomic Activities such as Whole Genome Sequencing and Related Phenotypes in the Framingham Heart Study","short_name":"FHS_HMB-IRB-NPU-MDS","commons":"BioData Catalyst","study_url":"","_subjects_count":908,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs000988.v5.p1.c1":{"gen3_discovery":{"authz":"","tags":[],"_unique_id":"phs000988.v5.p1.c1","study_id":"phs000988.v5.p1.c1","study_description":"","full_name":"","short_name":"","commons":"BioData Catalyst","study_url":"","_subjects_count":0,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs000988.v6.p1.c1":{"gen3_discovery":{"authz":"/programs/topmed/projects/CRA_DS-ASTHMA-IRB-MDS-RD","tags":[],"_unique_id":"phs000988.v6.p1.c1","study_id":"phs000988.v6.p1.c1","study_description":"This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed) Whole Genome Sequencing Program. TOPMed is part of a broader Precision Medicine Initiative, which aims to provide disease treatments that are tailored to an individual's unique genes and environment. TOPMed will contribute to this initiative through the integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles, protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental, and clinical data. In doing so, this program aims to uncover factors that increase or decrease the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized treatments. Two genotype call sets derived from WGS are now available, Freeze 9b (GRCh38) and Freeze 10b (GRCh38), with largely overlapping sample sets. Information about how to identify other TOPMed WGS accessions for cross-study analysis, as well as descriptions of TOPMed methods of data acquisition, data processing and quality control, are provided in the accompanying documents, \"TOPMed Whole Genome Sequencing Project - Freeze 9b, Phases 1-4\" and \"TOPMed Whole Genome Sequencing Project - Freeze 10b, Phases 1-8\". Please check the study list at the top of each of these methods documents to determine whether it applies to this study accession. This administrative supplement to the project, \"The Genetic Epidemiology of Asthma in Costa Rica\" (R37 HL066289) is in response to NOT-HL-14-029 to perform whole genome sequencing (WGS) on existing NHLBI populations. We focus on asthma because of its public health significance. Asthma affects 26 million U.S. children and adults, remains a major cause of morbidity (one-half million hospitalizations a year) and is the most common cause of school and work days lost. Asthma-related costs are estimated to be over $12.7 billion annually. The Asthma Probands for both the extended pedigrees and the trios utilized in this study were selected on the basis of a physician diagnosis of asthma; a history of recurrent asthma attacks or at least 2 respiratory symptoms; and either airway hyperresponsiveness to methacholine or significant response to bronchodilator (Albuterol) administration. These criteria are identical to the criteria used in the Childhood Asthma Management Program (CAMP). The three primary goals of this project are to: (1) identify common and rare genetic variants that determine asthma and its associated phenotypes (height, weight, IgE level, lung function, bronchodilator response, steroid treatment response) through whole genome sequencing (WGS); (2) perform novel family based association analysis of our WGS data to identify novel genes for asthma; and (3) integrate epigenomic and transcriptomic data with our WGS data and determine the epistatic interactions present using systems genomics approaches. Identification of the molecular determinants of asthma remains an important priority in translational science. Genome-wide association studies (GWAS) have been successful in this regard, identifying at least 10 novel susceptibility genes for asthma. However, as with most complex traits, the variants identified by GWAS explain only a fraction of the estimated heritability of this disorder. Herein, we propose a novel family-based study design and state-of-the-art genome sequencing techniques to map a set of sequence variants for asthma and its associated phenotypes and assess the interrelationships of the identified genes and variants using systems genomics methods. We have assembled a team of investigators highly-skilled and expert in whole genome sequencing (Drs. Michael Cho and Benjamin Raby), genetic association analysis (Drs. Scott T. Weiss, Jessica Lasky-Su and Christoph Lange), integrative genomics (Drs. Raby, Kelan Tantisira, Augusto Litonjua and Dawn DeMeo), and systems genomics (Drs. Weiss, Amitabh Sharma, Lange and Raby) to address this important problem with both a novel study design and data set. Study Design: Family/Twin/Trios Study Type: Parent-Offspring Trios dbGaP estimated ancestry using GRAF-pop Total number of consented subjects: 4283 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"NHLBI TOPMed: The Genetic Epidemiology of Asthma in Costa Rica","short_name":"CRA_DS-ASTHMA-IRB-MDS-RD","commons":"BioData Catalyst","study_url":"","_subjects_count":4283,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs000990.v1.p1.c1":{"gen3_discovery":{"authz":"/programs/heartfailure/projects/MiGEN_EX_UL_DS-CVD","tags":[],"_unique_id":"phs000990.v1.p1.c1","study_id":"phs000990.v1.p1.c1","study_description":"MI cases were recruited from the German MI Family Study and the Angio-Lub study. Controls were recruited from the German MI Family Study and the Angio-Lub study. All exome sequencing was performed at the Broad Institute of Harvard and MIT; samples sequence capture was performed using Illumina's ICE Capture reagent and sequencing was performed on an Illumina HiSeq 2000 or 2500. Study Design: Case-Control Study Type: Case-Control dbGaP estimated ancestry using GRAF-pop Total number of consented subjects: 1766 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Myocardial Infarction Genetics Exome Sequencing Consortium: University of Lubeck","short_name":"MiGEN_EX_UL_DS-CVD","commons":"BioData Catalyst","study_url":"","_subjects_count":1766,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs000993.v5.p2.c1":{"gen3_discovery":{"authz":"/programs/topmed/projects/HVH_HMB-IRB-MDS","tags":[{"name":"TOPMed","category":"Program"},{"name":"Genotype","category":"Data Type"},{"name":"dbGaP","category":"Study Registration"}],"_unique_id":"phs000993.v5.p2.c1","study_id":"phs000993.v5.p2.c1","study_description":"This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed) Whole Genome Sequencing Program. TOPMed is part of a broader Precision Medicine Initiative, which aims to provide disease treatments that are tailored to an individual's unique genes and environment. TOPMed will contribute to this initiative through the integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles, protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental, and clinical data. In doing so, this program aims to uncover factors that increase or decrease the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized treatments. Two genotype call sets derived from WGS are now available, Freeze 8 (GRCh38) and Freeze 9b (GRCh38), with largely overlapping sample sets. Information about how to identify other TOPMed WGS accessions for cross-study analysis, as well as descriptions of TOPMed methods of data acquisition, data processing and quality control, are provided in the accompanying documents, \"TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4\" and \"TOPMed Whole Genome Sequencing Project - Freeze 9b, Phases 1-4\". Please check the study list at the top of each of these methods documents to determine whether it applies to this study accession. Objectives The Heart and Vascular Health Study (HVH) is a case-control study of risk factors for the development of myocardial infarction (MI), stroke, venous thrombosis (VT), and atrial fibrillation (AF). The study setting is Group Health, an integrated health care delivery system in Washington State. Only VT cases and early-onset AF cases are included as part of TOPMed. Background The HVH study originated in 1988 with the examination of risk factors for MI. Over the ensuing years, the study has been funded by a series of grants which have added case subjects with stroke, VT, and AF. Study aims focused on the associations of medication use with cardiovascular events, and starting in 1997, the study aims expanded to include genetic associations with cardiovascular disease. Participants recruited in 2009 or later who provided blood samples for genetic analysis were asked for consent to deposit genetic and phenotypic data in dbGaP. Design As part of the HVH study, case subjects were identified by searching for ICD-9 codes consistent with MI, stroke, VT, or AF, and medical records were reviewed to confirm the diagnosis. Control subjects were identified at random from the Group Health enrollment and were matched to MI cases. All subjects have an index date. For cases, the index date was assigned as the date that the cardiovascular event (MI, stroke, VT, or AF) came to clinical attention. For controls, the index date was a random date within the range of the case index dates. For both cases and controls, information was collected from the inpatient and outpatient medical record, by telephone interview with consenting survivors, and from the Group Health pharmacy and laboratory databases. Consenting participants provided a blood specimen. Subjects Only VT and early-onset AF cases from HVH are included in TOPMed. Within the HVH study, VT and AF cases were diagnosed in both inpatient and outpatient settings, and only incident cases are eligible for inclusion in TOPMed. Genetic Research Genetic factors underlying cardiovascular disease are studied using DNA isolated from the blood samples. Phenotype data for HVH study participants are available through dbGaP phs001013. Study Design: Case Set Study Type: Case Set dbGaP estimated ancestry using GRAF-pop Total number of consented subjects: 709 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"NHLBI TOPMed: Heart and Vascular Health Study (HVH)","short_name":"HVH_HMB-IRB-MDS","commons":"BioData Catalyst","study_url":"https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000993.v5.p2","_subjects_count":686,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs000993.v5.p2.c2":{"gen3_discovery":{"authz":"/programs/topmed/projects/HVH_DS-CVD-IRB-MDS","tags":[{"name":"TOPMed","category":"Program"},{"name":"Genotype","category":"Data Type"},{"name":"dbGaP","category":"Study Registration"}],"_unique_id":"phs000993.v5.p2.c2","study_id":"phs000993.v5.p2.c2","study_description":"This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed) Whole Genome Sequencing Program. TOPMed is part of a broader Precision Medicine Initiative, which aims to provide disease treatments that are tailored to an individual's unique genes and environment. TOPMed will contribute to this initiative through the integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles, protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental, and clinical data. In doing so, this program aims to uncover factors that increase or decrease the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized treatments. Two genotype call sets derived from WGS are now available, Freeze 8 (GRCh38) and Freeze 9b (GRCh38), with largely overlapping sample sets. Information about how to identify other TOPMed WGS accessions for cross-study analysis, as well as descriptions of TOPMed methods of data acquisition, data processing and quality control, are provided in the accompanying documents, \"TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4\" and \"TOPMed Whole Genome Sequencing Project - Freeze 9b, Phases 1-4\". Please check the study list at the top of each of these methods documents to determine whether it applies to this study accession. Objectives The Heart and Vascular Health Study (HVH) is a case-control study of risk factors for the development of myocardial infarction (MI), stroke, venous thrombosis (VT), and atrial fibrillation (AF). The study setting is Group Health, an integrated health care delivery system in Washington State. Only VT cases and early-onset AF cases are included as part of TOPMed. Background The HVH study originated in 1988 with the examination of risk factors for MI. Over the ensuing years, the study has been funded by a series of grants which have added case subjects with stroke, VT, and AF. Study aims focused on the associations of medication use with cardiovascular events, and starting in 1997, the study aims expanded to include genetic associations with cardiovascular disease. Participants recruited in 2009 or later who provided blood samples for genetic analysis were asked for consent to deposit genetic and phenotypic data in dbGaP. Design As part of the HVH study, case subjects were identified by searching for ICD-9 codes consistent with MI, stroke, VT, or AF, and medical records were reviewed to confirm the diagnosis. Control subjects were identified at random from the Group Health enrollment and were matched to MI cases. All subjects have an index date. For cases, the index date was assigned as the date that the cardiovascular event (MI, stroke, VT, or AF) came to clinical attention. For controls, the index date was a random date within the range of the case index dates. For both cases and controls, information was collected from the inpatient and outpatient medical record, by telephone interview with consenting survivors, and from the Group Health pharmacy and laboratory databases. Consenting participants provided a blood specimen. Subjects Only VT and early-onset AF cases from HVH are included in TOPMed. Within the HVH study, VT and AF cases were diagnosed in both inpatient and outpatient settings, and only incident cases are eligible for inclusion in TOPMed. Genetic Research Genetic factors underlying cardiovascular disease are studied using DNA isolated from the blood samples. Phenotype data for HVH study participants are available through dbGaP phs001013. Study Design: Case Set Study Type: Case Set dbGaP estimated ancestry using GRAF-pop Total number of consented subjects: 709 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"NHLBI TOPMed: Heart and Vascular Health Study (HVH)","short_name":"HVH_DS-CVD-IRB-MDS","commons":"BioData Catalyst","study_url":"https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000993.v5.p2","_subjects_count":12,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs000997.v5.p2.c1":{"gen3_discovery":{"authz":"/programs/topmed/projects/VAFAR_HMB-IRB","tags":[{"name":"TOPMed","category":"Program"},{"name":"Genotype","category":"Data Type"},{"name":"Clinical Phenotype","category":"Data Type"},{"name":"dbGaP","category":"Study Registration"}],"_unique_id":"phs000997.v5.p2.c1","study_id":"phs000997.v5.p2.c1","study_description":"This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed) Whole Genome Sequencing Program. TOPMed is part of a broader Precision Medicine Initiative, which aims to provide disease treatments that are tailored to an individual's unique genes and environment. TOPMed will contribute to this initiative through the integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles, protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental, and clinical data. In doing so, this program aims to uncover factors that increase or decrease the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized treatments. Two genotype call sets derived from WGS are now available, Freeze 8 (GRCh38) and Freeze 9b (GRCh38), with largely overlapping sample sets. Information about how to identify other TOPMed WGS accessions for cross-study analysis, as well as descriptions of TOPMed methods of data acquisition, data processing and quality control, are provided in the accompanying documents, \"TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4\" and \"TOPMed Whole Genome Sequencing Project - Freeze 9b, Phases 1-4\". Please check the study list at the top of each of these methods documents to determine whether it applies to this study accession. The Vanderbilt Atrial Fibrillation Ablation Registry (VAFAR) was founded in 2011. Patients with AF referred for AF ablation are prospectively enrolled. A detailed clinical history is recorded, along with imaging data (cardiac MRI or CT). Blood samples are obtained for DNA extraction at the time of ablation. Details of the ablation procedure are recorded. Patients are longitudinally followed to monitor for AF recurrence. VAFAR contributed 171 samples submitted to dbGaP for WGS: 115 were from male subjects, of which 113 were white/non-Hispanic and 2 were Hispanic; 56 were from females, of which all 56 were white/non-Hispanic. Study Design: Case Set Study Type: Case Set dbGaP estimated ancestry using GRAF-pop Total number of consented subjects: 173 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"NHLBI TOPMed - NHGRI CCDG: The Vanderbilt AF Ablation Registry","short_name":"VAFAR_HMB-IRB","commons":"BioData Catalyst","study_url":"https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs000997.v5.p2","_subjects_count":173,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs000998.v2.p1.c1":{"gen3_discovery":{"authz":"/programs/heartfailure/projects/Endothelial_PAH_GRU","tags":[],"_unique_id":"phs000998.v2.p1.c1","study_id":"phs000998.v2.p1.c1","study_description":"The transcriptome of pulmonary arterial endothelial cells from healthy lungs and from lungs of patients with idiopathic pulmonary arterial hypertension have been analyzed and specific differences in disease-relevant pathways were identified. The genes identified as altered in these patients have direct effects on pulmonary arterial endothelial cell function. This finding may underlie the inability of the pulmonary vasculature to respond to and repair the damage observed in pulmonary hypertension. Study Design: Case-Control Study Type: Case-Control Total number of consented subjects: 34 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"RNA Sequencing of Pulmonary Arterial Endothelial Cells in Pulmonary Hypertensive Patients and Controls","short_name":"Endothelial_PAH_GRU","commons":"BioData Catalyst","study_url":"","_subjects_count":34,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs001001.v1.p1.c1":{"gen3_discovery":{"authz":"/programs/parent/projects/MGH_AF_HMB-IRB_","tags":[{"name":"Parent","category":"Program"},{"name":"Clinical Phenotype","category":"Data Type"},{"name":"dbGaP","category":"Study Registration"}],"_unique_id":"phs001001.v1.p1.c1","study_id":"phs001001.v1.p1.c1","study_description":"The Massachusetts General Hospital (MGH) Atrial Fibrillation Study was initiated in 2001. The study has enrolled serial probands, unaffected and affected family members with atrial fibrillation. At enrollment participants undergo a structured interview to systematically capture their past medical history, AF treatments, and family history. An electrocardiogram is performed; the results of an echocardiogram are obtained; and blood samples are obtained. The Massachusetts General Hospital (MGH) Atrial Fibrillation Study is utilized in the following dbGaP substudies. To view genotypes, analysis, other molecular data, and derived variables collected in these substudies, please click on the following substudies below or in the \"Substudies\" section of this top-level study page phs001001 Massachusetts General Hospital (MGH) Atrial Fibrillation Study. phs001116 MGH AF CHARGE-S phs001117 MGH AF Exome Sequencing phs001118 MGH AF Medical Resequencing Study Design: Case Set Study Type: Case Set Total number of consented subjects: 1025 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Massachusetts General Hospital (MGH) Atrial Fibrillation Study","short_name":"MGH_AF_HMB-IRB_","commons":"BioData Catalyst","study_url":"https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001001.v1.p1","_subjects_count":933,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs001001.v1.p1.c2":{"gen3_discovery":{"authz":"/programs/parent/projects/MGH_AF_DS-AF-IRB-RD_","tags":[{"name":"Parent","category":"Program"},{"name":"Clinical Phenotype","category":"Data Type"},{"name":"dbGaP","category":"Study Registration"}],"_unique_id":"phs001001.v1.p1.c2","study_id":"phs001001.v1.p1.c2","study_description":"The Massachusetts General Hospital (MGH) Atrial Fibrillation Study was initiated in 2001. The study has enrolled serial probands, unaffected and affected family members with atrial fibrillation. At enrollment participants undergo a structured interview to systematically capture their past medical history, AF treatments, and family history. An electrocardiogram is performed; the results of an echocardiogram are obtained; and blood samples are obtained. The Massachusetts General Hospital (MGH) Atrial Fibrillation Study is utilized in the following dbGaP substudies. To view genotypes, analysis, other molecular data, and derived variables collected in these substudies, please click on the following substudies below or in the \"Substudies\" section of this top-level study page phs001001 Massachusetts General Hospital (MGH) Atrial Fibrillation Study. phs001116 MGH AF CHARGE-S phs001117 MGH AF Exome Sequencing phs001118 MGH AF Medical Resequencing Study Design: Case Set Study Type: Case Set Total number of consented subjects: 1025 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Massachusetts General Hospital (MGH) Atrial Fibrillation Study","short_name":"MGH_AF_DS-AF-IRB-RD_","commons":"BioData Catalyst","study_url":"https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001001.v1.p1","_subjects_count":92,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs001012.v1.p1.c1":{"gen3_discovery":{"authz":"/programs/parent/projects/DHS_DS-DRC-IRB_","tags":[{"name":"Parent","category":"Program"},{"name":"Clinical Phenotype","category":"Data Type"},{"name":"dbGaP","category":"Study Registration"}],"_unique_id":"phs001012.v1.p1.c1","study_id":"phs001012.v1.p1.c1","study_description":"The Diabetes Heart Study is a family based study enriched for type 2 diabetes (T2D). The cohort included 1220 self-reported European Americans from 475 families (Bowden et al 2010 Review of Diabetic Studies 7:188-201: PMID: 21409311; Bowden et al 2008 Annals of Human Genetics 72:598-601 PMID: 18460048) and included siblings concordant for T2D; where possible unaffected siblings were also recruited. The cohort was recruited between 1998 and 2006. Participants were extensively phenotyped for measures of subclinical CVD and other known CVD risk factors. Primary outcomes were quantified burden of vascular calcified plaque in the coronary artery, carotid artery and abdominal aorta all determined from non-contrast computed tomography scans. Study Design: Cross-Sectional Study Type: Cross-Sectional Cohort dbGaP estimated ancestry using GRAF-pop Total number of consented subjects: 1177 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"The Diabetes Heart Study (DHS)","short_name":"DHS_DS-DRC-IRB_","commons":"BioData Catalyst","study_url":"https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001012.v1.p1","_subjects_count":1177,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs001013.v3.p2.c1":{"gen3_discovery":{"authz":"/programs/parent/projects/HVH_HMB-IRB-MDS_","tags":[{"name":"Parent","category":"Program"},{"name":"DCC Harmonized","category":"Data Type"},{"name":"Clinical Phenotype","category":"Data Type"},{"name":"dbGaP","category":"Study Registration"}],"_unique_id":"phs001013.v3.p2.c1","study_id":"phs001013.v3.p2.c1","study_description":"Objectives The Heart and Vascular Health Study (HVH) is a case-control study of risk factors for the development of myocardial infarction (MI), stroke, venous thrombosis (VT), and atrial fibrillation (AF). The study setting is Group Health, an integrated health care delivery system in Washington State. Background The HVH originated in 1988 with the examination of risk factors for MI. Over the ensuing years, the study has been funded by a series of grants, which have added case subjects with stroke, VT, and AF, and used a common control group. Study aims have focused on the associations of medication use with cardiovascular events. Starting in 1997, the study aims expanded to include genetic associations with cardiovascular disease. Participants recruited in 2009 or later and who provided blood samples for genetic analysis were asked for consent to deposit genetic and phenotype data in dbGaP. Design As part of the HVH study, case subjects were identified by searching for ICD-9 codes consistent with MI, stroke, VT, or AF, and medical records were reviewed to confirm the diagnosis. Control subjects were identified at random from the Group Health enrollment and were matched to MI cases. All subjects have an index date. For cases, the index date was assigned as the date that the cardiovascular event (MI, stroke, VT, or AF) came to clinical attention. For controls, the index date was a random date within the range of the case index dates. For both cases and controls, information was collected from the inpatient and outpatient medical record, by telephone interview with consenting survivors, and from the Group Health pharmacy and laboratory databases. Consenting participants provided a blood specimen. Genetic Research Genetic factors underlying cardiovascular disease are studied using DNA isolated from the blood samples. Study Design: Case-Control Study Type: Case-Control dbGaP estimated ancestry using GRAF-pop Total number of consented subjects: 1204 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Heart and Vascular Health Study (HVH)","short_name":"HVH_HMB-IRB-MDS_","commons":"BioData Catalyst","study_url":"https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001013.v3.p2","_subjects_count":1179,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs001013.v3.p2.c2":{"gen3_discovery":{"authz":"/programs/parent/projects/HVH_DS-CVD-IRB-MDS_","tags":[{"name":"Parent","category":"Program"},{"name":"DCC Harmonized","category":"Data Type"},{"name":"Clinical Phenotype","category":"Data Type"},{"name":"dbGaP","category":"Study Registration"}],"_unique_id":"phs001013.v3.p2.c2","study_id":"phs001013.v3.p2.c2","study_description":"Objectives The Heart and Vascular Health Study (HVH) is a case-control study of risk factors for the development of myocardial infarction (MI), stroke, venous thrombosis (VT), and atrial fibrillation (AF). The study setting is Group Health, an integrated health care delivery system in Washington State. Background The HVH originated in 1988 with the examination of risk factors for MI. Over the ensuing years, the study has been funded by a series of grants, which have added case subjects with stroke, VT, and AF, and used a common control group. Study aims have focused on the associations of medication use with cardiovascular events. Starting in 1997, the study aims expanded to include genetic associations with cardiovascular disease. Participants recruited in 2009 or later and who provided blood samples for genetic analysis were asked for consent to deposit genetic and phenotype data in dbGaP. Design As part of the HVH study, case subjects were identified by searching for ICD-9 codes consistent with MI, stroke, VT, or AF, and medical records were reviewed to confirm the diagnosis. Control subjects were identified at random from the Group Health enrollment and were matched to MI cases. All subjects have an index date. For cases, the index date was assigned as the date that the cardiovascular event (MI, stroke, VT, or AF) came to clinical attention. For controls, the index date was a random date within the range of the case index dates. For both cases and controls, information was collected from the inpatient and outpatient medical record, by telephone interview with consenting survivors, and from the Group Health pharmacy and laboratory databases. Consenting participants provided a blood specimen. Genetic Research Genetic factors underlying cardiovascular disease are studied using DNA isolated from the blood samples. Study Design: Case-Control Study Type: Case-Control dbGaP estimated ancestry using GRAF-pop Total number of consented subjects: 1204 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Heart and Vascular Health Study (HVH)","short_name":"HVH_DS-CVD-IRB-MDS_","commons":"BioData Catalyst","study_url":"https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001013.v3.p2","_subjects_count":25,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs001024.v5.p1.c1":{"gen3_discovery":{"authz":"","tags":[],"_unique_id":"phs001024.v5.p1.c1","study_id":"phs001024.v5.p1.c1","study_description":"","full_name":"","short_name":"","commons":"BioData Catalyst","study_url":"","_subjects_count":0,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs001024.v6.p1.c1":{"gen3_discovery":{"authz":"/programs/topmed/projects/PARTNERS_HMB","tags":[{"name":"TOPMed","category":"Program"},{"name":"Genotype","category":"Data Type"},{"name":"Clinical Phenotype","category":"Data Type"},{"name":"dbGaP","category":"Study Registration"}],"_unique_id":"phs001024.v6.p1.c1","study_id":"phs001024.v6.p1.c1","study_description":"This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed) Whole Genome Sequencing Program. TOPMed is part of a broader Precision Medicine Initiative, which aims to provide disease treatments that are tailored to an individual's unique genes and environment. TOPMed will contribute to this initiative through the integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles, protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental, and clinical data. In doing so, this program aims to uncover factors that increase or decrease the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized treatments. Two genotype call sets derived from WGS are now available, Freeze 9b (GRCh38) and Freeze 10b (GRCh38), with largely overlapping sample sets. Information about how to identify other TOPMed WGS accessions for cross-study analysis, as well as descriptions of TOPMed methods of data acquisition, data processing and quality control, are provided in the accompanying documents, \"TOPMed Whole Genome Sequencing Project - Freeze 9b, Phases 1-4\" and \"TOPMed Whole Genome Sequencing Project - Freeze 10b, Phases 1-8\". Please check the study list at the top of each of these methods documents to determine whether it applies to this study accession. The Atrial Fibrillation Genetics Consortium (AFGen) was organized to identify common and rare genetic variation associated with atrial fibrillation risk. In the current study, we have performed whole genome sequencing in cases with early-onset atrial fibrillation. Samples in this study were enrolled as a part of the Partners HealthCare Biobank. Cases with early-onset atrial fibrillation were identified from the Biobank (defined as atrial fibrillation onset prior to 61 years and in the absence of structural heart disease). Study Design: Case Set Study Type: Case Set dbGaP estimated ancestry using GRAF-pop Total number of consented subjects: 128 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"NHLBI TOPMed: Partners HealthCare Biobank","short_name":"PARTNERS_HMB","commons":"BioData Catalyst","study_url":"https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001024.v6.p1","_subjects_count":128,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs001032.v6.p2.c1":{"gen3_discovery":{"authz":"/programs/topmed/projects/VU_AF_GRU-IRB","tags":[{"name":"TOPMed","category":"Program"},{"name":"Genotype","category":"Data Type"},{"name":"dbGaP","category":"Study Registration"}],"_unique_id":"phs001032.v6.p2.c1","study_id":"phs001032.v6.p2.c1","study_description":"This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed) Whole Genome Sequencing Program. TOPMed is part of a broader Precision Medicine Initiative, which aims to provide disease treatments that are tailored to an individual's unique genes and environment. TOPMed will contribute to this initiative through the integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles, protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental, and clinical data. In doing so, this program aims to uncover factors that increase or decrease the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized treatments. Two genotype call sets derived from WGS are now available, Freeze 8 (GRCh38) and Freeze 9b (GRCh38), with largely overlapping sample sets. Information about how to identify other TOPMed WGS accessions for cross-study analysis, as well as descriptions of TOPMed methods of data acquisition, data processing and quality control, are provided in the accompanying documents, \"TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4\" and \"TOPMed Whole Genome Sequencing Project - Freeze 9b, Phases 1-4\". Please check the study list at the top of each of these methods documents to determine whether it applies to this study accession. The Vanderbilt Atrial Fibrillation (AF) Registry was founded in 2001. Patients with AF and family members are prospectively enrolled. At enrollment a detailed past medical history is obtained along with an AF symptom severity assessment. Blood samples are obtained for DNA extraction. Patients are followed longitudinally along with serial collection of AF symptom severity assessments. Study Design: Case Set Study Type: Case Set dbGaP estimated ancestry using GRAF-pop Total number of consented subjects: 1134 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"NHLBI TOPMed: The Vanderbilt Atrial Fibrillation Registry (VU_AF)","short_name":"VU_AF_GRU-IRB","commons":"BioData Catalyst","study_url":"https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001032.v6.p2","_subjects_count":1134,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs001040.v5.p1.c1":{"gen3_discovery":{"authz":"","tags":[],"_unique_id":"phs001040.v5.p1.c1","study_id":"phs001040.v5.p1.c1","study_description":"","full_name":"","short_name":"","commons":"BioData Catalyst","study_url":"","_subjects_count":0,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs001040.v6.p1.c1":{"gen3_discovery":{"authz":"/programs/topmed/projects/WGHS_HMB","tags":[{"name":"TOPMed","category":"Program"},{"name":"Genotype","category":"Data Type"},{"name":"Clinical Phenotype","category":"Data Type"},{"name":"dbGaP","category":"Study Registration"}],"_unique_id":"phs001040.v6.p1.c1","study_id":"phs001040.v6.p1.c1","study_description":"This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed) Whole Genome Sequencing Program. TOPMed is part of a broader Precision Medicine Initiative, which aims to provide disease treatments that are tailored to an individual's unique genes and environment. TOPMed will contribute to this initiative through the integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles, protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental, and clinical data. In doing so, this program aims to uncover factors that increase or decrease the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized treatments. Two genotype call sets derived from WGS are now available, Freeze 9b (GRCh38) and Freeze 10b (GRCh38), with largely overlapping sample sets. Information about how to identify other TOPMed WGS accessions for cross-study analysis, as well as descriptions of TOPMed methods of data acquisition, data processing and quality control, are provided in the accompanying documents, \"TOPMed Whole Genome Sequencing Project - Freeze 9b, Phases 1-4\" and \"TOPMed Whole Genome Sequencing Project - Freeze 10b, Phases 1-8\". Please check the study list at the top of each of these methods documents to determine whether it applies to this study accession. The Women's Genome Health Study (WGHS) is a prospective cohort comprised of over 25,000 initially healthy female health professionals enrolled in the Women's Health Study, which began in 1992-1994. All participants in WGHS provided baseline blood samples and extensive survey data. Women who reported atrial fibrillation during the course of the study were asked to report diagnoses of AF at baseline, 48 months, and then annually thereafter. Participants enrolled in the continued observational follow-up who reported an incident AF event on at least one yearly questionnaire were sent an additional questionnaire to confirm the episode and to collect additional information. They were also asked for permission to review their medical records, particularly available ECGs, rhythm strips, 24-hour ECGs, and information on cardiac structure and function. For all deceased participants who reported AF during the trial and extended follow-up period, family members were contacted to obtain consent and additional relevant information. An end-point committee of physicians reviewed medical records for reported events according to predefined criteria. An incident AF event was confirmed if there was ECG evidence of AF or if a medical report clearly indicated a personal history of AF. The earliest date in the medical records when documentation was believed to have occurred was set as the date of onset of AF. Study Design: Case Set Study Type: Case Set dbGaP estimated ancestry using GRAF-pop Total number of consented subjects: 118 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"NHLBI TOPMed: Novel Risk Factors for the Development of Atrial Fibrillation in Women","short_name":"WGHS_HMB","commons":"BioData Catalyst","study_url":"https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001040.v6.p1","_subjects_count":117,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs001058.v1.p1.c1":{"gen3_discovery":{"authz":"/programs/heartfailure/projects/MiGEN_EXS_BIOIMAGE_DS-CVD","tags":[],"_unique_id":"phs001058.v1.p1.c1","study_id":"phs001058.v1.p1.c1","study_description":"The BioImage Study (BioImage Study: A Clinical Study of Burden of Atherosclerotic Disease in an At-Risk Population, NCT00738725), is a prospective, observational study aimed at characterizing subclinical atherosclerosis in U.S. adults (55 to 80 years old) at risk for clinical atherosclerotic cardiovascular disease (PMID: 25790876). All exome sequencing was performed at the Broad Institute of Harvard and MIT; samples sequence capture was performed using Illumina's ICE Capture reagent and sequencing was performed on an Illumina HiSeq 2000 or 2500. Study Design: Case-Control Study Type: Case-Control dbGaP estimated ancestry using GRAF-pop Total number of consented subjects: 503 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Myocardial Infarction Genetics Exome Sequencing Consortium: BioImage Study","short_name":"MiGEN_EXS_BIOIMAGE_DS-CVD","commons":"BioData Catalyst","study_url":"","_subjects_count":503,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs001062.v5.p2.c1":{"gen3_discovery":{"authz":"/programs/topmed/projects/MGH_AF_HMB-IRB","tags":[{"name":"TOPMed","category":"Program"},{"name":"Genotype","category":"Data Type"},{"name":"dbGaP","category":"Study Registration"}],"_unique_id":"phs001062.v5.p2.c1","study_id":"phs001062.v5.p2.c1","study_description":"This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed) Whole Genome Sequencing Program. TOPMed is part of a broader Precision Medicine Initiative, which aims to provide disease treatments that are tailored to an individual's unique genes and environment. TOPMed will contribute to this initiative through the integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles, protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental, and clinical data. In doing so, this program aims to uncover factors that increase or decrease the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized treatments. Two genotype call sets derived from WGS are now available, Freeze 8 (GRCh38) and Freeze 9b (GRCh38), with largely overlapping sample sets. Information about how to identify other TOPMed WGS accessions for cross-study analysis, as well as descriptions of TOPMed methods of data acquisition, data processing and quality control, are provided in the accompanying documents, \"TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4\" and \"TOPMed Whole Genome Sequencing Project - Freeze 9b, Phases 1-4\". Please check the study list at the top of each of these methods documents to determine whether it applies to this study accession. The Massachusetts General Hospital (MGH) Atrial Fibrillation Study was initiated in 2001. The study has enrolled serial probands, unaffected and affected family members with atrial fibrillation. At enrollment participants undergo a structured interview to systematically capture their past medical history, AF treatments, and family history. An electrocardiogram is performed; the results of an echocardiogram are obtained; and blood samples are obtained. For the TOPMed WGS project only early-onset atrial fibrillation cases were sequenced. Early-onset atrial fibrillation was defined as an age of onset prior to 66 years of age. Comprehensive phenotypic and pedigree data for study participants are available through dbGaP phs001001. Study Design: Case Set Study Type: Case Set dbGaP estimated ancestry using GRAF-pop Total number of consented subjects: 1163 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"NHLBI TOPMed - NHGRI CCDG: Massachusetts General Hospital (MGH) Atrial Fibrillation Study","short_name":"MGH_AF_HMB-IRB","commons":"BioData Catalyst","study_url":"https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001062.v5.p2","_subjects_count":908,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs001062.v5.p2.c2":{"gen3_discovery":{"authz":"/programs/topmed/projects/MGH_AF_DS-AF-IRB-RD","tags":[{"name":"TOPMed","category":"Program"},{"name":"Genotype","category":"Data Type"},{"name":"dbGaP","category":"Study Registration"}],"_unique_id":"phs001062.v5.p2.c2","study_id":"phs001062.v5.p2.c2","study_description":"This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed) Whole Genome Sequencing Program. TOPMed is part of a broader Precision Medicine Initiative, which aims to provide disease treatments that are tailored to an individual's unique genes and environment. TOPMed will contribute to this initiative through the integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles, protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental, and clinical data. In doing so, this program aims to uncover factors that increase or decrease the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized treatments. Two genotype call sets derived from WGS are now available, Freeze 8 (GRCh38) and Freeze 9b (GRCh38), with largely overlapping sample sets. Information about how to identify other TOPMed WGS accessions for cross-study analysis, as well as descriptions of TOPMed methods of data acquisition, data processing and quality control, are provided in the accompanying documents, \"TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4\" and \"TOPMed Whole Genome Sequencing Project - Freeze 9b, Phases 1-4\". Please check the study list at the top of each of these methods documents to determine whether it applies to this study accession. The Massachusetts General Hospital (MGH) Atrial Fibrillation Study was initiated in 2001. The study has enrolled serial probands, unaffected and affected family members with atrial fibrillation. At enrollment participants undergo a structured interview to systematically capture their past medical history, AF treatments, and family history. An electrocardiogram is performed; the results of an echocardiogram are obtained; and blood samples are obtained. For the TOPMed WGS project only early-onset atrial fibrillation cases were sequenced. Early-onset atrial fibrillation was defined as an age of onset prior to 66 years of age. Comprehensive phenotypic and pedigree data for study participants are available through dbGaP phs001001. Study Design: Case Set Study Type: Case Set dbGaP estimated ancestry using GRAF-pop Total number of consented subjects: 1163 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"NHLBI TOPMed - NHGRI CCDG: Massachusetts General Hospital (MGH) Atrial Fibrillation Study","short_name":"MGH_AF_DS-AF-IRB-RD","commons":"BioData Catalyst","study_url":"https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001062.v5.p2","_subjects_count":255,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs001069.v2.p2.c1":{"gen3_discovery":{"authz":"/programs/substudy/projects/MIGen_JHS_HMB-IRB-NPU","tags":[],"_unique_id":"phs001069.v2.p2.c1","study_id":"phs001069.v2.p2.c1","study_description":"This sub-study phs001069 MIGen JHS contains sample phenotype and sequence data of subjects available from the phs001069 study. Summary level phenotypes for the NHLBI JHS Cohort study participants can be viewed at the top-level study page phs000286 JHS Cohort. Individual level data and sequence data for all JHS Cohort top-level study and substudies are available by requesting Authorized Access to the NHLBI JHS Cohort phs000286 study. The Jackson Heart Study (JHS) is a large, community-based, observational study whose participants were recruited from urban and rural areas of the three counties (Hinds, Madison and Rankin) that make up the Jackson, Mississippi, metropolitan statistical area (MSA). Participants were enrolled from each of the 4 recruitment pools: (1) random, 17%, (2) volunteer, 30%, (3) currently enrolled in the Atherosclerosis Risk in Communities (ARIC) Study, 31%, and (4) secondary family members, 22%. Recruitment was limited to non-institutionalized adult African Americans 35-84 years old, except in the family cohort where those 21 to 34 years of age were eligible. The final cohort of 5,301 participants includes 6.59% of all African American Jackson MSA residents aged 35-84 (N-76,426, US Census 2000). Major components of each exam include medical history, physical examination, blood/urine analytes and interview questions on areas such as: physical activity; stress, coping and spirituality; racism and discrimination; socioeconomic position; and access to health care. At 12-month intervals after the baseline clinic visit (Exam 1), participants are contacted by telephone to: update information; confirm vital statistics; document interim medical events, hospitalizations, and functional status; and obtain additional sociocultural information. Questions about medical events, symptoms of cardiovascular disease and functional status are repeated annually. Ongoing cohort surveillance includes abstraction of medical records and death certificates for relevant International Classification of Diseases (ICD) codes and adjudication of nonfatal events and deaths. All exome sequencing was performed at the Broad Institute of MIT and Harvard. Sample sequence capture was performed using Agilent SureSelect Human All Exon Kit v2 and sequencing was performed on an Illumina HiSeq 2000 or 2500. Study Weblinks: Jackson Heart Study ARIC Study Study Design: Control Set Study Type: Control Set Total number of consented subjects: 1065 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Myocardial Infarction Genetics Exome Sequencing Consortium: Jackson Heart Study","short_name":"MIGen_JHS_HMB-IRB-NPU","commons":"BioData Catalyst","study_url":"","_subjects_count":208,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs001069.v2.p2.c2":{"gen3_discovery":{"authz":"/programs/substudy/projects/MIGen_JHS_DS-FDO-IRB-NPU","tags":[],"_unique_id":"phs001069.v2.p2.c2","study_id":"phs001069.v2.p2.c2","study_description":"This sub-study phs001069 MIGen JHS contains sample phenotype and sequence data of subjects available from the phs001069 study. Summary level phenotypes for the NHLBI JHS Cohort study participants can be viewed at the top-level study page phs000286 JHS Cohort. Individual level data and sequence data for all JHS Cohort top-level study and substudies are available by requesting Authorized Access to the NHLBI JHS Cohort phs000286 study. The Jackson Heart Study (JHS) is a large, community-based, observational study whose participants were recruited from urban and rural areas of the three counties (Hinds, Madison and Rankin) that make up the Jackson, Mississippi, metropolitan statistical area (MSA). Participants were enrolled from each of the 4 recruitment pools: (1) random, 17%, (2) volunteer, 30%, (3) currently enrolled in the Atherosclerosis Risk in Communities (ARIC) Study, 31%, and (4) secondary family members, 22%. Recruitment was limited to non-institutionalized adult African Americans 35-84 years old, except in the family cohort where those 21 to 34 years of age were eligible. The final cohort of 5,301 participants includes 6.59% of all African American Jackson MSA residents aged 35-84 (N-76,426, US Census 2000). Major components of each exam include medical history, physical examination, blood/urine analytes and interview questions on areas such as: physical activity; stress, coping and spirituality; racism and discrimination; socioeconomic position; and access to health care. At 12-month intervals after the baseline clinic visit (Exam 1), participants are contacted by telephone to: update information; confirm vital statistics; document interim medical events, hospitalizations, and functional status; and obtain additional sociocultural information. Questions about medical events, symptoms of cardiovascular disease and functional status are repeated annually. Ongoing cohort surveillance includes abstraction of medical records and death certificates for relevant International Classification of Diseases (ICD) codes and adjudication of nonfatal events and deaths. All exome sequencing was performed at the Broad Institute of MIT and Harvard. Sample sequence capture was performed using Agilent SureSelect Human All Exon Kit v2 and sequencing was performed on an Illumina HiSeq 2000 or 2500. Study Weblinks: Jackson Heart Study ARIC Study Study Design: Control Set Study Type: Control Set Total number of consented subjects: 1065 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Myocardial Infarction Genetics Exome Sequencing Consortium: Jackson Heart Study","short_name":"MIGen_JHS_DS-FDO-IRB-NPU","commons":"BioData Catalyst","study_url":"","_subjects_count":63,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs001069.v2.p2.c3":{"gen3_discovery":{"authz":"/programs/substudy/projects/MIGen_JHS_HMB-IRB","tags":[],"_unique_id":"phs001069.v2.p2.c3","study_id":"phs001069.v2.p2.c3","study_description":"This sub-study phs001069 MIGen JHS contains sample phenotype and sequence data of subjects available from the phs001069 study. Summary level phenotypes for the NHLBI JHS Cohort study participants can be viewed at the top-level study page phs000286 JHS Cohort. Individual level data and sequence data for all JHS Cohort top-level study and substudies are available by requesting Authorized Access to the NHLBI JHS Cohort phs000286 study. The Jackson Heart Study (JHS) is a large, community-based, observational study whose participants were recruited from urban and rural areas of the three counties (Hinds, Madison and Rankin) that make up the Jackson, Mississippi, metropolitan statistical area (MSA). Participants were enrolled from each of the 4 recruitment pools: (1) random, 17%, (2) volunteer, 30%, (3) currently enrolled in the Atherosclerosis Risk in Communities (ARIC) Study, 31%, and (4) secondary family members, 22%. Recruitment was limited to non-institutionalized adult African Americans 35-84 years old, except in the family cohort where those 21 to 34 years of age were eligible. The final cohort of 5,301 participants includes 6.59% of all African American Jackson MSA residents aged 35-84 (N-76,426, US Census 2000). Major components of each exam include medical history, physical examination, blood/urine analytes and interview questions on areas such as: physical activity; stress, coping and spirituality; racism and discrimination; socioeconomic position; and access to health care. At 12-month intervals after the baseline clinic visit (Exam 1), participants are contacted by telephone to: update information; confirm vital statistics; document interim medical events, hospitalizations, and functional status; and obtain additional sociocultural information. Questions about medical events, symptoms of cardiovascular disease and functional status are repeated annually. Ongoing cohort surveillance includes abstraction of medical records and death certificates for relevant International Classification of Diseases (ICD) codes and adjudication of nonfatal events and deaths. All exome sequencing was performed at the Broad Institute of MIT and Harvard. Sample sequence capture was performed using Agilent SureSelect Human All Exon Kit v2 and sequencing was performed on an Illumina HiSeq 2000 or 2500. Study Weblinks: Jackson Heart Study ARIC Study Study Design: Control Set Study Type: Control Set Total number of consented subjects: 1065 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Myocardial Infarction Genetics Exome Sequencing Consortium: Jackson Heart Study","short_name":"MIGen_JHS_HMB-IRB","commons":"BioData Catalyst","study_url":"","_subjects_count":649,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs001069.v2.p2.c4":{"gen3_discovery":{"authz":"/programs/substudy/projects/MIGen_JHS_DS-FDO-IRB","tags":[],"_unique_id":"phs001069.v2.p2.c4","study_id":"phs001069.v2.p2.c4","study_description":"This sub-study phs001069 MIGen JHS contains sample phenotype and sequence data of subjects available from the phs001069 study. Summary level phenotypes for the NHLBI JHS Cohort study participants can be viewed at the top-level study page phs000286 JHS Cohort. Individual level data and sequence data for all JHS Cohort top-level study and substudies are available by requesting Authorized Access to the NHLBI JHS Cohort phs000286 study. The Jackson Heart Study (JHS) is a large, community-based, observational study whose participants were recruited from urban and rural areas of the three counties (Hinds, Madison and Rankin) that make up the Jackson, Mississippi, metropolitan statistical area (MSA). Participants were enrolled from each of the 4 recruitment pools: (1) random, 17%, (2) volunteer, 30%, (3) currently enrolled in the Atherosclerosis Risk in Communities (ARIC) Study, 31%, and (4) secondary family members, 22%. Recruitment was limited to non-institutionalized adult African Americans 35-84 years old, except in the family cohort where those 21 to 34 years of age were eligible. The final cohort of 5,301 participants includes 6.59% of all African American Jackson MSA residents aged 35-84 (N-76,426, US Census 2000). Major components of each exam include medical history, physical examination, blood/urine analytes and interview questions on areas such as: physical activity; stress, coping and spirituality; racism and discrimination; socioeconomic position; and access to health care. At 12-month intervals after the baseline clinic visit (Exam 1), participants are contacted by telephone to: update information; confirm vital statistics; document interim medical events, hospitalizations, and functional status; and obtain additional sociocultural information. Questions about medical events, symptoms of cardiovascular disease and functional status are repeated annually. Ongoing cohort surveillance includes abstraction of medical records and death certificates for relevant International Classification of Diseases (ICD) codes and adjudication of nonfatal events and deaths. All exome sequencing was performed at the Broad Institute of MIT and Harvard. Sample sequence capture was performed using Agilent SureSelect Human All Exon Kit v2 and sequencing was performed on an Illumina HiSeq 2000 or 2500. Study Weblinks: Jackson Heart Study ARIC Study Study Design: Control Set Study Type: Control Set Total number of consented subjects: 1065 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Myocardial Infarction Genetics Exome Sequencing Consortium: Jackson Heart Study","short_name":"MIGen_JHS_DS-FDO-IRB","commons":"BioData Catalyst","study_url":"","_subjects_count":145,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs001074.v1.p1.c2":{"gen3_discovery":{"authz":"/programs/parent/projects/GeneSTAR_DS-CVD-IRB-NPU-RD_","tags":[{"name":"Parent","category":"Program"},{"name":"Clinical Phenotype","category":"Data Type"},{"name":"dbGaP","category":"Study Registration"}],"_unique_id":"phs001074.v1.p1.c2","study_id":"phs001074.v1.p1.c2","study_description":"The causal mechanisms of common diseases and their therapies have been only marginally illuminated by genetic variants identified in genome wide association studies (GWAS) utilizing single nucleotide polymorphism (SNPs). Platelet activation pathways reflecting hemostasis and thrombosis are the underlying substrate for many cardiovascular diseases and related acute events. To overcome GWAS limitations, genomic studies are needed that integrate molecular surrogates for platelet-related phenotypes assayed in cell-based models derived from individuals of known genotypes and phenotypes. In our GWAS study of native platelet aggregation phenotypes and aggregation in response to low dose aspirin in 2200 subjects (GeneSTAR, Genetic Study of Aspirin Responsiveness), important genome wide \"signals\" (p<5x10-8) associated with native platelet aggregation and important \"signals\" associated with platelet responsiveness to aspirin were identified and replicated. Although we are currently performing functional genomics studies to elucidate our most promising findings in known genes (PEAR1, MET, PIKC3G), most \"signals\" occurred in intergenic regions or in introns. Mechanistic interpretation is limited by uncertainty as to which gene(s) are up- or down-regulated in the presence of most SNP modifications. In this 3 phase proposal, we will (1) create pluripotent stem cells (iPS) from peripheral blood mononuclear cells, and then differentiate these stem cells into megakaryocytes (2) develop an efficient strategy to produce iPS and megakaryocytes using a novel pooling method, and (3) produce iPS and megakaryocytes from 250 subjects in GeneSTAR (European Americans and African Americans), selected based on specific hypotheses derived from GWAS signals in native and post aspirin platelet function; characterize genetic mRNA transcripts using a comprehensive Affymetrix array; measure protein expression for transcripts of interest using mass spectrometry; examine mRNA and protein expression patterns for each GWAS signal to determine the functional pathway(s) involved in native platelet phenotypes; and examine the functional genomics of variations in responsiveness to aspirin using our prior genotyped and phenotyped population. Precise information about the exact functional processes in megakaryocytes and platelets may lead to innovative and tailored approaches to risk assessment and novel therapeutic targets to prevent first and recurrent cardiovascular and related thrombotic events. Study Weblinks: GeneSTAR Research Center, Genetic Studies of Atherosclerosis Risk Study Design: Prospective Longitudinal Cohort Study Type: Longitudinal Cohort Family dbGaP estimated ancestry using GRAF-pop Total number of consented subjects: 250 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"GeneSTAR (Genetic Study of Atherosclerosis Risk) NextGen Consortium: Functional Genomics of Platelet Aggregation Using iPS and Derived Megakaryocytes","short_name":"GeneSTAR_DS-CVD-IRB-NPU-RD_","commons":"BioData Catalyst","study_url":"https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001074.v1.p1","_subjects_count":250,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs001098.v3.p2.c1":{"gen3_discovery":{"authz":"/programs/substudy/projects/T2D_GENES_Exome_Seq_JHS_HMB-IRB-NPU","tags":[],"_unique_id":"phs001098.v3.p2.c1","study_id":"phs001098.v3.p2.c1","study_description":"This sub-study phs001098 T2D GENES Exome Seq contains genotype derived from sequence data and selected phenotype of subjects available from the phs001098 study. Summary level phenotypes for the NHLBI JHS Cohort study participants can be viewed at the top-level study page phs000286 JHS Cohort. Individual level phenotype data and molecular data for all JHS Cohort top-level study and substudies are available by requesting Authorized Access to the NHLBI JHS Cohort phs000286 study. T2D-GENES (Type 2 Diabetes Genetic Exploration by Next-generation sequencing in multi-Ethnic Samples) is an NIDDK-funded international research consortium which seeks to identify genetic variants for type 2 diabetes (T2D) through multiethnic sequencing studies. T2D-GENES Project 1 is a multi-ethnic sequencing study designed to assess whether less common variants play a role in T2D risk and to assess similarities and differences in the distribution of T2D risk variants across ancestry groups. The individuals were obtained from 14 cohorts that are listed in Table 1. The strategy was to perform deep exome sequencing of 12,940 individuals, 6,504 with T2D and 6,436 controls, divided among five ancestry groups: Europeans, East Asians, South Asians, American Hispanics, and African Americans. Sequencing was performed at the Broad Institute using the Agilent v2 capture reagent on Illumina HiSeq machines. Please note that while we summarize the full sample list in publications and below, the Kooperative Gesundheitsforschung in der Region Augsburg (KORA) study does not have a substudy, as it is not consented to be deposited in dbGaP. Table 1. T2D-GENES Whole Exome Sequencing Studies Ancestry Study Countries of Origin # Cases # Controls African American Jackson Heart Study US 502 527 African American Wake Forest School of Medicine Study US 518 532 East Asian Korea Association Research Project Korea 526 561 East Asian Singapore Diabetes Cohort Study; Singapore Prospective Study Program Singapore (Chinese) 486 592 European Ashkenazi US, Israel 506 352 European Metabolic Syndrome in Men Study (METSIM) Finland 484 498 European Finland-United States Investigation of NIDDM Genetics (FUSION) Study Finland 472 476 European Kooperative Gesundheitsforschung in der Region Augsburg (KORA) Germany 97 90 European UK Type 2 Diabetes Genetics Consortium (UKT2D) UK 322 320 European Malmo-Botnia Study Finland, Sweden 478 443 Hispanic San Antonio Family Heart Study, San Antonio Family Diabetes/Gallbladder Study, Veterans Administration Genetic Epidemiology Study, and the Investigation of Nephropathy and Diabetes Study Family Component US 272 219 Hispanic Starr County, Texas US 749 704 South Asian London Life Sciences Population Study (LOLIPOP) UK (Indian Asian) 530 538 South Asian Singapore Indian Eye Study Singapore (Indian Asian) 563 585 The Jackson Heart Study contributed 502 cases and 527 controls to T2D-GENES Project 1. Study Weblinks: T2D-GENES Consortium Type 2 Diabetes Genetics Study Design: Case-Control Study Type: Case-Control dbGaP estimated ancestry using GRAF-pop Total number of consented subjects: 1029 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Type 2 Diabetes Genetic Exploration by Next-Generation Sequencing in Multi-Ethnic Samples (T2D-GENES) Project 1: Jackson Heart Study","short_name":"T2D_GENES_Exome_Seq_JHS_HMB-IRB-NPU","commons":"BioData Catalyst","study_url":"","_subjects_count":267,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs001098.v3.p2.c2":{"gen3_discovery":{"authz":"/programs/substudy/projects/T2D_GENES_Exome_Seq_JHS_DS-FDO-IRB-NPU","tags":[],"_unique_id":"phs001098.v3.p2.c2","study_id":"phs001098.v3.p2.c2","study_description":"This sub-study phs001098 T2D GENES Exome Seq contains genotype derived from sequence data and selected phenotype of subjects available from the phs001098 study. Summary level phenotypes for the NHLBI JHS Cohort study participants can be viewed at the top-level study page phs000286 JHS Cohort. Individual level phenotype data and molecular data for all JHS Cohort top-level study and substudies are available by requesting Authorized Access to the NHLBI JHS Cohort phs000286 study. T2D-GENES (Type 2 Diabetes Genetic Exploration by Next-generation sequencing in multi-Ethnic Samples) is an NIDDK-funded international research consortium which seeks to identify genetic variants for type 2 diabetes (T2D) through multiethnic sequencing studies. T2D-GENES Project 1 is a multi-ethnic sequencing study designed to assess whether less common variants play a role in T2D risk and to assess similarities and differences in the distribution of T2D risk variants across ancestry groups. The individuals were obtained from 14 cohorts that are listed in Table 1. The strategy was to perform deep exome sequencing of 12,940 individuals, 6,504 with T2D and 6,436 controls, divided among five ancestry groups: Europeans, East Asians, South Asians, American Hispanics, and African Americans. Sequencing was performed at the Broad Institute using the Agilent v2 capture reagent on Illumina HiSeq machines. Please note that while we summarize the full sample list in publications and below, the Kooperative Gesundheitsforschung in der Region Augsburg (KORA) study does not have a substudy, as it is not consented to be deposited in dbGaP. Table 1. T2D-GENES Whole Exome Sequencing Studies Ancestry Study Countries of Origin # Cases # Controls African American Jackson Heart Study US 502 527 African American Wake Forest School of Medicine Study US 518 532 East Asian Korea Association Research Project Korea 526 561 East Asian Singapore Diabetes Cohort Study; Singapore Prospective Study Program Singapore (Chinese) 486 592 European Ashkenazi US, Israel 506 352 European Metabolic Syndrome in Men Study (METSIM) Finland 484 498 European Finland-United States Investigation of NIDDM Genetics (FUSION) Study Finland 472 476 European Kooperative Gesundheitsforschung in der Region Augsburg (KORA) Germany 97 90 European UK Type 2 Diabetes Genetics Consortium (UKT2D) UK 322 320 European Malmo-Botnia Study Finland, Sweden 478 443 Hispanic San Antonio Family Heart Study, San Antonio Family Diabetes/Gallbladder Study, Veterans Administration Genetic Epidemiology Study, and the Investigation of Nephropathy and Diabetes Study Family Component US 272 219 Hispanic Starr County, Texas US 749 704 South Asian London Life Sciences Population Study (LOLIPOP) UK (Indian Asian) 530 538 South Asian Singapore Indian Eye Study Singapore (Indian Asian) 563 585 The Jackson Heart Study contributed 502 cases and 527 controls to T2D-GENES Project 1. Study Weblinks: T2D-GENES Consortium Type 2 Diabetes Genetics Study Design: Case-Control Study Type: Case-Control dbGaP estimated ancestry using GRAF-pop Total number of consented subjects: 1029 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Type 2 Diabetes Genetic Exploration by Next-Generation Sequencing in Multi-Ethnic Samples (T2D-GENES) Project 1: Jackson Heart Study","short_name":"T2D_GENES_Exome_Seq_JHS_DS-FDO-IRB-NPU","commons":"BioData Catalyst","study_url":"","_subjects_count":42,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs001098.v3.p2.c3":{"gen3_discovery":{"authz":"/programs/substudy/projects/T2D_GENES_Exome_Seq_JHS_HMB-IRB","tags":[],"_unique_id":"phs001098.v3.p2.c3","study_id":"phs001098.v3.p2.c3","study_description":"This sub-study phs001098 T2D GENES Exome Seq contains genotype derived from sequence data and selected phenotype of subjects available from the phs001098 study. Summary level phenotypes for the NHLBI JHS Cohort study participants can be viewed at the top-level study page phs000286 JHS Cohort. Individual level phenotype data and molecular data for all JHS Cohort top-level study and substudies are available by requesting Authorized Access to the NHLBI JHS Cohort phs000286 study. T2D-GENES (Type 2 Diabetes Genetic Exploration by Next-generation sequencing in multi-Ethnic Samples) is an NIDDK-funded international research consortium which seeks to identify genetic variants for type 2 diabetes (T2D) through multiethnic sequencing studies. T2D-GENES Project 1 is a multi-ethnic sequencing study designed to assess whether less common variants play a role in T2D risk and to assess similarities and differences in the distribution of T2D risk variants across ancestry groups. The individuals were obtained from 14 cohorts that are listed in Table 1. The strategy was to perform deep exome sequencing of 12,940 individuals, 6,504 with T2D and 6,436 controls, divided among five ancestry groups: Europeans, East Asians, South Asians, American Hispanics, and African Americans. Sequencing was performed at the Broad Institute using the Agilent v2 capture reagent on Illumina HiSeq machines. Please note that while we summarize the full sample list in publications and below, the Kooperative Gesundheitsforschung in der Region Augsburg (KORA) study does not have a substudy, as it is not consented to be deposited in dbGaP. Table 1. T2D-GENES Whole Exome Sequencing Studies Ancestry Study Countries of Origin # Cases # Controls African American Jackson Heart Study US 502 527 African American Wake Forest School of Medicine Study US 518 532 East Asian Korea Association Research Project Korea 526 561 East Asian Singapore Diabetes Cohort Study; Singapore Prospective Study Program Singapore (Chinese) 486 592 European Ashkenazi US, Israel 506 352 European Metabolic Syndrome in Men Study (METSIM) Finland 484 498 European Finland-United States Investigation of NIDDM Genetics (FUSION) Study Finland 472 476 European Kooperative Gesundheitsforschung in der Region Augsburg (KORA) Germany 97 90 European UK Type 2 Diabetes Genetics Consortium (UKT2D) UK 322 320 European Malmo-Botnia Study Finland, Sweden 478 443 Hispanic San Antonio Family Heart Study, San Antonio Family Diabetes/Gallbladder Study, Veterans Administration Genetic Epidemiology Study, and the Investigation of Nephropathy and Diabetes Study Family Component US 272 219 Hispanic Starr County, Texas US 749 704 South Asian London Life Sciences Population Study (LOLIPOP) UK (Indian Asian) 530 538 South Asian Singapore Indian Eye Study Singapore (Indian Asian) 563 585 The Jackson Heart Study contributed 502 cases and 527 controls to T2D-GENES Project 1. Study Weblinks: T2D-GENES Consortium Type 2 Diabetes Genetics Study Design: Case-Control Study Type: Case-Control dbGaP estimated ancestry using GRAF-pop Total number of consented subjects: 1029 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Type 2 Diabetes Genetic Exploration by Next-Generation Sequencing in Multi-Ethnic Samples (T2D-GENES) Project 1: Jackson Heart Study","short_name":"T2D_GENES_Exome_Seq_JHS_HMB-IRB","commons":"BioData Catalyst","study_url":"","_subjects_count":586,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs001098.v3.p2.c4":{"gen3_discovery":{"authz":"/programs/substudy/projects/T2D_GENES_Exome_Seq_JHS_DS-FDO-IRB","tags":[],"_unique_id":"phs001098.v3.p2.c4","study_id":"phs001098.v3.p2.c4","study_description":"This sub-study phs001098 T2D GENES Exome Seq contains genotype derived from sequence data and selected phenotype of subjects available from the phs001098 study. Summary level phenotypes for the NHLBI JHS Cohort study participants can be viewed at the top-level study page phs000286 JHS Cohort. Individual level phenotype data and molecular data for all JHS Cohort top-level study and substudies are available by requesting Authorized Access to the NHLBI JHS Cohort phs000286 study. T2D-GENES (Type 2 Diabetes Genetic Exploration by Next-generation sequencing in multi-Ethnic Samples) is an NIDDK-funded international research consortium which seeks to identify genetic variants for type 2 diabetes (T2D) through multiethnic sequencing studies. T2D-GENES Project 1 is a multi-ethnic sequencing study designed to assess whether less common variants play a role in T2D risk and to assess similarities and differences in the distribution of T2D risk variants across ancestry groups. The individuals were obtained from 14 cohorts that are listed in Table 1. The strategy was to perform deep exome sequencing of 12,940 individuals, 6,504 with T2D and 6,436 controls, divided among five ancestry groups: Europeans, East Asians, South Asians, American Hispanics, and African Americans. Sequencing was performed at the Broad Institute using the Agilent v2 capture reagent on Illumina HiSeq machines. Please note that while we summarize the full sample list in publications and below, the Kooperative Gesundheitsforschung in der Region Augsburg (KORA) study does not have a substudy, as it is not consented to be deposited in dbGaP. Table 1. T2D-GENES Whole Exome Sequencing Studies Ancestry Study Countries of Origin # Cases # Controls African American Jackson Heart Study US 502 527 African American Wake Forest School of Medicine Study US 518 532 East Asian Korea Association Research Project Korea 526 561 East Asian Singapore Diabetes Cohort Study; Singapore Prospective Study Program Singapore (Chinese) 486 592 European Ashkenazi US, Israel 506 352 European Metabolic Syndrome in Men Study (METSIM) Finland 484 498 European Finland-United States Investigation of NIDDM Genetics (FUSION) Study Finland 472 476 European Kooperative Gesundheitsforschung in der Region Augsburg (KORA) Germany 97 90 European UK Type 2 Diabetes Genetics Consortium (UKT2D) UK 322 320 European Malmo-Botnia Study Finland, Sweden 478 443 Hispanic San Antonio Family Heart Study, San Antonio Family Diabetes/Gallbladder Study, Veterans Administration Genetic Epidemiology Study, and the Investigation of Nephropathy and Diabetes Study Family Component US 272 219 Hispanic Starr County, Texas US 749 704 South Asian London Life Sciences Population Study (LOLIPOP) UK (Indian Asian) 530 538 South Asian Singapore Indian Eye Study Singapore (Indian Asian) 563 585 The Jackson Heart Study contributed 502 cases and 527 controls to T2D-GENES Project 1. Study Weblinks: T2D-GENES Consortium Type 2 Diabetes Genetics Study Design: Case-Control Study Type: Case-Control dbGaP estimated ancestry using GRAF-pop Total number of consented subjects: 1029 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Type 2 Diabetes Genetic Exploration by Next-Generation Sequencing in Multi-Ethnic Samples (T2D-GENES) Project 1: Jackson Heart Study","short_name":"T2D_GENES_Exome_Seq_JHS_DS-FDO-IRB","commons":"BioData Catalyst","study_url":"","_subjects_count":134,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs001101.v1.p1.c1":{"gen3_discovery":{"authz":"/programs/heartfailure/projects/MiGEN_EXS_MDC_HMB-MDS","tags":[],"_unique_id":"phs001101.v1.p1.c1","study_id":"phs001101.v1.p1.c1","study_description":"The Malmo Diet and Cancer Study (MDCS) is a community-based prospective epidemiologic cohort of 28,449 subjects who were recruited for baseline examination between 1991 and 1996. From this cohort, 6103 subjects were randomly selected to participate in a cardiovascular cohort (MDCSCC), which seeks to investigate risk factors for cardiovascular disease. This study is a subset of those samples. All exome sequencing was performed at the Broad Institute of Harvard and MIT; samples sequence capture was performed using Illumina's ICE Capture reagent and sequencing was performed on an Illumina HiSeq 2000 or 2500. Study Design: Case-Control Study Type: Case-Control dbGaP estimated ancestry using GRAF-pop Total number of consented subjects: 1081 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Myocardial Infarction Genetics Exome Sequencing Consortium: Malmo Diet and Cancer Study","short_name":"MiGEN_EXS_MDC_HMB-MDS","commons":"BioData Catalyst","study_url":"","_subjects_count":1081,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs001143.v4.p1.c1":{"gen3_discovery":{"authz":"/programs/topmed/projects/BAGS_GRU-IRB","tags":[{"name":"TOPMed","category":"Program"},{"name":"Genotype","category":"Data Type"},{"name":"Clinical Phenotype","category":"Data Type"},{"name":"dbGaP","category":"Study Registration"}],"_unique_id":"phs001143.v4.p1.c1","study_id":"phs001143.v4.p1.c1","study_description":"This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed) Whole Genome Sequencing Program. TOPMed is part of a broader Precision Medicine Initiative, which aims to provide disease treatments that are tailored to an individual's unique genes and environment. TOPMed will contribute to this initiative through the integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles, protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental, and clinical data. In doing so, this program aims to uncover factors that increase or decrease the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized treatments. Two genotype call sets derived from WGS are now available, Freeze 8 (GRCh38) and Freeze 9b (GRCh38), with largely overlapping sample sets. Information about how to identify other TOPMed WGS accessions for cross-study analysis, as well as descriptions of TOPMed methods of data acquisition, data processing and quality control, are provided in the accompanying documents, \"TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4\" and \"TOPMed Whole Genome Sequencing Project - Freeze 9b, Phases 1-4\". Please check the study list at the top of each of these methods documents to determine whether it applies to this study accession. Asthma is a complex disease where the interplay between genetic factors and environmental exposures influences susceptibility and disease prognosis. Asthmatics of African descent tend to have more severe asthma and more severe clinical symptoms than individuals of European ancestry. The baseline prevalence of asthma in Barbados is high (~20%), and from admixture analyses, we have determined that the proportion of African ancestry among Barbadian founders is similar to U.S. African Americans, rendering this a unique population to disentangle the genetic basis for asthma disparities among African ancestry populations in general. We therefore performed whole genome sequencing on 1,100 individuals from the Barbados Genetics of Asthma Study (BAGS), in order to generate additional discovery of rare and structural variants that may control risk to asthma. Study Design: Family/Twin/Trios Study Type: Family dbGaP estimated ancestry using GRAF-pop Total number of consented subjects: 1527 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"NHLBI TOPMed: The Genetics and Epidemiology of Asthma in Barbados","short_name":"BAGS_GRU-IRB","commons":"BioData Catalyst","study_url":"https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001143.v4.p1","_subjects_count":1003,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs001180.v2.p1.c2":{"gen3_discovery":{"authz":"/programs/parent/projects/GALAII_DS-LD-IRB-COL_","tags":[{"name":"Parent","category":"Program"},{"name":"Clinical Phenotype","category":"Data Type"},{"name":"dbGaP","category":"Study Registration"}],"_unique_id":"phs001180.v2.p1.c2","study_id":"phs001180.v2.p1.c2","study_description":"A case-control pharmacogenetic study of bronchodilator drug response among racially admixed Latino children with asthma. Each participant had two spirometry measurements using the KoKo PFT System. With the first spirometry test, participant was administered with 4 puffs of HFA Albuterol. The second albuterol measurement was based on age, for participants under 16 years of age, additional 2 puffs were administered and for those over 16 years of age, additional 4 puffs were administered. The overall goal is to identify genetic factors which are predictive of drug response in children with asthma. The principal tools include a questionnaire and biological specimen collection. Participants are 8-21 years old at time of recruitment. Children with asthma have physician-diagnosed asthma, symptoms and medications. The GALAII Study is utilized in the following dbGaP substudies. To view genotypes, analysis, other molecular data, and derived variables collected in these substudies, please click on the following substudies below or in the \"Substudies\" box located on the right hand side of this top-level study page phs001180 GALAII Study. phs001274phs001274 GALAII GWAS Study Weblinks: Asthma Collaboratory Study Design: Case-Control Study Type: Case-Control Total number of consented subjects: 4458 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Genes-Environments and Admixture in Latino Asthmatics (GALA II) Study","short_name":"GALAII_DS-LD-IRB-COL_","commons":"BioData Catalyst","study_url":"https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001180.v2.p1","_subjects_count":4458,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs001189.v4.p1.c1":{"gen3_discovery":{"authz":"","tags":[],"_unique_id":"phs001189.v4.p1.c1","study_id":"phs001189.v4.p1.c1","study_description":"","full_name":"","short_name":"","commons":"BioData Catalyst","study_url":"","_subjects_count":0,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs001189.v5.p1.c1":{"gen3_discovery":{"authz":"/programs/topmed/projects/CCAF_AF_GRU-IRB","tags":[{"name":"TOPMed","category":"Program"},{"name":"Genotype","category":"Data Type"},{"name":"dbGaP","category":"Study Registration"}],"_unique_id":"phs001189.v5.p1.c1","study_id":"phs001189.v5.p1.c1","study_description":"This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed) Whole Genome Sequencing Program. TOPMed is part of a broader Precision Medicine Initiative, which aims to provide disease treatments that are tailored to an individual's unique genes and environment. TOPMed will contribute to this initiative through the integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles, protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental, and clinical data. In doing so, this program aims to uncover factors that increase or decrease the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized treatments. Two genotype call sets derived from WGS are now available, Freeze 9b (GRCh38) and Freeze 10b (GRCh38), with largely overlapping sample sets. Information about how to identify other TOPMed WGS accessions for cross-study analysis, as well as descriptions of TOPMed methods of data acquisition, data processing and quality control, are provided in the accompanying documents, \"TOPMed Whole Genome Sequencing Project - Freeze 9b, Phases 1-4\" and \"TOPMed Whole Genome Sequencing Project - Freeze 10b, Phases 1-8\". Please check the study list at the top of each of these methods documents to determine whether it applies to this study accession. The Cleveland Clinic Atrial Fibrillation Study consists of clinical and genetic data of patients with atrial fibrillation and control cohorts from the Cleveland Clinic CV/Arrhythmia Biobank, including the Cleveland Clinic Lone Atrial Fibrillation GeneBank. The Cleveland Clinic Lone AF GeneBank Study has enrolled patients with lone AF, defined as AF in the absence of significant structural heart disease. The CV/Arrhythmia Biobank has also enrolled participants with non-lone atrial fibrillation. All patients provided written informed consent. Study Design: Case Set Study Type: Case Set dbGaP estimated ancestry using GRAF-pop Total number of consented subjects: 363 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"NHLBI TOPMed: Cleveland Clinic Atrial Fibrillation (CCAF) Study","short_name":"CCAF_AF_GRU-IRB","commons":"BioData Catalyst","study_url":"https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001189.v5.p1","_subjects_count":363,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs001194.v2.p2.c1":{"gen3_discovery":{"authz":null,"tags":null,"_unique_id":"phs001194.v2.p2.c1","study_id":"phs001194.v2.p2.c1","study_description":null,"full_name":null,"short_name":null,"commons":"BioData Catalyst","study_url":null,"_subjects_count":0,"__manifest":null,"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs001194.v2.p2.c2":{"gen3_discovery":{"authz":null,"tags":null,"_unique_id":"phs001194.v2.p2.c2","study_id":"phs001194.v2.p2.c2","study_description":null,"full_name":null,"short_name":null,"commons":"BioData Catalyst","study_url":null,"_subjects_count":0,"__manifest":null,"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs001194.v4.p3.c1":{"gen3_discovery":{"authz":"/programs/parent/projects/PCGC_HMB_","tags":[],"_unique_id":"phs001194.v4.p3.c1","study_id":"phs001194.v4.p3.c1","study_description":"Multi-center, prospective observational cohort study of individuals with congenital heart defects (CHD). Phenotypic data and source DNA derived from 10,000 probands, parents, and families of interest are being collected to investigate relationships between genetic factors and phenotypic and clinical outcomes in patients with CHD. Phenotype data will be stored at dbGaP, while molecular and sequence data will be stored at BioData Catalyst. The PCGC Cohort is utilized in the following dbGaP substudies. Please click on the following substudies below or in the \"Substudies\" section of this top-level study page phs001194 PCGC Cohort. phs000571 PCGC: whole exome sequences, whole genome sequences, targeted sequences, MIP sequences, and SNP array data phs001843 PCGC-CMG Collaboration: whole genome sequences The Gabriella Miller Kids First Pediatric Research Program (Kids First) subset of the PCGC project (phs001194) is now accessible through a separate dbGaP study accession: phs001138. To access this dataset, please submit a Data Access Request (DAR) for phs001138. Approval of this DAR will be expedited for approved users of phs001194. To learn about other Kids First datasets visit https://kidsfirstdrc.org/.NHLBI's TOPMed program has provided additional Whole Genome Sequencing for PCGC participants - that data is accessible through a separate dbGaP sudy accession: phs001735. Access to this data set should be requested through a Data Access Request (DAR) for phs001735. Study Weblinks: From Bench to Bassinet: CHD Genes Study Design: Prospective Longitudinal Cohort Study Type: Cohort Parent-Offspring Trios Total number of consented subjects: 21963 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"National Heart, Lung, and Blood Institute (NHLBI) Bench to Bassinet Program: The Pediatric Cardiac Genetics Consortium (PCGC) Study","short_name":"PCGC_HMB_","commons":"BioData Catalyst","study_url":"","_subjects_count":21846,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs001194.v4.p3.c2":{"gen3_discovery":{"authz":"/programs/parent/projects/PCGC_DS-CHD_","tags":[],"_unique_id":"phs001194.v4.p3.c2","study_id":"phs001194.v4.p3.c2","study_description":"Multi-center, prospective observational cohort study of individuals with congenital heart defects (CHD). Phenotypic data and source DNA derived from 10,000 probands, parents, and families of interest are being collected to investigate relationships between genetic factors and phenotypic and clinical outcomes in patients with CHD. Phenotype data will be stored at dbGaP, while molecular and sequence data will be stored at BioData Catalyst. The PCGC Cohort is utilized in the following dbGaP substudies. Please click on the following substudies below or in the \"Substudies\" section of this top-level study page phs001194 PCGC Cohort. phs000571 PCGC: whole exome sequences, whole genome sequences, targeted sequences, MIP sequences, and SNP array data phs001843 PCGC-CMG Collaboration: whole genome sequences The Gabriella Miller Kids First Pediatric Research Program (Kids First) subset of the PCGC project (phs001194) is now accessible through a separate dbGaP study accession: phs001138. To access this dataset, please submit a Data Access Request (DAR) for phs001138. Approval of this DAR will be expedited for approved users of phs001194. To learn about other Kids First datasets visit https://kidsfirstdrc.org/.NHLBI's TOPMed program has provided additional Whole Genome Sequencing for PCGC participants - that data is accessible through a separate dbGaP sudy accession: phs001735. Access to this data set should be requested through a Data Access Request (DAR) for phs001735. Study Weblinks: From Bench to Bassinet: CHD Genes Study Design: Prospective Longitudinal Cohort Study Type: Cohort Parent-Offspring Trios Total number of consented subjects: 21963 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"National Heart, Lung, and Blood Institute (NHLBI) Bench to Bassinet Program: The Pediatric Cardiac Genetics Consortium (PCGC) Study","short_name":"PCGC_DS-CHD_","commons":"BioData Catalyst","study_url":"","_subjects_count":117,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs001207.v3.p1.c1":{"gen3_discovery":{"authz":"/programs/topmed/projects/Sarcoidosis_DS-SAR-IRB","tags":[{"name":"TOPMed","category":"Program"},{"name":"Genotype","category":"Data Type"},{"name":"Clinical Phenotype","category":"Data Type"},{"name":"dbGaP","category":"Study Registration"}],"_unique_id":"phs001207.v3.p1.c1","study_id":"phs001207.v3.p1.c1","study_description":"This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed) Whole Genome Sequencing Program. TOPMed is part of a broader Precision Medicine Initiative, which aims to provide disease treatments that are tailored to an individual's unique genes and environment. TOPMed will contribute to this initiative through the integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles, protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental, and clinical data. In doing so, this program aims to uncover factors that increase or decrease the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized treatments. Two genotype call sets derived from WGS are now available, Freeze 8 (GRCh38) and Freeze 9b (GRCh38), with largely overlapping sample sets. Information about how to identify other TOPMed WGS accessions for cross-study analysis, as well as descriptions of TOPMed methods of data acquisition, data processing and quality control, are provided in the accompanying documents, \"TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4\" and \"TOPMed Whole Genome Sequencing Project - Freeze 9b, Phases 1-4\". Please check the study list at the top of each of these methods documents to determine whether it applies to this study accession. This study aims to comprehensively interrogate the genomes of African American sarcoidosis families. Sarcoidosis is characterized by a hyperimmune response resulting in granuloma formation in multiple organs. It affects African Americans (AAs) more frequently and more severely than whites. While previous linkage, admixture, candidate gene and genome-wide association (GWA) studies show statistically compelling effects, causal variants are still unknown and much of sarcoidosis heritability is yet to be explained. This \"missing\" heritability likely includes effects of both common (minor allele frequency (MAF)>5%) and rare variants (MAF<5%), since, in AAs, the former are inadequately represented and the latter are completely unexplored by commercial genotyping arrays. These facts, coupled with the availability of next-generation sequencing compel us to perform an exhaustive search for genetic variants that form the basis of sarcoidosis. The data generated are certain to identify candidate causal variants, provide fundamental insight for functional studies and lead to important new hypotheses of inflammation resulting in new treatments in not only sarcoidosis but other inflammatory diseases as well. Study Design: Family/Twin/Trios Study Type: Affected Sib Pairs Family dbGaP estimated ancestry using GRAF-pop Total number of consented subjects: 1335 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"NHLBI TOPMed: African American Sarcoidosis Genetics Resource","short_name":"Sarcoidosis_DS-SAR-IRB","commons":"BioData Catalyst","study_url":"https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001207.v3.p1","_subjects_count":1333,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs001211.v4.p2.c1":{"gen3_discovery":{"authz":"","tags":[],"_unique_id":"phs001211.v4.p2.c1","study_id":"phs001211.v4.p2.c1","study_description":"","full_name":"","short_name":"","commons":"BioData Catalyst","study_url":"","_subjects_count":0,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs001211.v4.p2.c2":{"gen3_discovery":{"authz":"","tags":[],"_unique_id":"phs001211.v4.p2.c2","study_id":"phs001211.v4.p2.c2","study_description":"","full_name":"","short_name":"","commons":"BioData Catalyst","study_url":"","_subjects_count":0,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs001211.v5.p4.c1":{"gen3_discovery":{"authz":"/programs/topmed/projects/ARIC_HMB-IRB-NPU-MDS","tags":[],"_unique_id":"phs001211.v5.p4.c1","study_id":"phs001211.v5.p4.c1","study_description":"This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed) Whole Genome Sequencing Program. TOPMed is part of a broader Precision Medicine Initiative, which aims to provide disease treatments that are tailored to an individual's unique genes and environment. TOPMed will contribute to this initiative through the integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles, protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental, and clinical data. In doing so, this program aims to uncover factors that increase or decrease the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized treatments. Two genotype call sets derived from WGS are now available, Freeze 9b (GRCh38) and Freeze 10b (GRCh38), with largely overlapping sample sets. Information about how to identify other TOPMed WGS accessions for cross-study analysis, as well as descriptions of TOPMed methods of data acquisition, data processing and quality control, are provided in the accompanying documents, \"TOPMed Whole Genome Sequencing Project - Freeze 9b, Phases 1-4\" and \"TOPMed Whole Genome Sequencing Project - Freeze 10b, Phases 1-8\". Please check the study list at the top of each of these methods documents to determine whether it applies to this study accession. Participants from the Atherosclerosis Risk in Communities (ARIC) Study, a large population-based longitudinal cohort study, have been included in this Project and whole genome sequencing will be performed to contribute to analyses of early-onset atrial fibrillation and venous thromboembolism. Additional phenotype and genotype data are available for these individuals on dbGaP and can be accessed through the parent ARIC Cohort accession (phs000280). The National Heart, Lung and Blood Institute (NHLBI) Trans-Omics for Precision Medicine (TOPMed) program is designed to generate scientific resources to enhance understanding of fundamental biological processes that underlie heart, lung, blood and sleep disorders (HLBS). It is part of a broader Precision Medicine Initiative, which aims to provide disease treatments that are tailored to an individual's unique genes and environment. TOPMed will contribute to this initiative through the integration of whole genome sequencing (WGS) and other -omics (e.g., metabolic profiles, protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental, and clinical data. In doing so, this program seeks to uncover factors that increase or decrease the risk of disease, identify subtypes of disease, and develop more targeted and personalized treatments. The Whole Genome Sequencing (WGS) Project is part of NHLBI's TOPMed program and serves as an initial step for the larger initiative. Study Design: Case-Control Study Type: Case-Control dbGaP estimated ancestry using GRAF-pop Total number of consented subjects: 11585 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2025-10-09 and may not include exact formatting or images.","full_name":"NHLBI TOPMed - NHGRI CCDG: Atherosclerosis Risk in Communities (ARIC)","short_name":"ARIC_HMB-IRB-NPU-MDS","commons":"BioData Catalyst","study_url":"","_subjects_count":11496,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs001211.v5.p4.c2":{"gen3_discovery":{"authz":"/programs/topmed/projects/ARIC_DS-CVD-IRB-NPU-MDS","tags":[],"_unique_id":"phs001211.v5.p4.c2","study_id":"phs001211.v5.p4.c2","study_description":"This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed) Whole Genome Sequencing Program. TOPMed is part of a broader Precision Medicine Initiative, which aims to provide disease treatments that are tailored to an individual's unique genes and environment. TOPMed will contribute to this initiative through the integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles, protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental, and clinical data. In doing so, this program aims to uncover factors that increase or decrease the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized treatments. Two genotype call sets derived from WGS are now available, Freeze 9b (GRCh38) and Freeze 10b (GRCh38), with largely overlapping sample sets. Information about how to identify other TOPMed WGS accessions for cross-study analysis, as well as descriptions of TOPMed methods of data acquisition, data processing and quality control, are provided in the accompanying documents, \"TOPMed Whole Genome Sequencing Project - Freeze 9b, Phases 1-4\" and \"TOPMed Whole Genome Sequencing Project - Freeze 10b, Phases 1-8\". Please check the study list at the top of each of these methods documents to determine whether it applies to this study accession. Participants from the Atherosclerosis Risk in Communities (ARIC) Study, a large population-based longitudinal cohort study, have been included in this Project and whole genome sequencing will be performed to contribute to analyses of early-onset atrial fibrillation and venous thromboembolism. Additional phenotype and genotype data are available for these individuals on dbGaP and can be accessed through the parent ARIC Cohort accession (phs000280). The National Heart, Lung and Blood Institute (NHLBI) Trans-Omics for Precision Medicine (TOPMed) program is designed to generate scientific resources to enhance understanding of fundamental biological processes that underlie heart, lung, blood and sleep disorders (HLBS). It is part of a broader Precision Medicine Initiative, which aims to provide disease treatments that are tailored to an individual's unique genes and environment. TOPMed will contribute to this initiative through the integration of whole genome sequencing (WGS) and other -omics (e.g., metabolic profiles, protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental, and clinical data. In doing so, this program seeks to uncover factors that increase or decrease the risk of disease, identify subtypes of disease, and develop more targeted and personalized treatments. The Whole Genome Sequencing (WGS) Project is part of NHLBI's TOPMed program and serves as an initial step for the larger initiative. Study Design: Case-Control Study Type: Case-Control dbGaP estimated ancestry using GRAF-pop Total number of consented subjects: 11585 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2025-10-09 and may not include exact formatting or images.","full_name":"NHLBI TOPMed - NHGRI CCDG: Atherosclerosis Risk in Communities (ARIC)","short_name":"ARIC_DS-CVD-IRB-NPU-MDS","commons":"BioData Catalyst","study_url":"","_subjects_count":89,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs001212.v1.p1.c1":{"gen3_discovery":{"authz":"/programs/heartfailure/projects/Globin_iPS_GRU","tags":[],"_unique_id":"phs001212.v1.p1.c1","study_id":"phs001212.v1.p1.c1","study_description":"Implement an efficient, highly reproducible and 'scalable' system for the production of large numbers of sickle cell anemia-specific iPS cells (iPSC). Derive and characterize a novel, in vitro system for the production of an unlimited supply of erythroid lineage cells from the directed differentiation of 'clinical grade' transgene-free iPS cells; use this system to recapitulate erythroid-lineage ontogeny in vitro with the sequential development of primitive and definitive erythropoiesis, accompanied by the appropriate expression of stage-specific globin genes. Identify developmental gene expression profile differences between erythroid precursors that produce primarily HbF and those that produce primarily HbA or HbS. Determine the effects of the three known HbF major quantitative trait loci (QTL) on globin gene expression in disease-specific iPS cells during in vitro erythropoiesis. Search for novel HbF genetic modifiers associated with markedly elevated HbF levels found in sickle cell anemia patients naturally, or in response to hydroxyurea treatment, by examining gene expression profiles and mRNA sequence of their iPSC-derived erythroid cells. Develop and use a CRISPR-based gene editing platform to study the effect of novel HbF genetic modifiers, explore globin switching, and correct the HbS mutation in sickle iPSC lines. Study Weblinks: BU Center of Excellence in Sickle Cell Study Design: Case Set Study Type: Case Set dbGaP estimated ancestry using GRAF-pop Total number of consented subjects: 55 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2025-10-09 and may not include exact formatting or images.","full_name":"NextGen Consortium: Globin Gene Expression in Sickle Cell Genotype-Specific iPS Cells","short_name":"Globin_iPS_GRU","commons":"BioData Catalyst","study_url":"","_subjects_count":55,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs001215.v3.p2.c1":{"gen3_discovery":{"authz":"","tags":[],"_unique_id":"phs001215.v3.p2.c1","study_id":"phs001215.v3.p2.c1","study_description":"","full_name":"","short_name":"","commons":"BioData Catalyst","study_url":"","_subjects_count":0,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs001215.v4.p2.c1":{"gen3_discovery":{"authz":"/programs/topmed/projects/SAFHS_DS-DHD-IRB-PUB-MDS-RD","tags":[],"_unique_id":"phs001215.v4.p2.c1","study_id":"phs001215.v4.p2.c1","study_description":"This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed) Whole Genome Sequencing Program. TOPMed is part of a broader Precision Medicine Initiative, which aims to provide disease treatments that are tailored to an individual's unique genes and environment. TOPMed will contribute to this initiative through the integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles, protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental, and clinical data. In doing so, this program aims to uncover factors that increase or decrease the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized treatments. Two genotype call sets derived from WGS are now available, Freeze 8 (GRCh38) and Freeze 9b (GRCh38), with largely overlapping sample sets. Information about how to identify other TOPMed WGS accessions for cross-study analysis, as well as descriptions of TOPMed methods of data acquisition, data processing and quality control, are provided in the accompanying documents, \"TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4\" and \"TOPMed Whole Genome Sequencing Project - Freeze 9b, Phases 1-4\". Please check the study list at the top of each of these methods documents to determine whether it applies to this study accession. The San Antonio Family Heart Study (SAFHS) is a complex pedigree-based mixed longitudinal study designed to identify low frequency or rare variants influencing susceptibility to cardiovascular disease, using whole genome sequence (WGS) information from 2,590 individuals in large Mexican American pedigrees from San Antonio, Texas. The major objectives of this study are to identify low frequency or rare variants in and around known common variant signals for CVD, as well as to find novel low frequency or rare variants influencing susceptibility to CVD. WGS of the SAFHS cohort has been obtained through three efforts. Approximately 540 WGS were performed commercially at 50X by Complete Genomics, Inc (CGI) as part of the large T2D-GENES Project. The phenotype and genotype data for this group is available at dbGaP under accession number phs000462. An additional ~900 WGS at 30X were obtained through Illumina as part of the R01HL113322 \"Whole Genome Sequencing to Identify Causal Genetic Variants Influencing CVD Risk\" project. Finally, ~1,150 WGS at 30X WGS were obtained through Illumina funded by a supplement as part of the NHLBI's TOPMed program. Extensive phenotype data are provided for sequenced individuals primarily obtained from the P01HL45522 \"Genetics of Atherosclerosis in Mexican Americans\" for adults and R01HD049051 for children in these same families. Phenotype information was collected between 1991 and 2016. For this dataset, the SAFHS appellation represents an amalgamation of the original SAFHS participants and an expansion that reexamined families previously recruited for the San Antonio Family Diabetes Study (R01DK042273) and the San Antonio Family Gall Bladder Study (R01DK053889). Due to this substantial examination history, participants may have information from up to five visits. The clinical variables reported are coordinated with TOPMed and include major adverse cardiac events (MACE), T2D status and age at diagnosis, glycemic traits (fasting glucose and insulin), blood pressure, blood lipids (total cholesterol, HDL cholesterol, calculated LDL cholesterol and triglycerides). Additional phenotype data include the medication status at each visit, classified in four categories as any current use of diabetes, hypertension or lipid-lowering medications, and, for females, current use of female hormones. Anthropometric measurements include age, sex, height, weight, hip circumference, waist circumference and derived ratios. PBMC derived gene expression assays for a subset of ~1,060 individuals obtained using the Illumina Sentrix-6 chip is also available from the baseline examination. The WGS data have been jointly called and are available in the current TOPMed accession (phs001215). Study Design: Family/Twin/Trios Study Type: Family dbGaP estimated ancestry using GRAF-pop Total number of consented subjects: 2594 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2025-10-09 and may not include exact formatting or images.","full_name":"NHLBI TOPMed: San Antonio Family Heart Study (SAFHS)","short_name":"SAFHS_DS-DHD-IRB-PUB-MDS-RD","commons":"BioData Catalyst","study_url":"","_subjects_count":2594,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs001217.v3.p1.c1":{"gen3_discovery":{"authz":"/programs/topmed/projects/GenSalt_DS-HCR-IRB","tags":[{"name":"TOPMed","category":"Program"},{"name":"Genotype","category":"Data Type"},{"name":"dbGaP","category":"Study Registration"}],"_unique_id":"phs001217.v3.p1.c1","study_id":"phs001217.v3.p1.c1","study_description":"This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed) Whole Genome Sequencing Program. TOPMed is part of a broader Precision Medicine Initiative, which aims to provide disease treatments that are tailored to an individual's unique genes and environment. TOPMed will contribute to this initiative through the integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles, protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental, and clinical data. In doing so, this program aims to uncover factors that increase or decrease the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized treatments. Two genotype call sets derived from WGS are now available, Freeze 8 (GRCh38) and Freeze 9b (GRCh38), with largely overlapping sample sets. Information about how to identify other TOPMed WGS accessions for cross-study analysis, as well as descriptions of TOPMed methods of data acquisition, data processing and quality control, are provided in the accompanying documents, \"TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4\" and \"TOPMed Whole Genome Sequencing Project - Freeze 9b, Phases 1-4\". Please check the study list at the top of each of these methods documents to determine whether it applies to this study accession. The GenSalt study aims to identify genes which interact with dietary sodium and potassium intake to influence blood pressure in Han Chinese participants from rural north China. Whole genome sequencing will be conducted among 1,860 participants of the Genetic Epidemiology Network of Salt Sensitivity (GenSalt) Study. We will work in collaboration with participating TOPMed studies to identify novel common, low-frequency and rare variants associated with an array of cardiometabolic phenotypes. In addition, we will explore the relation of low-frequency and rare variants with salt-sensitivity among GenSalt study participants. Study Design: Family/Twin/Trios Study Type: Cohort Parent-Offspring Trios dbGaP estimated ancestry using GRAF-pop Total number of consented subjects: 3142 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2025-10-09 and may not include exact formatting or images.","full_name":"NHLBI TOPMed: Genetic Epidemiology Network of Salt Sensitivity (GenSalt)","short_name":"GenSalt_DS-HCR-IRB","commons":"BioData Catalyst","study_url":"https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001217.v3.p1","_subjects_count":1863,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs001218.v3.p1.c2":{"gen3_discovery":{"authz":"/programs/topmed/projects/GeneSTAR_DS-CVD-IRB-NPU-MDS","tags":[{"name":"TOPMed","category":"Program"},{"name":"Genotype","category":"Data Type"},{"name":"dbGaP","category":"Study Registration"}],"_unique_id":"phs001218.v3.p1.c2","study_id":"phs001218.v3.p1.c2","study_description":"This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed) Whole Genome Sequencing Program. TOPMed is part of a broader Precision Medicine Initiative, which aims to provide disease treatments that are tailored to an individual's unique genes and environment. TOPMed will contribute to this initiative through the integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles, protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental, and clinical data. In doing so, this program aims to uncover factors that increase or decrease the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized treatments. Two genotype call sets derived from WGS are now available, Freeze 8 (GRCh38) and Freeze 9b (GRCh38), with largely overlapping sample sets. Information about how to identify other TOPMed WGS accessions for cross-study analysis, as well as descriptions of TOPMed methods of data acquisition, data processing and quality control, are provided in the accompanying documents, \"TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4\" and \"TOPMed Whole Genome Sequencing Project - Freeze 9b, Phases 1-4\". Please check the study list at the top of each of these methods documents to determine whether it applies to this study accession. GeneSTAR began in 1982 as the Johns Hopkins Sibling and Family Heart Study, a prospective longitudinal family-based study conducted originally in healthy adult siblings of people with documented early onset coronary disease under 60 years of age. Commencing in 2003, the siblings, their offspring, and the coparent of the offspring participated in a 2 week trial of aspirin 81 mg/day with pre and post ex vivo platelet function assessed using multiple agonists in whole blood and platelet rich plasma. Extensive additional cardiovascular testing and risk assessment was done at baseline and serially. Follow-up was carried out to determine incident cardiovascular disease, stroke, peripheral arterial disease, diabetes, cancer, and related comorbidities, from 5 to 30 years after study entry. The goal of several additional phenotyping and interventional substudies has been to discover and amplify understanding of the mechanisms of atherogenic vascular diseases and attendant comorbidities. Study Weblinks: GeneSTAR Study Design: Prospective Longitudinal Cohort Study Type: Family Longitudinal Cohort dbGaP estimated ancestry using GRAF-pop Total number of consented subjects: 1787 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"NHLBI TOPMed: Genetic Study of Atherosclerosis Risk (GeneSTAR)","short_name":"GeneSTAR_DS-CVD-IRB-NPU-MDS","commons":"BioData Catalyst","study_url":"https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001218.v3.p1","_subjects_count":1783,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs001237.v2.p1.c1":{"gen3_discovery":{"authz":"","tags":[],"_unique_id":"phs001237.v2.p1.c1","study_id":"phs001237.v2.p1.c1","study_description":"","full_name":"","short_name":"","commons":"BioData Catalyst","study_url":"","_subjects_count":0,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs001237.v2.p1.c2":{"gen3_discovery":{"authz":"","tags":[],"_unique_id":"phs001237.v2.p1.c2","study_id":"phs001237.v2.p1.c2","study_description":"","full_name":"","short_name":"","commons":"BioData Catalyst","study_url":"","_subjects_count":0,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs001237.v3.p1.c1":{"gen3_discovery":{"authz":"","tags":[],"_unique_id":"phs001237.v3.p1.c1","study_id":"phs001237.v3.p1.c1","study_description":"","full_name":"","short_name":"","commons":"BioData Catalyst","study_url":"","_subjects_count":0,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs001237.v3.p1.c2":{"gen3_discovery":{"authz":"","tags":[],"_unique_id":"phs001237.v3.p1.c2","study_id":"phs001237.v3.p1.c2","study_description":"","full_name":"","short_name":"","commons":"BioData Catalyst","study_url":"","_subjects_count":0,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs001237.v4.p2.c1":{"gen3_discovery":{"authz":"/programs/topmed/projects/WHI_HMB-IRB","tags":[],"_unique_id":"phs001237.v4.p2.c1","study_id":"phs001237.v4.p2.c1","study_description":"This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed) Whole Genome Sequencing Program. TOPMed is part of a broader Precision Medicine Initiative, which aims to provide disease treatments that are tailored to an individual's unique genes and environment. TOPMed will contribute to this initiative through the integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles, protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental, and clinical data. In doing so, this program aims to uncover factors that increase or decrease the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized treatments. Two genotype call sets derived from WGS are now available, Freeze 9b (GRCh38) and Freeze 10b (GRCh38), with largely overlapping sample sets. Information about how to identify other TOPMed WGS accessions for cross-study analysis, as well as descriptions of TOPMed methods of data acquisition, data processing and quality control, are provided in the accompanying documents, \"TOPMed Whole Genome Sequencing Project - Freeze 9b, Phases 1-4\" and \"TOPMed Whole Genome Sequencing Project - Freeze 10b, Phases 1-8\". Please check the study list at the top of each of these methods documents to determine whether it applies to this study accession. This is Whole Genome Sequencing data from the TOPMed participation of the Women's Health Initiative. Approximately 11,100 subjects were involved in this study: approximately 1,100 cases of VTE, 4,000 cases of ischemic stroke, 900 cases of hemorrhagic stroke, and 5,100 controls. Summary level phenotypes for the WHI Cohort study participants can be viewed at the top-level study page phs000200 WHI Cohort. Individual level phenotype data and molecular data for all WHI top-level study and substudies are available by requesting Authorized Access to the WHI Cohort study phs000200. Study Weblinks: WHI NHLBI Women's Health Initiative Study Design: Prospective Longitudinal Cohort Study Type: Longitudinal dbGaP estimated ancestry using GRAF-pop Total number of consented subjects: 13107 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"NHLBI TOPMed: Women's Health Initiative (WHI)","short_name":"WHI_HMB-IRB","commons":"BioData Catalyst","study_url":"","_subjects_count":10793,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs001237.v4.p2.c2":{"gen3_discovery":{"authz":"/programs/topmed/projects/WHI_HMB-IRB-NPU","tags":[],"_unique_id":"phs001237.v4.p2.c2","study_id":"phs001237.v4.p2.c2","study_description":"This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed) Whole Genome Sequencing Program. TOPMed is part of a broader Precision Medicine Initiative, which aims to provide disease treatments that are tailored to an individual's unique genes and environment. TOPMed will contribute to this initiative through the integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles, protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental, and clinical data. In doing so, this program aims to uncover factors that increase or decrease the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized treatments. Two genotype call sets derived from WGS are now available, Freeze 9b (GRCh38) and Freeze 10b (GRCh38), with largely overlapping sample sets. Information about how to identify other TOPMed WGS accessions for cross-study analysis, as well as descriptions of TOPMed methods of data acquisition, data processing and quality control, are provided in the accompanying documents, \"TOPMed Whole Genome Sequencing Project - Freeze 9b, Phases 1-4\" and \"TOPMed Whole Genome Sequencing Project - Freeze 10b, Phases 1-8\". Please check the study list at the top of each of these methods documents to determine whether it applies to this study accession. This is Whole Genome Sequencing data from the TOPMed participation of the Women's Health Initiative. Approximately 11,100 subjects were involved in this study: approximately 1,100 cases of VTE, 4,000 cases of ischemic stroke, 900 cases of hemorrhagic stroke, and 5,100 controls. Summary level phenotypes for the WHI Cohort study participants can be viewed at the top-level study page phs000200 WHI Cohort. Individual level phenotype data and molecular data for all WHI top-level study and substudies are available by requesting Authorized Access to the WHI Cohort study phs000200. Study Weblinks: WHI NHLBI Women's Health Initiative Study Design: Prospective Longitudinal Cohort Study Type: Longitudinal dbGaP estimated ancestry using GRAF-pop Total number of consented subjects: 13107 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"NHLBI TOPMed: Women's Health Initiative (WHI)","short_name":"WHI_HMB-IRB-NPU","commons":"BioData Catalyst","study_url":"","_subjects_count":2314,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs001238.v2.p1.c1":{"gen3_discovery":{"authz":"/programs/parent/projects/GENOA_DS-ASC-RF-NPU_","tags":[{"name":"Parent","category":"Program"},{"name":"Clinical Phenotype","category":"Data Type"},{"name":"dbGaP","category":"Study Registration"}],"_unique_id":"phs001238.v2.p1.c1","study_id":"phs001238.v2.p1.c1","study_description":"The Genetic Epidemiology Network of Arteriopathy (GENOA) is one of four networks in the NHLBI Family-Blood Pressure Program (FBPP). GENOA's long-term objective is to elucidate the genetics of target organ complications of hypertension, including both atherosclerotic and arteriolosclerotic complications involving the heart, brain, kidneys, and peripheral arteries. The longitudinal GENOA Study recruited European-American and African-American sibships with at least 2 individuals with clinically diagnosed essential hypertension before age 60 years. All other members of the sibship were invited to participate regardless of their hypertension status. Participants were diagnosed with hypertension if they had either 1) a previous clinical diagnosis of hypertension by a physician with current anti-hypertensive treatment, or 2) an average systolic blood pressure ≥ 140 mm Hg or diastolic blood pressure ≥ 90 mm Hg based on the second and third readings at the time of their clinic visit. The Family Blood Pressure Program (FBPP), GENOA's parent program, is an unprecedented collaboration to identify genes influencing blood pressure (BP) levels, hypertension, and its target-organ damage. This program has conducted over 21,000 physical examinations, assembled a shared database of several hundred BP and hypertension-related phenotypic measurements, completed genome-wide linkage analyses for BP, hypertension, and hypertension associated risk factors and complications, and published over 130 manuscripts on program findings. The FBPP emerged from what was initially funded as four independent networks of investigators (HyperGEN, GenNet, SAPPHIRe and GENOA) competing to identify genetic determinants of hypertension in multiple ethnic groups. Realizing the greater likelihood of success through collaboration, the investigators created a single confederation with program-wide and network-specific goals. Study Weblinks: FBPP STAMPEED Study Design: Prospective Longitudinal Cohort Study Type: Sibling Cohort Total number of consented subjects: 3462 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Genetic Epidemiology Network of Arteriopathy (GENOA)","short_name":"GENOA_DS-ASC-RF-NPU_","commons":"BioData Catalyst","study_url":"https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001238.v2.p1","_subjects_count":3462,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs001252.v1.p1.c1":{"gen3_discovery":{"authz":"/programs/parent/projects/ECLIPSE_DS-COPD-RD_","tags":[{"name":"Parent","category":"Program"},{"name":"Clinical Phenotype","category":"Data Type"},{"name":"dbGaP","category":"Study Registration"}],"_unique_id":"phs001252.v1.p1.c1","study_id":"phs001252.v1.p1.c1","study_description":"ECLIPSE was a longitudinal observational study of 2164 COPD subjects and a smaller number of smoking controls (337) and nonsmoking controls (245) followed regularly for three years, with three chest CT scans (at baseline, one year, and three years) (Vestbo, European Respiratory Journal 2008; 31: 869). Inclusion criteria included age 40-75, at least 10 pack-years of smoking, and spirometry in GOLD grades 2-4 (COPD cases) or normal spirometry with post-bronchodilator FEV1 >85% predicted and FEV1/FVC>0.7 (controls). Study visits were performed at enrollment, three months, and every six months thereafter with spirometry, questionnaires, and other clinical evaluations. The ECLIPSE CT scans have been analyzed with the VIDA software for emphysema and airway phenotypes. ECLIPSE has provided key insights into the clinical epidemiology of COPD, including COPD exacerbations (Hurst, NEJM 2010; 363: 1128) and lung function decline in COPD (Vestbo, NEJM 2011; 365: 1184). ECLIPSE has been used in a number of genetic studies of COPD susceptibility and protein biomarkers(Faner, Thorax 2014; 69: 666). Genome-wide gene expression microarray data are available in 147 induced sputum samples from COPD subjects and 248 peripheral blood samples from COPD and control subjects. Study Weblinks: ECLIPSE Study Design: Case-Control Study Type: Case-Control Longitudinal Cohort Cohort dbGaP estimated ancestry using GRAF-pop Total number of consented subjects: 2746 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Evaluation of COPD Longitudinally to Identify Predictive Surrogate Endpoints (ECLIPSE)","short_name":"ECLIPSE_DS-COPD-RD_","commons":"BioData Catalyst","study_url":"https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001252.v1.p1","_subjects_count":2746,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs001258.v2.p1.c1":{"gen3_discovery":{"authz":"/programs/heartfailure/projects/exRNA_healthy_HMB","tags":[],"_unique_id":"phs001258.v2.p1.c1","study_id":"phs001258.v2.p1.c1","study_description":"We sequenced small RNAs from 183 plasma samples, 204 urine samples and 46 saliva samples from 55 college athletes ages 18-25 years. Many of the participants provided more than one sample, weeks or months apart, allowing us to assess variability in an individual's exRNA expression levels over time. Several individuals provided all three biofluid types at one time, producing data on individual expression levels across several biofluid types. Here we provide a systematic analysis of small exRNAs present in each biofluid, as well as an analysis of exogenous RNAs. We find that a large number of RNA fragments in plasma (63%) and urine (54%) have sequences that are assigned to YRNA and tRNA fragments respectively. Surprisingly, while many miRNAs can be detected, there are few miRNAs that are consistently detected in all samples from a single biofluid. Additionally, we performed whole transcriptome sequencing on 134 plasma and 115 urine samples and identified circRNA. Study Design: Prospective Longitudinal Cohort Study Type: Longitudinal Total number of consented subjects: 57 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Total exRNA Profiles from Plasma, Saliva, and Urine of Healthy Subjects","short_name":"exRNA_healthy_HMB","commons":"BioData Catalyst","study_url":"","_subjects_count":57,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs001293.v3.p1.c1":{"gen3_discovery":{"authz":"/programs/topmed/projects/HyperGEN_GRU-IRB","tags":[{"name":"TOPMed","category":"Program"},{"name":"Genotype","category":"Data Type"},{"name":"Clinical Phenotype","category":"Data Type"},{"name":"dbGaP","category":"Study Registration"}],"_unique_id":"phs001293.v3.p1.c1","study_id":"phs001293.v3.p1.c1","study_description":"This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed) Whole Genome Sequencing Program. TOPMed is part of a broader Precision Medicine Initiative, which aims to provide disease treatments that are tailored to an individual's unique genes and environment. TOPMed will contribute to this initiative through the integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles, protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental, and clinical data. In doing so, this program aims to uncover factors that increase or decrease the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized treatments. Two genotype call sets derived from WGS are now available, Freeze 8 (GRCh38) and Freeze 9b (GRCh38), with largely overlapping sample sets. Information about how to identify other TOPMed WGS accessions for cross-study analysis, as well as descriptions of TOPMed methods of data acquisition, data processing and quality control, are provided in the accompanying documents, \"TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4\" and \"TOPMed Whole Genome Sequencing Project - Freeze 9b, Phases 1-4\". Please check the study list at the top of each of these methods documents to determine whether it applies to this study accession. The Hypertension Genetic Epidemiology Network Study (HyperGEN) - Genetics of Left Ventricular (LV) Hypertrophy is a familial study aimed to understand genetic risk factors for LV hypertrophy by conducting genetic studies of continuous traits from echocardiography exams. The originating HyperGEN study aimed to understand genetic risk factors for hypertension. Data from detailed clinical exams as well as genotyping data for linkage studies, candidate gene studies and GWAS have been collected and is shared between HyperGEN and the ancillary HyperGEN - Genetics of LV Hypertrophy study. Study Design: Family/Twin/Trios Study Type: Family dbGaP estimated ancestry using GRAF-pop Total number of consented subjects: 2104 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"NHLBI TOPMed: HyperGEN - Genetics of Left Ventricular (LV) Hypertrophy","short_name":"HyperGEN_GRU-IRB","commons":"BioData Catalyst","study_url":"https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001293.v3.p1","_subjects_count":1771,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs001293.v3.p1.c2":{"gen3_discovery":{"authz":"/programs/topmed/projects/HyperGEN_DS-CVD-IRB-RD","tags":[{"name":"TOPMed","category":"Program"},{"name":"Genotype","category":"Data Type"},{"name":"Clinical Phenotype","category":"Data Type"},{"name":"dbGaP","category":"Study Registration"}],"_unique_id":"phs001293.v3.p1.c2","study_id":"phs001293.v3.p1.c2","study_description":"This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed) Whole Genome Sequencing Program. TOPMed is part of a broader Precision Medicine Initiative, which aims to provide disease treatments that are tailored to an individual's unique genes and environment. TOPMed will contribute to this initiative through the integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles, protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental, and clinical data. In doing so, this program aims to uncover factors that increase or decrease the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized treatments. Two genotype call sets derived from WGS are now available, Freeze 8 (GRCh38) and Freeze 9b (GRCh38), with largely overlapping sample sets. Information about how to identify other TOPMed WGS accessions for cross-study analysis, as well as descriptions of TOPMed methods of data acquisition, data processing and quality control, are provided in the accompanying documents, \"TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4\" and \"TOPMed Whole Genome Sequencing Project - Freeze 9b, Phases 1-4\". Please check the study list at the top of each of these methods documents to determine whether it applies to this study accession. The Hypertension Genetic Epidemiology Network Study (HyperGEN) - Genetics of Left Ventricular (LV) Hypertrophy is a familial study aimed to understand genetic risk factors for LV hypertrophy by conducting genetic studies of continuous traits from echocardiography exams. The originating HyperGEN study aimed to understand genetic risk factors for hypertension. Data from detailed clinical exams as well as genotyping data for linkage studies, candidate gene studies and GWAS have been collected and is shared between HyperGEN and the ancillary HyperGEN - Genetics of LV Hypertrophy study. Study Design: Family/Twin/Trios Study Type: Family dbGaP estimated ancestry using GRAF-pop Total number of consented subjects: 2104 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"NHLBI TOPMed: HyperGEN - Genetics of Left Ventricular (LV) Hypertrophy","short_name":"HyperGEN_DS-CVD-IRB-RD","commons":"BioData Catalyst","study_url":"https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001293.v3.p1","_subjects_count":329,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs001341.v1.p1.c1":{"gen3_discovery":{"authz":"/programs/heartfailure/projects/PhLiPS_GRU","tags":[{"name":"dbGaP","category":"Study Registration"}],"_unique_id":"phs001341.v1.p1.c1","study_id":"phs001341.v1.p1.c1","study_description":"The goal of the PhLiPS study is to create a library of induced pluripotent stem cell (iPSC) lines and iPSC-derived hepatocytes of diverse genotypes for use in metabolic profiling and interrogating lipid phenotypes. These cell lines were created as a part of the Next Generation Genetic Association Studies (Next Gen) Program, which was a five-year, $80 million program to investigate functional genetic variation in humans by assessing cellular profiles that are surrogates for disease phenotypes. To achieve this, researchers from multiple institutions across the U.S. were awarded grants to derive iPSC lines from more than 1,500 individuals representing various conditions as well as healthy controls for use in functional genomic (\"disease in a dish\") research. This extensive panel includes a diverse set of age, gender, and ethnic backgrounds, and therefore will be an invaluable tool for evaluations across demographics. Further enhancing the utility of these cell lines are data sets such as phenotyping, GWAS, genome sequencing, gene expression and -omics analyses (e.g., lipidomic, proteomic, methylomic) that can be matched to the cell lines. The PhLiPS Study focuses on individuals free of cardiovascular disease or with lipoprotein metabolism disorders in the community served by the Hospital of the University of Pennsylvania. Study Weblinks: NHLBI Next Gen - Lipid Conditions (Dr. Daniel Rader, University of Pennsylvania) Study Design: Prospective Longitudinal Cohort Study Type: Cohort dbGaP estimated ancestry using GRAF-pop Total number of consented subjects: 90 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"The National Heart, Lung, and Blood Institute (NHLBI)-funded Next Generation Genetic Association Studies (NextGen) Consortium: Phenotyping Lipid traits in iPS derived hepatocytes Study (PhLiPS Study)","short_name":"PhLiPS_GRU","commons":"BioData Catalyst","study_url":"https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001341.v1.p1","_subjects_count":90,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs001345.v3.p1.c1":{"gen3_discovery":{"authz":"/programs/topmed/projects/GENOA_DS-ASC-RF-NPU","tags":[{"name":"TOPMed","category":"Program"},{"name":"Genotype","category":"Data Type"},{"name":"dbGaP","category":"Study Registration"}],"_unique_id":"phs001345.v3.p1.c1","study_id":"phs001345.v3.p1.c1","study_description":"This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed) Whole Genome Sequencing Program. TOPMed is part of a broader Precision Medicine Initiative, which aims to provide disease treatments that are tailored to an individual's unique genes and environment. TOPMed will contribute to this initiative through the integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles, protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental, and clinical data. In doing so, this program aims to uncover factors that increase or decrease the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized treatments. Two genotype call sets derived from WGS are now available, Freeze 8 (GRCh38) and Freeze 9b (GRCh38), with largely overlapping sample sets. Information about how to identify other TOPMed WGS accessions for cross-study analysis, as well as descriptions of TOPMed methods of data acquisition, data processing and quality control, are provided in the accompanying documents, \"TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4\" and \"TOPMed Whole Genome Sequencing Project - Freeze 9b, Phases 1-4\". Please check the study list at the top of each of these methods documents to determine whether it applies to this study accession. The Genetic Epidemiology Network of Arteriopathy (GENOA) is one of four networks in the NHLBI Family-Blood Pressure Program (FBPP). GENOA's long-term objective is to elucidate the genetics of target organ complications of hypertension, including both atherosclerotic and arteriolosclerotic complications involving the heart, brain, kidneys, and peripheral arteries. The longitudinal GENOA Study recruited European-American and African-American sibships with at least 2 individuals with clinically diagnosed essential hypertension before age 60 years. All other members of the sibship were invited to participate regardless of their hypertension status. Participants were diagnosed with hypertension if they had either 1) a previous clinical diagnosis of hypertension by a physician with current anti-hypertensive treatment, or 2) an average systolic blood pressure = 140 mm Hg or diastolic blood pressure = 90 mm Hg based on the second and third readings at the time of their clinic visit. Only participants of the African-American Cohort were sequenced through TOPMed. The Family Blood Pressure Program (FBPP), GENOA's parent program, is an unprecedented collaboration to identify genes influencing blood pressure (BP) levels, hypertension, and its target-organ damage. This program has conducted over 21,000 physical examinations, assembled a shared database of several hundred BP and hypertension-related phenotypic measurements, completed genome-wide linkage analyses for BP, hypertension, and hypertension associated risk factors and complications, and published over 130 manuscripts on program findings. The FBPP emerged from what was initially funded as four independent networks of investigators (HyperGEN, GenNet, SAPPHIRe and GENOA) competing to identify genetic determinants of hypertension in multiple ethnic groups. Realizing the greater likelihood of success through collaboration, the investigators created a single confederation with program-wide and network-specific goals. Comprehensive phenotypic data for GENOA study participants are available through dbGaP phs001238. Study Weblinks: FBPP STAMPEED Study Design: Family/Twin/Trios Study Type: Cohort Sibling Cohort dbGaP estimated ancestry using GRAF-pop Total number of consented subjects: 1854 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"NHLBI TOPMed: Genetic Epidemiology Network of Arteriopathy (GENOA)","short_name":"GENOA_DS-ASC-RF-NPU","commons":"BioData Catalyst","study_url":"https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001345.v3.p1","_subjects_count":1253,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs001356.v2.p2.c1":{"gen3_discovery":{"authz":"/programs/substudy/projects/Exome_Chip_JHS_HMB-IRB-NPU","tags":[],"_unique_id":"phs001356.v2.p2.c1","study_id":"phs001356.v2.p2.c1","study_description":"This sub-study phs001356 Exome Chip contains sequence data and selected phenotype of subjects available from the phs001356 study. Summary-level phenotype data for the NHLBI JHS participants can be viewed at the top-level study page phs000286 JHS Cohort. Individual level phenotype data and molecular data for all JHS Cohort top-level study and substudies are available by requesting Authorized Access to the NHLBI JHS Cohort phs000286 study. There is a greater prevalence of cardiovascular disease among African Americans, and the purpose of the JHS cohort is to explore the reasons for this disparity and to uncover new approaches to reduce it. The JHS is a large, community-based, observational study whose 5301 participants were recruited from among the non-institutionalized African-American adults from urban and rural areas of the three counties (Hinds, Madison, and Rankin) that make up the Jackson, MS, metropolitan statistical area (MSA). Jackson is the capital of Mississippi, the state with the largest percentage (36.3%) of African Americans in the United States. The JHS design included participants from the Jackson ARIC study who had originally been recruited through random selection from a drivers' license registry. Approximately six months before the JHS was to begin, an amendment to the federal Driver's Privacy Protection Act was passed that changed the level of consent for public release of personal information from driver's license lists from an \"opt out\" to an \"opt in\" basis. The Mississippi Highway Patrol was no longer able to release a complete listing of all persons with driver's licenses or state identification cards, which prevented its use in the JHS. New JHS participants were chosen randomly from the Accudata America commercial listing, which provides householder name, address, zip code, phone number (if available), age group in decades, and family components. The Accudata® list was deemed to provide the most complete count of households for individuals aged 55 years and older in the Jackson MSA. A structured volunteer sample was also included in which demographic cells for recruitment were designed to mirror the eligible population. Enrollment was opened to volunteers who met census-derived age, sex, and socioeconomic status (SES) eligibility criteria for the Jackson MSA. In addition, a family component was included in the JHS. The sampling frame for the family study was a participant in any one of the ARlC, random, or volunteer samples whose family size met eligibility requirements. Eligibility included having at least two full siblings and four first degree relatives (parents, siblings, children over the age of 21) who lived in the Jackson MSA and who were willing to participate in the study. No upper age limit was placed on the family sample. Known contact information was obtained during the baseline clinic examination from the index family member with a verbal pedigree format to identify name(s), age(s), address (es), and telephone number(s). Recruitment was limited to persons 35-84 years old except in the family cohort, where those 21 years old and above were eligible. Only persons who otherwise met study criteria but were deemed to be physically or mentally incompetent by trained recruiters were excluded from study eligibility (see PMID 14632263). Study Weblinks: Jackson Heart Study Study Design: Prospective Longitudinal Cohort Study Type: Longitudinal Cohort dbGaP estimated ancestry using GRAF-pop Total number of consented subjects: 2788 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Exome Chip Genotyping: The Jackson Heart Study","short_name":"Exome_Chip_JHS_HMB-IRB-NPU","commons":"BioData Catalyst","study_url":"","_subjects_count":657,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs001356.v2.p2.c2":{"gen3_discovery":{"authz":"/programs/substudy/projects/Exome_Chip_JHS_DS-FDO-IRB-NPU","tags":[],"_unique_id":"phs001356.v2.p2.c2","study_id":"phs001356.v2.p2.c2","study_description":"This sub-study phs001356 Exome Chip contains sequence data and selected phenotype of subjects available from the phs001356 study. Summary-level phenotype data for the NHLBI JHS participants can be viewed at the top-level study page phs000286 JHS Cohort. Individual level phenotype data and molecular data for all JHS Cohort top-level study and substudies are available by requesting Authorized Access to the NHLBI JHS Cohort phs000286 study. There is a greater prevalence of cardiovascular disease among African Americans, and the purpose of the JHS cohort is to explore the reasons for this disparity and to uncover new approaches to reduce it. The JHS is a large, community-based, observational study whose 5301 participants were recruited from among the non-institutionalized African-American adults from urban and rural areas of the three counties (Hinds, Madison, and Rankin) that make up the Jackson, MS, metropolitan statistical area (MSA). Jackson is the capital of Mississippi, the state with the largest percentage (36.3%) of African Americans in the United States. The JHS design included participants from the Jackson ARIC study who had originally been recruited through random selection from a drivers' license registry. Approximately six months before the JHS was to begin, an amendment to the federal Driver's Privacy Protection Act was passed that changed the level of consent for public release of personal information from driver's license lists from an \"opt out\" to an \"opt in\" basis. The Mississippi Highway Patrol was no longer able to release a complete listing of all persons with driver's licenses or state identification cards, which prevented its use in the JHS. New JHS participants were chosen randomly from the Accudata America commercial listing, which provides householder name, address, zip code, phone number (if available), age group in decades, and family components. The Accudata® list was deemed to provide the most complete count of households for individuals aged 55 years and older in the Jackson MSA. A structured volunteer sample was also included in which demographic cells for recruitment were designed to mirror the eligible population. Enrollment was opened to volunteers who met census-derived age, sex, and socioeconomic status (SES) eligibility criteria for the Jackson MSA. In addition, a family component was included in the JHS. The sampling frame for the family study was a participant in any one of the ARlC, random, or volunteer samples whose family size met eligibility requirements. Eligibility included having at least two full siblings and four first degree relatives (parents, siblings, children over the age of 21) who lived in the Jackson MSA and who were willing to participate in the study. No upper age limit was placed on the family sample. Known contact information was obtained during the baseline clinic examination from the index family member with a verbal pedigree format to identify name(s), age(s), address (es), and telephone number(s). Recruitment was limited to persons 35-84 years old except in the family cohort, where those 21 years old and above were eligible. Only persons who otherwise met study criteria but were deemed to be physically or mentally incompetent by trained recruiters were excluded from study eligibility (see PMID 14632263). Study Weblinks: Jackson Heart Study Study Design: Prospective Longitudinal Cohort Study Type: Longitudinal Cohort dbGaP estimated ancestry using GRAF-pop Total number of consented subjects: 2788 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Exome Chip Genotyping: The Jackson Heart Study","short_name":"Exome_Chip_JHS_DS-FDO-IRB-NPU","commons":"BioData Catalyst","study_url":"","_subjects_count":128,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs001356.v2.p2.c3":{"gen3_discovery":{"authz":"/programs/substudy/projects/Exome_Chip_JHS_HMB-IRB","tags":[],"_unique_id":"phs001356.v2.p2.c3","study_id":"phs001356.v2.p2.c3","study_description":"This sub-study phs001356 Exome Chip contains sequence data and selected phenotype of subjects available from the phs001356 study. Summary-level phenotype data for the NHLBI JHS participants can be viewed at the top-level study page phs000286 JHS Cohort. Individual level phenotype data and molecular data for all JHS Cohort top-level study and substudies are available by requesting Authorized Access to the NHLBI JHS Cohort phs000286 study. There is a greater prevalence of cardiovascular disease among African Americans, and the purpose of the JHS cohort is to explore the reasons for this disparity and to uncover new approaches to reduce it. The JHS is a large, community-based, observational study whose 5301 participants were recruited from among the non-institutionalized African-American adults from urban and rural areas of the three counties (Hinds, Madison, and Rankin) that make up the Jackson, MS, metropolitan statistical area (MSA). Jackson is the capital of Mississippi, the state with the largest percentage (36.3%) of African Americans in the United States. The JHS design included participants from the Jackson ARIC study who had originally been recruited through random selection from a drivers' license registry. Approximately six months before the JHS was to begin, an amendment to the federal Driver's Privacy Protection Act was passed that changed the level of consent for public release of personal information from driver's license lists from an \"opt out\" to an \"opt in\" basis. The Mississippi Highway Patrol was no longer able to release a complete listing of all persons with driver's licenses or state identification cards, which prevented its use in the JHS. New JHS participants were chosen randomly from the Accudata America commercial listing, which provides householder name, address, zip code, phone number (if available), age group in decades, and family components. The Accudata® list was deemed to provide the most complete count of households for individuals aged 55 years and older in the Jackson MSA. A structured volunteer sample was also included in which demographic cells for recruitment were designed to mirror the eligible population. Enrollment was opened to volunteers who met census-derived age, sex, and socioeconomic status (SES) eligibility criteria for the Jackson MSA. In addition, a family component was included in the JHS. The sampling frame for the family study was a participant in any one of the ARlC, random, or volunteer samples whose family size met eligibility requirements. Eligibility included having at least two full siblings and four first degree relatives (parents, siblings, children over the age of 21) who lived in the Jackson MSA and who were willing to participate in the study. No upper age limit was placed on the family sample. Known contact information was obtained during the baseline clinic examination from the index family member with a verbal pedigree format to identify name(s), age(s), address (es), and telephone number(s). Recruitment was limited to persons 35-84 years old except in the family cohort, where those 21 years old and above were eligible. Only persons who otherwise met study criteria but were deemed to be physically or mentally incompetent by trained recruiters were excluded from study eligibility (see PMID 14632263). Study Weblinks: Jackson Heart Study Study Design: Prospective Longitudinal Cohort Study Type: Longitudinal Cohort dbGaP estimated ancestry using GRAF-pop Total number of consented subjects: 2788 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Exome Chip Genotyping: The Jackson Heart Study","short_name":"Exome_Chip_JHS_HMB-IRB","commons":"BioData Catalyst","study_url":"","_subjects_count":1626,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs001356.v2.p2.c4":{"gen3_discovery":{"authz":"/programs/substudy/projects/Exome_Chip_JHS_DS-FDO-IRB","tags":[],"_unique_id":"phs001356.v2.p2.c4","study_id":"phs001356.v2.p2.c4","study_description":"This sub-study phs001356 Exome Chip contains sequence data and selected phenotype of subjects available from the phs001356 study. Summary-level phenotype data for the NHLBI JHS participants can be viewed at the top-level study page phs000286 JHS Cohort. Individual level phenotype data and molecular data for all JHS Cohort top-level study and substudies are available by requesting Authorized Access to the NHLBI JHS Cohort phs000286 study. There is a greater prevalence of cardiovascular disease among African Americans, and the purpose of the JHS cohort is to explore the reasons for this disparity and to uncover new approaches to reduce it. The JHS is a large, community-based, observational study whose 5301 participants were recruited from among the non-institutionalized African-American adults from urban and rural areas of the three counties (Hinds, Madison, and Rankin) that make up the Jackson, MS, metropolitan statistical area (MSA). Jackson is the capital of Mississippi, the state with the largest percentage (36.3%) of African Americans in the United States. The JHS design included participants from the Jackson ARIC study who had originally been recruited through random selection from a drivers' license registry. Approximately six months before the JHS was to begin, an amendment to the federal Driver's Privacy Protection Act was passed that changed the level of consent for public release of personal information from driver's license lists from an \"opt out\" to an \"opt in\" basis. The Mississippi Highway Patrol was no longer able to release a complete listing of all persons with driver's licenses or state identification cards, which prevented its use in the JHS. New JHS participants were chosen randomly from the Accudata America commercial listing, which provides householder name, address, zip code, phone number (if available), age group in decades, and family components. The Accudata® list was deemed to provide the most complete count of households for individuals aged 55 years and older in the Jackson MSA. A structured volunteer sample was also included in which demographic cells for recruitment were designed to mirror the eligible population. Enrollment was opened to volunteers who met census-derived age, sex, and socioeconomic status (SES) eligibility criteria for the Jackson MSA. In addition, a family component was included in the JHS. The sampling frame for the family study was a participant in any one of the ARlC, random, or volunteer samples whose family size met eligibility requirements. Eligibility included having at least two full siblings and four first degree relatives (parents, siblings, children over the age of 21) who lived in the Jackson MSA and who were willing to participate in the study. No upper age limit was placed on the family sample. Known contact information was obtained during the baseline clinic examination from the index family member with a verbal pedigree format to identify name(s), age(s), address (es), and telephone number(s). Recruitment was limited to persons 35-84 years old except in the family cohort, where those 21 years old and above were eligible. Only persons who otherwise met study criteria but were deemed to be physically or mentally incompetent by trained recruiters were excluded from study eligibility (see PMID 14632263). Study Weblinks: Jackson Heart Study Study Design: Prospective Longitudinal Cohort Study Type: Longitudinal Cohort dbGaP estimated ancestry using GRAF-pop Total number of consented subjects: 2788 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Exome Chip Genotyping: The Jackson Heart Study","short_name":"Exome_Chip_JHS_DS-FDO-IRB","commons":"BioData Catalyst","study_url":"","_subjects_count":377,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs001359.v3.p1.c1":{"gen3_discovery":{"authz":"/programs/topmed/projects/GOLDN_DS-CVD-IRB","tags":[{"name":"TOPMed","category":"Program"},{"name":"Genotype","category":"Data Type"},{"name":"dbGaP","category":"Study Registration"}],"_unique_id":"phs001359.v3.p1.c1","study_id":"phs001359.v3.p1.c1","study_description":"This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed) Whole Genome Sequencing Program. TOPMed is part of a broader Precision Medicine Initiative, which aims to provide disease treatments that are tailored to an individual's unique genes and environment. TOPMed will contribute to this initiative through the integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles, protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental, and clinical data. In doing so, this program aims to uncover factors that increase or decrease the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized treatments. Two genotype call sets derived from WGS are now available, Freeze 8 (GRCh38) and Freeze 9b (GRCh38), with largely overlapping sample sets. Information about how to identify other TOPMed WGS accessions for cross-study analysis, as well as descriptions of TOPMed methods of data acquisition, data processing and quality control, are provided in the accompanying documents, \"TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4\" and \"TOPMed Whole Genome Sequencing Project - Freeze 9b, Phases 1-4\". Please check the study list at the top of each of these methods documents to determine whether it applies to this study accession. The GOLDN study was initiated to assess how genetic factors interact with environmental (diet and drug) interventions to influence blood levels of triglycerides and other atherogenic lipid species and inflammation markers (registered at clinicaltrials.gov, number NCT00083369). The study recruited Caucasian participants primarily from three-generational pedigrees from two NHLBI Family Heart Study (FHS) field centers (Minneapolis, MN and Salt Lake City, UT). Only families with at least two siblings were recruited and only participants who did not take lipid-lowering agents (pharmaceuticals or nutraceuticals) for at least 4 weeks prior to the initial visit were included. The diet intervention followed the protocol of Patsch et al. (1992). The whipping cream (83% fat) meal had 700 Calories/m2 body surface area (2.93 mJ/m2 body surface area): 3% of calories were derived from protein (instant nonfat dry milk) and 14% from carbohydrate (sugar). The ratio of polyunsaturated to saturated fat was 0.06 and the cholesterol content of the average meal was 240 mg. The mixture was blended with ice and flavorings. Blood samples were drawn immediately before (fasting) and at 3.5 and 6 hours after consuming the high-fat meal. The diet intervention was administered at baseline as well as after a 3-week treatment with 160 mg micronized fenofibrate. Participants were given the option to complete one or both (diet and drug) interventions. Of all participants, 1079 had phenotypic data and provided appropriate consent, and underwent whole genome sequencing through the Trans-Omics for Precision Medicine (TOPMed) program. Comprehensive phenotypic and pedigree data for GOLDN study participants are available through dbGaP phs000741. Study Weblinks: GOLDN Study Design: Prospective Longitudinal Cohort Study Type: Longitudinal dbGaP estimated ancestry using GRAF-pop Total number of consented subjects: 1069 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"NHLBI TOPMed: GOLDN Epigenetic Determinants of Lipid Response to Dietary Fat and Fenofibrate","short_name":"GOLDN_DS-CVD-IRB","commons":"BioData Catalyst","study_url":"https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001359.v3.p1","_subjects_count":959,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs001368.v3.p2.c1":{"gen3_discovery":{"authz":"","tags":[],"_unique_id":"phs001368.v3.p2.c1","study_id":"phs001368.v3.p2.c1","study_description":"","full_name":"","short_name":"","commons":"BioData Catalyst","study_url":"","_subjects_count":0,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs001368.v3.p2.c2":{"gen3_discovery":{"authz":"","tags":[],"_unique_id":"phs001368.v3.p2.c2","study_id":"phs001368.v3.p2.c2","study_description":"","full_name":"","short_name":"","commons":"BioData Catalyst","study_url":"","_subjects_count":0,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs001368.v3.p2.c4":{"gen3_discovery":{"authz":"","tags":[],"_unique_id":"phs001368.v3.p2.c4","study_id":"phs001368.v3.p2.c4","study_description":"","full_name":"","short_name":"","commons":"BioData Catalyst","study_url":"","_subjects_count":0,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs001368.v4.p2.c1":{"gen3_discovery":{"authz":"/programs/topmed/projects/CHS_HMB-MDS","tags":[],"_unique_id":"phs001368.v4.p2.c1","study_id":"phs001368.v4.p2.c1","study_description":"This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed) Whole Genome Sequencing Program. TOPMed is part of a broader Precision Medicine Initiative, which aims to provide disease treatments that are tailored to an individual's unique genes and environment. TOPMed will contribute to this initiative through the integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles, protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental, and clinical data. In doing so, this program aims to uncover factors that increase or decrease the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized treatments. Two genotype call sets derived from WGS are now available, Freeze 9b (GRCh38) and Freeze 10b (GRCh38), with largely overlapping sample sets. Information about how to identify other TOPMed WGS accessions for cross-study analysis, as well as descriptions of TOPMed methods of data acquisition, data processing and quality control, are provided in the accompanying documents, \"TOPMed Whole Genome Sequencing Project - Freeze 9b, Phases 1-4\" and \"TOPMed Whole Genome Sequencing Project - Freeze 10b, Phases 1-8\". Please check the study list at the top of each of these methods documents to determine whether it applies to this study accession. Participants from the Cardiovascular Health Study (CHS), a large population-based longitudinal cohort study (phs000287), have been included in the TOPMed project. Whole genome sequencing will be performed to contribute to multiple analyses, including cardiovascular disease risk factors, subclinical disease measures, the occurrence of myocardial infarction (MI) and stroke, and analyses of venous thromboembolism (VTE).Comprehensive phenotypic and pedigree data for study participants are available through dbGaP phs000287. Study Weblinks: CHS-NHLBI Study Design: Prospective Longitudinal Cohort Study Type: Longitudinal dbGaP estimated ancestry using GRAF-pop Total number of consented subjects: 4877 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"NHLBI TOPMed: Trans-Omics for Precision Medicine (TOPMed) Whole Genome Sequencing Project: Cardiovascular Health Study","short_name":"CHS_HMB-MDS","commons":"BioData Catalyst","study_url":"","_subjects_count":4743,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs001368.v4.p2.c2":{"gen3_discovery":{"authz":"/programs/topmed/projects/CHS_HMB-NPU-MDS","tags":[],"_unique_id":"phs001368.v4.p2.c2","study_id":"phs001368.v4.p2.c2","study_description":"This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed) Whole Genome Sequencing Program. TOPMed is part of a broader Precision Medicine Initiative, which aims to provide disease treatments that are tailored to an individual's unique genes and environment. TOPMed will contribute to this initiative through the integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles, protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental, and clinical data. In doing so, this program aims to uncover factors that increase or decrease the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized treatments. Two genotype call sets derived from WGS are now available, Freeze 9b (GRCh38) and Freeze 10b (GRCh38), with largely overlapping sample sets. Information about how to identify other TOPMed WGS accessions for cross-study analysis, as well as descriptions of TOPMed methods of data acquisition, data processing and quality control, are provided in the accompanying documents, \"TOPMed Whole Genome Sequencing Project - Freeze 9b, Phases 1-4\" and \"TOPMed Whole Genome Sequencing Project - Freeze 10b, Phases 1-8\". Please check the study list at the top of each of these methods documents to determine whether it applies to this study accession. Participants from the Cardiovascular Health Study (CHS), a large population-based longitudinal cohort study (phs000287), have been included in the TOPMed project. Whole genome sequencing will be performed to contribute to multiple analyses, including cardiovascular disease risk factors, subclinical disease measures, the occurrence of myocardial infarction (MI) and stroke, and analyses of venous thromboembolism (VTE).Comprehensive phenotypic and pedigree data for study participants are available through dbGaP phs000287. Study Weblinks: CHS-NHLBI Study Design: Prospective Longitudinal Cohort Study Type: Longitudinal dbGaP estimated ancestry using GRAF-pop Total number of consented subjects: 4877 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"NHLBI TOPMed: Trans-Omics for Precision Medicine (TOPMed) Whole Genome Sequencing Project: Cardiovascular Health Study","short_name":"CHS_HMB-NPU-MDS","commons":"BioData Catalyst","study_url":"","_subjects_count":130,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs001368.v4.p2.c3":{"gen3_discovery":{"authz":"/programs/topmed/projects/CHS_DS-CVD-MDS","tags":[],"_unique_id":"phs001368.v4.p2.c3","study_id":"phs001368.v4.p2.c3","study_description":"This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed) Whole Genome Sequencing Program. TOPMed is part of a broader Precision Medicine Initiative, which aims to provide disease treatments that are tailored to an individual's unique genes and environment. TOPMed will contribute to this initiative through the integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles, protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental, and clinical data. In doing so, this program aims to uncover factors that increase or decrease the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized treatments. Two genotype call sets derived from WGS are now available, Freeze 9b (GRCh38) and Freeze 10b (GRCh38), with largely overlapping sample sets. Information about how to identify other TOPMed WGS accessions for cross-study analysis, as well as descriptions of TOPMed methods of data acquisition, data processing and quality control, are provided in the accompanying documents, \"TOPMed Whole Genome Sequencing Project - Freeze 9b, Phases 1-4\" and \"TOPMed Whole Genome Sequencing Project - Freeze 10b, Phases 1-8\". Please check the study list at the top of each of these methods documents to determine whether it applies to this study accession. Participants from the Cardiovascular Health Study (CHS), a large population-based longitudinal cohort study (phs000287), have been included in the TOPMed project. Whole genome sequencing will be performed to contribute to multiple analyses, including cardiovascular disease risk factors, subclinical disease measures, the occurrence of myocardial infarction (MI) and stroke, and analyses of venous thromboembolism (VTE).Comprehensive phenotypic and pedigree data for study participants are available through dbGaP phs000287. Study Weblinks: CHS-NHLBI Study Design: Prospective Longitudinal Cohort Study Type: Longitudinal dbGaP estimated ancestry using GRAF-pop Total number of consented subjects: 4877 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"NHLBI TOPMed: Trans-Omics for Precision Medicine (TOPMed) Whole Genome Sequencing Project: Cardiovascular Health Study","short_name":"CHS_DS-CVD-MDS","commons":"BioData Catalyst","study_url":"","_subjects_count":1,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs001368.v4.p2.c4":{"gen3_discovery":{"authz":"/programs/topmed/projects/CHS_DS-CVD-NPU-MDS","tags":[],"_unique_id":"phs001368.v4.p2.c4","study_id":"phs001368.v4.p2.c4","study_description":"This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed) Whole Genome Sequencing Program. TOPMed is part of a broader Precision Medicine Initiative, which aims to provide disease treatments that are tailored to an individual's unique genes and environment. TOPMed will contribute to this initiative through the integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles, protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental, and clinical data. In doing so, this program aims to uncover factors that increase or decrease the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized treatments. Two genotype call sets derived from WGS are now available, Freeze 9b (GRCh38) and Freeze 10b (GRCh38), with largely overlapping sample sets. Information about how to identify other TOPMed WGS accessions for cross-study analysis, as well as descriptions of TOPMed methods of data acquisition, data processing and quality control, are provided in the accompanying documents, \"TOPMed Whole Genome Sequencing Project - Freeze 9b, Phases 1-4\" and \"TOPMed Whole Genome Sequencing Project - Freeze 10b, Phases 1-8\". Please check the study list at the top of each of these methods documents to determine whether it applies to this study accession. Participants from the Cardiovascular Health Study (CHS), a large population-based longitudinal cohort study (phs000287), have been included in the TOPMed project. Whole genome sequencing will be performed to contribute to multiple analyses, including cardiovascular disease risk factors, subclinical disease measures, the occurrence of myocardial infarction (MI) and stroke, and analyses of venous thromboembolism (VTE).Comprehensive phenotypic and pedigree data for study participants are available through dbGaP phs000287. Study Weblinks: CHS-NHLBI Study Design: Prospective Longitudinal Cohort Study Type: Longitudinal dbGaP estimated ancestry using GRAF-pop Total number of consented subjects: 4877 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"NHLBI TOPMed: Trans-Omics for Precision Medicine (TOPMed) Whole Genome Sequencing Project: Cardiovascular Health Study","short_name":"CHS_DS-CVD-NPU-MDS","commons":"BioData Catalyst","study_url":"","_subjects_count":3,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs001387.v3.p1.c3":{"gen3_discovery":{"authz":"/programs/topmed/projects/THRV_DS-CVD-IRB-COL-NPU-RD","tags":[{"name":"TOPMed","category":"Program"},{"name":"Genotype","category":"Data Type"},{"name":"Clinical Phenotype","category":"Data Type"},{"name":"dbGaP","category":"Study Registration"}],"_unique_id":"phs001387.v3.p1.c3","study_id":"phs001387.v3.p1.c3","study_description":"This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed) Whole Genome Sequencing Program. TOPMed is part of a broader Precision Medicine Initiative, which aims to provide disease treatments that are tailored to an individual's unique genes and environment. TOPMed will contribute to this initiative through the integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles, protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental, and clinical data. In doing so, this program aims to uncover factors that increase or decrease the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized treatments. Two genotype call sets derived from WGS are now available, Freeze 5b (GRCh38) and Freeze 8 (GRCh38), with largely overlapping sample sets. Information about how to identify other TOPMed WGS accessions for cross-study analysis, as well as descriptions of TOPMed methods of data acquisition, data processing and quality control, are provided in the accompanying documents, \"TOPMed Whole Genome Sequencing Project - Freeze 5b, Phases 1 and 2\" and \"TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4\". Please check the study list at the top of each of these methods documents to determine whether it applies to this study accession. The THRV-TOPMed study consists of three cohorts: The SAPPHIRe Family cohort (N=1,271), TSGH (Tri-Service General Hospital, a hospital-based cohort, N=160), and TCVGH (Taichung Veterans General Hospital, another hospital-based cohort, N=922), all based in Taiwan. 1,271 subjects were previously recruited as part of the NHLBI-sponsored SAPPHIRe Network (which is part of the Family Blood Pressure Program, FBPP). The SAPPHIRe families were recruited to have two or more hypertensive sibs, some families also with one normotensive/hypotensive sib. The two Hospital-based cohorts (TSGH and TCVGH) both recruited unrelated subjects with different recruitment criteria (matched with SAPPHIRe subjects for age, sex, and BMI category). Study Design: Prospective Longitudinal Cohort Study Type: Cohort dbGaP estimated ancestry using GRAF-pop Total number of consented subjects: 2353 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"NHLBI TOPMed: Rare Variants for Hypertension in Taiwan Chinese (THRV)","short_name":"THRV_DS-CVD-IRB-COL-NPU-RD","commons":"BioData Catalyst","study_url":"https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001387.v3.p1","_subjects_count":2329,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs001395.v2.p1.c1":{"gen3_discovery":{"authz":null,"tags":null,"_unique_id":"phs001395.v2.p1.c1","study_id":"phs001395.v2.p1.c1","study_description":null,"full_name":null,"short_name":null,"commons":"BioData Catalyst","study_url":null,"_subjects_count":0,"__manifest":null,"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs001395.v2.p1.c2":{"gen3_discovery":{"authz":null,"tags":null,"_unique_id":"phs001395.v2.p1.c2","study_id":"phs001395.v2.p1.c2","study_description":null,"full_name":null,"short_name":null,"commons":"BioData Catalyst","study_url":null,"_subjects_count":0,"__manifest":null,"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs001395.v3.p2.c1":{"gen3_discovery":{"authz":"/programs/topmed/projects/HCHS-SOL_HMB-NPU","tags":[],"_unique_id":"phs001395.v3.p2.c1","study_id":"phs001395.v3.p2.c1","study_description":"This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed) Whole Genome Sequencing Program. TOPMed is part of a broader Precision Medicine Initiative, which aims to provide disease treatments that are tailored to an individual's unique genes and environment. TOPMed will contribute to this initiative through the integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles, protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental, and clinical data. In doing so, this program aims to uncover factors that increase or decrease the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized treatments. Two genotype call sets derived from WGS are now available, Freeze 9b (GRCh38) and Freeze 10b (GRCh38), with largely overlapping sample sets. Information about how to identify other TOPMed WGS accessions for cross-study analysis, as well as descriptions of TOPMed methods of data acquisition, data processing and quality control, are provided in the accompanying documents, \"TOPMed Whole Genome Sequencing Project - Freeze 9b, Phases 1-4\" and \"TOPMed Whole Genome Sequencing Project - Freeze 10b, Phases 1-8\". Please check the study list at the top of each of these methods documents to determine whether it applies to this study accession. This study contains whole genome sequence data. A case-control sample of individuals from the Hispanic Community Health Study/Study of Latinos (HCHS/SOL), a multicenter prospective cohort study of 16,415 persons of Cuban, Dominican, Mexican, Puerto Rican, Central American, and South American background (phs000810), was selected for whole genome sequencing, including participants with a history of physician-diagnosed asthma and asthma-free participants. Study Weblinks: Hispanic Community Health Study / Study of Latinos NHLBI Trans-Omics for Precision Medicine Whole Genome Sequencing Program Study Design: Prospective Longitudinal Cohort Study Type: Cohort dbGaP estimated ancestry using GRAF-pop Total number of consented subjects: 8091 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"NHLBI TOPMed - NHGRI CCDG: Hispanic Community Health Study/Study of Latinos (HCHS/SOL)","short_name":"HCHS-SOL_HMB-NPU","commons":"BioData Catalyst","study_url":"","_subjects_count":1957,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs001395.v3.p2.c2":{"gen3_discovery":{"authz":"/programs/topmed/projects/HCHS-SOL_HMB","tags":[],"_unique_id":"phs001395.v3.p2.c2","study_id":"phs001395.v3.p2.c2","study_description":"This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed) Whole Genome Sequencing Program. TOPMed is part of a broader Precision Medicine Initiative, which aims to provide disease treatments that are tailored to an individual's unique genes and environment. TOPMed will contribute to this initiative through the integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles, protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental, and clinical data. In doing so, this program aims to uncover factors that increase or decrease the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized treatments. Two genotype call sets derived from WGS are now available, Freeze 9b (GRCh38) and Freeze 10b (GRCh38), with largely overlapping sample sets. Information about how to identify other TOPMed WGS accessions for cross-study analysis, as well as descriptions of TOPMed methods of data acquisition, data processing and quality control, are provided in the accompanying documents, \"TOPMed Whole Genome Sequencing Project - Freeze 9b, Phases 1-4\" and \"TOPMed Whole Genome Sequencing Project - Freeze 10b, Phases 1-8\". Please check the study list at the top of each of these methods documents to determine whether it applies to this study accession. This study contains whole genome sequence data. A case-control sample of individuals from the Hispanic Community Health Study/Study of Latinos (HCHS/SOL), a multicenter prospective cohort study of 16,415 persons of Cuban, Dominican, Mexican, Puerto Rican, Central American, and South American background (phs000810), was selected for whole genome sequencing, including participants with a history of physician-diagnosed asthma and asthma-free participants. Study Weblinks: Hispanic Community Health Study / Study of Latinos NHLBI Trans-Omics for Precision Medicine Whole Genome Sequencing Program Study Design: Prospective Longitudinal Cohort Study Type: Cohort dbGaP estimated ancestry using GRAF-pop Total number of consented subjects: 8091 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"NHLBI TOPMed - NHGRI CCDG: Hispanic Community Health Study/Study of Latinos (HCHS/SOL)","short_name":"HCHS-SOL_HMB","commons":"BioData Catalyst","study_url":"","_subjects_count":6134,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs001402.v2.p1.c1":{"gen3_discovery":{"authz":"","tags":[],"_unique_id":"phs001402.v2.p1.c1","study_id":"phs001402.v2.p1.c1","study_description":"","full_name":"","short_name":"","commons":"BioData Catalyst","study_url":"","_subjects_count":0,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs001402.v3.p1.c1":{"gen3_discovery":{"authz":"/programs/topmed/projects/Mayo_VTE_GRU","tags":[],"_unique_id":"phs001402.v3.p1.c1","study_id":"phs001402.v3.p1.c1","study_description":"This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed) Whole Genome Sequencing Program. TOPMed is part of a broader Precision Medicine Initiative, which aims to provide disease treatments that are tailored to an individual's unique genes and environment. TOPMed will contribute to this initiative through the integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles, protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental, and clinical data. In doing so, this program aims to uncover factors that increase or decrease the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized treatments. Two genotype call sets derived from WGS are now available, Freeze 8 (GRCh38) and Freeze 9b (GRCh38), with largely overlapping sample sets. Information about how to identify other TOPMed WGS accessions for cross-study analysis, as well as descriptions of TOPMed methods of data acquisition, data processing and quality control, are provided in the accompanying documents, \"TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4\" and \"TOPMed Whole Genome Sequencing Project - Freeze 9b, Phases 1-4\". Please check the study list at the top of each of these methods documents to determine whether it applies to this study accession. This study consists of 338 VTE cases from an inception cohort of Olmsted County, MN residents (OC) with a first lifetime objectively-diagnosed idiopathic VTE during the 40-year study period, 1966-2005. All living study subjects were invited to provide a whole blood sample at the Mayo Clinical Research Unit for leukocyte genomic DNA and plasma collection. For living study subjects who did not provide a blood sample, we retrieved any leftover blood (\"waste\" blood) from samples collected as part of routine clinical diagnostic testing and used this to extract DNA after obtaining patient consent. For deceased cases, with IRB approval, we extracted DNA from any available stored tissue within the Mayo Tissue Archive. This \"tissue\" DNA has been successfully genotyped in prior studies. Three trained and experienced study nurse abstractors reviewed the complete medical records in the community of all potential cases. Note: WGS sample IDs for the previous GENEVA study cases (phs000289) are included in this dataset. The phenotypes for the GENEVA study are located under the above phs number. Study Design: Case Set Study Type: Case Set dbGaP estimated ancestry using GRAF-pop Total number of consented subjects: 1535 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"NHLBI TOPMed: Whole Genome Sequencing of Venous Thromboembolism (WGS of VTE)","short_name":"Mayo_VTE_GRU","commons":"BioData Catalyst","study_url":"","_subjects_count":1535,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs001412.v3.p1.c1":{"gen3_discovery":{"authz":"/programs/topmed/projects/AACAC_HMB-IRB-COL-NPU","tags":[{"name":"TOPMed","category":"Program"},{"name":"Genotype","category":"Data Type"},{"name":"dbGaP","category":"Study Registration"}],"_unique_id":"phs001412.v3.p1.c1","study_id":"phs001412.v3.p1.c1","study_description":"This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed) Whole Genome Sequencing Program. TOPMed is part of a broader Precision Medicine Initiative, which aims to provide disease treatments that are tailored to an individual's unique genes and environment. TOPMed will contribute to this initiative through the integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles, protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental, and clinical data. In doing so, this program aims to uncover factors that increase or decrease the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized treatments. Two genotype call sets derived from WGS are now available, Freeze 8 (GRCh38) and Freeze 9b (GRCh38), with largely overlapping sample sets. Information about how to identify other TOPMed WGS accessions for cross-study analysis, as well as descriptions of TOPMed methods of data acquisition, data processing and quality control, are provided in the accompanying documents, \"TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4\" and \"TOPMed Whole Genome Sequencing Project - Freeze 9b, Phases 1-4\". Please check the study list at the top of each of these methods documents to determine whether it applies to this study accession. The Diabetes Heart Study (DHS) is a family-based study enriched for type 2 diabetes (T2D). The cohort included 1443 European American and African American participants from 564 families with multiple cases of type 2 diabetes (Bowden et al., 2010. Review of Diabetic Studies 7:188-201. PMID: 21409311). The cohort was recruited between 1998 and 2006. Participants were extensively phenotyped for measures of subclinical CVD and other known CVD risk factors. Primary outcomes were quantified burden of vascular calcified plaque in the coronary artery, carotid artery, and abdominal aorta all determined from non-contrast computed tomography scans. Study Design: Cross-Sectional Study Type: Cohort Cross-Sectional dbGaP estimated ancestry using GRAF-pop Total number of consented subjects: 405 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"NHLBI TOPMed: Diabetes Heart Study (DHS) African American Coronary Artery Calcification (AA CAC)","short_name":"AACAC_HMB-IRB-COL-NPU","commons":"BioData Catalyst","study_url":"https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001412.v3.p1","_subjects_count":400,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs001412.v3.p1.c2":{"gen3_discovery":{"authz":"/programs/topmed/projects/AACAC_DS-DHD-IRB-COL-NPU","tags":[{"name":"TOPMed","category":"Program"},{"name":"Genotype","category":"Data Type"},{"name":"dbGaP","category":"Study Registration"}],"_unique_id":"phs001412.v3.p1.c2","study_id":"phs001412.v3.p1.c2","study_description":"This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed) Whole Genome Sequencing Program. TOPMed is part of a broader Precision Medicine Initiative, which aims to provide disease treatments that are tailored to an individual's unique genes and environment. TOPMed will contribute to this initiative through the integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles, protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental, and clinical data. In doing so, this program aims to uncover factors that increase or decrease the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized treatments. Two genotype call sets derived from WGS are now available, Freeze 8 (GRCh38) and Freeze 9b (GRCh38), with largely overlapping sample sets. Information about how to identify other TOPMed WGS accessions for cross-study analysis, as well as descriptions of TOPMed methods of data acquisition, data processing and quality control, are provided in the accompanying documents, \"TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4\" and \"TOPMed Whole Genome Sequencing Project - Freeze 9b, Phases 1-4\". Please check the study list at the top of each of these methods documents to determine whether it applies to this study accession. The Diabetes Heart Study (DHS) is a family-based study enriched for type 2 diabetes (T2D). The cohort included 1443 European American and African American participants from 564 families with multiple cases of type 2 diabetes (Bowden et al., 2010. Review of Diabetic Studies 7:188-201. PMID: 21409311). The cohort was recruited between 1998 and 2006. Participants were extensively phenotyped for measures of subclinical CVD and other known CVD risk factors. Primary outcomes were quantified burden of vascular calcified plaque in the coronary artery, carotid artery, and abdominal aorta all determined from non-contrast computed tomography scans. Study Design: Cross-Sectional Study Type: Cohort Cross-Sectional dbGaP estimated ancestry using GRAF-pop Total number of consented subjects: 405 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"NHLBI TOPMed: Diabetes Heart Study (DHS) African American Coronary Artery Calcification (AA CAC)","short_name":"AACAC_DS-DHD-IRB-COL-NPU","commons":"BioData Catalyst","study_url":"https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001412.v3.p1","_subjects_count":3,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs001416.v3.p1.c1":{"gen3_discovery":{"authz":"","tags":[],"_unique_id":"phs001416.v3.p1.c1","study_id":"phs001416.v3.p1.c1","study_description":"","full_name":"","short_name":"","commons":"BioData Catalyst","study_url":"","_subjects_count":0,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs001416.v3.p1.c2":{"gen3_discovery":{"authz":"","tags":[],"_unique_id":"phs001416.v3.p1.c2","study_id":"phs001416.v3.p1.c2","study_description":"","full_name":"","short_name":"","commons":"BioData Catalyst","study_url":"","_subjects_count":0,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs001416.v4.p1.c1":{"gen3_discovery":{"authz":"/programs/topmed/projects/MESA_HMB","tags":[],"_unique_id":"phs001416.v4.p1.c1","study_id":"phs001416.v4.p1.c1","study_description":"This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed) Whole Genome Sequencing Program. TOPMed is part of a broader Precision Medicine Initiative, which aims to provide disease treatments that are tailored to an individual's unique genes and environment. TOPMed will contribute to this initiative through the integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles, protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental, and clinical data. In doing so, this program aims to uncover factors that increase or decrease the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized treatments. Two genotype call sets derived from WGS are now available, Freeze 9b (GRCh38) and Freeze 10b (GRCh38), with largely overlapping sample sets. Information about how to identify other TOPMed WGS accessions for cross-study analysis, as well as descriptions of TOPMed methods of data acquisition, data processing and quality control, are provided in the accompanying documents, \"TOPMed Whole Genome Sequencing Project - Freeze 9b, Phases 1-4\" and \"TOPMed Whole Genome Sequencing Project - Freeze 10b, Phases 1-8\". Please check the study list at the top of each of these methods documents to determine whether it applies to this study accession. The Multi-Ethnic Study of Atherosclerosis (MESA) is a study of the characteristics of subclinical cardiovascular disease (disease detected non-invasively before it has produced clinical signs and symptoms) and the risk factors that predict progression to clinically overt cardiovascular disease or progression of the subclinical disease. MESA researchers study a diverse, population-based sample of 6,814 asymptomatic men and women aged 45-84. Thirty-eight percent of the recruited participants are white, 28 percent African-American, 22 percent Hispanic, and 12 percent Asian, predominantly of Chinese descent. Comprehensive phenotypic and pedigree data for MESA study participants are available through dbGaP entry phs000209. MESA Participants were recruited from six field centers across the United States: Wake Forest University, Columbia University, Johns Hopkins University, University of Minnesota, Northwestern University and University of California - Los Angeles. Each participant received an extensive physical exam and determination of coronary calcification, ventricular mass and function, flow-mediated endothelial vasodilation, carotid intimal-medial wall thickness and presence of echogenic lucencies in the carotid artery, lower extremity vascular insufficiency, arterial wave forms, electrocardiographic (ECG) measures, standard coronary risk factors, sociodemographic factors, lifestyle factors, and psychosocial factors. Selected repetition of subclinical disease measures and risk factors at follow-up visits allows study of the progression of disease. Blood samples have been assayed for putative biochemical risk factors and stored for case-control studies. DNA has been extracted and lymphocytes cryopreserved (for possible immortalization) for study of candidate genes and possibly, genome-wide scanning, expression, and other genetic techniques. Participants are being followed for identification and characterization of cardiovascular disease events, including acute myocardial infarction and other forms of coronary heart disease (CHD), stroke, and congestive heart failure; for cardiovascular disease interventions; and for mortality. In addition to the six Field Centers, MESA involves a Coordinating Center, a Central Laboratory, and Central Reading Centers for Computed Tomography (CT), Magnetic Resonance Imaging (MRI), Ultrasound, and Electrocardiography (ECG). Protocol development, staff training, and pilot testing were performed in the first 18 months of the study. The first examination took place over two years, from July 2000 - July 2002. It was followed by five examination periods that were 17-20 months in length. Participants have been contacted every 9 to 12 months throughout the study to assess clinical morbidity and mortality. MESA Family The general goal of the MESA Family Study, an ancillary study to MESA funded by a grant from NHLBI, is to apply modern genetic analysis and genotyping methodologies to delineate the genetic determinants of early atherosclerosis. This is being accomplished by utilizing all the current organizational structures of the Multi-Ethnic Study of Atherosclerosis (MESA) and Genetic Centers at Cedars-Sinai Medical Center and University of Virginia. In the MESA Family Study, the goal is to locate and identify genes contributing to the genetic risk for cardiovascular disease (CVD), by looking at the early changes of atherosclerosis within families (mainly siblings). 2128 individuals from 594 families, yielding 3,026 sibpairs divided between African Americans and Hispanic-Americans, were recruited by utilizing the existing framework of MESA. MESA Family studied siblings of index subjects from the MESA study and from new sibpair families (with the same demographic characteristics) and is determining the extent of genetic contribution to the variation in coronary calcium (obtained via CT Scan) and carotid artery wall thickness (B-mode ultrasound) in the two largest non-majority U.S. populations. In a small proportion of subjects, parents of MESA index subjects participating in MESA Family were studied but only to have blood drawn for genotyping. The MESA Family cohort was recruited from the six MESA Field Centers. MESA Family participants underwent the same examination as MESA participants during May 2004 - May 2007. DNA was extracted and lymphocytes immortalized for study of candidate genes, genome-wide linkage scanning, and analyzed for linkage with these subclinical cardiovascular traits. While linkage analysis is the primary approach being used, an additional aspect of the MESA Family Study takes advantage of the existing MESA study population for testing a variety of candidate genes for association with the same subclinical traits. Genotyping and data analysis will occur throughout the study. Study Weblinks: MESA Study Design: Prospective Longitudinal Cohort Study Type: Family Longitudinal dbGaP estimated ancestry using GRAF-pop Total number of consented subjects: 7888 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"NHLBI TOPMed: MESA and MESA Family AA-CAC","short_name":"MESA_HMB","commons":"BioData Catalyst","study_url":"","_subjects_count":7068,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs001416.v4.p1.c2":{"gen3_discovery":{"authz":"/programs/topmed/projects/MESA_HMB-NPU","tags":[],"_unique_id":"phs001416.v4.p1.c2","study_id":"phs001416.v4.p1.c2","study_description":"This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed) Whole Genome Sequencing Program. TOPMed is part of a broader Precision Medicine Initiative, which aims to provide disease treatments that are tailored to an individual's unique genes and environment. TOPMed will contribute to this initiative through the integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles, protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental, and clinical data. In doing so, this program aims to uncover factors that increase or decrease the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized treatments. Two genotype call sets derived from WGS are now available, Freeze 9b (GRCh38) and Freeze 10b (GRCh38), with largely overlapping sample sets. Information about how to identify other TOPMed WGS accessions for cross-study analysis, as well as descriptions of TOPMed methods of data acquisition, data processing and quality control, are provided in the accompanying documents, \"TOPMed Whole Genome Sequencing Project - Freeze 9b, Phases 1-4\" and \"TOPMed Whole Genome Sequencing Project - Freeze 10b, Phases 1-8\". Please check the study list at the top of each of these methods documents to determine whether it applies to this study accession. The Multi-Ethnic Study of Atherosclerosis (MESA) is a study of the characteristics of subclinical cardiovascular disease (disease detected non-invasively before it has produced clinical signs and symptoms) and the risk factors that predict progression to clinically overt cardiovascular disease or progression of the subclinical disease. MESA researchers study a diverse, population-based sample of 6,814 asymptomatic men and women aged 45-84. Thirty-eight percent of the recruited participants are white, 28 percent African-American, 22 percent Hispanic, and 12 percent Asian, predominantly of Chinese descent. Comprehensive phenotypic and pedigree data for MESA study participants are available through dbGaP entry phs000209. MESA Participants were recruited from six field centers across the United States: Wake Forest University, Columbia University, Johns Hopkins University, University of Minnesota, Northwestern University and University of California - Los Angeles. Each participant received an extensive physical exam and determination of coronary calcification, ventricular mass and function, flow-mediated endothelial vasodilation, carotid intimal-medial wall thickness and presence of echogenic lucencies in the carotid artery, lower extremity vascular insufficiency, arterial wave forms, electrocardiographic (ECG) measures, standard coronary risk factors, sociodemographic factors, lifestyle factors, and psychosocial factors. Selected repetition of subclinical disease measures and risk factors at follow-up visits allows study of the progression of disease. Blood samples have been assayed for putative biochemical risk factors and stored for case-control studies. DNA has been extracted and lymphocytes cryopreserved (for possible immortalization) for study of candidate genes and possibly, genome-wide scanning, expression, and other genetic techniques. Participants are being followed for identification and characterization of cardiovascular disease events, including acute myocardial infarction and other forms of coronary heart disease (CHD), stroke, and congestive heart failure; for cardiovascular disease interventions; and for mortality. In addition to the six Field Centers, MESA involves a Coordinating Center, a Central Laboratory, and Central Reading Centers for Computed Tomography (CT), Magnetic Resonance Imaging (MRI), Ultrasound, and Electrocardiography (ECG). Protocol development, staff training, and pilot testing were performed in the first 18 months of the study. The first examination took place over two years, from July 2000 - July 2002. It was followed by five examination periods that were 17-20 months in length. Participants have been contacted every 9 to 12 months throughout the study to assess clinical morbidity and mortality. MESA Family The general goal of the MESA Family Study, an ancillary study to MESA funded by a grant from NHLBI, is to apply modern genetic analysis and genotyping methodologies to delineate the genetic determinants of early atherosclerosis. This is being accomplished by utilizing all the current organizational structures of the Multi-Ethnic Study of Atherosclerosis (MESA) and Genetic Centers at Cedars-Sinai Medical Center and University of Virginia. In the MESA Family Study, the goal is to locate and identify genes contributing to the genetic risk for cardiovascular disease (CVD), by looking at the early changes of atherosclerosis within families (mainly siblings). 2128 individuals from 594 families, yielding 3,026 sibpairs divided between African Americans and Hispanic-Americans, were recruited by utilizing the existing framework of MESA. MESA Family studied siblings of index subjects from the MESA study and from new sibpair families (with the same demographic characteristics) and is determining the extent of genetic contribution to the variation in coronary calcium (obtained via CT Scan) and carotid artery wall thickness (B-mode ultrasound) in the two largest non-majority U.S. populations. In a small proportion of subjects, parents of MESA index subjects participating in MESA Family were studied but only to have blood drawn for genotyping. The MESA Family cohort was recruited from the six MESA Field Centers. MESA Family participants underwent the same examination as MESA participants during May 2004 - May 2007. DNA was extracted and lymphocytes immortalized for study of candidate genes, genome-wide linkage scanning, and analyzed for linkage with these subclinical cardiovascular traits. While linkage analysis is the primary approach being used, an additional aspect of the MESA Family Study takes advantage of the existing MESA study population for testing a variety of candidate genes for association with the same subclinical traits. Genotyping and data analysis will occur throughout the study. Study Weblinks: MESA Study Design: Prospective Longitudinal Cohort Study Type: Family Longitudinal dbGaP estimated ancestry using GRAF-pop Total number of consented subjects: 7888 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"NHLBI TOPMed: MESA and MESA Family AA-CAC","short_name":"MESA_HMB-NPU","commons":"BioData Catalyst","study_url":"","_subjects_count":820,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs001434.v2.p1.c1":{"gen3_discovery":{"authz":"/programs/topmed/projects/miRhythm_GRU","tags":[{"name":"TOPMed","category":"Program"},{"name":"Genotype","category":"Data Type"},{"name":"Clinical Phenotype","category":"Data Type"},{"name":"dbGaP","category":"Study Registration"}],"_unique_id":"phs001434.v2.p1.c1","study_id":"phs001434.v2.p1.c1","study_description":"This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed) Whole Genome Sequencing Program. TOPMed is part of a broader Precision Medicine Initiative, which aims to provide disease treatments that are tailored to an individual's unique genes and environment. TOPMed will contribute to this initiative through the integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles, protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental, and clinical data. In doing so, this program aims to uncover factors that increase or decrease the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized treatments. Two genotype call sets derived from WGS are now available, Freeze 8 (GRCh38) and Freeze 9b (GRCh38), with largely overlapping sample sets. Information about how to identify other TOPMed WGS accessions for cross-study analysis, as well as descriptions of TOPMed methods of data acquisition, data processing and quality control, are provided in the accompanying documents, \"TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4\" and \"TOPMed Whole Genome Sequencing Project - Freeze 9b, Phases 1-4\". Please check the study list at the top of each of these methods documents to determine whether it applies to this study accession. The UMMS miRhythm Study is an ongoing study of adult patients undergoing an elective electrophysiology study or arrhythmia ablation procedure for a supraventricular or ventricular arrhythmia, including atrial fibrillation (AF). Atrial fibrillation is a major clinical and public health problem that is related to atrial pathologic remodeling. Few tools are available to quantify the activity or extent of this remodeling, rendering it difficult to identify individuals at risk for AF. Previous studies have suggested an important role for miRNA in cardiovascular disease through gene expression regulation, making this a promising avenue for studying AF mechanisms. The aim of the study is to determine the time-dependent changes to key circulating miRNAs in a model of planned atrial injury and remodeling via ablation. Such knowledge might provide additional insight into the biology and activity of the acute atrial injury response, and furthermore, inform new targets for development of preventative interventions or allow for better AF risk stratification. To assess pathways regulating atrial pathological remodeling, patient blood samples are collected prior to their ablation procedures and also at a regularly scheduled 1-month follow-up appointment. Plasma expression of miRNA is measured using high-throughput quantitative reverse transcriptase polymerase chain reaction (RT-qPCR), providing novel insights into the regulatory processes underlying AF, as well as acute atrial injury in vivo. Additionally, data collected from whole-genome sequencing (WGS) is used to supplement miRNA analyses and further explore new relations between genes and abnormal heart rhythm. Study Design: Case Set Study Type: Case Set dbGaP estimated ancestry using GRAF-pop Total number of consented subjects: 65 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"NHLBI TOPMed: Defining the Time-Dependent Genetic and Transcriptomic Responses to Cardiac Injury Among Patients with Arrhythmias","short_name":"miRhythm_GRU","commons":"BioData Catalyst","study_url":"https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001434.v2.p1","_subjects_count":65,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs001435.v2.p1.c1":{"gen3_discovery":{"authz":"/programs/topmed/projects/AustralianFamilialAF_HMB-NPU-MDS","tags":[{"name":"TOPMed","category":"Program"},{"name":"Genotype","category":"Data Type"},{"name":"Clinical Phenotype","category":"Data Type"},{"name":"dbGaP","category":"Study Registration"}],"_unique_id":"phs001435.v2.p1.c1","study_id":"phs001435.v2.p1.c1","study_description":"This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed) Whole Genome Sequencing Program. TOPMed is part of a broader Precision Medicine Initiative, which aims to provide disease treatments that are tailored to an individual's unique genes and environment. TOPMed will contribute to this initiative through the integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles, protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental, and clinical data. In doing so, this program aims to uncover factors that increase or decrease the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized treatments. Two genotype call sets derived from WGS are now available, Freeze 8 (GRCh38) and Freeze 9b (GRCh38), with largely overlapping sample sets. Information about how to identify other TOPMed WGS accessions for cross-study analysis, as well as descriptions of TOPMed methods of data acquisition, data processing and quality control, are provided in the accompanying documents, \"TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4\" and \"TOPMed Whole Genome Sequencing Project - Freeze 9b, Phases 1-4\". Please check the study list at the top of each of these methods documents to determine whether it applies to this study accession. In the Australian Familial AF Study, a cohort of probands with familial AF was recruited for genetics studies at the Victor Chang Cardiac Research Institute. Familial AF cases were identified from in-patient and out-patient populations at St. Vincent's Hospital and by referral from collaborating physicians throughout Australia. Study subjects underwent clinical evaluation with history, ECG and echocardiogram, and informed consent was obtained from all participants. 151 probands aged <66 years at the time of diagnosis were included in this analysis. The control cohort was comprised of age- and sex-matched individuals (n=151) who had no history of cardiovascular disease. In the current TOPMed study, we have performed whole genome sequencing in European Ancestry cases with early-onset atrial fibrillation (defined as atrial fibrillation onset prior to 61 years). Study Design: Case Set Study Type: Case Set dbGaP estimated ancestry using GRAF-pop Total number of consented subjects: 120 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"NHLBI TOPMed: Australian Familial Atrial Fibrillation Study","short_name":"AustralianFamilialAF_HMB-NPU-MDS","commons":"BioData Catalyst","study_url":"https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001435.v2.p1","_subjects_count":120,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs001446.v3.p2.c1":{"gen3_discovery":{"authz":"/programs/topmed/projects/SARP_GRU","tags":[{"name":"TOPMed","category":"Program"},{"name":"Genotype","category":"Data Type"},{"name":"dbGaP","category":"Study Registration"}],"_unique_id":"phs001446.v3.p2.c1","study_id":"phs001446.v3.p2.c1","study_description":"This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed) Whole Genome Sequencing Program. TOPMed is part of a broader Precision Medicine Initiative, which aims to provide disease treatments that are tailored to an individual's unique genes and environment. TOPMed will contribute to this initiative through the integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles, protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental, and clinical data. In doing so, this program aims to uncover factors that increase or decrease the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized treatments. Two genotype call sets derived from WGS are now available, Freeze 9b (GRCh38) and Freeze 10b (GRCh38), with largely overlapping sample sets. Information about how to identify other TOPMed WGS accessions for cross-study analysis, as well as descriptions of TOPMed methods of data acquisition, data processing and quality control, are provided in the accompanying documents, \"TOPMed Whole Genome Sequencing Project - Freeze 9b, Phases 1-4\" and \"TOPMed Whole Genome Sequencing Project - Freeze 10b, Phases 1-8\". Please check the study list at the top of each of these methods documents to determine whether it applies to this study accession. The overall goal of the Severe Asthma Research Program (SARP) is to identify and characterize subjects with severe asthma to understand pathophysiologic mechanisms in severe asthma. Subjects with mild and moderate asthma were recruited for comparison but the program was enriched for subjects with severe asthma from multiple centers. Subjects were comprehensively phenotyped for asthma related traits including lung function, atopy, questionnaires on medical and family history, exhaled nitric oxide and health care utilization including exacerbations and symptoms. Asthma is a heterogenous disease. Cluster analysis in SARP has shown multiple subphenotypes and endotypes. Study Design: Case Set Study Type: Case Set dbGaP estimated ancestry using GRAF-pop Total number of consented subjects: 1882 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"NHLBI TOPMed: Severe Asthma Research Program (SARP)","short_name":"SARP_GRU","commons":"BioData Catalyst","study_url":"https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001446.v3.p2","_subjects_count":1188,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs001446.v3.p2.c2":{"gen3_discovery":{"authz":"/programs/topmed/projects/SARP_DS-AAI-PUB","tags":[{"name":"TOPMed","category":"Program"},{"name":"Genotype","category":"Data Type"},{"name":"dbGaP","category":"Study Registration"}],"_unique_id":"phs001446.v3.p2.c2","study_id":"phs001446.v3.p2.c2","study_description":"This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed) Whole Genome Sequencing Program. TOPMed is part of a broader Precision Medicine Initiative, which aims to provide disease treatments that are tailored to an individual's unique genes and environment. TOPMed will contribute to this initiative through the integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles, protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental, and clinical data. In doing so, this program aims to uncover factors that increase or decrease the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized treatments. Two genotype call sets derived from WGS are now available, Freeze 9b (GRCh38) and Freeze 10b (GRCh38), with largely overlapping sample sets. Information about how to identify other TOPMed WGS accessions for cross-study analysis, as well as descriptions of TOPMed methods of data acquisition, data processing and quality control, are provided in the accompanying documents, \"TOPMed Whole Genome Sequencing Project - Freeze 9b, Phases 1-4\" and \"TOPMed Whole Genome Sequencing Project - Freeze 10b, Phases 1-8\". Please check the study list at the top of each of these methods documents to determine whether it applies to this study accession. The overall goal of the Severe Asthma Research Program (SARP) is to identify and characterize subjects with severe asthma to understand pathophysiologic mechanisms in severe asthma. Subjects with mild and moderate asthma were recruited for comparison but the program was enriched for subjects with severe asthma from multiple centers. Subjects were comprehensively phenotyped for asthma related traits including lung function, atopy, questionnaires on medical and family history, exhaled nitric oxide and health care utilization including exacerbations and symptoms. Asthma is a heterogenous disease. Cluster analysis in SARP has shown multiple subphenotypes and endotypes. Study Design: Case Set Study Type: Case Set dbGaP estimated ancestry using GRAF-pop Total number of consented subjects: 1882 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"NHLBI TOPMed: Severe Asthma Research Program (SARP)","short_name":"SARP_DS-AAI-PUB","commons":"BioData Catalyst","study_url":"https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001446.v3.p2","_subjects_count":671,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs001466.v2.p1.c1":{"gen3_discovery":{"authz":"/programs/topmed/projects/pharmHU_HMB","tags":[{"name":"TOPMed","category":"Program"},{"name":"Genotype","category":"Data Type"},{"name":"Clinical Phenotype","category":"Data Type"},{"name":"dbGaP","category":"Study Registration"}],"_unique_id":"phs001466.v2.p1.c1","study_id":"phs001466.v2.p1.c1","study_description":"This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed) Whole Genome Sequencing Program. TOPMed is part of a broader Precision Medicine Initiative, which aims to provide disease treatments that are tailored to an individual's unique genes and environment. TOPMed will contribute to this initiative through the integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles, protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental, and clinical data. In doing so, this program aims to uncover factors that increase or decrease the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized treatments. Two genotype call sets derived from WGS are now available, Freeze 8 (GRCh38) and Freeze 9b (GRCh38), with largely overlapping sample sets. Information about how to identify other TOPMed WGS accessions for cross-study analysis, as well as descriptions of TOPMed methods of data acquisition, data processing and quality control, are provided in the accompanying documents, \"TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4\" and \"TOPMed Whole Genome Sequencing Project - Freeze 9b, Phases 1-4\". Please check the study list at the top of each of these methods documents to determine whether it applies to this study accession. Sickle cell disease (SCD) is characterized by the presence of sickle hemoglobin (HbS) within circulating erythrocytes resulting in hemolytic anemia, vascular occlusion, and end organ damage due to alterations in the shape and deformability of the cell membrane. The disease is inherited in an autosomal recessive pattern, and is most commonly caused by a single nucleotide substitution in the hemoglobin subunit beta (HBB) gene located on chromosome 11. Participants in this study include children with SCD treated with hydroxyurea to pharmacologically increase fetal hemoglobin (HbF) levels and reduce disease severity. Therefore, the primary phenotype of interest in this study is the change in HbF levels in response to hydroxyurea treatment. Genetic factors have been shown to influence inter-individual variation in drug response, and identification of novel genes and variants associated with clinical outcomes in SCD will be achieved through collaboration between Baylor College of Medicine, Augusta University, Columbia University Medical Center, Emory University School of Medicine and Children's Healthcare of Atlanta, and St. Jude Children's Research Hospital. The NHLBI TOPMed Program is designed to generate scientific resources to enhance understanding of fundamental biological processes that underlie heart, lung, blood and sleep disorders (HLBS). It is part of a broader Precision Medicine Initiative, which aims to provide disease treatments that are tailored to an individual's unique genes and environment. Study Design: Case Set Study Type: Case Set dbGaP estimated ancestry using GRAF-pop Total number of consented subjects: 900 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"NHLBI TOPMed: Pharmacogenomics of Hydroxyurea in Sickle Cell Disease (PharmHU)","short_name":"pharmHU_HMB","commons":"BioData Catalyst","study_url":"https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001466.v2.p1","_subjects_count":740,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs001466.v2.p1.c2":{"gen3_discovery":{"authz":"/programs/topmed/projects/pharmHU_DS-SCD-RD","tags":[{"name":"TOPMed","category":"Program"},{"name":"Genotype","category":"Data Type"},{"name":"Clinical Phenotype","category":"Data Type"},{"name":"dbGaP","category":"Study Registration"}],"_unique_id":"phs001466.v2.p1.c2","study_id":"phs001466.v2.p1.c2","study_description":"This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed) Whole Genome Sequencing Program. TOPMed is part of a broader Precision Medicine Initiative, which aims to provide disease treatments that are tailored to an individual's unique genes and environment. TOPMed will contribute to this initiative through the integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles, protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental, and clinical data. In doing so, this program aims to uncover factors that increase or decrease the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized treatments. Two genotype call sets derived from WGS are now available, Freeze 8 (GRCh38) and Freeze 9b (GRCh38), with largely overlapping sample sets. Information about how to identify other TOPMed WGS accessions for cross-study analysis, as well as descriptions of TOPMed methods of data acquisition, data processing and quality control, are provided in the accompanying documents, \"TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4\" and \"TOPMed Whole Genome Sequencing Project - Freeze 9b, Phases 1-4\". Please check the study list at the top of each of these methods documents to determine whether it applies to this study accession. Sickle cell disease (SCD) is characterized by the presence of sickle hemoglobin (HbS) within circulating erythrocytes resulting in hemolytic anemia, vascular occlusion, and end organ damage due to alterations in the shape and deformability of the cell membrane. The disease is inherited in an autosomal recessive pattern, and is most commonly caused by a single nucleotide substitution in the hemoglobin subunit beta (HBB) gene located on chromosome 11. Participants in this study include children with SCD treated with hydroxyurea to pharmacologically increase fetal hemoglobin (HbF) levels and reduce disease severity. Therefore, the primary phenotype of interest in this study is the change in HbF levels in response to hydroxyurea treatment. Genetic factors have been shown to influence inter-individual variation in drug response, and identification of novel genes and variants associated with clinical outcomes in SCD will be achieved through collaboration between Baylor College of Medicine, Augusta University, Columbia University Medical Center, Emory University School of Medicine and Children's Healthcare of Atlanta, and St. Jude Children's Research Hospital. The NHLBI TOPMed Program is designed to generate scientific resources to enhance understanding of fundamental biological processes that underlie heart, lung, blood and sleep disorders (HLBS). It is part of a broader Precision Medicine Initiative, which aims to provide disease treatments that are tailored to an individual's unique genes and environment. Study Design: Case Set Study Type: Case Set dbGaP estimated ancestry using GRAF-pop Total number of consented subjects: 900 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"NHLBI TOPMed: Pharmacogenomics of Hydroxyurea in Sickle Cell Disease (PharmHU)","short_name":"pharmHU_DS-SCD-RD","commons":"BioData Catalyst","study_url":"https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001466.v2.p1","_subjects_count":43,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs001466.v2.p1.c3":{"gen3_discovery":{"authz":"/programs/topmed/projects/pharmHU_DS-SCD","tags":[{"name":"TOPMed","category":"Program"},{"name":"Genotype","category":"Data Type"},{"name":"Clinical Phenotype","category":"Data Type"},{"name":"dbGaP","category":"Study Registration"}],"_unique_id":"phs001466.v2.p1.c3","study_id":"phs001466.v2.p1.c3","study_description":"This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed) Whole Genome Sequencing Program. TOPMed is part of a broader Precision Medicine Initiative, which aims to provide disease treatments that are tailored to an individual's unique genes and environment. TOPMed will contribute to this initiative through the integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles, protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental, and clinical data. In doing so, this program aims to uncover factors that increase or decrease the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized treatments. Two genotype call sets derived from WGS are now available, Freeze 8 (GRCh38) and Freeze 9b (GRCh38), with largely overlapping sample sets. Information about how to identify other TOPMed WGS accessions for cross-study analysis, as well as descriptions of TOPMed methods of data acquisition, data processing and quality control, are provided in the accompanying documents, \"TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4\" and \"TOPMed Whole Genome Sequencing Project - Freeze 9b, Phases 1-4\". Please check the study list at the top of each of these methods documents to determine whether it applies to this study accession. Sickle cell disease (SCD) is characterized by the presence of sickle hemoglobin (HbS) within circulating erythrocytes resulting in hemolytic anemia, vascular occlusion, and end organ damage due to alterations in the shape and deformability of the cell membrane. The disease is inherited in an autosomal recessive pattern, and is most commonly caused by a single nucleotide substitution in the hemoglobin subunit beta (HBB) gene located on chromosome 11. Participants in this study include children with SCD treated with hydroxyurea to pharmacologically increase fetal hemoglobin (HbF) levels and reduce disease severity. Therefore, the primary phenotype of interest in this study is the change in HbF levels in response to hydroxyurea treatment. Genetic factors have been shown to influence inter-individual variation in drug response, and identification of novel genes and variants associated with clinical outcomes in SCD will be achieved through collaboration between Baylor College of Medicine, Augusta University, Columbia University Medical Center, Emory University School of Medicine and Children's Healthcare of Atlanta, and St. Jude Children's Research Hospital. The NHLBI TOPMed Program is designed to generate scientific resources to enhance understanding of fundamental biological processes that underlie heart, lung, blood and sleep disorders (HLBS). It is part of a broader Precision Medicine Initiative, which aims to provide disease treatments that are tailored to an individual's unique genes and environment. Study Design: Case Set Study Type: Case Set dbGaP estimated ancestry using GRAF-pop Total number of consented subjects: 900 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"NHLBI TOPMed: Pharmacogenomics of Hydroxyurea in Sickle Cell Disease (PharmHU)","short_name":"pharmHU_DS-SCD","commons":"BioData Catalyst","study_url":"https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001466.v2.p1","_subjects_count":100,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs001467.v2.p1.c1":{"gen3_discovery":{"authz":"","tags":[],"_unique_id":"phs001467.v2.p1.c1","study_id":"phs001467.v2.p1.c1","study_description":"","full_name":"","short_name":"","commons":"BioData Catalyst","study_url":"","_subjects_count":0,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs001467.v2.p2.c1":{"gen3_discovery":{"authz":"/programs/topmed/projects/SAPPHIRE_asthma_HMB-COL","tags":[{"name":"TOPMed","category":"Program"},{"name":"Genotype","category":"Data Type"},{"name":"dbGaP","category":"Study Registration"}],"_unique_id":"phs001467.v2.p2.c1","study_id":"phs001467.v2.p2.c1","study_description":"This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed) Whole Genome Sequencing Program. TOPMed is part of a broader Precision Medicine Initiative, which aims to provide disease treatments that are tailored to an individual's unique genes and environment. TOPMed will contribute to this initiative through the integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles, protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental, and clinical data. In doing so, this program aims to uncover factors that increase or decrease the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized treatments. Two genotype call sets derived from WGS are now available, Freeze 8 (GRCh38) and Freeze 9b (GRCh38), with largely overlapping sample sets. Information about how to identify other TOPMed WGS accessions for cross-study analysis, as well as descriptions of TOPMed methods of data acquisition, data processing and quality control, are provided in the accompanying documents, \"TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4\" and \"TOPMed Whole Genome Sequencing Project - Freeze 9b, Phases 1-4\". Please check the study list at the top of each of these methods documents to determine whether it applies to this study accession. Started in 2007, the Study of Asthma Phenotypes and Pharmacogenomic Interactions by Race-ethnicity (SAPPHIRE) is one of the largest asthma cohort studies in the United States. Its overarching goal is to elucidate the genetic underpinnings of asthma and asthma medication treatment response. The cohort was recruited from a large health care system serving southeast Michigan and the Detroit metropolitan area, and the participants broadly represent the demographic and socioeconomic diversity of the region. Control participants (i.e., patients without a diagnosis with asthma) were recruited from the same health system and geographic region. By virtue of their health system enrollment, both asthma case and control patients have longitudinal clinical information which was routinely collected as part of their care. Both case and control patients underwent at detailed evaluation at the time of enrollment which included lung function testing and bronchodilator response. The SAPPHIRE cohort is a member of the Asthma Translational Genomics Collaborative (ATGC). The latter was selected for whole genome sequencing in Phase 3 of the National Heart Lung and Blood Institute's TOPMed Program. The SAPPHIRE sample selected for sequencing includes African American and/or Latino individuals with and without asthma. Study Weblinks: Williams Lab - SAPPHIRE Study Design: Prospective Longitudinal Cohort Study Type: Case-Control Cohort dbGaP estimated ancestry using GRAF-pop Total number of consented subjects: 4857 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"NHLBI TOPMed: Study of Asthma Phenotypes and Pharmacogenomic Interactions by Race-Ethnicity (SAPPHIRE)","short_name":"SAPPHIRE_asthma_HMB-COL","commons":"BioData Catalyst","study_url":"https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001467.v2.p2","_subjects_count":4780,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs001468.v3.p1.c1":{"gen3_discovery":{"authz":"/programs/topmed/projects/REDS-III_Brazil_SCD_GRU-IRB-PUB-COL-NPU","tags":[{"name":"TOPMed","category":"Program"},{"name":"Genotype","category":"Data Type"},{"name":"dbGaP","category":"Study Registration"}],"_unique_id":"phs001468.v3.p1.c1","study_id":"phs001468.v3.p1.c1","study_description":"This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed) Whole Genome Sequencing Program. TOPMed is part of a broader Precision Medicine Initiative, which aims to provide disease treatments that are tailored to an individual's unique genes and environment. TOPMed will contribute to this initiative through the integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles, protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental, and clinical data. In doing so, this program aims to uncover factors that increase or decrease the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized treatments. Two genotype call sets derived from WGS are now available, Freeze 8 (GRCh38) and Freeze 9b (GRCh38), with largely overlapping sample sets. Information about how to identify other TOPMed WGS accessions for cross-study analysis, as well as descriptions of TOPMed methods of data acquisition, data processing and quality control, are provided in the accompanying documents, \"TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4\" and \"TOPMed Whole Genome Sequencing Project - Freeze 9b, Phases 1-4\". Please check the study list at the top of each of these methods documents to determine whether it applies to this study accession. Establishing a Brazilian Sickle Cell Disease Cohort and Identifying Molecular Determinants of Response to Transfusions, Genetic Determinants of Alloimmunization, and Risk Factors Associated with HIV Infection. The REDS-III Brazil SCD Cohort study focused on transfusion practices and predictors of health outcomes in patients with Sickle Cell Disease (SCD) and began in the Fall of 2013. The four primary aims of this study are: 1) Aim A - Establish a cohort of SCD patients with a comprehensive centralized electronic database of detailed clinical, laboratory and transfusion information, as well as establish a repository of blood samples to support biological studies relevant to SCD pathogenesis and transfusion complications; 2) Aim B - Characterize changes in markers of inflammation in response to transfusion by analyzing chemokine/cytokine panels in serial post transfusion specimens; 3) Aim C - Identify single nucleotide polymorphisms (SNPs) that contribute to the risk of red blood cell alloimmunization in SCD by performing a genome-wide association (GWA) study in transfused SCD patients; and, 4) Aim D - Characterize risk of HIV and HIV outcomes in the Brazilian SCD population and compare SCD outcomes among HIV sero-positive and sero-negative SCD patients. Patients are enrolled from six hospitals affiliated with the participating four REDS-III Brazil hemocenters. Study Weblinks: REDS-III Study Design: Prospective Longitudinal Cohort Study Type: Cohort dbGaP estimated ancestry using GRAF-pop Total number of consented subjects: 2795 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"NHLBI TOPMed: Recipient Epidemiology and Donor Evaluation Study-III Brazil Sickle Cell Disease Cohort (REDS-BSCDC)","short_name":"REDS-III_Brazil_SCD_GRU-IRB-PUB-COL-NPU","commons":"BioData Catalyst","study_url":"https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001468.v3.p1","_subjects_count":2630,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs001472.v2.p1.c1":{"gen3_discovery":{"authz":"","tags":[],"_unique_id":"phs001472.v2.p1.c1","study_id":"phs001472.v2.p1.c1","study_description":"","full_name":"","short_name":"","commons":"BioData Catalyst","study_url":"","_subjects_count":0,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs001472.v3.p2.c1":{"gen3_discovery":{"authz":"/programs/topmed/projects/ECLIPSE_DS-CS-MDS-RD","tags":[{"name":"TOPMed","category":"Program"},{"name":"Genotype","category":"Data Type"},{"name":"dbGaP","category":"Study Registration"}],"_unique_id":"phs001472.v3.p2.c1","study_id":"phs001472.v3.p2.c1","study_description":"This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed) Whole Genome Sequencing Program. TOPMed is part of a broader Precision Medicine Initiative, which aims to provide disease treatments that are tailored to an individual's unique genes and environment. TOPMed will contribute to this initiative through the integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles, protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental, and clinical data. In doing so, this program aims to uncover factors that increase or decrease the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized treatments. Two genotype call sets derived from WGS are now available, Freeze 9b (GRCh38) and Freeze 10b (GRCh38), with largely overlapping sample sets. Information about how to identify other TOPMed WGS accessions for cross-study analysis, as well as descriptions of TOPMed methods of data acquisition, data processing and quality control, are provided in the accompanying documents, \"TOPMed Whole Genome Sequencing Project - Freeze 9b, Phases 1-4\" and \"TOPMed Whole Genome Sequencing Project - Freeze 10b, Phases 1-8\". Please check the study list at the top of each of these methods documents to determine whether it applies to this study accession. ECLIPSE was a longitudinal observational study of 2164 COPD subjects and a smaller number of smoking controls (337) and nonsmoking controls (245) followed regularly for three years, with three chest CT scans (at baseline, one year, and three years) (Vestbo et al., 2008, PMID: 18216052). Subjects were enrolled at clinical centers in the US, Canada, Europe, and New Zealand. Inclusion criteria included subjects ages 40-75, at least 10 pack-years of smoking, and spirometry in GOLD grades 2-4 (COPD cases) or normal spirometry with post-bronchodilator FEV1 >85% (predicted) and FEV1/FVC>0.7 (controls). Study visits were performed at enrollment, three months, and every six months thereafter with spirometry, questionnaires, and other clinical evaluations. The ECLIPSE CT scans have been analyzed with the VIDA software for emphysema and airway phenotypes. ECLIPSE has provided key insights into the clinical epidemiology of COPD, including COPD exacerbations (Hurst, et. al., 2010, PMID: 20843247) and lung function decline in COPD (Vestbo, et. al., 2011, PMID: 21991892). ECLIPSE has been used in a number of genetic studies of COPD susceptibility and protein biomarkers (Faner, et. al., 2014, PMID: 24310110). Genome-wide gene expression microarray data are available in 147 induced sputum samples from COPD subjects and 248 peripheral blood samples from COPD and control subjects. Phenotype data for ECLIPSE subjects is available through dbGaP phs001252. Study Weblinks: What is ECLIPSE Study Design: Case-Control Study Type: Case-Control Longitudinal dbGaP estimated ancestry using GRAF-pop Total number of consented subjects: 2331 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"NHLBI TOPMed: Evaluation of COPD Longitudinally to Identify Predictive Surrogate Endpoints (ECLIPSE)","short_name":"ECLIPSE_DS-CS-MDS-RD","commons":"BioData Catalyst","study_url":"https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001472.v3.p2","_subjects_count":2356,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs001514.v1.p1.c1":{"gen3_discovery":{"authz":"","tags":[],"_unique_id":"phs001514.v1.p1.c1","study_id":"phs001514.v1.p1.c1","study_description":"","full_name":"","short_name":"","commons":"BioData Catalyst","study_url":"","_subjects_count":0,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs001514.v1.p1.c2":{"gen3_discovery":{"authz":"","tags":[],"_unique_id":"phs001514.v1.p1.c2","study_id":"phs001514.v1.p1.c2","study_description":"","full_name":"","short_name":"","commons":"BioData Catalyst","study_url":"","_subjects_count":0,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs001514.v2.p1.c1":{"gen3_discovery":{"authz":"/programs/topmed/projects/Walk_PHaSST_SCD_HMB-IRB-PUB-COL-NPU-MDS-GSO","tags":[{"name":"TOPMed","category":"Program"},{"name":"Genotype","category":"Data Type"},{"name":"Clinical Phenotype","category":"Data Type"},{"name":"dbGaP","category":"Study Registration"}],"_unique_id":"phs001514.v2.p1.c1","study_id":"phs001514.v2.p1.c1","study_description":"This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed) Whole Genome Sequencing Program. TOPMed is part of a broader Precision Medicine Initiative, which aims to provide disease treatments that are tailored to an individual's unique genes and environment. TOPMed will contribute to this initiative through the integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles, protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental, and clinical data. In doing so, this program aims to uncover factors that increase or decrease the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized treatments. Two genotype call sets derived from WGS are now available, Freeze 8 (GRCh38) and Freeze 9b (GRCh38), with largely overlapping sample sets. Information about how to identify other TOPMed WGS accessions for cross-study analysis, as well as descriptions of TOPMed methods of data acquisition, data processing and quality control, are provided in the accompanying documents, \"TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4\" and \"TOPMed Whole Genome Sequencing Project - Freeze 9b, Phases 1-4\". Please check the study list at the top of each of these methods documents to determine whether it applies to this study accession. Walk-PHaSST study is a multi-center clinical trial to evaluate the effects of sildenafil on Sickle Cell Disease (SCD) population with low exercise capacity associated with an increased Doppler-estimated pulmonary artery systolic pressure (as assessed by the tricuspid regurgitant velocity (TRV)). It is a double-blind, placebo-controlled trial to assess the safety, tolerability, and efficacy of sildenafil in patients with SCD who had both an elevated TRV and decreased exercise capacity. The screening phase of the study enrolled 720 subjects and 74 of them were randomized for the clinical trial. For the screening cohort, we have collected general demographics and race/ethnicity, hemoglobin genotype, physical examination, laboratory screening, transthoracic Doppler echocardiography, and 6 minute walk test in 9 US and 1 UK site. The walk-PHaSST biorepository have banked samples from 610 of the screening subjects. A total of 592 subjects from the screening phase are included in the TOPMed program for WGS. Study Design: Cross-Sectional Study Type: Clinical Trial Cross-Sectional dbGaP estimated ancestry using GRAF-pop Total number of consented subjects: 445 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"NHLBI TOPMed: Walk-PHaSST Sickle Cell Disease (SCD)","short_name":"Walk_PHaSST_SCD_HMB-IRB-PUB-COL-NPU-MDS-GSO","commons":"BioData Catalyst","study_url":"https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001514.v2.p1","_subjects_count":390,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs001514.v2.p1.c2":{"gen3_discovery":{"authz":"/programs/topmed/projects/Walk_PHaSST_SCD_DS-SCD-IRB-PUB-COL-NPU-MDS-RD","tags":[{"name":"TOPMed","category":"Program"},{"name":"Genotype","category":"Data Type"},{"name":"Clinical Phenotype","category":"Data Type"},{"name":"dbGaP","category":"Study Registration"}],"_unique_id":"phs001514.v2.p1.c2","study_id":"phs001514.v2.p1.c2","study_description":"This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed) Whole Genome Sequencing Program. TOPMed is part of a broader Precision Medicine Initiative, which aims to provide disease treatments that are tailored to an individual's unique genes and environment. TOPMed will contribute to this initiative through the integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles, protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental, and clinical data. In doing so, this program aims to uncover factors that increase or decrease the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized treatments. Two genotype call sets derived from WGS are now available, Freeze 8 (GRCh38) and Freeze 9b (GRCh38), with largely overlapping sample sets. Information about how to identify other TOPMed WGS accessions for cross-study analysis, as well as descriptions of TOPMed methods of data acquisition, data processing and quality control, are provided in the accompanying documents, \"TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4\" and \"TOPMed Whole Genome Sequencing Project - Freeze 9b, Phases 1-4\". Please check the study list at the top of each of these methods documents to determine whether it applies to this study accession. Walk-PHaSST study is a multi-center clinical trial to evaluate the effects of sildenafil on Sickle Cell Disease (SCD) population with low exercise capacity associated with an increased Doppler-estimated pulmonary artery systolic pressure (as assessed by the tricuspid regurgitant velocity (TRV)). It is a double-blind, placebo-controlled trial to assess the safety, tolerability, and efficacy of sildenafil in patients with SCD who had both an elevated TRV and decreased exercise capacity. The screening phase of the study enrolled 720 subjects and 74 of them were randomized for the clinical trial. For the screening cohort, we have collected general demographics and race/ethnicity, hemoglobin genotype, physical examination, laboratory screening, transthoracic Doppler echocardiography, and 6 minute walk test in 9 US and 1 UK site. The walk-PHaSST biorepository have banked samples from 610 of the screening subjects. A total of 592 subjects from the screening phase are included in the TOPMed program for WGS. Study Design: Cross-Sectional Study Type: Clinical Trial Cross-Sectional dbGaP estimated ancestry using GRAF-pop Total number of consented subjects: 445 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"NHLBI TOPMed: Walk-PHaSST Sickle Cell Disease (SCD)","short_name":"Walk_PHaSST_SCD_DS-SCD-IRB-PUB-COL-NPU-MDS-RD","commons":"BioData Catalyst","study_url":"https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001514.v2.p1","_subjects_count":50,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs001515.v1.p1.c1":{"gen3_discovery":{"authz":"","tags":[],"_unique_id":"phs001515.v1.p1.c1","study_id":"phs001515.v1.p1.c1","study_description":"","full_name":"","short_name":"","commons":"BioData Catalyst","study_url":"","_subjects_count":0,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs001515.v2.p2.c1":{"gen3_discovery":{"authz":"/programs/topmed/projects/MLOF_HMB-PUB","tags":[],"_unique_id":"phs001515.v2.p2.c1","study_id":"phs001515.v2.p2.c1","study_description":"This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed) Whole Genome Sequencing Program. TOPMed is part of a broader Precision Medicine Initiative, which aims to provide disease treatments that are tailored to an individual's unique genes and environment. TOPMed will contribute to this initiative through the integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles, protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental, and clinical data. In doing so, this program aims to uncover factors that increase or decrease the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized treatments. Two genotype call sets derived from WGS are now available, Freeze 8 (GRCh38) and Freeze 9b (GRCh38), with largely overlapping sample sets. Information about how to identify other TOPMed WGS accessions for cross-study analysis, as well as descriptions of TOPMed methods of data acquisition, data processing and quality control, are provided in the accompanying documents, \"TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4\" and \"TOPMed Whole Genome Sequencing Project - Freeze 9b, Phases 1-4\". Please check the study list at the top of each of these methods documents to determine whether it applies to this study accession. Hemophilia A and B are X-linked bleeding disorders resulting from a deficiency in coagulation factor VIII (FVIII) or factor IX (FIX), respectively. Hemophilia affects approximately 1/5000 male births worldwide, and results in premature death and disability due to bleeding if coagulation factor replacement therapy is not used effectively. Hemophilia is clinically categorized by coagulation factor activity levels and ranges in severity from mild (6% to 30%) to moderate (1-5%) to severe (<1%). Many female \"carriers\" of hemophilia also have decreased factor activity and morbidity from bleeding. Hemophilia A and B are almost always caused by identifiable mutations in the F8 and F9 genes, respectively, and these mutations are found throughout the structural genes. Although the hemophilias are monogenic disorders, there are wide variations in disease severity and therapeutic outcomes which are not readily explained by the disease causing mutations alone. The My Life Our Future (MLOF) project (www.mylifeourfuture.org) is a national resource developed by a partnership of BloodworksNW (BWNW, formerly the Puget Sound Blood Center), the American Thrombosis and Hemostasis Network (ATHN), the National Hemophilia Foundation (NHF) and Bioverativ, to provide free F8 and F9 gene variant analysis to patients with hemophilia A or B, and to establish a research repository of DNA sequence, DNA, RNA, buffy coat, serum and plasma. The sequence analysis and serum samples are linked to a phenotypic database hosted by ATHN, with samples submitted and clinical data entered at ~100 hemophilia treatment centers (HTCs) nationwide. (See ATHN Research Report Brief in the resource center at www.athn.org). MLOF has become the largest hemophilia genetic project worldwide. The roles of the MLOF partners are: BWNW, to serve as the central laboratory for the project and house the research repository; ATHN, to support and provide the administrative link with HTCs, to facilitate the collection of accurate phenotypic data, to conduct research review and approval for use of the repository and with BWNW to provide samples and data for research projects; NHF, to provide consumer education and facilitate consumer input into the project; and Bioverativ, to provide financial support and scientific input. The project is governed by a Steering Committee consisting of one representative from each organization. Subject samples chosen from the MLOF parent study for TOPMed and WGS were drawn from those who gave (or parents gave) informed consent for the Research Repository and included patients of all severities and type, but with an emphasis on those with severe hemophilia and others at increased risk of neutralizing antibody (inhibitor) formation and who had samples in the Research Repository (plasma, serum, RNA) for potential additional -omic studies. Also included were samples from subjects where a likely causative variant for hemophilia was not found in the F8 or F9 coding region, intron-exon boundaries or immediate upstream and downstream regions. Since hemophilia is an X-linked disorder, the majority of subjects are male. Racial distribution is similar to the overall population distribution. Study Weblinks: mylifeourfuture Study Design: Cross-Sectional Study Type: Cross-Sectional dbGaP estimated ancestry using GRAF-pop Total number of consented subjects: 9104 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"NHLBI TOPMed: My Life Our Future (MLOF) Research Repository of Patients with Hemophilia A (Factor VIII Deficiency) or Hemophilia B (Factor IX Deficiency)","short_name":"MLOF_HMB-PUB","commons":"BioData Catalyst","study_url":"","_subjects_count":9104,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs001536.v3.p2.c1":{"gen3_discovery":{"authz":"/programs/dbGaP/projects/CCDG_ARIC_HMB-IRB","tags":[],"_unique_id":"phs001536.v3.p2.c1","study_id":"phs001536.v3.p2.c1","study_description":"This sub-study phs001536 CCDG_ARIC contains genotype, sequence data, and selected phenotype of subjects available from the phs001536 study. Summary level phenotypes for the NHLBI ARIC Cohort study participants can be viewed at the top-level study page phs000280 ARIC Cohort. Individual level phenotype data and molecular data for all ARIC Cohort top-level study and sub-study are available by requesting Authorized Access to the NHLBI ARIC Cohort phs000280 study. Cardiovascular diseases (CVD), especially coronary heart disease, heart failure and cerebrovascular disease remain the leading causes of death in men and women across all race groups in the United States. Substantial evidence exists for genetic factors underlying CVD risk, and their discovery offers an opportunity to enhance understanding of disease mechanisms, to provide specific diagnostic and prognostic indicators, and to identify novel therapeutic targets. Most contemporary genomic studies have achieved adequate power by increasing the size of the discovery sample to tens or hundreds of thousands of individuals. An alternative approach for detecting novel genes with variants of functional effect is to measure phenotypes that more immediately reflect genome function. By focusing on proximal measures of multiple cellular, physiologic and metabolic processes, the size of a gene's effect relative to the corresponding risk factor level or disease endpoint is optimized. In this study, whole genome sequencing (WGS) was carried out to identify genomic regions influencing the human serum metabolome in a random sample of 4,000 individuals from the Hispanic Community Health Study/Study of Latinos (HCHS/SOL), a longitudinal cohort study of 16,415 diverse Latino Americans. In order to represent the three most common ethnic groups in the United States, 4,000 European American and African American participants were also selected from the prospective Atherosclerosis Risk in Communities (ARIC) Study (N = 15,792 at baseline). The goals of the study will be achieved by pursuing the following specific aims: 1) test the association between WGS data and metabolomics data already available in the same individuals to identify genomic regions and specific alleles that significantly influence individual metabolite levels and metabolomics patterns; 2) analyze existing genomic data (i.e., array genotype data) and the WGS data obtained in this study to evaluate whether the genomic variants identified in Aim 1 predict prevalent (i.e., cross-sectional) or incident (i.e., future) CVD events among approximately 12,800 HCHS/SOL and 14,758 ARIC study participants; and 3) create novel interfaces for the broader scientific community to access these data, including a searchable visualization tool and database of annotated genome-metabolome results. This study contains the Atherosclerosis Risk in Communities (ARIC) subset of the Center for Common Disease Genomics study. Additional data from the Center for Common Disease Genomics is also available via dbGaP. All sequencing was carried out at the Human Genome Sequencing Center at Baylor College of Medicine. Study Design: Prospective Longitudinal Cohort Study Type: Cohort dbGaP estimated ancestry using GRAF-pop Total number of consented subjects: 2631 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Center for Common Disease Genomics: Atherosclerosis Risk in Communities (ARIC) Study","short_name":"CCDG_ARIC_HMB-IRB","commons":"BioData Catalyst","study_url":"","_subjects_count":2565,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs001536.v3.p2.c2":{"gen3_discovery":{"authz":"/programs/dbGaP/projects/CCDG_ARIC_DS-CVD-IRB","tags":[],"_unique_id":"phs001536.v3.p2.c2","study_id":"phs001536.v3.p2.c2","study_description":"This sub-study phs001536 CCDG_ARIC contains genotype, sequence data, and selected phenotype of subjects available from the phs001536 study. Summary level phenotypes for the NHLBI ARIC Cohort study participants can be viewed at the top-level study page phs000280 ARIC Cohort. Individual level phenotype data and molecular data for all ARIC Cohort top-level study and sub-study are available by requesting Authorized Access to the NHLBI ARIC Cohort phs000280 study. Cardiovascular diseases (CVD), especially coronary heart disease, heart failure and cerebrovascular disease remain the leading causes of death in men and women across all race groups in the United States. Substantial evidence exists for genetic factors underlying CVD risk, and their discovery offers an opportunity to enhance understanding of disease mechanisms, to provide specific diagnostic and prognostic indicators, and to identify novel therapeutic targets. Most contemporary genomic studies have achieved adequate power by increasing the size of the discovery sample to tens or hundreds of thousands of individuals. An alternative approach for detecting novel genes with variants of functional effect is to measure phenotypes that more immediately reflect genome function. By focusing on proximal measures of multiple cellular, physiologic and metabolic processes, the size of a gene's effect relative to the corresponding risk factor level or disease endpoint is optimized. In this study, whole genome sequencing (WGS) was carried out to identify genomic regions influencing the human serum metabolome in a random sample of 4,000 individuals from the Hispanic Community Health Study/Study of Latinos (HCHS/SOL), a longitudinal cohort study of 16,415 diverse Latino Americans. In order to represent the three most common ethnic groups in the United States, 4,000 European American and African American participants were also selected from the prospective Atherosclerosis Risk in Communities (ARIC) Study (N = 15,792 at baseline). The goals of the study will be achieved by pursuing the following specific aims: 1) test the association between WGS data and metabolomics data already available in the same individuals to identify genomic regions and specific alleles that significantly influence individual metabolite levels and metabolomics patterns; 2) analyze existing genomic data (i.e., array genotype data) and the WGS data obtained in this study to evaluate whether the genomic variants identified in Aim 1 predict prevalent (i.e., cross-sectional) or incident (i.e., future) CVD events among approximately 12,800 HCHS/SOL and 14,758 ARIC study participants; and 3) create novel interfaces for the broader scientific community to access these data, including a searchable visualization tool and database of annotated genome-metabolome results. This study contains the Atherosclerosis Risk in Communities (ARIC) subset of the Center for Common Disease Genomics study. Additional data from the Center for Common Disease Genomics is also available via dbGaP. All sequencing was carried out at the Human Genome Sequencing Center at Baylor College of Medicine. Study Design: Prospective Longitudinal Cohort Study Type: Cohort dbGaP estimated ancestry using GRAF-pop Total number of consented subjects: 2631 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Center for Common Disease Genomics: Atherosclerosis Risk in Communities (ARIC) Study","short_name":"CCDG_ARIC_DS-CVD-IRB","commons":"BioData Catalyst","study_url":"","_subjects_count":66,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs001539.v4.p1.c1":{"gen3_discovery":{"authz":"/programs/heartfailure/projects/MAGNet_HMB-MDS","tags":[{"name":"dbGaP","category":"Study Registration"}],"_unique_id":"phs001539.v4.p1.c1","study_id":"phs001539.v4.p1.c1","study_description":"The MAGNet repository includes non-failing samples from organ donors with no history of heart failure and failing samples from explanted hearts of donors receiving a heart transplant. The study protocol was approved by the Institutional Review Board at the University of Pennsylvania, and all patients provided written informed consent to participate. Study Weblinks: MAGNet Study Design: Case-Control Study Type: Case-Control Total number of consented subjects: 151 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Myocardial Applied Genomics Network (MAGNet) Study","short_name":"MAGNet_HMB-MDS","commons":"BioData Catalyst","study_url":"https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001539.v4.p1","_subjects_count":151,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs001542.v2.p1.c2":{"gen3_discovery":{"authz":"/programs/topmed/projects/GALA_DS-LD-IRB-COL","tags":[{"name":"TOPMed","category":"Program"},{"name":"Genotype","category":"Data Type"},{"name":"dbGaP","category":"Study Registration"}],"_unique_id":"phs001542.v2.p1.c2","study_id":"phs001542.v2.p1.c2","study_description":"This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed) Whole Genome Sequencing Program. TOPMed is part of a broader Precision Medicine Initiative, which aims to provide disease treatments that are tailored to an individual's unique genes and environment. TOPMed will contribute to this initiative through the integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles, protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental, and clinical data. In doing so, this program aims to uncover factors that increase or decrease the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized treatments. Two genotype call sets derived from WGS are now available, Freeze 8 (GRCh38) and Freeze 9b (GRCh38), with largely overlapping sample sets. Information about how to identify other TOPMed WGS accessions for cross-study analysis, as well as descriptions of TOPMed methods of data acquisition, data processing and quality control, are provided in the accompanying documents, \"TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4\" and \"TOPMed Whole Genome Sequencing Project - Freeze 9b, Phases 1-4\". Please check the study list at the top of each of these methods documents to determine whether it applies to this study accession. This is a case pharmacogenetic study of bronchodilator drug response (Albuterol) among racially admixed Latino children with asthma between the ages of 8-40. Lung function testing was performed using the KoKo PFT system and each participant was administered albuterol dependent on age. Participants under 16 years of age, were administered 2 puffs of albuterol from a standard metered dose inhaler and 4 puffs for participants over 16 years old. The overall goal is to identify genetic factors which are predictive of drug response in children with asthma. The principal tools include a questionnaire and biological specimen collection. Participants with asthma have physician-diagnosed asthma, symptoms and medications. Study Weblinks: Asthma Collaboratory Study Design: Case Set Study Type: Case Set dbGaP estimated ancestry using GRAF-pop Total number of consented subjects: 1024 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"NHLBI TOPMed: Genetics of Asthma in Latino Americans (GALA)","short_name":"GALA_DS-LD-IRB-COL","commons":"BioData Catalyst","study_url":"https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001542.v2.p1","_subjects_count":1024,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs001543.v3.p1.c1":{"gen3_discovery":{"authz":"/programs/topmed/projects/AFLMU_HMB-IRB-PUB-COL-NPU-MDS","tags":[{"name":"TOPMed","category":"Program"},{"name":"Genotype","category":"Data Type"},{"name":"Clinical Phenotype","category":"Data Type"},{"name":"dbGaP","category":"Study Registration"}],"_unique_id":"phs001543.v3.p1.c1","study_id":"phs001543.v3.p1.c1","study_description":"This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed) Whole Genome Sequencing Program. TOPMed is part of a broader Precision Medicine Initiative, which aims to provide disease treatments that are tailored to an individual's unique genes and environment. TOPMed will contribute to this initiative through the integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles, protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental, and clinical data. In doing so, this program aims to uncover factors that increase or decrease the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized treatments. Two genotype call sets derived from WGS are now available, Freeze 9b (GRCh38) and Freeze 10b (GRCh38), with largely overlapping sample sets. Information about how to identify other TOPMed WGS accessions for cross-study analysis, as well as descriptions of TOPMed methods of data acquisition, data processing and quality control, are provided in the accompanying documents, \"TOPMed Whole Genome Sequencing Project - Freeze 9b, Phases 1-4\" and \"TOPMed Whole Genome Sequencing Project - Freeze 10b, Phases 1-8\". Please check the study list at the top of each of these methods documents to determine whether it applies to this study accession. The Atrial Fibrillation Biobank Ludwig Maximilian University (AFLMU) Study contributes to the spectrum of disease by adding carefully characterized patients with atrial fibrillation. Atrial fibrillation, one of the most common human arrhythmias confers major morbidity, mortality and health care cost, and has been demonstrated to be caused and influenced by genetic and -omics factors. Particularly, AFLMU enrolled patients with an early onset of atrial fibrillation to increase the genetic burden on disease pathophysiology. All patients were recruited applying standardized protocols to maintain homogeneity in data and DNA quality. Study Design: Case Set Study Type: Case Set dbGaP estimated ancestry using GRAF-pop Total number of consented subjects: 350 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"NHLBI TOPMed - NHGRI CCDG: AF Biobank LMU in the context of the MED Biobank LMU","short_name":"AFLMU_HMB-IRB-PUB-COL-NPU-MDS","commons":"BioData Catalyst","study_url":"https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001543.v3.p1","_subjects_count":350,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs001544.v2.p1.c1":{"gen3_discovery":{"authz":"","tags":[],"_unique_id":"phs001544.v2.p1.c1","study_id":"phs001544.v2.p1.c1","study_description":"","full_name":"","short_name":"","commons":"BioData Catalyst","study_url":"","_subjects_count":0,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs001544.v3.p1.c1":{"gen3_discovery":{"authz":"/programs/topmed/projects/MPP_HMB-NPU-MDS","tags":[{"name":"TOPMed","category":"Program"},{"name":"Genotype","category":"Data Type"},{"name":"Clinical Phenotype","category":"Data Type"},{"name":"dbGaP","category":"Study Registration"}],"_unique_id":"phs001544.v3.p1.c1","study_id":"phs001544.v3.p1.c1","study_description":"This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed) Whole Genome Sequencing Program. TOPMed is part of a broader Precision Medicine Initiative, which aims to provide disease treatments that are tailored to an individual's unique genes and environment. TOPMed will contribute to this initiative through the integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles, protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental, and clinical data. In doing so, this program aims to uncover factors that increase or decrease the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized treatments. Two genotype call sets derived from WGS are now available, Freeze 9b (GRCh38) and Freeze 10b (GRCh38), with largely overlapping sample sets. Information about how to identify other TOPMed WGS accessions for cross-study analysis, as well as descriptions of TOPMed methods of data acquisition, data processing and quality control, are provided in the accompanying documents, \"TOPMed Whole Genome Sequencing Project - Freeze 9b, Phases 1-4\" and \"TOPMed Whole Genome Sequencing Project - Freeze 10b, Phases 1-8\". Please check the study list at the top of each of these methods documents to determine whether it applies to this study accession. The Malmö Preventive Project (MPP) was a community-based disease prevention program including 33,346 inhabitants from the city of Malmö in Southern Sweden. Complete birth cohorts between 1921-1949 were invited, and the participation rate was 71%. Participants underwent screening between 1974 to 1992 for cardiovascular risk factors, alcohol abuse, and breast cancer. Between 2002-2006, surviving participants were invited to a reexamination which included blood sampling from which DNA has been extracted. Subjects with prevalent or incident AF were identified from national registers as previously described, and cases with DNA were then matched in a 1:1 fashion to controls with DNA from the same cohort by sex, age (±1 year), and date of baseline exam (±1 year). Also, controls required a follow-up exceeding that of the corresponding AF case. Study Design: Case Set Study Type: Case Set dbGaP estimated ancestry using GRAF-pop Total number of consented subjects: 121 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"NHLBI TOPMed - NHGRI CCDG: Malmo Preventive Project (MPP)","short_name":"MPP_HMB-NPU-MDS","commons":"BioData Catalyst","study_url":"https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001544.v3.p1","_subjects_count":121,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs001545.v2.p1.c1":{"gen3_discovery":{"authz":"/programs/topmed/projects/INSPIRE_AF_DS-MULTIPLE_DISEASES-MDS","tags":[{"name":"TOPMed","category":"Program"},{"name":"Genotype","category":"Data Type"},{"name":"Clinical Phenotype","category":"Data Type"},{"name":"dbGaP","category":"Study Registration"}],"_unique_id":"phs001545.v2.p1.c1","study_id":"phs001545.v2.p1.c1","study_description":"This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed) Whole Genome Sequencing Program. TOPMed is part of a broader Precision Medicine Initiative, which aims to provide disease treatments that are tailored to an individual's unique genes and environment. TOPMed will contribute to this initiative through the integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles, protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental, and clinical data. In doing so, this program aims to uncover factors that increase or decrease the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized treatments. Two genotype call sets derived from WGS are now available, Freeze 8 (GRCh38) and Freeze 9b (GRCh38), with largely overlapping sample sets. Information about how to identify other TOPMed WGS accessions for cross-study analysis, as well as descriptions of TOPMed methods of data acquisition, data processing and quality control, are provided in the accompanying documents, \"TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4\" and \"TOPMed Whole Genome Sequencing Project - Freeze 9b, Phases 1-4\". Please check the study list at the top of each of these methods documents to determine whether it applies to this study accession. The INtermountain Healthcare Biological Samples Collection Project and Investigational REgistry for the On-going Study of Disease Origin, Progression and Treatment (Intermountain INSPIRE Registry) purpose is to collect biological samples, clinical information and laboratory data from Intermountain Healthcare patients. The registry originally collected samples in patients undergoing a coronary angiography as part of the Intermountain Heart Collaborative Study. It has been expanded to collect samples in patients diagnosed with all types of medical conditions, and patients from the general population including those who have not been diagnosed with health related issues. Just over 25,000 individuals have provided samples as part of this registry. The registry enables researchers to develop a comprehensive collection of information that may help in disease management, including determining best medical practices for predicting, preventing and treating medical conditions. Study Design: Case Set Study Type: Case Set dbGaP estimated ancestry using GRAF-pop Total number of consented subjects: 476 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"NHLBI TOPMed - NHGRI CCDG: Intermountain INSPIRE Registry","short_name":"INSPIRE_AF_DS-MULTIPLE_DISEASES-MDS","commons":"BioData Catalyst","study_url":"https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001545.v2.p1","_subjects_count":475,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs001546.v2.p1.c1":{"gen3_discovery":{"authz":"/programs/topmed/projects/DECAF_GRU","tags":[{"name":"TOPMed","category":"Program"},{"name":"Genotype","category":"Data Type"},{"name":"Clinical Phenotype","category":"Data Type"},{"name":"dbGaP","category":"Study Registration"}],"_unique_id":"phs001546.v2.p1.c1","study_id":"phs001546.v2.p1.c1","study_description":"This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed) Whole Genome Sequencing Program. TOPMed is part of a broader Precision Medicine Initiative, which aims to provide disease treatments that are tailored to an individual's unique genes and environment. TOPMed will contribute to this initiative through the integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles, protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental, and clinical data. In doing so, this program aims to uncover factors that increase or decrease the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized treatments. Two genotype call sets derived from WGS are now available, Freeze 8 (GRCh38) and Freeze 9b (GRCh38), with largely overlapping sample sets. Information about how to identify other TOPMed WGS accessions for cross-study analysis, as well as descriptions of TOPMed methods of data acquisition, data processing and quality control, are provided in the accompanying documents, \"TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4\" and \"TOPMed Whole Genome Sequencing Project - Freeze 9b, Phases 1-4\". Please check the study list at the top of each of these methods documents to determine whether it applies to this study accession. The DECAF trial was conducted at the Texas Cardiac Arrhythmia Institute (TCAI) in 2013 in collaboration with the University of Texas at Austin. Four hundred consecutive AF patients undergoing catheter ablation were enrolled. All participants provided voluntary informed consents. Blood samples were collected before the ablation procedure and labeled with anonymous patient identifier. The researchers at UT Austin responsible for DNA extraction and genetic analysis were blinded about the clinical characteristics and identification of the study participants. AF cases included adults >18 years of age from both sex and all AF types. Study Design: Prospective Longitudinal Cohort Study Type: Longitudinal dbGaP estimated ancestry using GRAF-pop Total number of consented subjects: 6 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"NHLBI TOPMed: Determining the Association of Chromosomal Variants with Non-PV Triggers and Ablation-Outcome in AF (DECAF)","short_name":"DECAF_GRU","commons":"BioData Catalyst","study_url":"https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001546.v2.p1","_subjects_count":6,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs001547.v2.p1.c1":{"gen3_discovery":{"authz":"","tags":[],"_unique_id":"phs001547.v2.p1.c1","study_id":"phs001547.v2.p1.c1","study_description":"","full_name":"","short_name":"","commons":"BioData Catalyst","study_url":"","_subjects_count":0,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs001547.v3.p1.c1":{"gen3_discovery":{"authz":"/programs/topmed/projects/GENAF_HMB-NPU","tags":[{"name":"TOPMed","category":"Program"},{"name":"Genotype","category":"Data Type"},{"name":"Clinical Phenotype","category":"Data Type"},{"name":"dbGaP","category":"Study Registration"}],"_unique_id":"phs001547.v3.p1.c1","study_id":"phs001547.v3.p1.c1","study_description":"This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed) Whole Genome Sequencing Program. TOPMed is part of a broader Precision Medicine Initiative, which aims to provide disease treatments that are tailored to an individual's unique genes and environment. TOPMed will contribute to this initiative through the integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles, protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental, and clinical data. In doing so, this program aims to uncover factors that increase or decrease the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized treatments. Two genotype call sets derived from WGS are now available, Freeze 9b (GRCh38) and Freeze 10b (GRCh38), with largely overlapping sample sets. Information about how to identify other TOPMed WGS accessions for cross-study analysis, as well as descriptions of TOPMed methods of data acquisition, data processing and quality control, are provided in the accompanying documents, \"TOPMed Whole Genome Sequencing Project - Freeze 9b, Phases 1-4\" and \"TOPMed Whole Genome Sequencing Project - Freeze 10b, Phases 1-8\". Please check the study list at the top of each of these methods documents to determine whether it applies to this study accession. The Genetics in AF (GENAF) study enrolled individuals with early-onset lone AF before age 50 in Norway between 2009 and 2016. Early-onset was defined as diagnosis of AF before age 50. Lone AF was defined as AF in the absence of clinical or echocardiographic findings of cardiovascular disease, hypertension, metabolic or pulmonary disease. AF was documented in ECG. All participants underwent clinical examination, including ECG, echocardiography, and blood draw, from which DNA has been extracted. The study conforms to the principles of the Declaration of Helsinki and was approved by the Regional Ethics Committee (REK) in Norway (Protocol reference number: 2009/2224-5). All included patients gave written informed consent. Study Design: Case Set Study Type: Case Set dbGaP estimated ancestry using GRAF-pop Total number of consented subjects: 90 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"NHLBI TOPMed - NHGRI CCDG: The GENetics in Atrial Fibrillation (GENAF) Study","short_name":"GENAF_HMB-NPU","commons":"BioData Catalyst","study_url":"https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001547.v3.p1","_subjects_count":90,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs001569.v1.p1.c1":{"gen3_discovery":{"authz":"/programs/topmed/projects/PROMIS_GRU","tags":[],"_unique_id":"phs001569.v1.p1.c1","study_id":"phs001569.v1.p1.c1","study_description":"This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed) Whole Genome Sequencing Program. TOPMed is part of a broader Precision Medicine Initiative, which aims to provide disease treatments that are tailored to an individual's unique genes and environment. TOPMed will contribute to this initiative through the integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles, protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental, and clinical data. In doing so, this program aims to uncover factors that increase or decrease the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized treatments. One genotype call set derived from WGS is now available, Freeze 10b (GRCh38). Information about how to identify other TOPMed WGS accessions for cross-study analysis, as well as descriptions of TOPMed methods of data acquisition, data processing and quality control, are provided in the accompanying document, \"TOPMed Whole Genome Sequencing Project - Freeze 10b, Phases 1-8\". Please check the study list at the top of each of these methods documents to determine whether it applies to this study accession. The Pakistan Risk of Myocardial Infarction (PROMIS) study is a retrospective multicenter case-control cohort study of individuals with and without coronary heart disease from Pakistan. Multiple biological samples have been collected from the participants including DNA, plasma, serum, and whole blood. The goal of the study is to recruit 20,000 cases and 20,000 controls of Pakistani descent. Eligible cases were individuals aged 30-80 who presented to the emergency department of a participating recruitment center in Pakistan with clinical symptoms consistent with a myocardial infarction (MI), ECG changes consistent with MI, elevated troponin levels consistent with MI, and no prior history of cardiovascular disease. Controls were individuals of Pakistani descent who did not have a self-reported history of cardiovascular disease. This site hosts data generated via NHLBI's TOPMed program and NHGRI's Common Disease Genomics (CCDG) program. Both whole exome and whole genome data are presented here, namely 4,211 whole genomes from TOPMed, 3,859 whole genomes from NHLBI supplemental funds, 1,136 whole genomes and 16,855 whole exomes from CCDG. Please note that there is additional legacy whole exome data (7,298 subjects) also generated via NHGRI funds as part of the MIGen Exome Sequencing project that can be found in dbGaP at phs000917. Study Design: Case-Control Study Type: Case-Control Cohort Total number of consented subjects: 26061 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"NHLBI TOPMed - NHGRI CCDG: Pakistan Risk of Myocardial Infarction Study (PROMIS)","short_name":"PROMIS_GRU","commons":"BioData Catalyst","study_url":"","_subjects_count":8070,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs001592.v1.p1.c1":{"gen3_discovery":{"authz":"/programs/heartfailure/projects/CardioATVB_DS-CVD","tags":[{"name":"dbGaP","category":"Study Registration"}],"_unique_id":"phs001592.v1.p1.c1","study_id":"phs001592.v1.p1.c1","study_description":"Italian Atherosclerosis Thrombosis and Vascular Biology study is a prospective, nationwide, case-control study involving 125 coronary care units in Italy. The cases were patients who were hospitalised for a first MI before the age of 45 years and underwent coronary angiography. Acute MI was defined as resting chest pain lasting more than 30 minutes, accompanied by persistent electrocardiographic changes, and confirmed by an increase in total creatine kinase or in the MB fraction to more than twice the upper normal limits. The controls were healthy subjects without a history of thromboembolic disease who were unrelated to the patients, but individually matched with them by age, gender and geographical origin. They were enrolled from among the blood donors or staff of the same participating hospitals. Recruitment of cases and controls took place between 1994 and 2007. This site hosts data from ~60 whole exomes. Study Design: Case-Control Study Type: Case-Control dbGaP estimated ancestry using GRAF-pop Total number of consented subjects: 58 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Center for Common Disease Genomics [CCDG] - Cardiovascular ATVB: Atherosclerosis Thrombosis and Vascular Biology","short_name":"CardioATVB_DS-CVD","commons":"BioData Catalyst","study_url":"https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001592.v1.p1","_subjects_count":58,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs001598.v2.p1.c1":{"gen3_discovery":{"authz":"","tags":[],"_unique_id":"phs001598.v2.p1.c1","study_id":"phs001598.v2.p1.c1","study_description":"","full_name":"","short_name":"","commons":"BioData Catalyst","study_url":"","_subjects_count":0,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs001598.v3.p1.c1":{"gen3_discovery":{"authz":"/programs/topmed/projects/JHU_AF_HMB-NPU-MDS","tags":[{"name":"TOPMed","category":"Program"},{"name":"Genotype","category":"Data Type"},{"name":"Clinical Phenotype","category":"Data Type"},{"name":"dbGaP","category":"Study Registration"}],"_unique_id":"phs001598.v3.p1.c1","study_id":"phs001598.v3.p1.c1","study_description":"This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed) Whole Genome Sequencing Program. TOPMed is part of a broader Precision Medicine Initiative, which aims to provide disease treatments that are tailored to an individual's unique genes and environment. TOPMed will contribute to this initiative through the integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles, protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental, and clinical data. In doing so, this program aims to uncover factors that increase or decrease the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized treatments. Two genotype call sets derived from WGS are now available, Freeze 9b (GRCh38) and Freeze 10b (GRCh38), with largely overlapping sample sets. Information about how to identify other TOPMed WGS accessions for cross-study analysis, as well as descriptions of TOPMed methods of data acquisition, data processing and quality control, are provided in the accompanying documents, \"TOPMed Whole Genome Sequencing Project - Freeze 9b, Phases 1-4\" and \"TOPMed Whole Genome Sequencing Project - Freeze 10b, Phases 1-8\". Please check the study list at the top of each of these methods documents to determine whether it applies to this study accession. Atrial fibrillation (AF), the most common sustained cardiac arrhythmia, is the primary cause of many hospital admissions, and is associated with significant secondary morbidity by increasing the risk of stroke, heart failure, and all-cause mortality. The incidence of AF is on the rise, and it is projected that by the year 2050 more than 10 million patients will be affected by AF in the United States alone. Anti-arrhythmic medications have limited success in maintaining sinus rhythm, are associated with side effects, and appear ineffective at reducing mortality compared to a strategy of rate control and anticoagulation. Given the significant morbidity associated with this common arrhythmia, surgical and catheter ablation techniques have been developed to treat AF. However, despite the incorporation of various strategies for ablation, long-term recurrence rates of AF remain higher than 25 percent after ablation. Current techniques for catheter ablation of AF include pulmonary vein isolation and complex fractionated atrial electrogram (CFAE) ablation. However, the contribution of each strategy to long-term procedural success and the relative importance of each strategy for different patients remain unknown. Recent advances in cardiac imaging have allowed detailed analysis of left atrial myocardial anatomy. Parallel advances in molecular genetics have identified several candidate genes involved in familial and non-familial AF. However, the pathophysiology of AF generation and maintenance, and the potential contribution of such genetic or anatomic substrates for patient selection, and for target identification during catheter ablation have not yet been examined. Advances in molecular genetics and imaging, coupled with techniques for endocardial and epicardial mapping in the electrophysiology laboratory present an opportunity to significantly improve our understanding of (1) The relation of paroxysmal versus persistent AF with (a) structural left atrial changes (left/right atrial scar, wall thinning, pulmonary vein anomalies, and coronary sinus dilation) and with (b) candidate genetic variants. (2) The relation of candidate genetic variants with (a) structural left atrial changes and with (b) electrophysiologic properties (atrial effective refractory period (AERP) inhomogeneity, voltage abnormalities, trigger burden and location, C FAE extent and location), (3) The relation of structural left atrial changes with (a) CFAE location as targets for catheter ablation and with (b) reversible conduction block/myocardial injury after pulmonary vein isolation, and (4) Individualized endocardial targets for AF ablation based on candidate genes and anatomic substrates. The proposed study will improve our understanding of the underlying pathophysiology of AF, and may improve current techniques for treatment of this important arrhythmia. Study Design: Case Set Study Type: Case Set dbGaP estimated ancestry using GRAF-pop Total number of consented subjects: 290 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"NHLBI TOPMed - NHGRI CCDG: The Johns Hopkins University School of Medicine Atrial Fibrillation Genetics Study","short_name":"JHU_AF_HMB-NPU-MDS","commons":"BioData Catalyst","study_url":"https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001598.v3.p1","_subjects_count":290,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs001599.v1.p1.c1":{"gen3_discovery":{"authz":"/programs/topmed/projects/BostonBrazil_SCD_HMB-IRB-COL","tags":[{"name":"TOPMed","category":"Program"},{"name":"Genotype","category":"Data Type"},{"name":"dbGaP","category":"Study Registration"}],"_unique_id":"phs001599.v1.p1.c1","study_id":"phs001599.v1.p1.c1","study_description":"This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed) Whole Genome Sequencing Program. TOPMed is part of a broader Precision Medicine Initiative, which aims to provide disease treatments that are tailored to an individual's unique genes and environment. TOPMed will contribute to this initiative through the integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles, protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental, and clinical data. In doing so, this program aims to uncover factors that increase or decrease the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized treatments. Two genotype call sets derived from WGS are now available, Freeze 8 (GRCh38) and Freeze 9b (GRCh38), with largely overlapping sample sets. Information about how to identify other TOPMed WGS accessions for cross-study analysis, as well as descriptions of TOPMed methods of data acquisition, data processing and quality control, are provided in the accompanying documents, \"TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4\" and \"TOPMed Whole Genome Sequencing Project - Freeze 9b, Phases 1-4\". Please check the study list at the top of each of these methods documents to determine whether it applies to this study accession. This study involves sequencing of patients with a diagnosis of sickle cell disease from Brazil. No exclusionary criteria were employed and any eligible patients that consented to this study were recruited. Study Design: Prospective Longitudinal Cohort Study Type: Cohort dbGaP estimated ancestry using GRAF-pop Total number of consented subjects: 943 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"NHLBI TOPMed: Boston-Brazil Sickle Cell Disease (SCD) Cohort","short_name":"BostonBrazil_SCD_HMB-IRB-COL","commons":"BioData Catalyst","study_url":"https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001599.v1.p1","_subjects_count":943,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs001600.v2.p2.c1":{"gen3_discovery":{"authz":"/programs/topmed/projects/CATHGEN_DS-CVD-IRB","tags":[{"name":"TOPMed","category":"Program"},{"name":"Genotype","category":"Data Type"},{"name":"dbGaP","category":"Study Registration"}],"_unique_id":"phs001600.v2.p2.c1","study_id":"phs001600.v2.p2.c1","study_description":"This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed) Whole Genome Sequencing Program. TOPMed is part of a broader Precision Medicine Initiative, which aims to provide disease treatments that are tailored to an individual's unique genes and environment. TOPMed will contribute to this initiative through the integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles, protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental, and clinical data. In doing so, this program aims to uncover factors that increase or decrease the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized treatments. Two genotype call sets derived from WGS are now available, Freeze 8 (GRCh38) and Freeze 9b (GRCh38), with largely overlapping sample sets. Information about how to identify other TOPMed WGS accessions for cross-study analysis, as well as descriptions of TOPMed methods of data acquisition, data processing and quality control, are provided in the accompanying documents, \"TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4\" and \"TOPMed Whole Genome Sequencing Project - Freeze 9b, Phases 1-4\". Please check the study list at the top of each of these methods documents to determine whether it applies to this study accession. The CATHeterization GENetics (CATHGEN) biorepository collected biospecimens and clinical data on individuals age ≥18 undergoing cardiac catheterization for concern of ischemic heart disease at a single center (Duke University Medical Center) from 2000-2010; a total of N=9334 individuals were collected. Samples were matched at the individual level to clinical data collected at the time of catheterization and stored in the Duke Databank for Cardiovascular Diseases (DDCD). Clinical data included subject demographics, cardiometabolic risk factors, cardiac history including symptoms, age-of-onset of cardiovascular diseases, coronary anatomy and cardiac function at catheterization, laboratory data, and yearly follow-up for hospitalizations, vital status, medication use and lifestyle factors. AF cases were defined as individuals who had ever had AF based on any ECG available at Duke University or ICD-9 code for AF used for inpatient or outpatient billing. Study Design: Case Set Study Type: Case Set dbGaP estimated ancestry using GRAF-pop Total number of consented subjects: 1271 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"NHLBI TOPMed - NHGRI CCDG: Early-onset Atrial Fibrillation in the CATHeterization GENetics (CATHGEN) Cohort","short_name":"CATHGEN_DS-CVD-IRB","commons":"BioData Catalyst","study_url":"https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001600.v2.p2","_subjects_count":1271,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs001601.v2.p1.c1":{"gen3_discovery":{"authz":"/programs/topmed/projects/CCDG_PMBB_AF_HMB-IRB-PUB","tags":[{"name":"TOPMed","category":"Program"},{"name":"Genotype","category":"Data Type"},{"name":"dbGaP","category":"Study Registration"}],"_unique_id":"phs001601.v2.p1.c1","study_id":"phs001601.v2.p1.c1","study_description":"No Study Description Available","full_name":"NHLBI TOPMed - NHGRI CCDG: Penn Medicine BioBank Early Onset Atrial Fibrillation Study (CCDG_PMBB_AF)","short_name":"CCDG_PMBB_AF_HMB-IRB-PUB","commons":"BioData Catalyst","study_url":"https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001601.v2.p1","_subjects_count":2235,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs001602.v2.p1.c1":{"gen3_discovery":{"authz":"/programs/topmed/projects/ChildrensHS_GAP_GRU","tags":[{"name":"TOPMed","category":"Program"},{"name":"Genotype","category":"Data Type"},{"name":"Clinical Phenotype","category":"Data Type"},{"name":"dbGaP","category":"Study Registration"}],"_unique_id":"phs001602.v2.p1.c1","study_id":"phs001602.v2.p1.c1","study_description":"This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed) Whole Genome Sequencing Program. TOPMed is part of a broader Precision Medicine Initiative, which aims to provide disease treatments that are tailored to an individual's unique genes and environment. TOPMed will contribute to this initiative through the integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles, protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental, and clinical data. In doing so, this program aims to uncover factors that increase or decrease the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized treatments. Two genotype call sets derived from WGS are now available, Freeze 8 (GRCh38) and Freeze 9b (GRCh38), with largely overlapping sample sets. Information about how to identify other TOPMed WGS accessions for cross-study analysis, as well as descriptions of TOPMed methods of data acquisition, data processing and quality control, are provided in the accompanying documents, \"TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4\" and \"TOPMed Whole Genome Sequencing Project - Freeze 9b, Phases 1-4\". Please check the study list at the top of each of these methods documents to determine whether it applies to this study accession. The Integrative Genetic Approaches to Gene-Air Pollution Interactions in Asthma (GAP) study was proposed to use an innovative genetics approach in mice and humans to identify novel variants that interact with traffic-related pollutant exposures to affect lung function phenotypes and the risk of childhood asthma. The study participants were enrolled from the original southern California Children's Health Study (CHS). In the TOPMed project, seven Hispanic White participants who did not have asthma history were included in the WGS analysis. Study Design: Case-Control Study Type: Case-Control dbGaP estimated ancestry using GRAF-pop Total number of consented subjects: 7 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"NHLBI TOPMed: Children's Health Study (CHS) Integrative Genetic Approaches to Gene-Air Pollution Interactions in Asthma (GAP)","short_name":"ChildrensHS_GAP_GRU","commons":"BioData Catalyst","study_url":"https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001602.v2.p1","_subjects_count":7,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs001603.v2.p1.c1":{"gen3_discovery":{"authz":"/programs/topmed/projects/ChildrensHS_IGERA_GRU","tags":[{"name":"TOPMed","category":"Program"},{"name":"Genotype","category":"Data Type"},{"name":"Clinical Phenotype","category":"Data Type"},{"name":"dbGaP","category":"Study Registration"}],"_unique_id":"phs001603.v2.p1.c1","study_id":"phs001603.v2.p1.c1","study_description":"This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed) Whole Genome Sequencing Program. TOPMed is part of a broader Precision Medicine Initiative, which aims to provide disease treatments that are tailored to an individual's unique genes and environment. TOPMed will contribute to this initiative through the integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles, protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental, and clinical data. In doing so, this program aims to uncover factors that increase or decrease the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized treatments. Two genotype call sets derived from WGS are now available, Freeze 8 (GRCh38) and Freeze 9b (GRCh38), with largely overlapping sample sets. Information about how to identify other TOPMed WGS accessions for cross-study analysis, as well as descriptions of TOPMed methods of data acquisition, data processing and quality control, are provided in the accompanying documents, \"TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4\" and \"TOPMed Whole Genome Sequencing Project - Freeze 9b, Phases 1-4\". Please check the study list at the top of each of these methods documents to determine whether it applies to this study accession. The Integrative Genomics and Environmental Research of Asthma (IGERA) Study was proposed to collect immortalized cell lines, RNA, cDNA and DNA from 400 well-characterized subjects who participated in the southern California Children's Health Study (CHS) and to develop an accompanying database for these samples consisting of extensive phenotype, exposure, genome-wide genotype, gene expression, and methylation data. A subset of Hispanic-White participants (n=160) were included in the TOPMed project, including 77 asthma cases and 83 controls. Study Design: Case-Control Study Type: Case-Control dbGaP estimated ancestry using GRAF-pop Total number of consented subjects: 160 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"NHLBI TOPMed: Children's Health Study (CHS) Integrative Genomics and Environmental Research of Asthma (IGERA)","short_name":"ChildrensHS_IGERA_GRU","commons":"BioData Catalyst","study_url":"https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001603.v2.p1","_subjects_count":156,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs001604.v2.p1.c1":{"gen3_discovery":{"authz":"/programs/topmed/projects/ChildrensHS_MetaAir_GRU","tags":[{"name":"TOPMed","category":"Program"},{"name":"Genotype","category":"Data Type"},{"name":"Clinical Phenotype","category":"Data Type"},{"name":"dbGaP","category":"Study Registration"}],"_unique_id":"phs001604.v2.p1.c1","study_id":"phs001604.v2.p1.c1","study_description":"This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed) Whole Genome Sequencing Program. TOPMed is part of a broader Precision Medicine Initiative, which aims to provide disease treatments that are tailored to an individual's unique genes and environment. TOPMed will contribute to this initiative through the integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles, protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental, and clinical data. In doing so, this program aims to uncover factors that increase or decrease the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized treatments. Two genotype call sets derived from WGS are now available, Freeze 8 (GRCh38) and Freeze 9b (GRCh38), with largely overlapping sample sets. Information about how to identify other TOPMed WGS accessions for cross-study analysis, as well as descriptions of TOPMed methods of data acquisition, data processing and quality control, are provided in the accompanying documents, \"TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4\" and \"TOPMed Whole Genome Sequencing Project - Freeze 9b, Phases 1-4\". Please check the study list at the top of each of these methods documents to determine whether it applies to this study accession. The Effects of Air Pollution on the Development of Obesity in Children (Meta-AIR) study was proposed to study a subset of the Children's Health Study (CHS) participants representing the extremes of long-term traffic-related air pollution exposure occurring in Southern California CHS communities. The primary aim of the Meta-AIR study was to investigate whether lifetime exposure to air pollution increases risk for obesity and metabolic dysfunction at 17-18 years of age. A total of 56 Hispanic White participants (16 asthma cases and 40 controls) were included in the TOPMed project. Study Design: Case-Control Study Type: Case-Control dbGaP estimated ancestry using GRAF-pop Total number of consented subjects: 56 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"NHLBI TOPMed: Children's Health Study (CHS) Effects of Air Pollution on the Development of Obesity in Children (Meta-AIR)","short_name":"ChildrensHS_MetaAir_GRU","commons":"BioData Catalyst","study_url":"https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001604.v2.p1","_subjects_count":56,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs001605.v2.p1.c2":{"gen3_discovery":{"authz":null,"tags":null,"_unique_id":"phs001605.v2.p1.c2","study_id":"phs001605.v2.p1.c2","study_description":null,"full_name":null,"short_name":null,"commons":"BioData Catalyst","study_url":null,"_subjects_count":0,"__manifest":null,"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs001605.v3.p1.c2":{"gen3_discovery":{"authz":"/programs/topmed/projects/CHIRAH_DS-ASTHMA-IRB-COL","tags":[],"_unique_id":"phs001605.v3.p1.c2","study_id":"phs001605.v3.p1.c2","study_description":"This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed) Whole Genome Sequencing Program. TOPMed is part of a broader Precision Medicine Initiative, which aims to provide disease treatments that are tailored to an individual's unique genes and environment. TOPMed will contribute to this initiative through the integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles, protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental, and clinical data. In doing so, this program aims to uncover factors that increase or decrease the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized treatments. Two genotype call sets derived from WGS are now available, Freeze 9b (GRCh38) and Freeze 10b (GRCh38), with largely overlapping sample sets. Information about how to identify other TOPMed WGS accessions for cross-study analysis, as well as descriptions of TOPMed methods of data acquisition, data processing and quality control, are provided in the accompanying documents, \"TOPMed Whole Genome Sequencing Project - Freeze 9b, Phases 1-4\" and \"TOPMed Whole Genome Sequencing Project - Freeze 10b, Phases 1-8\". Please check the study list at the top of each of these methods documents to determine whether it applies to this study accession. The CHIRAH project was a community-based study of the factors associated with asthma morbidity in the African American population. CHIRAH evaluated the role of various variables (biologic/environmental, psychologic/behavioral, and socioeconomic) on asthma morbidity and the function of changes in these variables on asthma morbidity in a longitudinal fashion. This involved collection of a cohort-based on school screening which was sampled to include similar numbers of underprivileged and non-underprivileged subjects which roughly equally represented self-reported African Americans and self-reported non-African Americans. Subjects were followed up every 3 months of this cohort over the course of 2 years. Study Design: Case Set Study Type: Case Set dbGaP estimated ancestry using GRAF-pop Total number of consented subjects: 292 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"NHLBI TOPMed: Chicago Initiative to Raise Asthma Health Equity (CHIRAH)","short_name":"CHIRAH_DS-ASTHMA-IRB-COL","commons":"BioData Catalyst","study_url":"","_subjects_count":292,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs001606.v2.p1.c1":{"gen3_discovery":{"authz":"","tags":[],"_unique_id":"phs001606.v2.p1.c1","study_id":"phs001606.v2.p1.c1","study_description":"","full_name":"","short_name":"","commons":"BioData Catalyst","study_url":"","_subjects_count":0,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs001606.v3.p1.c1":{"gen3_discovery":{"authz":"/programs/topmed/projects/EGCUT_GRU","tags":[{"name":"TOPMed","category":"Program"},{"name":"Genotype","category":"Data Type"},{"name":"Clinical Phenotype","category":"Data Type"},{"name":"dbGaP","category":"Study Registration"}],"_unique_id":"phs001606.v3.p1.c1","study_id":"phs001606.v3.p1.c1","study_description":"This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed) Whole Genome Sequencing Program. TOPMed is part of a broader Precision Medicine Initiative, which aims to provide disease treatments that are tailored to an individual's unique genes and environment. TOPMed will contribute to this initiative through the integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles, protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental, and clinical data. In doing so, this program aims to uncover factors that increase or decrease the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized treatments. Two genotype call sets derived from WGS are now available, Freeze 9b (GRCh38) and Freeze 10b (GRCh38), with largely overlapping sample sets. Information about how to identify other TOPMed WGS accessions for cross-study analysis, as well as descriptions of TOPMed methods of data acquisition, data processing and quality control, are provided in the accompanying documents, \"TOPMed Whole Genome Sequencing Project - Freeze 9b, Phases 1-4\" and \"TOPMed Whole Genome Sequencing Project - Freeze 10b, Phases 1-8\". Please check the study list at the top of each of these methods documents to determine whether it applies to this study accession. The Estonian Biobank is the population-based biobank of the Estonian Genome Centre of University of Tartu. The biobank is conducted according to the Estonian Gene Research Act and all participants have signed broad informed consent. The cohort size is currently 51,535 people from 18 years of age and up. Study Weblinks: EGCUT Estonian BioBank Study Design: Case Set Study Type: Case Set dbGaP estimated ancestry using GRAF-pop Total number of consented subjects: 324 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"NHLBI TOPMed: Early-Onset Atrial Fibrillation in the Estonian Biobank","short_name":"EGCUT_GRU","commons":"BioData Catalyst","study_url":"https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001606.v3.p1","_subjects_count":324,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs001607.v2.p2.c1":{"gen3_discovery":{"authz":"","tags":[],"_unique_id":"phs001607.v2.p2.c1","study_id":"phs001607.v2.p2.c1","study_description":"","full_name":"","short_name":"","commons":"BioData Catalyst","study_url":"","_subjects_count":0,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs001607.v2.p2.c2":{"gen3_discovery":{"authz":"","tags":[],"_unique_id":"phs001607.v2.p2.c2","study_id":"phs001607.v2.p2.c2","study_description":"","full_name":"","short_name":"","commons":"BioData Catalyst","study_url":"","_subjects_count":0,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs001607.v2.p2.c3":{"gen3_discovery":{"authz":"","tags":[],"_unique_id":"phs001607.v2.p2.c3","study_id":"phs001607.v2.p2.c3","study_description":"","full_name":"","short_name":"","commons":"BioData Catalyst","study_url":"","_subjects_count":0,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs001607.v2.p2.c4":{"gen3_discovery":{"authz":"","tags":[],"_unique_id":"phs001607.v2.p2.c4","study_id":"phs001607.v2.p2.c4","study_description":"","full_name":"","short_name":"","commons":"BioData Catalyst","study_url":"","_subjects_count":0,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs001607.v2.p2.c5":{"gen3_discovery":{"authz":"","tags":[],"_unique_id":"phs001607.v2.p2.c5","study_id":"phs001607.v2.p2.c5","study_description":"","full_name":"","short_name":"","commons":"BioData Catalyst","study_url":"","_subjects_count":0,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs001607.v3.p2.c1":{"gen3_discovery":{"authz":"","tags":[],"_unique_id":"phs001607.v3.p2.c1","study_id":"phs001607.v3.p2.c1","study_description":"","full_name":"","short_name":"","commons":"BioData Catalyst","study_url":"","_subjects_count":0,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs001607.v3.p2.c2":{"gen3_discovery":{"authz":"","tags":[],"_unique_id":"phs001607.v3.p2.c2","study_id":"phs001607.v3.p2.c2","study_description":"","full_name":"","short_name":"","commons":"BioData Catalyst","study_url":"","_subjects_count":0,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs001607.v3.p2.c3":{"gen3_discovery":{"authz":"","tags":[],"_unique_id":"phs001607.v3.p2.c3","study_id":"phs001607.v3.p2.c3","study_description":"","full_name":"","short_name":"","commons":"BioData Catalyst","study_url":"","_subjects_count":0,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs001607.v3.p2.c4":{"gen3_discovery":{"authz":"","tags":[],"_unique_id":"phs001607.v3.p2.c4","study_id":"phs001607.v3.p2.c4","study_description":"","full_name":"","short_name":"","commons":"BioData Catalyst","study_url":"","_subjects_count":0,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs001607.v3.p2.c5":{"gen3_discovery":{"authz":"","tags":[],"_unique_id":"phs001607.v3.p2.c5","study_id":"phs001607.v3.p2.c5","study_description":"","full_name":"","short_name":"","commons":"BioData Catalyst","study_url":"","_subjects_count":0,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs001607.v4.p2.c6":{"gen3_discovery":{"authz":"/programs/topmed/projects/IPF_DS-LD-IRB-COL-NPU","tags":[],"_unique_id":"phs001607.v4.p2.c6","study_id":"phs001607.v4.p2.c6","study_description":"No Study Description Available","full_name":"","short_name":"IPF_DS-LD-IRB-COL-NPU","commons":"BioData Catalyst","study_url":"","_subjects_count":361,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs001607.v4.p3.c1":{"gen3_discovery":{"authz":"/programs/topmed/projects/IPF_DS-ILD-IRB-NPU","tags":[],"_unique_id":"phs001607.v4.p3.c1","study_id":"phs001607.v4.p3.c1","study_description":"This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed) Whole Genome Sequencing Program. TOPMed is part of a broader Precision Medicine Initiative, which aims to provide disease treatments that are tailored to an individual's unique genes and environment. TOPMed will contribute to this initiative through the integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles, protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental, and clinical data. In doing so, this program aims to uncover factors that increase or decrease the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized treatments. Two genotype call sets derived from WGS are now available, Freeze 9b (GRCh38) and Freeze 10b (GRCh38), with largely overlapping sample sets. Information about how to identify other TOPMed WGS accessions for cross-study analysis, as well as descriptions of TOPMed methods of data acquisition, data processing and quality control, are provided in the accompanying documents, \"TOPMed Whole Genome Sequencing Project - Freeze 9b, Phases 1-4\" and \"TOPMed Whole Genome Sequencing Project - Freeze 10b, Phases 1-8\". Please check the study list at the top of each of these methods documents to determine whether it applies to this study accession. This is a set of cases diagnosed with idiopathic pulmonary fibrosis, a fatal interstitial lung disease. These cases were included in the TOPMed phase three studies. The planned study will compare these cases to within-TOPMed controls for genome-wide association studies. Study Design: Case Set Study Type: Case Set dbGaP estimated ancestry using GRAF-pop Total number of consented subjects: 3696 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"NHLBI TOPMed: Pulmonary Fibrosis Whole Genome Sequencing","short_name":"IPF_DS-ILD-IRB-NPU","commons":"BioData Catalyst","study_url":"","_subjects_count":356,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs001607.v4.p3.c2":{"gen3_discovery":{"authz":"/programs/topmed/projects/IPF_DS-LD-IRB-NPU","tags":[],"_unique_id":"phs001607.v4.p3.c2","study_id":"phs001607.v4.p3.c2","study_description":"This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed) Whole Genome Sequencing Program. TOPMed is part of a broader Precision Medicine Initiative, which aims to provide disease treatments that are tailored to an individual's unique genes and environment. TOPMed will contribute to this initiative through the integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles, protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental, and clinical data. In doing so, this program aims to uncover factors that increase or decrease the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized treatments. Two genotype call sets derived from WGS are now available, Freeze 9b (GRCh38) and Freeze 10b (GRCh38), with largely overlapping sample sets. Information about how to identify other TOPMed WGS accessions for cross-study analysis, as well as descriptions of TOPMed methods of data acquisition, data processing and quality control, are provided in the accompanying documents, \"TOPMed Whole Genome Sequencing Project - Freeze 9b, Phases 1-4\" and \"TOPMed Whole Genome Sequencing Project - Freeze 10b, Phases 1-8\". Please check the study list at the top of each of these methods documents to determine whether it applies to this study accession. This is a set of cases diagnosed with idiopathic pulmonary fibrosis, a fatal interstitial lung disease. These cases were included in the TOPMed phase three studies. The planned study will compare these cases to within-TOPMed controls for genome-wide association studies. Study Design: Case Set Study Type: Case Set dbGaP estimated ancestry using GRAF-pop Total number of consented subjects: 3696 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"NHLBI TOPMed: Pulmonary Fibrosis Whole Genome Sequencing","short_name":"IPF_DS-LD-IRB-NPU","commons":"BioData Catalyst","study_url":"","_subjects_count":2388,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs001607.v4.p3.c3":{"gen3_discovery":{"authz":"/programs/topmed/projects/IPF_DS-PFIB-IRB-NPU","tags":[],"_unique_id":"phs001607.v4.p3.c3","study_id":"phs001607.v4.p3.c3","study_description":"This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed) Whole Genome Sequencing Program. TOPMed is part of a broader Precision Medicine Initiative, which aims to provide disease treatments that are tailored to an individual's unique genes and environment. TOPMed will contribute to this initiative through the integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles, protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental, and clinical data. In doing so, this program aims to uncover factors that increase or decrease the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized treatments. Two genotype call sets derived from WGS are now available, Freeze 9b (GRCh38) and Freeze 10b (GRCh38), with largely overlapping sample sets. Information about how to identify other TOPMed WGS accessions for cross-study analysis, as well as descriptions of TOPMed methods of data acquisition, data processing and quality control, are provided in the accompanying documents, \"TOPMed Whole Genome Sequencing Project - Freeze 9b, Phases 1-4\" and \"TOPMed Whole Genome Sequencing Project - Freeze 10b, Phases 1-8\". Please check the study list at the top of each of these methods documents to determine whether it applies to this study accession. This is a set of cases diagnosed with idiopathic pulmonary fibrosis, a fatal interstitial lung disease. These cases were included in the TOPMed phase three studies. The planned study will compare these cases to within-TOPMed controls for genome-wide association studies. Study Design: Case Set Study Type: Case Set dbGaP estimated ancestry using GRAF-pop Total number of consented subjects: 3696 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"NHLBI TOPMed: Pulmonary Fibrosis Whole Genome Sequencing","short_name":"IPF_DS-PFIB-IRB-NPU","commons":"BioData Catalyst","study_url":"","_subjects_count":97,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs001607.v4.p3.c4":{"gen3_discovery":{"authz":"/programs/topmed/projects/IPF_DS-PUL-ILD-IRB-NPU","tags":[],"_unique_id":"phs001607.v4.p3.c4","study_id":"phs001607.v4.p3.c4","study_description":"This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed) Whole Genome Sequencing Program. TOPMed is part of a broader Precision Medicine Initiative, which aims to provide disease treatments that are tailored to an individual's unique genes and environment. TOPMed will contribute to this initiative through the integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles, protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental, and clinical data. In doing so, this program aims to uncover factors that increase or decrease the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized treatments. Two genotype call sets derived from WGS are now available, Freeze 9b (GRCh38) and Freeze 10b (GRCh38), with largely overlapping sample sets. Information about how to identify other TOPMed WGS accessions for cross-study analysis, as well as descriptions of TOPMed methods of data acquisition, data processing and quality control, are provided in the accompanying documents, \"TOPMed Whole Genome Sequencing Project - Freeze 9b, Phases 1-4\" and \"TOPMed Whole Genome Sequencing Project - Freeze 10b, Phases 1-8\". Please check the study list at the top of each of these methods documents to determine whether it applies to this study accession. This is a set of cases diagnosed with idiopathic pulmonary fibrosis, a fatal interstitial lung disease. These cases were included in the TOPMed phase three studies. The planned study will compare these cases to within-TOPMed controls for genome-wide association studies. Study Design: Case Set Study Type: Case Set dbGaP estimated ancestry using GRAF-pop Total number of consented subjects: 3696 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"NHLBI TOPMed: Pulmonary Fibrosis Whole Genome Sequencing","short_name":"IPF_DS-PUL-ILD-IRB-NPU","commons":"BioData Catalyst","study_url":"","_subjects_count":14,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs001607.v4.p3.c5":{"gen3_discovery":{"authz":"/programs/topmed/projects/IPF_HMB-IRB-NPU","tags":[],"_unique_id":"phs001607.v4.p3.c5","study_id":"phs001607.v4.p3.c5","study_description":"This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed) Whole Genome Sequencing Program. TOPMed is part of a broader Precision Medicine Initiative, which aims to provide disease treatments that are tailored to an individual's unique genes and environment. TOPMed will contribute to this initiative through the integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles, protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental, and clinical data. In doing so, this program aims to uncover factors that increase or decrease the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized treatments. Two genotype call sets derived from WGS are now available, Freeze 9b (GRCh38) and Freeze 10b (GRCh38), with largely overlapping sample sets. Information about how to identify other TOPMed WGS accessions for cross-study analysis, as well as descriptions of TOPMed methods of data acquisition, data processing and quality control, are provided in the accompanying documents, \"TOPMed Whole Genome Sequencing Project - Freeze 9b, Phases 1-4\" and \"TOPMed Whole Genome Sequencing Project - Freeze 10b, Phases 1-8\". Please check the study list at the top of each of these methods documents to determine whether it applies to this study accession. This is a set of cases diagnosed with idiopathic pulmonary fibrosis, a fatal interstitial lung disease. These cases were included in the TOPMed phase three studies. The planned study will compare these cases to within-TOPMed controls for genome-wide association studies. Study Design: Case Set Study Type: Case Set dbGaP estimated ancestry using GRAF-pop Total number of consented subjects: 3696 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"NHLBI TOPMed: Pulmonary Fibrosis Whole Genome Sequencing","short_name":"IPF_HMB-IRB-NPU","commons":"BioData Catalyst","study_url":"","_subjects_count":480,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs001608.v1.p1.c1":{"gen3_discovery":{"authz":"","tags":[],"_unique_id":"phs001608.v1.p1.c1","study_id":"phs001608.v1.p1.c1","study_description":"","full_name":"","short_name":"","commons":"BioData Catalyst","study_url":"","_subjects_count":0,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs001608.v2.p1.c1":{"gen3_discovery":{"authz":"/programs/topmed/projects/OMG_SCD_DS-SCD-IRB-PUB-COL-MDS-RD","tags":[{"name":"TOPMed","category":"Program"},{"name":"Genotype","category":"Data Type"},{"name":"Clinical Phenotype","category":"Data Type"},{"name":"dbGaP","category":"Study Registration"}],"_unique_id":"phs001608.v2.p1.c1","study_id":"phs001608.v2.p1.c1","study_description":"This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed) Whole Genome Sequencing Program. TOPMed is part of a broader Precision Medicine Initiative, which aims to provide disease treatments that are tailored to an individual's unique genes and environment. TOPMed will contribute to this initiative through the integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles, protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental, and clinical data. In doing so, this program aims to uncover factors that increase or decrease the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized treatments. Two genotype call sets derived from WGS are now available, Freeze 8 (GRCh38) and Freeze 9b (GRCh38), with largely overlapping sample sets. Information about how to identify other TOPMed WGS accessions for cross-study analysis, as well as descriptions of TOPMed methods of data acquisition, data processing and quality control, are provided in the accompanying documents, \"TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4\" and \"TOPMed Whole Genome Sequencing Project - Freeze 9b, Phases 1-4\". Please check the study list at the top of each of these methods documents to determine whether it applies to this study accession. Sickle cell disease (SCD) is caused by homozygosity for a single mutation of the beta hemoglobin gene. Despite the constancy of this genetic abnormality, the clinical course of patients with SCD is remarkably variable. SCD can affect the function and cause the failure of multiple organ systems through the pathophysiologic processes of vaso-occlusion and hemolysis. These pathophysiological processes are complex and expected to impact multiple organ systems in a variety of ways. This study, therefore, was designed to identify genetic factors that predispose SCD patients to develop specific end-organ complications and to experience more or less severe clinical courses. We enrolled > 700 patients with Hb SS, Hb S-beta0 thalassemia and HbSC being followed primarily at three southeastern U.S. regional institutions (Duke University Medical Center, University of North Carolina Medical Center, and Emory University Medical Center). Medical information obtained included the presence or absence of specific targeted outcomes (overall disease severity as well as specific types of end organ damage). Clinical data include medical status (history, physical, examination, and laboratory results) and information regarding potentially confounding environmental factors. Limited plasma samples are available for correlative studies (e.g. of cytokine levels, coagulation activation). Targeted SNP for candidate gene analysis as well as GWAS has been performed on most samples. Whole genome sequencing has been conducted through the TOPMed Consortium. The subjects in this analysis were collected as part of a larger study, \"Outcome Modifying Genes in Sickle Cell Disease\" (OMG-SCD) aimed at identifying genetic modifiers for sickle cell disease. More information about the study can be found in Elmariah et al. (2014), PMID: 24478166. Clinical and genetic data have been used to identify genetic characteristics predisposing patients with SCD to a more or less severe overall clinical course as well as to individual organ-specific complications. It is anticipated that identification of such genetic factors will reveal new therapeutic targets individualized to specific complications of SCD, leading to improved outcomes and increased life expectancy for patients with SCD. Study Design: Case Set Study Type: Case Set dbGaP estimated ancestry using GRAF-pop Total number of consented subjects: 642 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"NHLBI TOPMed: Outcome Modifying Genes in Sickle Cell Disease (OMG)","short_name":"OMG_SCD_DS-SCD-IRB-PUB-COL-MDS-RD","commons":"BioData Catalyst","study_url":"https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001608.v2.p1","_subjects_count":640,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs001610.v6.p16.c1":{"gen3_discovery":{"authz":"/programs/dbGaP/projects/T2D_GENES_FHS_HMB-IRB-MDS","tags":[],"_unique_id":"phs001610.v6.p16.c1","study_id":"phs001610.v6.p16.c1","study_description":"This substudy phs001610 Framingham T2D-GENES contains next-generation sequencing in multi-ethnic samples. Summary level phenotypes for the Framingham Cohort study participants can be viewed at the top-level study page phs000007 Framingham Cohort. Individual level phenotype data and molecular data for all Framingham top-level study and substudies are available by requesting Authorized Access to the Framingham Cohort study phs000007. The ~52,000 sample Type 2 Diabetes Exome Sequencing project is a collaboration of six consortia with various funding mechanisms that have joined together to investigate genetic variants for type 2 diabetes (T2D) using the largest T2D case/control sample set compiled to date. This includes samples from: Type 2 Diabetes Genetic Exploration by Next-generation sequencing in multi-Ethnic Samples (T2D-GENES) Genetics of Type 2 Diabetes (GoT2D) Exome Sequencing Project (ESP) Slim Initiative in Genomic Medicine for the Americas (SIGMA) Lundbeck Foundation Centre for Applied Medical Genomics in Personalised Disease Prediction, Prevention, and Care (LuCAMP) Progress in Diabetes Genetics in Youth (ProDIGY) This data generated from the Framingham Heart Study (FHS) cohort was part of the T2D-GENES (Type 2 Diabetes Genetic Exploration by Next-generation sequencing in multi-Ethnic Samples) consortium, which is a NIDDK-funded international research consortium that seeks to identify genetic variants for type 2 diabetes (T2D) through multiethnic sequencing studies. The T2D-GENES Project is a multi-ethnic sequencing study designed to assess whether less common variants play a role in T2D risk and to assess similarities and differences in the distribution of T2D risk variants across ancestry groups. The individuals were obtained from over 20 cohorts across the 6 consortia that are listed in Table 1. The strategy was to perform deep exome sequencing of individuals, 24,991 with T2D and 24,953 controls, divided among five ancestry groups: Europeans, East Asians, South Asians, American Hispanics, and African Americans. The T2D-GENES, ProDIGY and SIGMA studies, sequencing was performed at the Broad Institute using the Agilent v2 capture reagent or Illumina Rapid Capture on Illumina HiSeq machines. Please note that while we summarize the full sample list in publications and below, two of the cohorts below are not in dbGAP, due to the samples not being consented for deposition. This includes the Kooperative Gesundheitsforschung in der Region Augsburg (KORA) study and Lundbeck Foundation Centre for Applied Medical Genomics in Personalised Disease Prediction, Prevention, and Care (LuCamp) study. The Exome Sequencing Project (ESP) was deposited in dbGAP as part of their initial study and the phs numbers for that project can be found here: https://esp.gs.washington.edu/drupal/dbGaP_Releases. Table 1. 52,000 sample T2D Case/Control Whole Exome Sequencing Studies Ancestry Consortia Study Countries of Origin # Cases # Controls African American T2D-GENES Project 1 Jackson Heart Study US 500 526 African American T2D-GENES Project 1 Wake Forest School of Medicine Study US 518 530 African American ESP Exome Sequencing Project (ESP) US 467 1374 African American T2D-GENES Follow up study BioMe Biobank Program (BioMe) US 1297 1256 East Asian T2D-GENES Project 1 Korea Association Research Project Korea 526 561 East Asian T2D-GENES Project 1& Follow up Study Singapore Diabetes Cohort Study; Singapore Prospective Study Program Singapore (Chinese) 1486 1568 East Asian T2D-GENES Follow up study Korea SNUH South Korea 450 475 East Asian T2D-GENES Follow up study Research Studies in Hong Kong (Hong Kong) Hong Kong 493 485 European T2D-GENES Project 1 Ashkenazi US, Israel 506 355 European T2D-GENES Project 1 Metabolic Syndrome in Men Study (METSIM) Finland 484 498 European GoT2D Finland-United States Investigation of NIDDM Genetics (FUSION) Study Finland 472 476 European GoT2D Kooperative Gesundheitsforschung in der Region Augsburg (KORA) Germany 97 90 European GoT2D UK Type 2 Diabetes Genetics Consortium (UKT2D) UK 322 320 European GoT2D Malmo-Botnia Study Finland, Sweden 478 443 European LuCamp Lundbeck Foundation Centre for Applied Medical Genomics in Personalised Disease Prediction, Prevention, and Care (LuCamp) Denmark 997 997 European ESP Exome Sequencing Project (ESP) US 390 2843 European T2D-GENES Follow up study Genetics of Diabetes and Audit Research Tayside Study (GoDARTS) Scotland, UK 960 966 European T2D-GENES Follow up study Framingham Heart Study (FHS) US 396 596 Hispanic T2D-GENES Project 1 San Antonio Family Heart Study, San Antonio Family Diabetes/ Gallbladder Study, Veterans Administration Genetic Epidemiology Study, and the Investigation of Nephropathy and Diabetes Study Family Component US 272 218 Hispanic T2D-GENES Project 1 & SIGMAv2 Starr County, Texas US 1762 1738 Hispanic SIGMAv1 Mexico City Diabetes Study Mexico 281 549 Hispanic SIGMAv1 & v2 Multiethnic Cohort (MEC) US 1476 1443 Hispanic SIGMAv1 & v2 UNAM/INCMNSZ Diabetes Study (UIDS) Mexico 1998 1977 Hispanic SIGMAv1 & v2 Diabetes in Mexico Study (DMS) Mexico 1522 1546 Multi ethnic ProDIGY Treatment Options for Type 2 Diabetes in Adolescents and Youth (TODAY) US 3097 0 Multi ethnic ProDIGY SEARCH for Diabetes in Youth (SEARCH) US 553 0 South Asian T2D-GENES Project 1 London Life Sciences Population Study (LOLIPOP) UK (Indian Asian) 531 538 South Asian T2D-GENES Project 1 & Follow up study Singapore Indian Eye Study Singapore (Indian Asian) 1640 1478 South Asian T2D-GENES Follow up study Pakistan Risk of Myocardial Infarction Study (PROMIS) Pakistan 914 932 The FHS study contributed 396 cases and 596 controls to T2D-GENES Follow up study. Study Weblinks: T2D-GENES Consortium T2D-GENES The Framingham Heart Study NHLBI Framingham Heart Study Study Design: Case-Control Study Type: Case-Control Total number of consented subjects: 989 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Type 2 Diabetes Genetic Exploration by Next Generation Sequencing in Multi-Ethnic Samples (T2D-GENES) Follow-up Study: Framingham Heart Study","short_name":"T2D_GENES_FHS_HMB-IRB-MDS","commons":"BioData Catalyst","study_url":"","_subjects_count":798,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs001610.v6.p16.c2":{"gen3_discovery":{"authz":"/programs/dbGaP/projects/T2D_GENES_FHS_HMB-IRB-NPU-MDS","tags":[],"_unique_id":"phs001610.v6.p16.c2","study_id":"phs001610.v6.p16.c2","study_description":"This substudy phs001610 Framingham T2D-GENES contains next-generation sequencing in multi-ethnic samples. Summary level phenotypes for the Framingham Cohort study participants can be viewed at the top-level study page phs000007 Framingham Cohort. Individual level phenotype data and molecular data for all Framingham top-level study and substudies are available by requesting Authorized Access to the Framingham Cohort study phs000007. The ~52,000 sample Type 2 Diabetes Exome Sequencing project is a collaboration of six consortia with various funding mechanisms that have joined together to investigate genetic variants for type 2 diabetes (T2D) using the largest T2D case/control sample set compiled to date. This includes samples from: Type 2 Diabetes Genetic Exploration by Next-generation sequencing in multi-Ethnic Samples (T2D-GENES) Genetics of Type 2 Diabetes (GoT2D) Exome Sequencing Project (ESP) Slim Initiative in Genomic Medicine for the Americas (SIGMA) Lundbeck Foundation Centre for Applied Medical Genomics in Personalised Disease Prediction, Prevention, and Care (LuCAMP) Progress in Diabetes Genetics in Youth (ProDIGY) This data generated from the Framingham Heart Study (FHS) cohort was part of the T2D-GENES (Type 2 Diabetes Genetic Exploration by Next-generation sequencing in multi-Ethnic Samples) consortium, which is a NIDDK-funded international research consortium that seeks to identify genetic variants for type 2 diabetes (T2D) through multiethnic sequencing studies. The T2D-GENES Project is a multi-ethnic sequencing study designed to assess whether less common variants play a role in T2D risk and to assess similarities and differences in the distribution of T2D risk variants across ancestry groups. The individuals were obtained from over 20 cohorts across the 6 consortia that are listed in Table 1. The strategy was to perform deep exome sequencing of individuals, 24,991 with T2D and 24,953 controls, divided among five ancestry groups: Europeans, East Asians, South Asians, American Hispanics, and African Americans. The T2D-GENES, ProDIGY and SIGMA studies, sequencing was performed at the Broad Institute using the Agilent v2 capture reagent or Illumina Rapid Capture on Illumina HiSeq machines. Please note that while we summarize the full sample list in publications and below, two of the cohorts below are not in dbGAP, due to the samples not being consented for deposition. This includes the Kooperative Gesundheitsforschung in der Region Augsburg (KORA) study and Lundbeck Foundation Centre for Applied Medical Genomics in Personalised Disease Prediction, Prevention, and Care (LuCamp) study. The Exome Sequencing Project (ESP) was deposited in dbGAP as part of their initial study and the phs numbers for that project can be found here: https://esp.gs.washington.edu/drupal/dbGaP_Releases. Table 1. 52,000 sample T2D Case/Control Whole Exome Sequencing Studies Ancestry Consortia Study Countries of Origin # Cases # Controls African American T2D-GENES Project 1 Jackson Heart Study US 500 526 African American T2D-GENES Project 1 Wake Forest School of Medicine Study US 518 530 African American ESP Exome Sequencing Project (ESP) US 467 1374 African American T2D-GENES Follow up study BioMe Biobank Program (BioMe) US 1297 1256 East Asian T2D-GENES Project 1 Korea Association Research Project Korea 526 561 East Asian T2D-GENES Project 1& Follow up Study Singapore Diabetes Cohort Study; Singapore Prospective Study Program Singapore (Chinese) 1486 1568 East Asian T2D-GENES Follow up study Korea SNUH South Korea 450 475 East Asian T2D-GENES Follow up study Research Studies in Hong Kong (Hong Kong) Hong Kong 493 485 European T2D-GENES Project 1 Ashkenazi US, Israel 506 355 European T2D-GENES Project 1 Metabolic Syndrome in Men Study (METSIM) Finland 484 498 European GoT2D Finland-United States Investigation of NIDDM Genetics (FUSION) Study Finland 472 476 European GoT2D Kooperative Gesundheitsforschung in der Region Augsburg (KORA) Germany 97 90 European GoT2D UK Type 2 Diabetes Genetics Consortium (UKT2D) UK 322 320 European GoT2D Malmo-Botnia Study Finland, Sweden 478 443 European LuCamp Lundbeck Foundation Centre for Applied Medical Genomics in Personalised Disease Prediction, Prevention, and Care (LuCamp) Denmark 997 997 European ESP Exome Sequencing Project (ESP) US 390 2843 European T2D-GENES Follow up study Genetics of Diabetes and Audit Research Tayside Study (GoDARTS) Scotland, UK 960 966 European T2D-GENES Follow up study Framingham Heart Study (FHS) US 396 596 Hispanic T2D-GENES Project 1 San Antonio Family Heart Study, San Antonio Family Diabetes/ Gallbladder Study, Veterans Administration Genetic Epidemiology Study, and the Investigation of Nephropathy and Diabetes Study Family Component US 272 218 Hispanic T2D-GENES Project 1 & SIGMAv2 Starr County, Texas US 1762 1738 Hispanic SIGMAv1 Mexico City Diabetes Study Mexico 281 549 Hispanic SIGMAv1 & v2 Multiethnic Cohort (MEC) US 1476 1443 Hispanic SIGMAv1 & v2 UNAM/INCMNSZ Diabetes Study (UIDS) Mexico 1998 1977 Hispanic SIGMAv1 & v2 Diabetes in Mexico Study (DMS) Mexico 1522 1546 Multi ethnic ProDIGY Treatment Options for Type 2 Diabetes in Adolescents and Youth (TODAY) US 3097 0 Multi ethnic ProDIGY SEARCH for Diabetes in Youth (SEARCH) US 553 0 South Asian T2D-GENES Project 1 London Life Sciences Population Study (LOLIPOP) UK (Indian Asian) 531 538 South Asian T2D-GENES Project 1 & Follow up study Singapore Indian Eye Study Singapore (Indian Asian) 1640 1478 South Asian T2D-GENES Follow up study Pakistan Risk of Myocardial Infarction Study (PROMIS) Pakistan 914 932 The FHS study contributed 396 cases and 596 controls to T2D-GENES Follow up study. Study Weblinks: T2D-GENES Consortium T2D-GENES The Framingham Heart Study NHLBI Framingham Heart Study Study Design: Case-Control Study Type: Case-Control Total number of consented subjects: 989 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Type 2 Diabetes Genetic Exploration by Next Generation Sequencing in Multi-Ethnic Samples (T2D-GENES) Follow-up Study: Framingham Heart Study","short_name":"T2D_GENES_FHS_HMB-IRB-NPU-MDS","commons":"BioData Catalyst","study_url":"","_subjects_count":191,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs001612.v1.p1.c1":{"gen3_discovery":{"authz":"","tags":[],"_unique_id":"phs001612.v1.p1.c1","study_id":"phs001612.v1.p1.c1","study_description":"","full_name":"","short_name":"","commons":"BioData Catalyst","study_url":"","_subjects_count":0,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs001612.v1.p1.c2":{"gen3_discovery":{"authz":"","tags":[],"_unique_id":"phs001612.v1.p1.c2","study_id":"phs001612.v1.p1.c2","study_description":"","full_name":"","short_name":"","commons":"BioData Catalyst","study_url":"","_subjects_count":0,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs001612.v3.p3.c1":{"gen3_discovery":{"authz":"/programs/topmed/projects/CARDIA_HMB-IRB","tags":[],"_unique_id":"phs001612.v3.p3.c1","study_id":"phs001612.v3.p3.c1","study_description":"This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed) Whole Genome Sequencing Program. TOPMed is part of a broader Precision Medicine Initiative, which aims to provide disease treatments that are tailored to an individual's unique genes and environment. TOPMed will contribute to this initiative through the integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles, protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental, and clinical data. In doing so, this program aims to uncover factors that increase or decrease the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized treatments. Two genotype call sets derived from WGS are now available, Freeze 9b (GRCh38) and Freeze 10b (GRCh38), with largely overlapping sample sets. Information about how to identify other TOPMed WGS accessions for cross-study analysis, as well as descriptions of TOPMed methods of data acquisition, data processing and quality control, are provided in the accompanying documents, \"TOPMed Whole Genome Sequencing Project - Freeze 9b, Phases 1-4\" and \"TOPMed Whole Genome Sequencing Project - Freeze 10b, Phases 1-8\". Please check the study list at the top of each of these methods documents to determine whether it applies to this study accession. CARDIA is a study examining the etiology and natural history of cardiovascular disease beginning in young adulthood. In 1985-1986, a cohort of 5115 healthy black and white men and women, aged 18-30 years, were selected to have approximately the same number of people in subgroups of age (18-24 and 25-30), sex, race, and education (high school or less, and more than high school) within each of four US Field Centers. These same participants were asked to participate in follow-up examinations during 1987-1988 (Year 2), 1990-1991 (Year 5), 1992-1993 (Year 7), 1995-1996 (Year 10), 2000-2001 (Year 15), 2005-2006 (Year 20), 2010-2011 (Year 25) and 2015-2016 (Year 30). In addition to the follow-up examinations, participants are contacted regularly for the ascertainment of information on out-patient procedures and hospitalizations experienced between contacts. Within the past five years, 95% of the original surviving cohort has been contacted. While the specifics of each examination have differed somewhat, data have been collected on a variety of factors believed to be related to heart disease. These include conditions with clear links to heart disease, such as blood pressure, cholesterol and other lipids. Data have also been collected on physical measurements, such as weight and skinfold fat, as well as lifestyle factors such as substance use (tobacco and alcohol), dietary and exercise patterns, behavioral and psychological variables, medical and family history, and other chemistries (e.g., insulin and glucose). In addition, subclinical atherosclerosis was measured via echocardiography during Years 5, 10, and 25, computed tomography during Years 15 and 20, and carotid ultrasound during Year 20.Comprehensive phenotypic data for study participants are available through dbGaP phs000285. Study Weblinks: CARDIA: Coronary Artery Risk Development in Young Adults Study Design: Prospective Longitudinal Cohort Study Type: Longitudinal dbGaP estimated ancestry using GRAF-pop Total number of consented subjects: 3598 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"NHLBI TOPMed: Coronary Artery Risk Development in Young Adults (CARDIA)","short_name":"CARDIA_HMB-IRB","commons":"BioData Catalyst","study_url":"","_subjects_count":3475,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs001612.v3.p3.c2":{"gen3_discovery":{"authz":"/programs/topmed/projects/CARDIA_HMB-IRB-NPU","tags":[],"_unique_id":"phs001612.v3.p3.c2","study_id":"phs001612.v3.p3.c2","study_description":"This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed) Whole Genome Sequencing Program. TOPMed is part of a broader Precision Medicine Initiative, which aims to provide disease treatments that are tailored to an individual's unique genes and environment. TOPMed will contribute to this initiative through the integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles, protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental, and clinical data. In doing so, this program aims to uncover factors that increase or decrease the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized treatments. Two genotype call sets derived from WGS are now available, Freeze 9b (GRCh38) and Freeze 10b (GRCh38), with largely overlapping sample sets. Information about how to identify other TOPMed WGS accessions for cross-study analysis, as well as descriptions of TOPMed methods of data acquisition, data processing and quality control, are provided in the accompanying documents, \"TOPMed Whole Genome Sequencing Project - Freeze 9b, Phases 1-4\" and \"TOPMed Whole Genome Sequencing Project - Freeze 10b, Phases 1-8\". Please check the study list at the top of each of these methods documents to determine whether it applies to this study accession. CARDIA is a study examining the etiology and natural history of cardiovascular disease beginning in young adulthood. In 1985-1986, a cohort of 5115 healthy black and white men and women, aged 18-30 years, were selected to have approximately the same number of people in subgroups of age (18-24 and 25-30), sex, race, and education (high school or less, and more than high school) within each of four US Field Centers. These same participants were asked to participate in follow-up examinations during 1987-1988 (Year 2), 1990-1991 (Year 5), 1992-1993 (Year 7), 1995-1996 (Year 10), 2000-2001 (Year 15), 2005-2006 (Year 20), 2010-2011 (Year 25) and 2015-2016 (Year 30). In addition to the follow-up examinations, participants are contacted regularly for the ascertainment of information on out-patient procedures and hospitalizations experienced between contacts. Within the past five years, 95% of the original surviving cohort has been contacted. While the specifics of each examination have differed somewhat, data have been collected on a variety of factors believed to be related to heart disease. These include conditions with clear links to heart disease, such as blood pressure, cholesterol and other lipids. Data have also been collected on physical measurements, such as weight and skinfold fat, as well as lifestyle factors such as substance use (tobacco and alcohol), dietary and exercise patterns, behavioral and psychological variables, medical and family history, and other chemistries (e.g., insulin and glucose). In addition, subclinical atherosclerosis was measured via echocardiography during Years 5, 10, and 25, computed tomography during Years 15 and 20, and carotid ultrasound during Year 20.Comprehensive phenotypic data for study participants are available through dbGaP phs000285. Study Weblinks: CARDIA: Coronary Artery Risk Development in Young Adults Study Design: Prospective Longitudinal Cohort Study Type: Longitudinal dbGaP estimated ancestry using GRAF-pop Total number of consented subjects: 3598 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"NHLBI TOPMed: Coronary Artery Risk Development in Young Adults (CARDIA)","short_name":"CARDIA_HMB-IRB-NPU","commons":"BioData Catalyst","study_url":"","_subjects_count":123,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs001624.v1.p1.c1":{"gen3_discovery":{"authz":"","tags":[],"_unique_id":"phs001624.v1.p1.c1","study_id":"phs001624.v1.p1.c1","study_description":"","full_name":"","short_name":"","commons":"BioData Catalyst","study_url":"","_subjects_count":0,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs001624.v3.p2.c1":{"gen3_discovery":{"authz":"/programs/topmed/projects/BioVU_AF_HMB-GSO","tags":[{"name":"TOPMed","category":"Program"},{"name":"Genotype","category":"Data Type"},{"name":"Clinical Phenotype","category":"Data Type"},{"name":"dbGaP","category":"Study Registration"}],"_unique_id":"phs001624.v3.p2.c1","study_id":"phs001624.v3.p2.c1","study_description":"This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed) Whole Genome Sequencing Program. TOPMed is part of a broader Precision Medicine Initiative, which aims to provide disease treatments that are tailored to an individual's unique genes and environment. TOPMed will contribute to this initiative through the integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles, protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental, and clinical data. In doing so, this program aims to uncover factors that increase or decrease the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized treatments. Two genotype call sets derived from WGS are now available, Freeze 9b (GRCh38) and Freeze 10b (GRCh38), with largely overlapping sample sets. Information about how to identify other TOPMed WGS accessions for cross-study analysis, as well as descriptions of TOPMed methods of data acquisition, data processing and quality control, are provided in the accompanying documents, \"TOPMed Whole Genome Sequencing Project - Freeze 9b, Phases 1-4\" and \"TOPMed Whole Genome Sequencing Project - Freeze 10b, Phases 1-8\". Please check the study list at the top of each of these methods documents to determine whether it applies to this study accession. Atrial fibrillation (also called AFib or AF) is a quivering or irregular heartbeat (arrhythmia) that can lead to blood clots, stroke, heart failure and other heart-related complications. At least 2.7 million Americans are living with AFib. Individuals with early onset atrial fibrillation (AF) are included in this study of cases from the BioVU sample repository. BioVU is Vanderbilt's biobank of DNA extracted from leftover and otherwise discarded clinical blood specimens. BioVU operates as a consented biorepository; all individuals must sign the BioVU consent form in order to donate future specimens. BioVU subjects are de-identified and linked to the Synthetic Derivative enabling researchers to access genetic data/DNA material as well as dense, longitudinal electronic medical record (EMR) information. Study Design: Case-Control Study Type: Case-Control dbGaP estimated ancestry using GRAF-pop Total number of consented subjects: 2666 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"NHLBI TOPMed - NHGRI CCDG: The Vanderbilt University BioVU Atrial Fibrillation Genetics Study","short_name":"BioVU_AF_HMB-GSO","commons":"BioData Catalyst","study_url":"https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001624.v3.p2","_subjects_count":2117,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs001644.v1.p1.c1":{"gen3_discovery":{"authz":"","tags":[],"_unique_id":"phs001644.v1.p1.c1","study_id":"phs001644.v1.p1.c1","study_description":"","full_name":"","short_name":"","commons":"BioData Catalyst","study_url":"","_subjects_count":0,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs001644.v3.p2.c1":{"gen3_discovery":{"authz":"/programs/topmed/projects/BioMe_HMB-NPU","tags":[{"name":"TOPMed","category":"Program"},{"name":"Genotype","category":"Data Type"},{"name":"dbGaP","category":"Study Registration"}],"_unique_id":"phs001644.v3.p2.c1","study_id":"phs001644.v3.p2.c1","study_description":"This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed) Whole Genome Sequencing Program. TOPMed is part of a broader Precision Medicine Initiative, which aims to provide disease treatments that are tailored to an individual's unique genes and environment. TOPMed will contribute to this initiative through the integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles, protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental, and clinical data. In doing so, this program aims to uncover factors that increase or decrease the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized treatments. Two genotype call sets derived from WGS are now available, Freeze 9b (GRCh38) and Freeze 10b (GRCh38), with largely overlapping sample sets. Information about how to identify other TOPMed WGS accessions for cross-study analysis, as well as descriptions of TOPMed methods of data acquisition, data processing and quality control, are provided in the accompanying documents, \"TOPMed Whole Genome Sequencing Project - Freeze 9b, Phases 1-4\" and \"TOPMed Whole Genome Sequencing Project - Freeze 10b, Phases 1-8\". Please check the study list at the top of each of these methods documents to determine whether it applies to this study accession. The IPM BioMe Biobank, founded in September 2007, is an ongoing, broadly-consented electronic health record (EHR)-linked clinical care biobank that enrolls participants non-selectively from the Mount Sinai Medical Center patient population. BioMe currently comprises >42,000 participants from diverse ancestries, characterized by a broad spectrum of longitudinal biomedical traits. Participants are enrolled through an opt-in process and consent to be followed throughout their clinical care (past, present, and future) in real-time, allowing us to integrate their genomic information with their EHRs for discovery research and clinical care implementation. BioMe participants consent for recall, based on their genotype and/or phenotype, permitting in-depth follow-up and functional studies for selected participants at any time. Phenotypic and genomic data are stored in a secure database and made available to investigators, contingent on approval by the BioMe Governing Board. BioMe uses a \"data-broker\" system to protect confidentiality. Ancestral diversity - BioMe participants represent a broad racial, ethnic and socioeconomic diversity with a distinct and population-specific disease burden. Specifically, BioMe participants are of African (AA), Hispanic/Latino (HL), European (EA) and other/mixed ancestry. BioMe participants are predominantly of African (AA, 24%), Hispanic/Latino (HL, 35%), European (EA, 32%), and other ancestry (OA, 10%). Participants who self-identify as Hispanic/Latino further report to be of Puerto Rican (39%), Dominican (23%), Central/South American (17%), Mexican (5%) or other Hispanic (16%) ancestry. More than 40% of European ancestry participants are genetically determined to be of Ashkenazi Jewish ancestry. With this broad ancestral diversity, BioMe is uniquely positioned to examine the impact of demographic and evolutionary forces that have shaped common disease risk. Phenotypes available in BioMe - BioMe has a high-quality and validated set of fully implemented clinical phenotype data that has been culled by a multi-disciplinary team of experienced investigators, clinicians, information technologists, data-managers, and programmers who apply advanced medical informatics and data mining tools to extract and harmonize EHRs. BioMe, as a cohort, offers a great versatility for designing nested case-control sample-sets, particularly for studying longitudinal traits and co-morbidity in disease burden. Biomedical and clinical outcomes: The BioMe Biobank is linked to Mount Sinai's system-wide Epic EHR, which captures a full spectrum of biomedical phenotypes, including clinical outcomes, covariate and exposure data from past, present and future health care encounters. As such, the BioMe Biobank has a longitudinal design as participants consent to make all of their EHR data from past (dating back as far as 2003), present and future inpatient or outpatient encounters available for research, without restriction. The median number of outpatient encounters is 21 per participant, reflecting predominant enrollment of participants with common chronic conditions from primary care facilities. Environmental data: The clinical and EHR information is complemented by detailed demographic and lifestyle information, including ancestry, residence history, country of origin, personal and familial medical history, education, socio-economic status, physical activity, smoking, dietary habits, alcohol intake, and body weight history, which is collected in a systematic manner by interview-based questionnaire at time of enrollment. The IPM BioMe Biobank contributed ~10,600 DNA samples for whole genome sequencing to the TOPMed program. Samples were selected for the Coronary Artery Disease (CAD) and the Chronic Obstructive Pulmonary Disease (COPD) working groups. Using a Case-Definition-Algorithm (CDA), we identified ~4,100 individuals with CAD (~50% women) and ~3,000 individuals as controls (65% women). In addition, we identified ~800 individuals with COPD (62% women) and 1800 individuals as controls (72% women). Another 600 BioMe participants with Atrial Fibrillation, all of African ancestry, were included. Study Weblinks: The Charles Bronfman Institute for Personalized Medicine Study Design: Prospective Longitudinal Cohort Study Type: Cohort Genotype Sequencing dbGaP estimated ancestry using GRAF-pop Total number of consented subjects: 12050 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"NHLBI TOPMed - NHGRI CCDG: The BioMe Biobank at Mount Sinai","short_name":"BioMe_HMB-NPU","commons":"BioData Catalyst","study_url":"https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001644.v3.p2","_subjects_count":15974,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs001661.v2.p1.c1":{"gen3_discovery":{"authz":"","tags":[],"_unique_id":"phs001661.v2.p1.c1","study_id":"phs001661.v2.p1.c1","study_description":"","full_name":"","short_name":"","commons":"BioData Catalyst","study_url":"","_subjects_count":0,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs001661.v3.p1.c1":{"gen3_discovery":{"authz":null,"tags":null,"_unique_id":"phs001661.v3.p1.c1","study_id":"phs001661.v3.p1.c1","study_description":null,"full_name":null,"short_name":null,"commons":"BioData Catalyst","study_url":null,"_subjects_count":0,"__manifest":null,"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs001661.v4.p1.c1":{"gen3_discovery":{"authz":"/programs/topmed/projects/GCPD-A_DS-ASTHMA-GSO","tags":[],"_unique_id":"phs001661.v4.p1.c1","study_id":"phs001661.v4.p1.c1","study_description":"This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed) Whole Genome Sequencing Program. TOPMed is part of a broader Precision Medicine Initiative, which aims to provide disease treatments that are tailored to an individual's unique genes and environment. TOPMed will contribute to this initiative through the integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles, protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental, and clinical data. In doing so, this program aims to uncover factors that increase or decrease the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized treatments. Two genotype call sets derived from WGS are now available, Freeze 9b (GRCh38) and Freeze 10b (GRCh38), with largely overlapping sample sets. Information about how to identify other TOPMed WGS accessions for cross-study analysis, as well as descriptions of TOPMed methods of data acquisition, data processing and quality control, are provided in the accompanying documents, \"TOPMed Whole Genome Sequencing Project - Freeze 9b, Phases 1-4\" and \"TOPMed Whole Genome Sequencing Project - Freeze 10b, Phases 1-8\". Please check the study list at the top of each of these methods documents to determine whether it applies to this study accession. The Center for Applied Genomics (CAG) at the Children's Hospital of Philadelphia (CHOP) is focused on addressing the roles of both single nucleotide variants and structural copy number variants, and their functional impact, together with gene-environment interactions and their influence on asthma drug response. Study Design: Case-Control Study Type: Case-Control dbGaP estimated ancestry using GRAF-pop Total number of consented subjects: 5464 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"NHLBI TOPMed: Genetic Causes of Complex Pediatric Disorders - Asthma (GCPD-A)","short_name":"GCPD-A_DS-ASTHMA-GSO","commons":"BioData Catalyst","study_url":"","_subjects_count":5464,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs001662.v1.p1.c2":{"gen3_discovery":{"authz":"","tags":[],"_unique_id":"phs001662.v1.p1.c2","study_id":"phs001662.v1.p1.c2","study_description":"","full_name":"","short_name":"","commons":"BioData Catalyst","study_url":"","_subjects_count":0,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs001662.v2.p1.c2":{"gen3_discovery":{"authz":null,"tags":null,"_unique_id":"phs001662.v2.p1.c2","study_id":"phs001662.v2.p1.c2","study_description":null,"full_name":null,"short_name":null,"commons":"BioData Catalyst","study_url":null,"_subjects_count":0,"__manifest":null,"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs001662.v3.p1.c2":{"gen3_discovery":{"authz":null,"tags":null,"_unique_id":"phs001662.v3.p1.c2","study_id":"phs001662.v3.p1.c2","study_description":null,"full_name":null,"short_name":null,"commons":"BioData Catalyst","study_url":null,"_subjects_count":0,"__manifest":null,"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs001662.v4.p2.c2":{"gen3_discovery":{"authz":"/programs/topmed/projects/LTRC_HMB-MDS","tags":[],"_unique_id":"phs001662.v4.p2.c2","study_id":"phs001662.v4.p2.c2","study_description":"This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed) Whole Genome Sequencing Program. TOPMed is part of a broader Precision Medicine Initiative, which aims to provide disease treatments that are tailored to an individual's unique genes and environment. TOPMed will contribute to this initiative through the integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles, protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental, and clinical data. In doing so, this program aims to uncover factors that increase or decrease the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized treatments. Two genotype call sets derived from WGS are now available, Freeze 9b (GRCh38) and Freeze 10b (GRCh38), with largely overlapping sample sets. Information about how to identify other TOPMed WGS accessions for cross-study analysis, as well as descriptions of TOPMed methods of data acquisition, data processing and quality control, are provided in the accompanying documents, \"TOPMed Whole Genome Sequencing Project - Freeze 9b, Phases 1-4\" and \"TOPMed Whole Genome Sequencing Project - Freeze 10b, Phases 1-8\". Please check the study list at the top of each of these methods documents to determine whether it applies to this study accession. Chronic obstructive pulmonary disease (COPD), a disease state characterized by airflow limitation that is not fully reversible, is the third leading cause of death in the U.S. COPD is a heterogeneous syndrome, with affected individuals demonstrating marked differences in lung structure (emphysema vs. airway disease); physiology (airflow obstruction); and other clinical features (e.g., exacerbations, co-morbid illnesses). Multiple genomic regions influencing COPD susceptibility have been identified by genome-wide association studies (GWAS), and rare coding variants can also influence risk for COPD. However, only a small percentage of the estimated heritability for COPD risk can be explained by known genetic loci. Like most complex diseases, COPD is influenced by multiple genetic determinants (each with modest individual effects). Emerging evidence supports the paradigm that complex disease genetic determinants are part of a network of interacting genes and proteins; perturbations of this network can increase disease risk. To identify this network, multiple Omics data will need to be analyzed with methods to account for nonlinear relationships and interactions between key genes and proteins. Our overall hypothesis is that integrated network analysis of genetic, transcriptomic, proteomic, and epigenetic data from biospecimens ranging from lung tissue to nasal epithelial cells to blood in highly phenotyped subjects will provide insights into COPD pathogenesis and heterogeneity. We will leverage the well-phenotyped, NHLBI-funded Lung Tissue Research Consortium (LTRC) to address these questions. We will perform multi-omics analysis in 1548 lung tissue and blood samples from the LTRC. With these multi-omics data, we will utilize a systems biology approach to understand relationships between multiple genetic determinants and multiple types of Omics data. We will begin by performing single Omics analyses in COPD vs. control lung, nasal, and blood samples. Next, we will integrate single Omics data with genetic variants identified by WGS to assist in fine mapping genetic determinants of COPD. We will then perform integrated network analysis of COPD with genetic and multiple Omics data using correlation-based, gene regulatory, and Bayesian networks. Subjects were recruited from Mayo Clinic, Universities of Colorado, Michigan, and Pittsburgh, and Temple University. Study Weblinks: LTRC Study Design: Case-Control Study Type: Case-Control dbGaP estimated ancestry using GRAF-pop Total number of consented subjects: 1609 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"NHLBI TOPMed: Lung Tissue Research Consortium (LTRC)","short_name":"LTRC_HMB-MDS","commons":"BioData Catalyst","study_url":"","_subjects_count":1609,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs001672.v11.p1.c1":{"gen3_discovery":{"authz":null,"tags":null,"_unique_id":"phs001672.v11.p1.c1","study_id":"phs001672.v11.p1.c1","study_description":null,"full_name":null,"short_name":null,"commons":"BioData Catalyst","study_url":null,"_subjects_count":0,"__manifest":null,"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs001672.v13.p1.c1":{"gen3_discovery":{"authz":"/programs/dbGaP/projects/MVP_MDS","tags":[],"_unique_id":"phs001672.v13.p1.c1","study_id":"phs001672.v13.p1.c1","study_description":"MVP is an ongoing prospective cohort study and mega-biobank in the Department of Veterans Affairs Healthcare System designed to study genetic influences on health and disease among veterans. Study Weblinks: MVP Study Design: Prospective Longitudinal Cohort Study Type: Cohort Electronic Medical Records Longitudinal Prospective NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Veterans Administration (VA) Million Veteran Program (MVP) Summary Results from Omics Studies","short_name":"MVP_MDS","commons":"BioData Catalyst","study_url":"","_subjects_count":0,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs001679.v1.p1.c1":{"gen3_discovery":{"authz":"/programs/heartfailure/projects/TRANSCRibE_GRU","tags":[],"_unique_id":"phs001679.v1.p1.c1","study_id":"phs001679.v1.p1.c1","study_description":"Myocardial ischemia occurs when there is a mismatch between coronary oxygen delivery and metabolic requirements of the myocardium, which may be clinically manifested during angina, coronary angioplasty or cardiopulmonary bypass (CPB). Myocardial ischemia may lead to a spectrum of myocardial stunning, hibernating myocardium, and ultimately cell death if the ischemic insult is severe. In the human heart, irreversible damage begins after approximately 20 to 40 minutes of oxygen deprivation. Observed molecular and cellular changes of myocardial ischemia are characteristic of an inflammatory response, but the exact mechanisms that underlie this pathological process are unclear and may not be full emulated by animal models of ischemia or infarction. Thus, we felt it valuable to investigate a human ischemia model. During cardiac surgery, CPB with aortic cross-clamping (AoXC) and cardioplegic arrest is associated with excellent clinical outcomes and suitable operative conditions. However, despite the use of cardioprotective strategies, AoXc during CPB is accompanied by a variable, yet obligate ischemic period lasting 1 to 3 hours, resulting in hypoxia, metabolic substrate depletion, reperfusion injury, apoptosis, and necrosis. Cardiac specific biomarkers of ischemia and infarction, including troponin, are elevated even after routine coronary artery bypass graft surgery and correlate with the duration of ischemia from AoXc.This process of CPB provides us with the ability to examine the transcriptional profile before and after an expected, consistent, and reproducible human ischemic event, albeit induced by cold cardioplegic arrest and not coronary occlusion. In addition, the absence of reperfusion in this time period allows us to examine the transcriptomic response to intermittent ischemia, without having to account for the perturbations of reperfusion injury. Although various animal models have been used to examine the effects of ischemia on cardiac function, no human data exist which examine the early transcriptomic response to a left ventricular (LV) ischemic insult. We therefore characterized the effect of cold cardioplegia induced acute ischemia on the transcriptional profile of the LV by performing whole transcriptome next-generation RNA-sequencing (RNA-seq) in patients undergoing cardiac surgery by sampling human LV tissue prior to, and after, the obligate ischemia during AoXC. We hypothesized that the cold cardioplegia induced ischemic injury will dramatically alter transcription in the human myocardium, and that we would identify genes and pathways, which will identify interventional targets for pharmacological therapy. Methods:We have collected left ventricle tissue samples and blood sample from patients undergoing heart surgery. We obtained punch biopsies (~3-5μg total RNA content) from the site of a routinely placed surgical vent in the anterolateral apical left ventricular wall of patients undergoing elective aortic valve replacement surgery with cardiopulmonary bypass. After an average of 79 minutes of aortic cross-clamping with intermittent cold blood cardioplegia for myocardial protection every 20 minutes, a second biopsy was obtained in the same manner. Tissue samples were immediately placed in RNAlater® (Ambion, ThermoFisher Scientific, Waltham, MA), and after 48 hours at +4°C were stored at -80°C until RNA extraction. Total RNA was isolated with Trizol and RNA quality was assessed using the Agilent Bioanalyzer 2100 (Agilent, Santa Clara, CA). Libraries were prepared by poly(A) mRNA isolation and reverse transcription Polymerase Chain Reaction (RT-PCR), then sequenced on the Illumina HiSeq2000 or HiSeq2500 (Illumina, San Diego, CA). As samples were analyzed at different times, different read lengths were employed, initially using single-end reads (n=20) and then transitioning to paired end reads (n=216), ranging from 36 - 100 base pairs. Raw sequencing files were processed using Sickle, Skewer, and STAR software, and aligned to GrCh37 or UCSC Hg19. DNA was isolated from whole blood using standard methods. SNP genotyping was performed using the Illumina Omni2.5Exome-8 BeadChip array with additional exome content (Illumina, San Diego, CA) chip, version 1.1. We first phased and imputed 93 subjects using a phasing tool called SHAPEIT and an imputation tool called MINIMAC, with 1000 Genomes phase 1 version 3 for the reference panel. We then phased and imputed 26 more subjects using SHAPEIT, an imputation tool called IMPUTE2, and 1000 Genomes phase 3 version 5. Study Weblinks: TRANSCRibE Study Design: Prospective Longitudinal Cohort Study Type: Clinical Cohort Cohort Epigenetics Exome Sequencing Full Transcriptome Sequencing Genotype Genotype/Expression Genotype/Expression array Individual-Level Genomic Data Longitudinal Observational Prospective RNA Sequencing Sequencing Tissue Expression Transcriptome Analysis Transcriptome Sequencing dbGaP estimated ancestry using GRAF-pop Total number of consented subjects: 119 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"TRanscriptomic ANalySis of left ventriCulaR gene Expression (TRANSCRibE)","short_name":"TRANSCRibE_GRU","commons":"BioData Catalyst","study_url":"","_subjects_count":79,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs001679.v1.p1.c2":{"gen3_discovery":{"authz":"/programs/heartfailure/projects/TRANSCRibE_DS-CI","tags":[],"_unique_id":"phs001679.v1.p1.c2","study_id":"phs001679.v1.p1.c2","study_description":"Myocardial ischemia occurs when there is a mismatch between coronary oxygen delivery and metabolic requirements of the myocardium, which may be clinically manifested during angina, coronary angioplasty or cardiopulmonary bypass (CPB). Myocardial ischemia may lead to a spectrum of myocardial stunning, hibernating myocardium, and ultimately cell death if the ischemic insult is severe. In the human heart, irreversible damage begins after approximately 20 to 40 minutes of oxygen deprivation. Observed molecular and cellular changes of myocardial ischemia are characteristic of an inflammatory response, but the exact mechanisms that underlie this pathological process are unclear and may not be full emulated by animal models of ischemia or infarction. Thus, we felt it valuable to investigate a human ischemia model. During cardiac surgery, CPB with aortic cross-clamping (AoXC) and cardioplegic arrest is associated with excellent clinical outcomes and suitable operative conditions. However, despite the use of cardioprotective strategies, AoXc during CPB is accompanied by a variable, yet obligate ischemic period lasting 1 to 3 hours, resulting in hypoxia, metabolic substrate depletion, reperfusion injury, apoptosis, and necrosis. Cardiac specific biomarkers of ischemia and infarction, including troponin, are elevated even after routine coronary artery bypass graft surgery and correlate with the duration of ischemia from AoXc.This process of CPB provides us with the ability to examine the transcriptional profile before and after an expected, consistent, and reproducible human ischemic event, albeit induced by cold cardioplegic arrest and not coronary occlusion. In addition, the absence of reperfusion in this time period allows us to examine the transcriptomic response to intermittent ischemia, without having to account for the perturbations of reperfusion injury. Although various animal models have been used to examine the effects of ischemia on cardiac function, no human data exist which examine the early transcriptomic response to a left ventricular (LV) ischemic insult. We therefore characterized the effect of cold cardioplegia induced acute ischemia on the transcriptional profile of the LV by performing whole transcriptome next-generation RNA-sequencing (RNA-seq) in patients undergoing cardiac surgery by sampling human LV tissue prior to, and after, the obligate ischemia during AoXC. We hypothesized that the cold cardioplegia induced ischemic injury will dramatically alter transcription in the human myocardium, and that we would identify genes and pathways, which will identify interventional targets for pharmacological therapy. Methods:We have collected left ventricle tissue samples and blood sample from patients undergoing heart surgery. We obtained punch biopsies (~3-5μg total RNA content) from the site of a routinely placed surgical vent in the anterolateral apical left ventricular wall of patients undergoing elective aortic valve replacement surgery with cardiopulmonary bypass. After an average of 79 minutes of aortic cross-clamping with intermittent cold blood cardioplegia for myocardial protection every 20 minutes, a second biopsy was obtained in the same manner. Tissue samples were immediately placed in RNAlater® (Ambion, ThermoFisher Scientific, Waltham, MA), and after 48 hours at +4°C were stored at -80°C until RNA extraction. Total RNA was isolated with Trizol and RNA quality was assessed using the Agilent Bioanalyzer 2100 (Agilent, Santa Clara, CA). Libraries were prepared by poly(A) mRNA isolation and reverse transcription Polymerase Chain Reaction (RT-PCR), then sequenced on the Illumina HiSeq2000 or HiSeq2500 (Illumina, San Diego, CA). As samples were analyzed at different times, different read lengths were employed, initially using single-end reads (n=20) and then transitioning to paired end reads (n=216), ranging from 36 - 100 base pairs. Raw sequencing files were processed using Sickle, Skewer, and STAR software, and aligned to GrCh37 or UCSC Hg19. DNA was isolated from whole blood using standard methods. SNP genotyping was performed using the Illumina Omni2.5Exome-8 BeadChip array with additional exome content (Illumina, San Diego, CA) chip, version 1.1. We first phased and imputed 93 subjects using a phasing tool called SHAPEIT and an imputation tool called MINIMAC, with 1000 Genomes phase 1 version 3 for the reference panel. We then phased and imputed 26 more subjects using SHAPEIT, an imputation tool called IMPUTE2, and 1000 Genomes phase 3 version 5. Study Weblinks: TRANSCRibE Study Design: Prospective Longitudinal Cohort Study Type: Clinical Cohort Cohort Epigenetics Exome Sequencing Full Transcriptome Sequencing Genotype Genotype/Expression Genotype/Expression array Individual-Level Genomic Data Longitudinal Observational Prospective RNA Sequencing Sequencing Tissue Expression Transcriptome Analysis Transcriptome Sequencing dbGaP estimated ancestry using GRAF-pop Total number of consented subjects: 119 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"TRanscriptomic ANalySis of left ventriCulaR gene Expression (TRANSCRibE)","short_name":"TRANSCRibE_DS-CI","commons":"BioData Catalyst","study_url":"","_subjects_count":40,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs001682.v1.p1.c1":{"gen3_discovery":{"authz":"","tags":[],"_unique_id":"phs001682.v1.p1.c1","study_id":"phs001682.v1.p1.c1","study_description":"","full_name":"","short_name":"","commons":"BioData Catalyst","study_url":"","_subjects_count":0,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs001682.v2.p1.c1":{"gen3_discovery":{"authz":null,"tags":null,"_unique_id":"phs001682.v2.p1.c1","study_id":"phs001682.v2.p1.c1","study_description":null,"full_name":null,"short_name":null,"commons":"BioData Catalyst","study_url":null,"_subjects_count":0,"__manifest":null,"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs001682.v3.p1.c1":{"gen3_discovery":{"authz":"/programs/topmed/projects/PUSH_SCD_DS-SCD-IRB-PUB-COL","tags":[],"_unique_id":"phs001682.v3.p1.c1","study_id":"phs001682.v3.p1.c1","study_description":"This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed) Whole Genome Sequencing Program. TOPMed is part of a broader Precision Medicine Initiative, which aims to provide disease treatments that are tailored to an individual's unique genes and environment. TOPMed will contribute to this initiative through the integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles, protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental, and clinical data. In doing so, this program aims to uncover factors that increase or decrease the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized treatments. Two genotype call sets derived from WGS are now available, Freeze 9b (GRCh38) and Freeze 10b (GRCh38), with largely overlapping sample sets. Information about how to identify other TOPMed WGS accessions for cross-study analysis, as well as descriptions of TOPMed methods of data acquisition, data processing and quality control, are provided in the accompanying documents, \"TOPMed Whole Genome Sequencing Project - Freeze 9b, Phases 1-4\" and \"TOPMed Whole Genome Sequencing Project - Freeze 10b, Phases 1-8\". Please check the study list at the top of each of these methods documents to determine whether it applies to this study accession. During Visit One, the PUSH Study will perform echocardiography on 600 children and adolescent with patients with sickle cell disease (SCD) and 100 control children and adolescents at three Field Centers, namely Howard University, Children's National Medical Center and University of Michigan. Patients or their parents will be approached and asked to give informed consent. If they appear to have a difficult reading, reading of the consent will be offered. Patients or their parents not appearing to comprehend the consent will not be eligible. As a part of this visit, each participant or parent will sign informed consent, complete a Participant Contact Information Form, complete a Medical History Form, undergo physical examination with completion of a Physical Examination Form and have blood drawn. Each participant must have echocardiography performed with measurement of Tricuspid Regurgitant Jet Velocity (TRV). In addition, attempts will be made 1) to perform a six-minute walk test, 2) to collect information from a recent (within six months) Transcranial Doppler Study (TCD) or to perform TCD, and 3) to perform pulmonary function tests. Study personnel will review all forms for completeness and conduct phlebotomy. Blood will be shipped to the Central Lab. Results of all procedures and tests will be transmitted to the Data Manager at Howard University. Sequencing was only done on sickle cell participants. Study Design: Case-Control Study Type: Case-Control dbGaP estimated ancestry using GRAF-pop Total number of consented subjects: 432 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"NHLBI TOPMed: Pulmonary Hypertension and the Hypoxic Response in SCD (PUSH)","short_name":"PUSH_SCD_DS-SCD-IRB-PUB-COL","commons":"BioData Catalyst","study_url":"","_subjects_count":432,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs001725.v1.p1.c1":{"gen3_discovery":{"authz":"","tags":[],"_unique_id":"phs001725.v1.p1.c1","study_id":"phs001725.v1.p1.c1","study_description":"","full_name":"","short_name":"","commons":"BioData Catalyst","study_url":"","_subjects_count":0,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs001725.v2.p1.c1":{"gen3_discovery":{"authz":null,"tags":null,"_unique_id":"phs001725.v2.p1.c1","study_id":"phs001725.v2.p1.c1","study_description":null,"full_name":null,"short_name":null,"commons":"BioData Catalyst","study_url":null,"_subjects_count":0,"__manifest":null,"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs001725.v3.p1.c1":{"gen3_discovery":{"authz":"/programs/topmed/projects/GGAF_GRU","tags":[],"_unique_id":"phs001725.v3.p1.c1","study_id":"phs001725.v3.p1.c1","study_description":"This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed) Whole Genome Sequencing Program. TOPMed is part of a broader Precision Medicine Initiative, which aims to provide disease treatments that are tailored to an individual's unique genes and environment. TOPMed will contribute to this initiative through the integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles, protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental, and clinical data. In doing so, this program aims to uncover factors that increase or decrease the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized treatments. Two genotype call sets derived from WGS are now available, Freeze 9b (GRCh38) and Freeze 10b (GRCh38), with largely overlapping sample sets. Information about how to identify other TOPMed WGS accessions for cross-study analysis, as well as descriptions of TOPMed methods of data acquisition, data processing and quality control, are provided in the accompanying documents, \"TOPMed Whole Genome Sequencing Project - Freeze 9b, Phases 1-4\" and \"TOPMed Whole Genome Sequencing Project - Freeze 10b, Phases 1-8\". Please check the study list at the top of each of these methods documents to determine whether it applies to this study accession. Atrial fibrillation (also called AFib or AF) is a quivering or irregular heartbeat (arrhythmia) that can lead to blood clots, stroke, heart failure and other heart-related complications. The Groningen Genetics of Atrial Fibrillation (GGAF) cohort is a cohort composed from 5 different sources of individuals with atrial fibrillation (AF) and age and sex-matched controls. Written informed consent was provided from all participating individuals, and all 5 studies were approved by the ethical committee at the University Medical Center (www.atrialfibrillationresearch.nl) and Maastricht University. All samples selected for TOPMed WGS are from individuals with atrial fibrillation. Study Design: Prospective Longitudinal Cohort Study Type: Cohort dbGaP estimated ancestry using GRAF-pop Total number of consented subjects: 640 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"NHLBI TOPMed - NHGRI CCDG: Groningen Genetics of Atrial Fibrillation (GGAF) Study","short_name":"GGAF_GRU","commons":"BioData Catalyst","study_url":"","_subjects_count":640,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs001726.v1.p1.c1":{"gen3_discovery":{"authz":"","tags":[],"_unique_id":"phs001726.v1.p1.c1","study_id":"phs001726.v1.p1.c1","study_description":"","full_name":"","short_name":"","commons":"BioData Catalyst","study_url":"","_subjects_count":0,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs001726.v3.p1.c1":{"gen3_discovery":{"authz":"/programs/topmed/projects/CAMP_DS-AST-COPD","tags":[{"name":"TOPMed","category":"Program"},{"name":"Genotype","category":"Data Type"},{"name":"dbGaP","category":"Study Registration"}],"_unique_id":"phs001726.v3.p1.c1","study_id":"phs001726.v3.p1.c1","study_description":"This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed) Whole Genome Sequencing Program. TOPMed is part of a broader Precision Medicine Initiative, which aims to provide disease treatments that are tailored to an individual's unique genes and environment. TOPMed will contribute to this initiative through the integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles, protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental, and clinical data. In doing so, this program aims to uncover factors that increase or decrease the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized treatments. Two genotype call sets derived from WGS are now available, Freeze 9b (GRCh38) and Freeze 10b (GRCh38), with largely overlapping sample sets. Information about how to identify other TOPMed WGS accessions for cross-study analysis, as well as descriptions of TOPMed methods of data acquisition, data processing and quality control, are provided in the accompanying documents, \"TOPMed Whole Genome Sequencing Project - Freeze 9b, Phases 1-4\" and \"TOPMed Whole Genome Sequencing Project - Freeze 10b, Phases 1-8\". Please check the study list at the top of each of these methods documents to determine whether it applies to this study accession. The Childhood Asthma Management Program (CAMP) was designed to evaluate whether continuous, long-term treatment (over a period of four to six years) with either an inhaled corticosteroid (budesonide) or an inhaled noncorticosteroid drug (nedocromil) safely produces an improvement in lung growth as compared with treatment for symptoms only (with albuterol and, if necessary, prednisone, administered as needed). The primary outcome in the study was lung growth, as assessed by the change in forced expiratory volume in one second (FEV1, expressed as a percentage of the predicted value) after the administration of a bronchodilator. Secondary outcomes included the degree of airway responsiveness, morbidity, physical growth, and psychological development. Study Design: Family/Twin/Trios Study Type: Parent-Offspring Trios dbGaP estimated ancestry using GRAF-pop Total number of consented subjects: 2785 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"NHLBI TOPMed: Childhood Asthma Management Program (CAMP)","short_name":"CAMP_DS-AST-COPD","commons":"BioData Catalyst","study_url":"https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001726.v3.p1","_subjects_count":2024,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs001727.v1.p1.c2":{"gen3_discovery":{"authz":"","tags":[],"_unique_id":"phs001727.v1.p1.c2","study_id":"phs001727.v1.p1.c2","study_description":"","full_name":"","short_name":"","commons":"BioData Catalyst","study_url":"","_subjects_count":0,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs001727.v3.p1.c2":{"gen3_discovery":{"authz":"/programs/topmed/projects/PIMA_DS-ASTHMA-IRB-COL","tags":[{"name":"TOPMed","category":"Program"},{"name":"Genotype","category":"Data Type"},{"name":"Clinical Phenotype","category":"Data Type"},{"name":"dbGaP","category":"Study Registration"}],"_unique_id":"phs001727.v3.p1.c2","study_id":"phs001727.v3.p1.c2","study_description":"This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed) Whole Genome Sequencing Program. TOPMed is part of a broader Precision Medicine Initiative, which aims to provide disease treatments that are tailored to an individual's unique genes and environment. TOPMed will contribute to this initiative through the integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles, protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental, and clinical data. In doing so, this program aims to uncover factors that increase or decrease the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized treatments. Two genotype call sets derived from WGS are now available, Freeze 9b (GRCh38) and Freeze 10b (GRCh38), with largely overlapping sample sets. Information about how to identify other TOPMed WGS accessions for cross-study analysis, as well as descriptions of TOPMed methods of data acquisition, data processing and quality control, are provided in the accompanying documents, \"TOPMed Whole Genome Sequencing Project - Freeze 9b, Phases 1-4\" and \"TOPMed Whole Genome Sequencing Project - Freeze 10b, Phases 1-8\". Please check the study list at the top of each of these methods documents to determine whether it applies to this study accession. Study designed to further our understanding of the pathogenesis of asthma exacerbations in children. Children enrolled in the study (n=217) were all asthmatic and primarily Hispanic white. The children were followed for 18 months until they experienced an asthma exacerbation or completed the follow-up without an exacerbation. The time to the first asthma exacerbation was considered the outcome. The acute and convalescent immune phenotype of each asthma exacerbation was documented. Study Weblinks: PIMA Study Design: Prospective Longitudinal Cohort Study Type: Cohort dbGaP estimated ancestry using GRAF-pop Total number of consented subjects: 73 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"NHLBI TOPMed: Pathways to Immunologically Mediated Asthma (PIMA)","short_name":"PIMA_DS-ASTHMA-IRB-COL","commons":"BioData Catalyst","study_url":"https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001727.v3.p1","_subjects_count":73,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs001728.v1.p1.c2":{"gen3_discovery":{"authz":"","tags":[],"_unique_id":"phs001728.v1.p1.c2","study_id":"phs001728.v1.p1.c2","study_description":"","full_name":"","short_name":"","commons":"BioData Catalyst","study_url":"","_subjects_count":0,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs001728.v3.p1.c2":{"gen3_discovery":{"authz":"/programs/topmed/projects/CARE_BADGER_DS-ASTHMA-IRB-COL","tags":[{"name":"TOPMed","category":"Program"},{"name":"Genotype","category":"Data Type"},{"name":"Clinical Phenotype","category":"Data Type"},{"name":"dbGaP","category":"Study Registration"}],"_unique_id":"phs001728.v3.p1.c2","study_id":"phs001728.v3.p1.c2","study_description":"This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed) Whole Genome Sequencing Program. TOPMed is part of a broader Precision Medicine Initiative, which aims to provide disease treatments that are tailored to an individual's unique genes and environment. TOPMed will contribute to this initiative through the integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles, protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental, and clinical data. In doing so, this program aims to uncover factors that increase or decrease the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized treatments. Two genotype call sets derived from WGS are now available, Freeze 9b (GRCh38) and Freeze 10b (GRCh38), with largely overlapping sample sets. Information about how to identify other TOPMed WGS accessions for cross-study analysis, as well as descriptions of TOPMed methods of data acquisition, data processing and quality control, are provided in the accompanying documents, \"TOPMed Whole Genome Sequencing Project - Freeze 9b, Phases 1-4\" and \"TOPMed Whole Genome Sequencing Project - Freeze 10b, Phases 1-8\". Please check the study list at the top of each of these methods documents to determine whether it applies to this study accession. BADGER is a 56-week randomized, double-blind, three-treatment, three-period cross-over trial that will evaluate the differential improvement in control that is achieved following three separate treatment interventions in children whose asthma is not acceptably controlled on a low dose of ICS (per NAEPP guidelines). All participants will enter an 8-week run-in period during which time they will receive a dose of 1x ICS (fluticasone 200 μg/day). During this 8-week time period, running 2-week averages to establish the lack of acceptable asthma control will be calculated. Thus, a child could qualify for randomization at any time during this 8-week run-in period. This approach should maximize both patient safety and successful enrollment. Children will continue to receive 1x ICS during the entire treatment phase. During each period of the treatment phase, they also will receive one add-on therapy in the form of LABA, LTRA or additional 1x ICS. The order of the add-on therapy assignment will be determined by randomization into one of six treatment sequences (order determined randomly). Each treatment period will be 16 weeks in length; the initial 4 weeks of each period will be considered to be the washout period for the previous treatment. The primary outcome measures will be frequency of asthma exacerbations, asthma control days, and FEV1. Study Weblinks: BADGER Study Design: Prospective Longitudinal Cohort Study Type: Cohort dbGaP estimated ancestry using GRAF-pop Total number of consented subjects: 50 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"NHLBI TOPMed: Best ADd-on Therapy Giving Effective Response (BADGER)","short_name":"CARE_BADGER_DS-ASTHMA-IRB-COL","commons":"BioData Catalyst","study_url":"https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001728.v3.p1","_subjects_count":50,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs001729.v1.p1.c2":{"gen3_discovery":{"authz":"","tags":[],"_unique_id":"phs001729.v1.p1.c2","study_id":"phs001729.v1.p1.c2","study_description":"","full_name":"","short_name":"","commons":"BioData Catalyst","study_url":"","_subjects_count":0,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs001729.v3.p1.c2":{"gen3_discovery":{"authz":"/programs/topmed/projects/CARE_CLIC_DS-ASTHMA-IRB-COL","tags":[{"name":"TOPMed","category":"Program"},{"name":"Genotype","category":"Data Type"},{"name":"dbGaP","category":"Study Registration"}],"_unique_id":"phs001729.v3.p1.c2","study_id":"phs001729.v3.p1.c2","study_description":"This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed) Whole Genome Sequencing Program. TOPMed is part of a broader Precision Medicine Initiative, which aims to provide disease treatments that are tailored to an individual's unique genes and environment. TOPMed will contribute to this initiative through the integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles, protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental, and clinical data. In doing so, this program aims to uncover factors that increase or decrease the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized treatments. Two genotype call sets derived from WGS are now available, Freeze 9b (GRCh38) and Freeze 10b (GRCh38), with largely overlapping sample sets. Information about how to identify other TOPMed WGS accessions for cross-study analysis, as well as descriptions of TOPMed methods of data acquisition, data processing and quality control, are provided in the accompanying documents, \"TOPMed Whole Genome Sequencing Project - Freeze 9b, Phases 1-4\" and \"TOPMed Whole Genome Sequencing Project - Freeze 10b, Phases 1-8\". Please check the study list at the top of each of these methods documents to determine whether it applies to this study accession. Within-subject clinical responses to either inhaled corticosteroids or Montelukast were compared in 126 children with mild to moderate asthma. Study Weblinks: CLIC Study Design: Prospective Longitudinal Cohort Study Type: Cohort dbGaP estimated ancestry using GRAF-pop Total number of consented subjects: 19 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"NHLBI TOPMed: Characterizing the Response to a Leukotriene Receptor Antagonist and an Inhaled Corticosteroid (CLIC)","short_name":"CARE_CLIC_DS-ASTHMA-IRB-COL","commons":"BioData Catalyst","study_url":"https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001729.v3.p1","_subjects_count":19,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs001730.v1.p1.c2":{"gen3_discovery":{"authz":"","tags":[],"_unique_id":"phs001730.v1.p1.c2","study_id":"phs001730.v1.p1.c2","study_description":"","full_name":"","short_name":"","commons":"BioData Catalyst","study_url":"","_subjects_count":0,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs001730.v2.p1.c2":{"gen3_discovery":{"authz":"/programs/topmed/projects/CARE_PACT_DS-ASTHMA-IRB-COL","tags":[{"name":"TOPMed","category":"Program"},{"name":"Genotype","category":"Data Type"},{"name":"dbGaP","category":"Study Registration"}],"_unique_id":"phs001730.v2.p1.c2","study_id":"phs001730.v2.p1.c2","study_description":"This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed) Whole Genome Sequencing Program. TOPMed is part of a broader Precision Medicine Initiative, which aims to provide disease treatments that are tailored to an individual's unique genes and environment. TOPMed will contribute to this initiative through the integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles, protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental, and clinical data. In doing so, this program aims to uncover factors that increase or decrease the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized treatments. Two genotype call sets derived from WGS are now available, Freeze 8 (GRCh38) and Freeze 9b (GRCh38), with largely overlapping sample sets. Information about how to identify other TOPMed WGS accessions for cross-study analysis, as well as descriptions of TOPMed methods of data acquisition, data processing and quality control, are provided in the accompanying documents, \"TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4\" and \"TOPMed Whole Genome Sequencing Project - Freeze 9b, Phases 1-4\". Please check the study list at the top of each of these methods documents to determine whether it applies to this study accession. After a 2-4 week assessment/characterization run-in period, 6-14 year-old children who met NAEPP criteria for mild-moderate persistent asthma specifically based on symptom criteria and methacholine PC20 ≤ 12.5 mg/ml and FEV1 ≥ 80% were randomized to one of the three active treatment arms for 12 months. Randomization was stratified according to clinical center, bronchodilator response (< 12% or ≥ 12%), race (Caucasian or non-Caucasian), and methacholine PC20 (< 2 or ≥ 2 mg/ml). The primary outcome variable was the proportion of asthma-free days during the 12-month treatment period. Secondary outcomes included other measures of asthma control (percentage of rescue-free days, albuterol-free days, and episode-free days; the number of asthma exacerbations requiring prednisone therapy and the time to the first asthma exacerbation), forced oscillation and spirometry, reversibility (FEV1 pre- and post 2 puffs of albuterol MDI), methacholine PC20, exhaled nitric oxide, and asthma-related quality of life. Study Weblinks: PACT Study Design: Prospective Longitudinal Cohort Study Type: Cohort dbGaP estimated ancestry using GRAF-pop Total number of consented subjects: 41 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"NHLBI TOPMed: Pediatric Asthma Controller Trial (PACT)","short_name":"CARE_PACT_DS-ASTHMA-IRB-COL","commons":"BioData Catalyst","study_url":"https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001730.v2.p1","_subjects_count":41,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs001732.v1.p1.c2":{"gen3_discovery":{"authz":"","tags":[],"_unique_id":"phs001732.v1.p1.c2","study_id":"phs001732.v1.p1.c2","study_description":"","full_name":"","short_name":"","commons":"BioData Catalyst","study_url":"","_subjects_count":0,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs001732.v2.p1.c2":{"gen3_discovery":{"authz":null,"tags":null,"_unique_id":"phs001732.v2.p1.c2","study_id":"phs001732.v2.p1.c2","study_description":null,"full_name":null,"short_name":null,"commons":"BioData Catalyst","study_url":null,"_subjects_count":0,"__manifest":null,"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs001732.v3.p1.c2":{"gen3_discovery":{"authz":"/programs/topmed/projects/CARE_TREXA_DS-ASTHMA-IRB-COL","tags":[],"_unique_id":"phs001732.v3.p1.c2","study_id":"phs001732.v3.p1.c2","study_description":"This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed) Whole Genome Sequencing Program. TOPMed is part of a broader Precision Medicine Initiative, which aims to provide disease treatments that are tailored to an individual's unique genes and environment. TOPMed will contribute to this initiative through the integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles, protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental, and clinical data. In doing so, this program aims to uncover factors that increase or decrease the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized treatments. Two genotype call sets derived from WGS are now available, Freeze 9b (GRCh38) and Freeze 10b (GRCh38), with largely overlapping sample sets. Information about how to identify other TOPMed WGS accessions for cross-study analysis, as well as descriptions of TOPMed methods of data acquisition, data processing and quality control, are provided in the accompanying documents, \"TOPMed Whole Genome Sequencing Project - Freeze 9b, Phases 1-4\" and \"TOPMed Whole Genome Sequencing Project - Freeze 10b, Phases 1-8\". Please check the study list at the top of each of these methods documents to determine whether it applies to this study accession. TREXA is a 44-week randomized, double-blind, double-masked, four-treatment, parallel trial that will evaluate the weaning strategy that provides the best protection against the development of exacerbations in children whose asthma is acceptably controlled on a low dose of ICS (per NAEPP guidelines). Following the 4 weeks of the run-in period on a 1x dose of ICS (100 µg fluticasone b.i.d. or its equivalent), children who do not meet the definition of acceptable asthma control will be randomized to the parallel BADGER protocol; those who meet the definition of acceptable asthma control will be enrolled into the 44-week treatment phase of the study. The primary outcome measure will be time to first exacerbation requiring a prednisone course. Study Weblinks: TREXA Study Design: Prospective Longitudinal Cohort Study Type: Cohort dbGaP estimated ancestry using GRAF-pop Total number of consented subjects: 89 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"NHLBI TOPMed: TReating Children to Prevent EXacerbations of Asthma (TREXA)","short_name":"CARE_TREXA_DS-ASTHMA-IRB-COL","commons":"BioData Catalyst","study_url":"","_subjects_count":89,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs001735.v2.p1.c1":{"gen3_discovery":{"authz":"/programs/topmed/projects/PCGC_CHD_HMB","tags":[{"name":"TOPMed","category":"Program"},{"name":"Genotype","category":"Data Type"},{"name":"dbGaP","category":"Study Registration"}],"_unique_id":"phs001735.v2.p1.c1","study_id":"phs001735.v2.p1.c1","study_description":"This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed) Whole Genome Sequencing Program. TOPMed is part of a broader Precision Medicine Initiative, which aims to provide disease treatments that are tailored to an individual's unique genes and environment. TOPMed will contribute to this initiative through the integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles, protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental, and clinical data. In doing so, this program aims to uncover factors that increase or decrease the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized treatments. Two genotype call sets derived from WGS are now available, Freeze 8 (GRCh38) and Freeze 9b (GRCh38), with largely overlapping sample sets. Information about how to identify other TOPMed WGS accessions for cross-study analysis, as well as descriptions of TOPMed methods of data acquisition, data processing and quality control, are provided in the accompanying documents, \"TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4\" and \"TOPMed Whole Genome Sequencing Project - Freeze 9b, Phases 1-4\". Please check the study list at the top of each of these methods documents to determine whether it applies to this study accession. The Pediatric Cardiovascular Genetics Consortium (PCGC) proposes to define genetic causes for congenital heart defects (CHD) as part of the TOPMed Program are the most common form of heart disease in childhood and are also the most prevalent form of birth defects, occurring in 2-3% of live births. The PCGC has recruited and clinically characterized = 10,000 CHD probands and parents (CHD trios). From whole exome sequencing (WES) of >2800 CHD trios, we identified a substantial enrichment of damaging de novo mutations in genes important for cardiogenesis, particularly implicating histone modifier enzyme gene defects. Analysis of whole genome sequencing (WGS) of 350 probands with CHD unexplained by WES and their parents preliminarily implicated de novo mutations in enhancers of genes previously shown to cause CHD in mouse knock out models. Sequencing of RNA (RNAseq) from discarded cardiac tissues from CHD probands has revealed likely causal allele-specific expression (ASE) as well as biallelic loss of expression (LOE). We have also discovered de novo epimutations, differentially methylated regions (DMRs), some with underlying de novo DNA variation, that are detectable in peripheral blood leukocytes and appear to underlie 10% of CHD. Of note, these assorted 'omic' approaches have enabled one another, both for attributing causality and assessing functional impact. Based on these extensive preliminary data, we hypothesize that PCGC probands with uninformative exomic analyses (WES-negative) harbor de novo genetic and/or epigenetic mutations in critical regulatory elements that participate in developmental expression of cardiac genes. To identify these etiologies, we propose analyses of WGS in 1000 WES-negative CHD trios, prioritizing those with probands with banked CHD tissues (n=78), one damaging variant in a recessive CHD gene, and older fathers (age>45). We also request WGS for 230 probands, for whom we have cardiac tissues but not parental DNAs. We request RNAseq for 308 cardiac tissues. For DNA methylation, which TOPMed will offer through the Illumina 850k array platform, we are requesting analysis of DNAs from peripheral blood leukocytes for all probands for whom WGS will be performed (1000 from trios, 230 singletons) as well as DNAs from cardiac tissues (n=308) to pair with the WGS, RNAseq and blood DNA methylation data. We will use existing resources and capabilities of the PCGC to confirm relevant mutations and those of its companion consortium in the Bench to Bassinet Program, the Cardiovascular Development Consortium, to inform analyses of non-coding mutations as well as to perform confirmatory functional genomics studies using cell and animal models. We expect that the studies resulting from data generated through TOPMed will provide novel insights into the molecular basis for CHD and fundamental knowledge about genes and pathways involved in cardiac development. Aside from being relevant to CHD, we anticipate that our findings will inform the understanding of later-onset cardiovascular diseases, including some arising in adulthood. Study Weblinks: From Bench to Bassinet: CHD Genes Study Design: Prospective Longitudinal Cohort Study Type: Case Set Parent-Offspring Trios dbGaP estimated ancestry using GRAF-pop Total number of consented subjects: 4550 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"NHLBI TOPMed: Pediatric Cardiac Genomics Consortium (PCGC)'s Congenital Heart Disease Biobank","short_name":"PCGC_CHD_HMB","commons":"BioData Catalyst","study_url":"https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001735.v2.p1","_subjects_count":4542,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs001735.v2.p1.c2":{"gen3_discovery":{"authz":"/programs/topmed/projects/PCGC_CHD_DS-CHD","tags":[{"name":"TOPMed","category":"Program"},{"name":"Genotype","category":"Data Type"},{"name":"dbGaP","category":"Study Registration"}],"_unique_id":"phs001735.v2.p1.c2","study_id":"phs001735.v2.p1.c2","study_description":"This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed) Whole Genome Sequencing Program. TOPMed is part of a broader Precision Medicine Initiative, which aims to provide disease treatments that are tailored to an individual's unique genes and environment. TOPMed will contribute to this initiative through the integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles, protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental, and clinical data. In doing so, this program aims to uncover factors that increase or decrease the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized treatments. Two genotype call sets derived from WGS are now available, Freeze 8 (GRCh38) and Freeze 9b (GRCh38), with largely overlapping sample sets. Information about how to identify other TOPMed WGS accessions for cross-study analysis, as well as descriptions of TOPMed methods of data acquisition, data processing and quality control, are provided in the accompanying documents, \"TOPMed Whole Genome Sequencing Project - Freeze 8, Phases 1-4\" and \"TOPMed Whole Genome Sequencing Project - Freeze 9b, Phases 1-4\". Please check the study list at the top of each of these methods documents to determine whether it applies to this study accession. The Pediatric Cardiovascular Genetics Consortium (PCGC) proposes to define genetic causes for congenital heart defects (CHD) as part of the TOPMed Program are the most common form of heart disease in childhood and are also the most prevalent form of birth defects, occurring in 2-3% of live births. The PCGC has recruited and clinically characterized = 10,000 CHD probands and parents (CHD trios). From whole exome sequencing (WES) of >2800 CHD trios, we identified a substantial enrichment of damaging de novo mutations in genes important for cardiogenesis, particularly implicating histone modifier enzyme gene defects. Analysis of whole genome sequencing (WGS) of 350 probands with CHD unexplained by WES and their parents preliminarily implicated de novo mutations in enhancers of genes previously shown to cause CHD in mouse knock out models. Sequencing of RNA (RNAseq) from discarded cardiac tissues from CHD probands has revealed likely causal allele-specific expression (ASE) as well as biallelic loss of expression (LOE). We have also discovered de novo epimutations, differentially methylated regions (DMRs), some with underlying de novo DNA variation, that are detectable in peripheral blood leukocytes and appear to underlie 10% of CHD. Of note, these assorted 'omic' approaches have enabled one another, both for attributing causality and assessing functional impact. Based on these extensive preliminary data, we hypothesize that PCGC probands with uninformative exomic analyses (WES-negative) harbor de novo genetic and/or epigenetic mutations in critical regulatory elements that participate in developmental expression of cardiac genes. To identify these etiologies, we propose analyses of WGS in 1000 WES-negative CHD trios, prioritizing those with probands with banked CHD tissues (n=78), one damaging variant in a recessive CHD gene, and older fathers (age>45). We also request WGS for 230 probands, for whom we have cardiac tissues but not parental DNAs. We request RNAseq for 308 cardiac tissues. For DNA methylation, which TOPMed will offer through the Illumina 850k array platform, we are requesting analysis of DNAs from peripheral blood leukocytes for all probands for whom WGS will be performed (1000 from trios, 230 singletons) as well as DNAs from cardiac tissues (n=308) to pair with the WGS, RNAseq and blood DNA methylation data. We will use existing resources and capabilities of the PCGC to confirm relevant mutations and those of its companion consortium in the Bench to Bassinet Program, the Cardiovascular Development Consortium, to inform analyses of non-coding mutations as well as to perform confirmatory functional genomics studies using cell and animal models. We expect that the studies resulting from data generated through TOPMed will provide novel insights into the molecular basis for CHD and fundamental knowledge about genes and pathways involved in cardiac development. Aside from being relevant to CHD, we anticipate that our findings will inform the understanding of later-onset cardiovascular diseases, including some arising in adulthood. Study Weblinks: From Bench to Bassinet: CHD Genes Study Design: Prospective Longitudinal Cohort Study Type: Case Set Parent-Offspring Trios dbGaP estimated ancestry using GRAF-pop Total number of consented subjects: 4550 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"NHLBI TOPMed: Pediatric Cardiac Genomics Consortium (PCGC)'s Congenital Heart Disease Biobank","short_name":"PCGC_CHD_DS-CHD","commons":"BioData Catalyst","study_url":"https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001735.v2.p1","_subjects_count":8,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs001759.v1.p1.c1":{"gen3_discovery":{"authz":"/programs/heartfailure/projects/exRNA_CSF_HMB","tags":[{"name":"dbGaP","category":"Study Registration"}],"_unique_id":"phs001759.v1.p1.c1","study_id":"phs001759.v1.p1.c1","study_description":"Brain injury resulting from hemorrhagic stroke is clinically challenging to manage and results in high rates of morbidity and mortality. The pathophysiology of brain damage resulting from aneurysmal subarachnoid hemorrhage (aSAH) is largely unknown, and methods to treat and monitor patients are variable with no meaningful correlations to patient outcome. Prediction of patient risk for serious neurological complications is currently a significant clinical obstacle. An extracellular RNA (exRNA) biomarker to predict onset and severity of brain damage would improve patient outcomes. We sequenced plasma and CSF samples from adult patients with SAH. Samples were collected from post bleed day 1 to day 7. Total exRNA was isolated from each sample. In addition, we prepared a subset of 140 CSF samples, isolating the RNA contained within extracellular vesicles and vesicle-depleted biofluid. Study Design: Case Set Study Type: Case Set Total number of consented subjects: 7 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Profiles of Extracellular RNA in Cerebrospinal Fluid and Plasma from Subarachnoid Hemorrhage Patients","short_name":"exRNA_CSF_HMB","commons":"BioData Catalyst","study_url":"https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001759.v1.p1","_subjects_count":7,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs001814.v1.p1.c1":{"gen3_discovery":{"authz":"/programs/heartfailure/projects/MolGen_CHD_GRU","tags":[],"_unique_id":"phs001814.v1.p1.c1","study_id":"phs001814.v1.p1.c1","study_description":"Heterotaxy syndrome is a congenital anomaly syndrome accompanied by thoracic and abdominal situs abnormalities. The study cohort comprises of individuals with heterotaxy or related congenital heart disease (CHD) who have undergone exome sequencing. The purpose of the study is to elucidate the molecular genetics of the disorder as well as contribute to knowledge about the biology of normal and abnormal development of left-right anatomic asymmetry. These results will further help delineate genotype-phenotype associations and provide important information on the causes, management, and prognosis of heterotaxy syndrome. Study Design: Case Set Study Type: Case Set Cohort dbGaP estimated ancestry using GRAF-pop Total number of consented subjects: 279 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Molecular Genetics of Heterotaxy and Related Congenital Heart Defects","short_name":"MolGen_CHD_GRU","commons":"BioData Catalyst","study_url":"","_subjects_count":279,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs001843.v1.p2.c1":{"gen3_discovery":{"authz":"/programs/PCGC/projects/CMG_WGS_HMB","tags":[{"name":"Clinical Phenotype","category":"Data Type"},{"name":"dbGaP","category":"Study Registration"}],"_unique_id":"phs001843.v1.p2.c1","study_id":"phs001843.v1.p2.c1","study_description":"This substudy phs001843 PCGC Study - CMG Collaboration contains whole genome sequences. Summary level phenotypes for the PCGC Cohort study participants can be viewed at the top-level study page phs001194 PCGC Cohort. Individual level phenotype data and molecular data for all PCGC top-level study and substudies are available by requesting Authorized Access to the PCGC Cohort study phs001194. Mendelian cardiovascular disorders provide crucial insights into the genetic susceptibility to more common forms of cardiovascular disease. While Mendelian cardiovascular disorders are individually rare, collectively they impose a significant public health burden. This proposal focuses on 2 specific categories of cardiovascular disease for which we have extensive research expertise and existing cohorts, congenital heart disease (CHD) and inherited arrhythmia syndromes. The tremendous burden on the health care system and on families with these Mendelian cardiovascular disorders underscore the urgency to understand their genomic bases, in order to design improved strategies for risk stratification, surveillance and medical intervention. Emerging evidence supports the use of whole-genome sequencing (WGS) over whole-exome sequencing (WES) for detecting coding variants in discovery projects, in addition to the obvious advantages of detecting features invisible to WES: structural variants (SV) and non-coding variants. We believe the way forward lies in widening the scope for discovery to include the patient's entire genome - and all types of variants. While family-based studies are crucial for genomic discovery, obtaining a sufficient number of high-risk pedigrees to achieve meaningful conclusions remains a challenge for most research institutions. For this proposal, we will leverage 2 powerful resources for the identification, ascertainment and recruitment of high-risk cardiovascular disease pedigrees: (1) the NHLBI-sponsored Pediatric Cardiac Genomics Consortium (PCGC) and (2) the Utah Population Database (UPDB). We propose to perform WGS on PCGC and UPDB cohorts with autosomal dominant disease to achieve the following Specific Aims: Aim 1) Identify the genomic basis for CHD in high-risk pedigrees derived from the PCGC and UPDB; and Aim 2) Identify the genomic basis for inherited arrhythmia disorders, using extended pedigrees derived from the UPDB. Aim 2 focuses on familial forms of AF, undiagnosed Long QT Syndrome, Wolff-Parkinson White syndrome and progressive conduction disorders. A WGS approach in high-risk pedigrees coupled with our validated bioinformatics pipeline, will allow the identification and prioritization of disease-causing SVs and sequence variants in coding and non-coding regulatory elements. These variants will be functionally characterized and validated in downstream experiments (heterologous expression systems, zebrafish cardiac assays, induced pluripotent stem cell-derived cardiomyocytes) that are beyond the scope of this X01. For this proposal, we have assembled the right combination of clinical expertise, resources for patient recruitment and computational know-how to enable these game-changing methodologies and to apply them to the challenge of cardiovascular Mendelian disease-gene discovery. Study Weblinks: Bench to Bassinet Program Study Design: Family/Twin/Trios Study Type: Family Cohort Total number of consented subjects: 130 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Pediatric Cardiac Genomics Consortium (PCGC) Study - Centers for Mendelian Genomics Collaboration","short_name":"CMG_WGS_HMB","commons":"BioData Catalyst","study_url":"https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001843.v1.p2","_subjects_count":127,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs001892.v1.p1.c1":{"gen3_discovery":{"authz":"/programs/heartfailure/projects/miRNA_Maternal_Plasma_GRU","tags":[{"name":"dbGaP","category":"Study Registration"}],"_unique_id":"phs001892.v1.p1.c1","study_id":"phs001892.v1.p1.c1","study_description":"We compared several performance characteristics of four miRNA profiling methods: small RNA-sequencing, HTG EdgeSeq, Abcam FirePlex, and NanoString nCounter. We used pools of synthetic miRNAs and extracellular RNA from healthy individuals to assess these characteristics. Study Design: Case-Control Study Type: Case-Control Total number of consented subjects: 13 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"miRNA Profiling of Maternal and Non-Maternal Healthy Adult Blood Plasma Using Small RNA-Sequencing","short_name":"miRNA_Maternal_Plasma_GRU","commons":"BioData Catalyst","study_url":"https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001892.v1.p1","_subjects_count":13,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs001927.v1.p1.c1":{"gen3_discovery":{"authz":null,"tags":null,"_unique_id":"phs001927.v1.p1.c1","study_id":"phs001927.v1.p1.c1","study_description":null,"full_name":null,"short_name":null,"commons":"BioData Catalyst","study_url":null,"_subjects_count":0,"__manifest":null,"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs001927.v1.p1.c2":{"gen3_discovery":{"authz":null,"tags":null,"_unique_id":"phs001927.v1.p1.c2","study_id":"phs001927.v1.p1.c2","study_description":null,"full_name":null,"short_name":null,"commons":"BioData Catalyst","study_url":null,"_subjects_count":0,"__manifest":null,"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs001927.v1.p1.c3":{"gen3_discovery":{"authz":null,"tags":null,"_unique_id":"phs001927.v1.p1.c3","study_id":"phs001927.v1.p1.c3","study_description":null,"full_name":null,"short_name":null,"commons":"BioData Catalyst","study_url":null,"_subjects_count":0,"__manifest":null,"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs001927.v1.p1.c4":{"gen3_discovery":{"authz":null,"tags":null,"_unique_id":"phs001927.v1.p1.c4","study_id":"phs001927.v1.p1.c4","study_description":null,"full_name":null,"short_name":null,"commons":"BioData Catalyst","study_url":null,"_subjects_count":0,"__manifest":null,"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs001927.v2.p2.c1":{"gen3_discovery":{"authz":"/programs/topmed/projects/SPIROMICS_GRU","tags":[],"_unique_id":"phs001927.v2.p2.c1","study_id":"phs001927.v2.p2.c1","study_description":"This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed) Whole Genome Sequencing Program. TOPMed is part of a broader Precision Medicine Initiative, which aims to provide disease treatments that are tailored to an individual's unique genes and environment. TOPMed will contribute to this initiative through the integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles, protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental, and clinical data. In doing so, this program aims to uncover factors that increase or decrease the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized treatments. Two genotype call sets derived from WGS are now available, Freeze 9b (GRCh38) and Freeze 10b (GRCh38), with largely overlapping sample sets. Information about how to identify other TOPMed WGS accessions for cross-study analysis, as well as descriptions of TOPMed methods of data acquisition, data processing and quality control, are provided in the accompanying documents, \"TOPMed Whole Genome Sequencing Project - Freeze 9b, Phases 1-4\" and \"TOPMed Whole Genome Sequencing Project - Freeze 10b, Phases 1-8\". Please check the study list at the top of each of these methods documents to determine whether it applies to this study accession. Subpopulations and Intermediate Outcome Measures in COPD Study Description Subpopulations and intermediate outcome measures in COPD study (SPIROMICS) supports the prospective collection and analysis of phenotypic, biomarker, genetic, genomic, and clinical data from subjects with COPD for the purpose of identifying subpopulations and intermediate outcome measures. It is funded by the National Heart, Lung, and Blood Institute and is coordinated by the University of North Carolina at Chapel Hill. Molecular fingerprinting and extensive subject phenotyping will be performed to identify disease subpopulations and to identify and validate surrogate markers of disease severity, which will be useful as intermediate outcome measures for future clinical trials. Secondary aims are to clarify the natural history of COPD, to develop bioinformatic resources that will enable the utilization and sharing of data in studies of COPD and related diseases, and to create a collection of clinical, biomarker, radiographic, and genetic data that can be used by external investigators for other studies of COPD. Participating Institutions: Research participants for SPIROMICS will be enrolled, phenotyped, and followed at twelve SPIROMICS Clinical Centers: Columbia University, Temple University, Johns Hopkins University, Wake Forest University, University of Michigan, University of Illinois at Chicago, University of Iowa, University of Utah, National Jewish Health, University of California at San Francisco, and University of California at Los Angeles. The University of North Carolina at Chapel Hill serves as the Genomics and Informatics Center. The Radiology Reading Center is based at the University of Iowa. The PFT Reading Center is based at the University of California at Los Angeles. Study Design: SPIROMICS is a prospective cohort study that enrolled approximately 2,981 participants at twelve clinical centers over five years. Participants are distributed across four enrollment strata (i.e., Never-smokers, Smokers without COPD, Mild/Moderate COPD, and Severe COPD). Study Visits: Participants have up to four in-person visits (Baseline and Annual Clinic Visits at years 1, 2, 3 after Baseline). Study questionnaires and spirometry are completed at all main study visits. Blood and urine samples are collected at visits 1, 2, and 4. Sputum samples are collected at Visit 1. The CT scans are completed and Baseline and Visit 2. Participants also receive quarterly follow-up calls to assess health status and determine if an exacerbation has occurred. Substudies Bronchoscopy and Immunophenotyping Substudy The Bronchoscopy Substudy will enroll 50 subjects per site, for a total of 300 participants. These participants will be recruited across all four study strata. This substudy includes two study visits. During the first visit, sputum samples are collected for Immunophenotyping analysis at the Immunophenotyping Core Lab based at the University of Michigan. Participants then return for a second visit during which samples are collected via bronchoscopy, including bronchoalveolar lavage, epithelial brushings and bronchial biopsies. Immunophenotyping analysis is also conducted on BAL and blood collected during the bronchoscopy study visit. Repeatability Substudy The entire baseline clinic visit was repeated on 98 volunteers to determine reliability of measurement procedures. All baseline study-related procedures and questionnaires, including the CT scan, were re-administered and new samples of blood, urine, saliva, and sputum were collected. Field center staff processed these biospecimen samples according to the same protocol. Exacerbation Substudy The Exacerbation Substudy is a prospective, longitudinal observational study of up to 400 participants, which will allow the assessment of participant-driven health care utilization (HCU) events and symptom-defined exacerbation events over time. HCU-driven events are defined by change in medical treatment in response to a perceived COPD Exacerbation. Symptom-based events will be defined by using EXACT-PRO (EXacerbations of Chronic Pulmonary Disease Tool - Patient Reported Outcome), a daily symptom diary developed to measure the frequency, severity, and duration of exacerbations in clinical trials. All participants are provided with a PDA on which to complete the diary. Participants reporting a possible COPD exacerbation will be brought into the study clinic for a study visit to collect biological specimens and questionnaire data. The overall objectives of the Exacerbation Substudy are to: Obtain clinical data and specimens on SPIROMICS participants before and during an acute COPD exacerbation defined by Health care utilization triggered by the subject, or Symptomatic change (triggered by an EXACT defined threshold) Describe symptomatic changes occurring around HCU and symptom-defined (EXACT) events and their relationship to clinical and specimen data, Characterize the non-exacerbation \"stable\" state in COPD using the EXACT, including: Symptom variability (EXACT), Clinical data and specimen parameters during a stable state (baseline), The relationship between clinical and specimen data and symptom severity and variability. Explore the characteristics of stable patients, defined as those who do not experience HCU or symptom-defined (EXACT) events during the sub-study period, using baseline clinical data and specimens, and compare these characteristics with patients who experience HCU and/or symptom-defined events. Examine the relationship between HCU and symptom-defined exacerbation frequency during the first one-year period of follow-up for exacerbations and health outcomes, including 12-month change in lung function and COPD health status, and longer-term morbidity and mortality, with the latter derived from long-term data from the larger SPIROMICS study. Study Weblinks: SubPopulations and InteRmediate Outcome Measures In COPD Study (SPIROMICS) Study Design: Prospective Longitudinal Cohort Study Type: Cohort dbGaP estimated ancestry using GRAF-pop Total number of consented subjects: 2423 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"NHLBI TOPMed: SubPopulations and InteRmediate Outcome Measures In COPD Study (SPIROMICS)","short_name":"SPIROMICS_GRU","commons":"BioData Catalyst","study_url":"","_subjects_count":2255,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs001927.v2.p2.c2":{"gen3_discovery":{"authz":"/programs/topmed/projects/SPIROMICS_GRU-NPU","tags":[],"_unique_id":"phs001927.v2.p2.c2","study_id":"phs001927.v2.p2.c2","study_description":"This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed) Whole Genome Sequencing Program. TOPMed is part of a broader Precision Medicine Initiative, which aims to provide disease treatments that are tailored to an individual's unique genes and environment. TOPMed will contribute to this initiative through the integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles, protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental, and clinical data. In doing so, this program aims to uncover factors that increase or decrease the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized treatments. Two genotype call sets derived from WGS are now available, Freeze 9b (GRCh38) and Freeze 10b (GRCh38), with largely overlapping sample sets. Information about how to identify other TOPMed WGS accessions for cross-study analysis, as well as descriptions of TOPMed methods of data acquisition, data processing and quality control, are provided in the accompanying documents, \"TOPMed Whole Genome Sequencing Project - Freeze 9b, Phases 1-4\" and \"TOPMed Whole Genome Sequencing Project - Freeze 10b, Phases 1-8\". Please check the study list at the top of each of these methods documents to determine whether it applies to this study accession. Subpopulations and Intermediate Outcome Measures in COPD Study Description Subpopulations and intermediate outcome measures in COPD study (SPIROMICS) supports the prospective collection and analysis of phenotypic, biomarker, genetic, genomic, and clinical data from subjects with COPD for the purpose of identifying subpopulations and intermediate outcome measures. It is funded by the National Heart, Lung, and Blood Institute and is coordinated by the University of North Carolina at Chapel Hill. Molecular fingerprinting and extensive subject phenotyping will be performed to identify disease subpopulations and to identify and validate surrogate markers of disease severity, which will be useful as intermediate outcome measures for future clinical trials. Secondary aims are to clarify the natural history of COPD, to develop bioinformatic resources that will enable the utilization and sharing of data in studies of COPD and related diseases, and to create a collection of clinical, biomarker, radiographic, and genetic data that can be used by external investigators for other studies of COPD. Participating Institutions: Research participants for SPIROMICS will be enrolled, phenotyped, and followed at twelve SPIROMICS Clinical Centers: Columbia University, Temple University, Johns Hopkins University, Wake Forest University, University of Michigan, University of Illinois at Chicago, University of Iowa, University of Utah, National Jewish Health, University of California at San Francisco, and University of California at Los Angeles. The University of North Carolina at Chapel Hill serves as the Genomics and Informatics Center. The Radiology Reading Center is based at the University of Iowa. The PFT Reading Center is based at the University of California at Los Angeles. Study Design: SPIROMICS is a prospective cohort study that enrolled approximately 2,981 participants at twelve clinical centers over five years. Participants are distributed across four enrollment strata (i.e., Never-smokers, Smokers without COPD, Mild/Moderate COPD, and Severe COPD). Study Visits: Participants have up to four in-person visits (Baseline and Annual Clinic Visits at years 1, 2, 3 after Baseline). Study questionnaires and spirometry are completed at all main study visits. Blood and urine samples are collected at visits 1, 2, and 4. Sputum samples are collected at Visit 1. The CT scans are completed and Baseline and Visit 2. Participants also receive quarterly follow-up calls to assess health status and determine if an exacerbation has occurred. Substudies Bronchoscopy and Immunophenotyping Substudy The Bronchoscopy Substudy will enroll 50 subjects per site, for a total of 300 participants. These participants will be recruited across all four study strata. This substudy includes two study visits. During the first visit, sputum samples are collected for Immunophenotyping analysis at the Immunophenotyping Core Lab based at the University of Michigan. Participants then return for a second visit during which samples are collected via bronchoscopy, including bronchoalveolar lavage, epithelial brushings and bronchial biopsies. Immunophenotyping analysis is also conducted on BAL and blood collected during the bronchoscopy study visit. Repeatability Substudy The entire baseline clinic visit was repeated on 98 volunteers to determine reliability of measurement procedures. All baseline study-related procedures and questionnaires, including the CT scan, were re-administered and new samples of blood, urine, saliva, and sputum were collected. Field center staff processed these biospecimen samples according to the same protocol. Exacerbation Substudy The Exacerbation Substudy is a prospective, longitudinal observational study of up to 400 participants, which will allow the assessment of participant-driven health care utilization (HCU) events and symptom-defined exacerbation events over time. HCU-driven events are defined by change in medical treatment in response to a perceived COPD Exacerbation. Symptom-based events will be defined by using EXACT-PRO (EXacerbations of Chronic Pulmonary Disease Tool - Patient Reported Outcome), a daily symptom diary developed to measure the frequency, severity, and duration of exacerbations in clinical trials. All participants are provided with a PDA on which to complete the diary. Participants reporting a possible COPD exacerbation will be brought into the study clinic for a study visit to collect biological specimens and questionnaire data. The overall objectives of the Exacerbation Substudy are to: Obtain clinical data and specimens on SPIROMICS participants before and during an acute COPD exacerbation defined by Health care utilization triggered by the subject, or Symptomatic change (triggered by an EXACT defined threshold) Describe symptomatic changes occurring around HCU and symptom-defined (EXACT) events and their relationship to clinical and specimen data, Characterize the non-exacerbation \"stable\" state in COPD using the EXACT, including: Symptom variability (EXACT), Clinical data and specimen parameters during a stable state (baseline), The relationship between clinical and specimen data and symptom severity and variability. Explore the characteristics of stable patients, defined as those who do not experience HCU or symptom-defined (EXACT) events during the sub-study period, using baseline clinical data and specimens, and compare these characteristics with patients who experience HCU and/or symptom-defined events. Examine the relationship between HCU and symptom-defined exacerbation frequency during the first one-year period of follow-up for exacerbations and health outcomes, including 12-month change in lung function and COPD health status, and longer-term morbidity and mortality, with the latter derived from long-term data from the larger SPIROMICS study. Study Weblinks: SubPopulations and InteRmediate Outcome Measures In COPD Study (SPIROMICS) Study Design: Prospective Longitudinal Cohort Study Type: Cohort dbGaP estimated ancestry using GRAF-pop Total number of consented subjects: 2423 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"NHLBI TOPMed: SubPopulations and InteRmediate Outcome Measures In COPD Study (SPIROMICS)","short_name":"SPIROMICS_GRU-NPU","commons":"BioData Catalyst","study_url":"","_subjects_count":90,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs001927.v2.p2.c3":{"gen3_discovery":{"authz":"/programs/topmed/projects/SPIROMICS_DS-COPD","tags":[],"_unique_id":"phs001927.v2.p2.c3","study_id":"phs001927.v2.p2.c3","study_description":"This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed) Whole Genome Sequencing Program. TOPMed is part of a broader Precision Medicine Initiative, which aims to provide disease treatments that are tailored to an individual's unique genes and environment. TOPMed will contribute to this initiative through the integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles, protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental, and clinical data. In doing so, this program aims to uncover factors that increase or decrease the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized treatments. Two genotype call sets derived from WGS are now available, Freeze 9b (GRCh38) and Freeze 10b (GRCh38), with largely overlapping sample sets. Information about how to identify other TOPMed WGS accessions for cross-study analysis, as well as descriptions of TOPMed methods of data acquisition, data processing and quality control, are provided in the accompanying documents, \"TOPMed Whole Genome Sequencing Project - Freeze 9b, Phases 1-4\" and \"TOPMed Whole Genome Sequencing Project - Freeze 10b, Phases 1-8\". Please check the study list at the top of each of these methods documents to determine whether it applies to this study accession. Subpopulations and Intermediate Outcome Measures in COPD Study Description Subpopulations and intermediate outcome measures in COPD study (SPIROMICS) supports the prospective collection and analysis of phenotypic, biomarker, genetic, genomic, and clinical data from subjects with COPD for the purpose of identifying subpopulations and intermediate outcome measures. It is funded by the National Heart, Lung, and Blood Institute and is coordinated by the University of North Carolina at Chapel Hill. Molecular fingerprinting and extensive subject phenotyping will be performed to identify disease subpopulations and to identify and validate surrogate markers of disease severity, which will be useful as intermediate outcome measures for future clinical trials. Secondary aims are to clarify the natural history of COPD, to develop bioinformatic resources that will enable the utilization and sharing of data in studies of COPD and related diseases, and to create a collection of clinical, biomarker, radiographic, and genetic data that can be used by external investigators for other studies of COPD. Participating Institutions: Research participants for SPIROMICS will be enrolled, phenotyped, and followed at twelve SPIROMICS Clinical Centers: Columbia University, Temple University, Johns Hopkins University, Wake Forest University, University of Michigan, University of Illinois at Chicago, University of Iowa, University of Utah, National Jewish Health, University of California at San Francisco, and University of California at Los Angeles. The University of North Carolina at Chapel Hill serves as the Genomics and Informatics Center. The Radiology Reading Center is based at the University of Iowa. The PFT Reading Center is based at the University of California at Los Angeles. Study Design: SPIROMICS is a prospective cohort study that enrolled approximately 2,981 participants at twelve clinical centers over five years. Participants are distributed across four enrollment strata (i.e., Never-smokers, Smokers without COPD, Mild/Moderate COPD, and Severe COPD). Study Visits: Participants have up to four in-person visits (Baseline and Annual Clinic Visits at years 1, 2, 3 after Baseline). Study questionnaires and spirometry are completed at all main study visits. Blood and urine samples are collected at visits 1, 2, and 4. Sputum samples are collected at Visit 1. The CT scans are completed and Baseline and Visit 2. Participants also receive quarterly follow-up calls to assess health status and determine if an exacerbation has occurred. Substudies Bronchoscopy and Immunophenotyping Substudy The Bronchoscopy Substudy will enroll 50 subjects per site, for a total of 300 participants. These participants will be recruited across all four study strata. This substudy includes two study visits. During the first visit, sputum samples are collected for Immunophenotyping analysis at the Immunophenotyping Core Lab based at the University of Michigan. Participants then return for a second visit during which samples are collected via bronchoscopy, including bronchoalveolar lavage, epithelial brushings and bronchial biopsies. Immunophenotyping analysis is also conducted on BAL and blood collected during the bronchoscopy study visit. Repeatability Substudy The entire baseline clinic visit was repeated on 98 volunteers to determine reliability of measurement procedures. All baseline study-related procedures and questionnaires, including the CT scan, were re-administered and new samples of blood, urine, saliva, and sputum were collected. Field center staff processed these biospecimen samples according to the same protocol. Exacerbation Substudy The Exacerbation Substudy is a prospective, longitudinal observational study of up to 400 participants, which will allow the assessment of participant-driven health care utilization (HCU) events and symptom-defined exacerbation events over time. HCU-driven events are defined by change in medical treatment in response to a perceived COPD Exacerbation. Symptom-based events will be defined by using EXACT-PRO (EXacerbations of Chronic Pulmonary Disease Tool - Patient Reported Outcome), a daily symptom diary developed to measure the frequency, severity, and duration of exacerbations in clinical trials. All participants are provided with a PDA on which to complete the diary. Participants reporting a possible COPD exacerbation will be brought into the study clinic for a study visit to collect biological specimens and questionnaire data. The overall objectives of the Exacerbation Substudy are to: Obtain clinical data and specimens on SPIROMICS participants before and during an acute COPD exacerbation defined by Health care utilization triggered by the subject, or Symptomatic change (triggered by an EXACT defined threshold) Describe symptomatic changes occurring around HCU and symptom-defined (EXACT) events and their relationship to clinical and specimen data, Characterize the non-exacerbation \"stable\" state in COPD using the EXACT, including: Symptom variability (EXACT), Clinical data and specimen parameters during a stable state (baseline), The relationship between clinical and specimen data and symptom severity and variability. Explore the characteristics of stable patients, defined as those who do not experience HCU or symptom-defined (EXACT) events during the sub-study period, using baseline clinical data and specimens, and compare these characteristics with patients who experience HCU and/or symptom-defined events. Examine the relationship between HCU and symptom-defined exacerbation frequency during the first one-year period of follow-up for exacerbations and health outcomes, including 12-month change in lung function and COPD health status, and longer-term morbidity and mortality, with the latter derived from long-term data from the larger SPIROMICS study. Study Weblinks: SubPopulations and InteRmediate Outcome Measures In COPD Study (SPIROMICS) Study Design: Prospective Longitudinal Cohort Study Type: Cohort dbGaP estimated ancestry using GRAF-pop Total number of consented subjects: 2423 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"NHLBI TOPMed: SubPopulations and InteRmediate Outcome Measures In COPD Study (SPIROMICS)","short_name":"SPIROMICS_DS-COPD","commons":"BioData Catalyst","study_url":"","_subjects_count":31,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs001927.v2.p2.c4":{"gen3_discovery":{"authz":"/programs/topmed/projects/SPIROMICS_DS-COPD-NPU","tags":[],"_unique_id":"phs001927.v2.p2.c4","study_id":"phs001927.v2.p2.c4","study_description":"This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed) Whole Genome Sequencing Program. TOPMed is part of a broader Precision Medicine Initiative, which aims to provide disease treatments that are tailored to an individual's unique genes and environment. TOPMed will contribute to this initiative through the integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles, protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental, and clinical data. In doing so, this program aims to uncover factors that increase or decrease the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized treatments. Two genotype call sets derived from WGS are now available, Freeze 9b (GRCh38) and Freeze 10b (GRCh38), with largely overlapping sample sets. Information about how to identify other TOPMed WGS accessions for cross-study analysis, as well as descriptions of TOPMed methods of data acquisition, data processing and quality control, are provided in the accompanying documents, \"TOPMed Whole Genome Sequencing Project - Freeze 9b, Phases 1-4\" and \"TOPMed Whole Genome Sequencing Project - Freeze 10b, Phases 1-8\". Please check the study list at the top of each of these methods documents to determine whether it applies to this study accession. Subpopulations and Intermediate Outcome Measures in COPD Study Description Subpopulations and intermediate outcome measures in COPD study (SPIROMICS) supports the prospective collection and analysis of phenotypic, biomarker, genetic, genomic, and clinical data from subjects with COPD for the purpose of identifying subpopulations and intermediate outcome measures. It is funded by the National Heart, Lung, and Blood Institute and is coordinated by the University of North Carolina at Chapel Hill. Molecular fingerprinting and extensive subject phenotyping will be performed to identify disease subpopulations and to identify and validate surrogate markers of disease severity, which will be useful as intermediate outcome measures for future clinical trials. Secondary aims are to clarify the natural history of COPD, to develop bioinformatic resources that will enable the utilization and sharing of data in studies of COPD and related diseases, and to create a collection of clinical, biomarker, radiographic, and genetic data that can be used by external investigators for other studies of COPD. Participating Institutions: Research participants for SPIROMICS will be enrolled, phenotyped, and followed at twelve SPIROMICS Clinical Centers: Columbia University, Temple University, Johns Hopkins University, Wake Forest University, University of Michigan, University of Illinois at Chicago, University of Iowa, University of Utah, National Jewish Health, University of California at San Francisco, and University of California at Los Angeles. The University of North Carolina at Chapel Hill serves as the Genomics and Informatics Center. The Radiology Reading Center is based at the University of Iowa. The PFT Reading Center is based at the University of California at Los Angeles. Study Design: SPIROMICS is a prospective cohort study that enrolled approximately 2,981 participants at twelve clinical centers over five years. Participants are distributed across four enrollment strata (i.e., Never-smokers, Smokers without COPD, Mild/Moderate COPD, and Severe COPD). Study Visits: Participants have up to four in-person visits (Baseline and Annual Clinic Visits at years 1, 2, 3 after Baseline). Study questionnaires and spirometry are completed at all main study visits. Blood and urine samples are collected at visits 1, 2, and 4. Sputum samples are collected at Visit 1. The CT scans are completed and Baseline and Visit 2. Participants also receive quarterly follow-up calls to assess health status and determine if an exacerbation has occurred. Substudies Bronchoscopy and Immunophenotyping Substudy The Bronchoscopy Substudy will enroll 50 subjects per site, for a total of 300 participants. These participants will be recruited across all four study strata. This substudy includes two study visits. During the first visit, sputum samples are collected for Immunophenotyping analysis at the Immunophenotyping Core Lab based at the University of Michigan. Participants then return for a second visit during which samples are collected via bronchoscopy, including bronchoalveolar lavage, epithelial brushings and bronchial biopsies. Immunophenotyping analysis is also conducted on BAL and blood collected during the bronchoscopy study visit. Repeatability Substudy The entire baseline clinic visit was repeated on 98 volunteers to determine reliability of measurement procedures. All baseline study-related procedures and questionnaires, including the CT scan, were re-administered and new samples of blood, urine, saliva, and sputum were collected. Field center staff processed these biospecimen samples according to the same protocol. Exacerbation Substudy The Exacerbation Substudy is a prospective, longitudinal observational study of up to 400 participants, which will allow the assessment of participant-driven health care utilization (HCU) events and symptom-defined exacerbation events over time. HCU-driven events are defined by change in medical treatment in response to a perceived COPD Exacerbation. Symptom-based events will be defined by using EXACT-PRO (EXacerbations of Chronic Pulmonary Disease Tool - Patient Reported Outcome), a daily symptom diary developed to measure the frequency, severity, and duration of exacerbations in clinical trials. All participants are provided with a PDA on which to complete the diary. Participants reporting a possible COPD exacerbation will be brought into the study clinic for a study visit to collect biological specimens and questionnaire data. The overall objectives of the Exacerbation Substudy are to: Obtain clinical data and specimens on SPIROMICS participants before and during an acute COPD exacerbation defined by Health care utilization triggered by the subject, or Symptomatic change (triggered by an EXACT defined threshold) Describe symptomatic changes occurring around HCU and symptom-defined (EXACT) events and their relationship to clinical and specimen data, Characterize the non-exacerbation \"stable\" state in COPD using the EXACT, including: Symptom variability (EXACT), Clinical data and specimen parameters during a stable state (baseline), The relationship between clinical and specimen data and symptom severity and variability. Explore the characteristics of stable patients, defined as those who do not experience HCU or symptom-defined (EXACT) events during the sub-study period, using baseline clinical data and specimens, and compare these characteristics with patients who experience HCU and/or symptom-defined events. Examine the relationship between HCU and symptom-defined exacerbation frequency during the first one-year period of follow-up for exacerbations and health outcomes, including 12-month change in lung function and COPD health status, and longer-term morbidity and mortality, with the latter derived from long-term data from the larger SPIROMICS study. Study Weblinks: SubPopulations and InteRmediate Outcome Measures In COPD Study (SPIROMICS) Study Design: Prospective Longitudinal Cohort Study Type: Cohort dbGaP estimated ancestry using GRAF-pop Total number of consented subjects: 2423 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"NHLBI TOPMed: SubPopulations and InteRmediate Outcome Measures In COPD Study (SPIROMICS)","short_name":"SPIROMICS_DS-COPD-NPU","commons":"BioData Catalyst","study_url":"","_subjects_count":20,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs001927.v2.p2.c5":{"gen3_discovery":{"authz":"/programs/topmed/projects/SPIROMICS_GRU-COL","tags":[],"_unique_id":"phs001927.v2.p2.c5","study_id":"phs001927.v2.p2.c5","study_description":"This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed) Whole Genome Sequencing Program. TOPMed is part of a broader Precision Medicine Initiative, which aims to provide disease treatments that are tailored to an individual's unique genes and environment. TOPMed will contribute to this initiative through the integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles, protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental, and clinical data. In doing so, this program aims to uncover factors that increase or decrease the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized treatments. Two genotype call sets derived from WGS are now available, Freeze 9b (GRCh38) and Freeze 10b (GRCh38), with largely overlapping sample sets. Information about how to identify other TOPMed WGS accessions for cross-study analysis, as well as descriptions of TOPMed methods of data acquisition, data processing and quality control, are provided in the accompanying documents, \"TOPMed Whole Genome Sequencing Project - Freeze 9b, Phases 1-4\" and \"TOPMed Whole Genome Sequencing Project - Freeze 10b, Phases 1-8\". Please check the study list at the top of each of these methods documents to determine whether it applies to this study accession. Subpopulations and Intermediate Outcome Measures in COPD Study Description Subpopulations and intermediate outcome measures in COPD study (SPIROMICS) supports the prospective collection and analysis of phenotypic, biomarker, genetic, genomic, and clinical data from subjects with COPD for the purpose of identifying subpopulations and intermediate outcome measures. It is funded by the National Heart, Lung, and Blood Institute and is coordinated by the University of North Carolina at Chapel Hill. Molecular fingerprinting and extensive subject phenotyping will be performed to identify disease subpopulations and to identify and validate surrogate markers of disease severity, which will be useful as intermediate outcome measures for future clinical trials. Secondary aims are to clarify the natural history of COPD, to develop bioinformatic resources that will enable the utilization and sharing of data in studies of COPD and related diseases, and to create a collection of clinical, biomarker, radiographic, and genetic data that can be used by external investigators for other studies of COPD. Participating Institutions: Research participants for SPIROMICS will be enrolled, phenotyped, and followed at twelve SPIROMICS Clinical Centers: Columbia University, Temple University, Johns Hopkins University, Wake Forest University, University of Michigan, University of Illinois at Chicago, University of Iowa, University of Utah, National Jewish Health, University of California at San Francisco, and University of California at Los Angeles. The University of North Carolina at Chapel Hill serves as the Genomics and Informatics Center. The Radiology Reading Center is based at the University of Iowa. The PFT Reading Center is based at the University of California at Los Angeles. Study Design: SPIROMICS is a prospective cohort study that enrolled approximately 2,981 participants at twelve clinical centers over five years. Participants are distributed across four enrollment strata (i.e., Never-smokers, Smokers without COPD, Mild/Moderate COPD, and Severe COPD). Study Visits: Participants have up to four in-person visits (Baseline and Annual Clinic Visits at years 1, 2, 3 after Baseline). Study questionnaires and spirometry are completed at all main study visits. Blood and urine samples are collected at visits 1, 2, and 4. Sputum samples are collected at Visit 1. The CT scans are completed and Baseline and Visit 2. Participants also receive quarterly follow-up calls to assess health status and determine if an exacerbation has occurred. Substudies Bronchoscopy and Immunophenotyping Substudy The Bronchoscopy Substudy will enroll 50 subjects per site, for a total of 300 participants. These participants will be recruited across all four study strata. This substudy includes two study visits. During the first visit, sputum samples are collected for Immunophenotyping analysis at the Immunophenotyping Core Lab based at the University of Michigan. Participants then return for a second visit during which samples are collected via bronchoscopy, including bronchoalveolar lavage, epithelial brushings and bronchial biopsies. Immunophenotyping analysis is also conducted on BAL and blood collected during the bronchoscopy study visit. Repeatability Substudy The entire baseline clinic visit was repeated on 98 volunteers to determine reliability of measurement procedures. All baseline study-related procedures and questionnaires, including the CT scan, were re-administered and new samples of blood, urine, saliva, and sputum were collected. Field center staff processed these biospecimen samples according to the same protocol. Exacerbation Substudy The Exacerbation Substudy is a prospective, longitudinal observational study of up to 400 participants, which will allow the assessment of participant-driven health care utilization (HCU) events and symptom-defined exacerbation events over time. HCU-driven events are defined by change in medical treatment in response to a perceived COPD Exacerbation. Symptom-based events will be defined by using EXACT-PRO (EXacerbations of Chronic Pulmonary Disease Tool - Patient Reported Outcome), a daily symptom diary developed to measure the frequency, severity, and duration of exacerbations in clinical trials. All participants are provided with a PDA on which to complete the diary. Participants reporting a possible COPD exacerbation will be brought into the study clinic for a study visit to collect biological specimens and questionnaire data. The overall objectives of the Exacerbation Substudy are to: Obtain clinical data and specimens on SPIROMICS participants before and during an acute COPD exacerbation defined by Health care utilization triggered by the subject, or Symptomatic change (triggered by an EXACT defined threshold) Describe symptomatic changes occurring around HCU and symptom-defined (EXACT) events and their relationship to clinical and specimen data, Characterize the non-exacerbation \"stable\" state in COPD using the EXACT, including: Symptom variability (EXACT), Clinical data and specimen parameters during a stable state (baseline), The relationship between clinical and specimen data and symptom severity and variability. Explore the characteristics of stable patients, defined as those who do not experience HCU or symptom-defined (EXACT) events during the sub-study period, using baseline clinical data and specimens, and compare these characteristics with patients who experience HCU and/or symptom-defined events. Examine the relationship between HCU and symptom-defined exacerbation frequency during the first one-year period of follow-up for exacerbations and health outcomes, including 12-month change in lung function and COPD health status, and longer-term morbidity and mortality, with the latter derived from long-term data from the larger SPIROMICS study. Study Weblinks: SubPopulations and InteRmediate Outcome Measures In COPD Study (SPIROMICS) Study Design: Prospective Longitudinal Cohort Study Type: Cohort dbGaP estimated ancestry using GRAF-pop Total number of consented subjects: 2423 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"NHLBI TOPMed: SubPopulations and InteRmediate Outcome Measures In COPD Study (SPIROMICS)","short_name":"SPIROMICS_GRU-COL","commons":"BioData Catalyst","study_url":"","_subjects_count":4,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs001927.v2.p2.c6":{"gen3_discovery":{"authz":"/programs/topmed/projects/SPIROMICS_GRU-COL-NPU","tags":[],"_unique_id":"phs001927.v2.p2.c6","study_id":"phs001927.v2.p2.c6","study_description":"This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed) Whole Genome Sequencing Program. TOPMed is part of a broader Precision Medicine Initiative, which aims to provide disease treatments that are tailored to an individual's unique genes and environment. TOPMed will contribute to this initiative through the integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles, protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental, and clinical data. In doing so, this program aims to uncover factors that increase or decrease the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized treatments. Two genotype call sets derived from WGS are now available, Freeze 9b (GRCh38) and Freeze 10b (GRCh38), with largely overlapping sample sets. Information about how to identify other TOPMed WGS accessions for cross-study analysis, as well as descriptions of TOPMed methods of data acquisition, data processing and quality control, are provided in the accompanying documents, \"TOPMed Whole Genome Sequencing Project - Freeze 9b, Phases 1-4\" and \"TOPMed Whole Genome Sequencing Project - Freeze 10b, Phases 1-8\". Please check the study list at the top of each of these methods documents to determine whether it applies to this study accession. Subpopulations and Intermediate Outcome Measures in COPD Study Description Subpopulations and intermediate outcome measures in COPD study (SPIROMICS) supports the prospective collection and analysis of phenotypic, biomarker, genetic, genomic, and clinical data from subjects with COPD for the purpose of identifying subpopulations and intermediate outcome measures. It is funded by the National Heart, Lung, and Blood Institute and is coordinated by the University of North Carolina at Chapel Hill. Molecular fingerprinting and extensive subject phenotyping will be performed to identify disease subpopulations and to identify and validate surrogate markers of disease severity, which will be useful as intermediate outcome measures for future clinical trials. Secondary aims are to clarify the natural history of COPD, to develop bioinformatic resources that will enable the utilization and sharing of data in studies of COPD and related diseases, and to create a collection of clinical, biomarker, radiographic, and genetic data that can be used by external investigators for other studies of COPD. Participating Institutions: Research participants for SPIROMICS will be enrolled, phenotyped, and followed at twelve SPIROMICS Clinical Centers: Columbia University, Temple University, Johns Hopkins University, Wake Forest University, University of Michigan, University of Illinois at Chicago, University of Iowa, University of Utah, National Jewish Health, University of California at San Francisco, and University of California at Los Angeles. The University of North Carolina at Chapel Hill serves as the Genomics and Informatics Center. The Radiology Reading Center is based at the University of Iowa. The PFT Reading Center is based at the University of California at Los Angeles. Study Design: SPIROMICS is a prospective cohort study that enrolled approximately 2,981 participants at twelve clinical centers over five years. Participants are distributed across four enrollment strata (i.e., Never-smokers, Smokers without COPD, Mild/Moderate COPD, and Severe COPD). Study Visits: Participants have up to four in-person visits (Baseline and Annual Clinic Visits at years 1, 2, 3 after Baseline). Study questionnaires and spirometry are completed at all main study visits. Blood and urine samples are collected at visits 1, 2, and 4. Sputum samples are collected at Visit 1. The CT scans are completed and Baseline and Visit 2. Participants also receive quarterly follow-up calls to assess health status and determine if an exacerbation has occurred. Substudies Bronchoscopy and Immunophenotyping Substudy The Bronchoscopy Substudy will enroll 50 subjects per site, for a total of 300 participants. These participants will be recruited across all four study strata. This substudy includes two study visits. During the first visit, sputum samples are collected for Immunophenotyping analysis at the Immunophenotyping Core Lab based at the University of Michigan. Participants then return for a second visit during which samples are collected via bronchoscopy, including bronchoalveolar lavage, epithelial brushings and bronchial biopsies. Immunophenotyping analysis is also conducted on BAL and blood collected during the bronchoscopy study visit. Repeatability Substudy The entire baseline clinic visit was repeated on 98 volunteers to determine reliability of measurement procedures. All baseline study-related procedures and questionnaires, including the CT scan, were re-administered and new samples of blood, urine, saliva, and sputum were collected. Field center staff processed these biospecimen samples according to the same protocol. Exacerbation Substudy The Exacerbation Substudy is a prospective, longitudinal observational study of up to 400 participants, which will allow the assessment of participant-driven health care utilization (HCU) events and symptom-defined exacerbation events over time. HCU-driven events are defined by change in medical treatment in response to a perceived COPD Exacerbation. Symptom-based events will be defined by using EXACT-PRO (EXacerbations of Chronic Pulmonary Disease Tool - Patient Reported Outcome), a daily symptom diary developed to measure the frequency, severity, and duration of exacerbations in clinical trials. All participants are provided with a PDA on which to complete the diary. Participants reporting a possible COPD exacerbation will be brought into the study clinic for a study visit to collect biological specimens and questionnaire data. The overall objectives of the Exacerbation Substudy are to: Obtain clinical data and specimens on SPIROMICS participants before and during an acute COPD exacerbation defined by Health care utilization triggered by the subject, or Symptomatic change (triggered by an EXACT defined threshold) Describe symptomatic changes occurring around HCU and symptom-defined (EXACT) events and their relationship to clinical and specimen data, Characterize the non-exacerbation \"stable\" state in COPD using the EXACT, including: Symptom variability (EXACT), Clinical data and specimen parameters during a stable state (baseline), The relationship between clinical and specimen data and symptom severity and variability. Explore the characteristics of stable patients, defined as those who do not experience HCU or symptom-defined (EXACT) events during the sub-study period, using baseline clinical data and specimens, and compare these characteristics with patients who experience HCU and/or symptom-defined events. Examine the relationship between HCU and symptom-defined exacerbation frequency during the first one-year period of follow-up for exacerbations and health outcomes, including 12-month change in lung function and COPD health status, and longer-term morbidity and mortality, with the latter derived from long-term data from the larger SPIROMICS study. Study Weblinks: SubPopulations and InteRmediate Outcome Measures In COPD Study (SPIROMICS) Study Design: Prospective Longitudinal Cohort Study Type: Cohort dbGaP estimated ancestry using GRAF-pop Total number of consented subjects: 2423 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"NHLBI TOPMed: SubPopulations and InteRmediate Outcome Measures In COPD Study (SPIROMICS)","short_name":"SPIROMICS_GRU-COL-NPU","commons":"BioData Catalyst","study_url":"","_subjects_count":11,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs001927.v2.p2.c7":{"gen3_discovery":{"authz":"/programs/topmed/projects/SPIROMICS_DS-COPD-COL","tags":[],"_unique_id":"phs001927.v2.p2.c7","study_id":"phs001927.v2.p2.c7","study_description":"This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed) Whole Genome Sequencing Program. TOPMed is part of a broader Precision Medicine Initiative, which aims to provide disease treatments that are tailored to an individual's unique genes and environment. TOPMed will contribute to this initiative through the integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles, protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental, and clinical data. In doing so, this program aims to uncover factors that increase or decrease the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized treatments. Two genotype call sets derived from WGS are now available, Freeze 9b (GRCh38) and Freeze 10b (GRCh38), with largely overlapping sample sets. Information about how to identify other TOPMed WGS accessions for cross-study analysis, as well as descriptions of TOPMed methods of data acquisition, data processing and quality control, are provided in the accompanying documents, \"TOPMed Whole Genome Sequencing Project - Freeze 9b, Phases 1-4\" and \"TOPMed Whole Genome Sequencing Project - Freeze 10b, Phases 1-8\". Please check the study list at the top of each of these methods documents to determine whether it applies to this study accession. Subpopulations and Intermediate Outcome Measures in COPD Study Description Subpopulations and intermediate outcome measures in COPD study (SPIROMICS) supports the prospective collection and analysis of phenotypic, biomarker, genetic, genomic, and clinical data from subjects with COPD for the purpose of identifying subpopulations and intermediate outcome measures. It is funded by the National Heart, Lung, and Blood Institute and is coordinated by the University of North Carolina at Chapel Hill. Molecular fingerprinting and extensive subject phenotyping will be performed to identify disease subpopulations and to identify and validate surrogate markers of disease severity, which will be useful as intermediate outcome measures for future clinical trials. Secondary aims are to clarify the natural history of COPD, to develop bioinformatic resources that will enable the utilization and sharing of data in studies of COPD and related diseases, and to create a collection of clinical, biomarker, radiographic, and genetic data that can be used by external investigators for other studies of COPD. Participating Institutions: Research participants for SPIROMICS will be enrolled, phenotyped, and followed at twelve SPIROMICS Clinical Centers: Columbia University, Temple University, Johns Hopkins University, Wake Forest University, University of Michigan, University of Illinois at Chicago, University of Iowa, University of Utah, National Jewish Health, University of California at San Francisco, and University of California at Los Angeles. The University of North Carolina at Chapel Hill serves as the Genomics and Informatics Center. The Radiology Reading Center is based at the University of Iowa. The PFT Reading Center is based at the University of California at Los Angeles. Study Design: SPIROMICS is a prospective cohort study that enrolled approximately 2,981 participants at twelve clinical centers over five years. Participants are distributed across four enrollment strata (i.e., Never-smokers, Smokers without COPD, Mild/Moderate COPD, and Severe COPD). Study Visits: Participants have up to four in-person visits (Baseline and Annual Clinic Visits at years 1, 2, 3 after Baseline). Study questionnaires and spirometry are completed at all main study visits. Blood and urine samples are collected at visits 1, 2, and 4. Sputum samples are collected at Visit 1. The CT scans are completed and Baseline and Visit 2. Participants also receive quarterly follow-up calls to assess health status and determine if an exacerbation has occurred. Substudies Bronchoscopy and Immunophenotyping Substudy The Bronchoscopy Substudy will enroll 50 subjects per site, for a total of 300 participants. These participants will be recruited across all four study strata. This substudy includes two study visits. During the first visit, sputum samples are collected for Immunophenotyping analysis at the Immunophenotyping Core Lab based at the University of Michigan. Participants then return for a second visit during which samples are collected via bronchoscopy, including bronchoalveolar lavage, epithelial brushings and bronchial biopsies. Immunophenotyping analysis is also conducted on BAL and blood collected during the bronchoscopy study visit. Repeatability Substudy The entire baseline clinic visit was repeated on 98 volunteers to determine reliability of measurement procedures. All baseline study-related procedures and questionnaires, including the CT scan, were re-administered and new samples of blood, urine, saliva, and sputum were collected. Field center staff processed these biospecimen samples according to the same protocol. Exacerbation Substudy The Exacerbation Substudy is a prospective, longitudinal observational study of up to 400 participants, which will allow the assessment of participant-driven health care utilization (HCU) events and symptom-defined exacerbation events over time. HCU-driven events are defined by change in medical treatment in response to a perceived COPD Exacerbation. Symptom-based events will be defined by using EXACT-PRO (EXacerbations of Chronic Pulmonary Disease Tool - Patient Reported Outcome), a daily symptom diary developed to measure the frequency, severity, and duration of exacerbations in clinical trials. All participants are provided with a PDA on which to complete the diary. Participants reporting a possible COPD exacerbation will be brought into the study clinic for a study visit to collect biological specimens and questionnaire data. The overall objectives of the Exacerbation Substudy are to: Obtain clinical data and specimens on SPIROMICS participants before and during an acute COPD exacerbation defined by Health care utilization triggered by the subject, or Symptomatic change (triggered by an EXACT defined threshold) Describe symptomatic changes occurring around HCU and symptom-defined (EXACT) events and their relationship to clinical and specimen data, Characterize the non-exacerbation \"stable\" state in COPD using the EXACT, including: Symptom variability (EXACT), Clinical data and specimen parameters during a stable state (baseline), The relationship between clinical and specimen data and symptom severity and variability. Explore the characteristics of stable patients, defined as those who do not experience HCU or symptom-defined (EXACT) events during the sub-study period, using baseline clinical data and specimens, and compare these characteristics with patients who experience HCU and/or symptom-defined events. Examine the relationship between HCU and symptom-defined exacerbation frequency during the first one-year period of follow-up for exacerbations and health outcomes, including 12-month change in lung function and COPD health status, and longer-term morbidity and mortality, with the latter derived from long-term data from the larger SPIROMICS study. Study Weblinks: SubPopulations and InteRmediate Outcome Measures In COPD Study (SPIROMICS) Study Design: Prospective Longitudinal Cohort Study Type: Cohort dbGaP estimated ancestry using GRAF-pop Total number of consented subjects: 2423 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"NHLBI TOPMed: SubPopulations and InteRmediate Outcome Measures In COPD Study (SPIROMICS)","short_name":"SPIROMICS_DS-COPD-COL","commons":"BioData Catalyst","study_url":"","_subjects_count":2,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs001927.v2.p2.c8":{"gen3_discovery":{"authz":"/programs/topmed/projects/SPIROMICS_DS-COPD-COL-NPU","tags":[],"_unique_id":"phs001927.v2.p2.c8","study_id":"phs001927.v2.p2.c8","study_description":"This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed) Whole Genome Sequencing Program. TOPMed is part of a broader Precision Medicine Initiative, which aims to provide disease treatments that are tailored to an individual's unique genes and environment. TOPMed will contribute to this initiative through the integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles, protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental, and clinical data. In doing so, this program aims to uncover factors that increase or decrease the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized treatments. Two genotype call sets derived from WGS are now available, Freeze 9b (GRCh38) and Freeze 10b (GRCh38), with largely overlapping sample sets. Information about how to identify other TOPMed WGS accessions for cross-study analysis, as well as descriptions of TOPMed methods of data acquisition, data processing and quality control, are provided in the accompanying documents, \"TOPMed Whole Genome Sequencing Project - Freeze 9b, Phases 1-4\" and \"TOPMed Whole Genome Sequencing Project - Freeze 10b, Phases 1-8\". Please check the study list at the top of each of these methods documents to determine whether it applies to this study accession. Subpopulations and Intermediate Outcome Measures in COPD Study Description Subpopulations and intermediate outcome measures in COPD study (SPIROMICS) supports the prospective collection and analysis of phenotypic, biomarker, genetic, genomic, and clinical data from subjects with COPD for the purpose of identifying subpopulations and intermediate outcome measures. It is funded by the National Heart, Lung, and Blood Institute and is coordinated by the University of North Carolina at Chapel Hill. Molecular fingerprinting and extensive subject phenotyping will be performed to identify disease subpopulations and to identify and validate surrogate markers of disease severity, which will be useful as intermediate outcome measures for future clinical trials. Secondary aims are to clarify the natural history of COPD, to develop bioinformatic resources that will enable the utilization and sharing of data in studies of COPD and related diseases, and to create a collection of clinical, biomarker, radiographic, and genetic data that can be used by external investigators for other studies of COPD. Participating Institutions: Research participants for SPIROMICS will be enrolled, phenotyped, and followed at twelve SPIROMICS Clinical Centers: Columbia University, Temple University, Johns Hopkins University, Wake Forest University, University of Michigan, University of Illinois at Chicago, University of Iowa, University of Utah, National Jewish Health, University of California at San Francisco, and University of California at Los Angeles. The University of North Carolina at Chapel Hill serves as the Genomics and Informatics Center. The Radiology Reading Center is based at the University of Iowa. The PFT Reading Center is based at the University of California at Los Angeles. Study Design: SPIROMICS is a prospective cohort study that enrolled approximately 2,981 participants at twelve clinical centers over five years. Participants are distributed across four enrollment strata (i.e., Never-smokers, Smokers without COPD, Mild/Moderate COPD, and Severe COPD). Study Visits: Participants have up to four in-person visits (Baseline and Annual Clinic Visits at years 1, 2, 3 after Baseline). Study questionnaires and spirometry are completed at all main study visits. Blood and urine samples are collected at visits 1, 2, and 4. Sputum samples are collected at Visit 1. The CT scans are completed and Baseline and Visit 2. Participants also receive quarterly follow-up calls to assess health status and determine if an exacerbation has occurred. Substudies Bronchoscopy and Immunophenotyping Substudy The Bronchoscopy Substudy will enroll 50 subjects per site, for a total of 300 participants. These participants will be recruited across all four study strata. This substudy includes two study visits. During the first visit, sputum samples are collected for Immunophenotyping analysis at the Immunophenotyping Core Lab based at the University of Michigan. Participants then return for a second visit during which samples are collected via bronchoscopy, including bronchoalveolar lavage, epithelial brushings and bronchial biopsies. Immunophenotyping analysis is also conducted on BAL and blood collected during the bronchoscopy study visit. Repeatability Substudy The entire baseline clinic visit was repeated on 98 volunteers to determine reliability of measurement procedures. All baseline study-related procedures and questionnaires, including the CT scan, were re-administered and new samples of blood, urine, saliva, and sputum were collected. Field center staff processed these biospecimen samples according to the same protocol. Exacerbation Substudy The Exacerbation Substudy is a prospective, longitudinal observational study of up to 400 participants, which will allow the assessment of participant-driven health care utilization (HCU) events and symptom-defined exacerbation events over time. HCU-driven events are defined by change in medical treatment in response to a perceived COPD Exacerbation. Symptom-based events will be defined by using EXACT-PRO (EXacerbations of Chronic Pulmonary Disease Tool - Patient Reported Outcome), a daily symptom diary developed to measure the frequency, severity, and duration of exacerbations in clinical trials. All participants are provided with a PDA on which to complete the diary. Participants reporting a possible COPD exacerbation will be brought into the study clinic for a study visit to collect biological specimens and questionnaire data. The overall objectives of the Exacerbation Substudy are to: Obtain clinical data and specimens on SPIROMICS participants before and during an acute COPD exacerbation defined by Health care utilization triggered by the subject, or Symptomatic change (triggered by an EXACT defined threshold) Describe symptomatic changes occurring around HCU and symptom-defined (EXACT) events and their relationship to clinical and specimen data, Characterize the non-exacerbation \"stable\" state in COPD using the EXACT, including: Symptom variability (EXACT), Clinical data and specimen parameters during a stable state (baseline), The relationship between clinical and specimen data and symptom severity and variability. Explore the characteristics of stable patients, defined as those who do not experience HCU or symptom-defined (EXACT) events during the sub-study period, using baseline clinical data and specimens, and compare these characteristics with patients who experience HCU and/or symptom-defined events. Examine the relationship between HCU and symptom-defined exacerbation frequency during the first one-year period of follow-up for exacerbations and health outcomes, including 12-month change in lung function and COPD health status, and longer-term morbidity and mortality, with the latter derived from long-term data from the larger SPIROMICS study. Study Weblinks: SubPopulations and InteRmediate Outcome Measures In COPD Study (SPIROMICS) Study Design: Prospective Longitudinal Cohort Study Type: Cohort dbGaP estimated ancestry using GRAF-pop Total number of consented subjects: 2423 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"NHLBI TOPMed: SubPopulations and InteRmediate Outcome Measures In COPD Study (SPIROMICS)","short_name":"SPIROMICS_DS-COPD-COL-NPU","commons":"BioData Catalyst","study_url":"","_subjects_count":10,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs001933.v2.p1.c1":{"gen3_discovery":{"authz":"/programs/topmed/projects/UCSF_Afib_HMB-MDS","tags":[{"name":"TOPMed","category":"Program"},{"name":"Genotype","category":"Data Type"},{"name":"dbGaP","category":"Study Registration"}],"_unique_id":"phs001933.v2.p1.c1","study_id":"phs001933.v2.p1.c1","study_description":"This study is part of the NHLBI Trans-Omics for Precision Medicine (TOPMed) Whole Genome Sequencing Program. TOPMed is part of a broader Precision Medicine Initiative, which aims to provide disease treatments that are tailored to an individual's unique genes and environment. TOPMed will contribute to this initiative through the integration of whole-genome sequencing (WGS) and other -omics (e.g., metabolic profiles, protein and RNA expression patterns) data with molecular, behavioral, imaging, environmental, and clinical data. In doing so, this program aims to uncover factors that increase or decrease the risk of disease, to identify subtypes of disease, and to develop more targeted and personalized treatments. Two genotype call sets derived from WGS are now available, Freeze 9b (GRCh38) and Freeze 10b (GRCh38), with largely overlapping sample sets. Information about how to identify other TOPMed WGS accessions for cross-study analysis, as well as descriptions of TOPMed methods of data acquisition, data processing and quality control, are provided in the accompanying documents, \"TOPMed Whole Genome Sequencing Project - Freeze 9b, Phases 1-4\" and \"TOPMed Whole Genome Sequencing Project - Freeze 10b, Phases 1-8\". Please check the study list at the top of each of these methods documents to determine whether it applies to this study accession. The University of California San Francisco (UCSF) Cardiovascular Research Institute (CVRI) Resource in Arteriosclerosis and Metabolic Disease is an ongoing multi-ethnic study of adults ≥ 18 years of age which was started in 1989 and now includes 28,000 participants recruited from the UCSF medical system. Within the Resource lies data and biospecimens from nearly 1,000 patients presenting to the electrophysiology laboratory for electrophysiology procedures that were densely phenotyped for electrophysiologic characteristics with biospecimens collected from various intra and extra-cardiac chambers. Phenotyping of all participants was achieved via interview and review of medical records. A subset of 113 participants with early-onset atrial fibrillation underwent WGS as a part of the TOPMed Program. Study Design: Case Set Study Type: Case Set dbGaP estimated ancestry using GRAF-pop Total number of consented subjects: 113 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"NHLBI TOPMed - NHGRI CCDG: UCSF Atrial Fibrillation Study","short_name":"UCSF_Afib_HMB-MDS","commons":"BioData Catalyst","study_url":"https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001933.v2.p1","_subjects_count":113,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs001961.v2.p1.c1":{"gen3_discovery":{"authz":"","tags":[],"_unique_id":"phs001961.v2.p1.c1","study_id":"phs001961.v2.p1.c1","study_description":"","full_name":"","short_name":"","commons":"BioData Catalyst","study_url":"","_subjects_count":0,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs001961.v3.p1.c1":{"gen3_discovery":{"authz":"/programs/LungMAP/projects/MALD_GRU","tags":[],"_unique_id":"phs001961.v3.p1.c1","study_id":"phs001961.v3.p1.c1","study_description":"Mammalian fetal lung development is a complex biological process. Despite considerable progress, a comprehensive understanding of the dynamic regulatory networks that govern postnatal alveolar lung development is still lacking. The purpose of this study as part of the LungMAP consortium (www.lungmap.net) is to understand the transcriptional changes in the process of mammalian lung development. Study Weblinks: NCBI GEO GSE161383 Study Design: Control Set Study Type: Longitudinal Total number of consented subjects: 54 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"LungMAP: Molecular Atlas of Lung Development - Human Lung Tissue","short_name":"MALD_GRU","commons":"BioData Catalyst","study_url":"","_subjects_count":49,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs001974.v8.p1.c1":{"gen3_discovery":{"authz":"/programs/topmed/projects/sumstats_GRU","tags":[],"_unique_id":"phs001974.v8.p1.c1","study_id":"phs001974.v8.p1.c1","study_description":"The NHLBI Trans-Omics for Precision Medicine (TOPMed) program aims to identify the genetic basis of variation in biomedical phenotypes, with emphasis on those related to heart, lung, blood and sleep disorders, as part of a broader Precision Medicine Initiative. The TOPMed program has provided whole genome sequencing (WGS) to over 80 different studies that had previously recruited participants and collected extensive phenotype data. Many TOPMed investigators affiliated with these studies have organized their activities into phenotype-focused Working Groups and have developed genotype-phenotype association projects. These analyses have resulted in valuable cross-study Genomic Summary Results (GSR) that include whole genome association test results of both common and rare variants. Most of the analyses include data from multiple studies, some of which are based on sensitive populations, precluding public sharing of GSR. This dbGaP accession provides a mechanism for sharing sensitive GSR, using the controlled-access mechanisms of dbGaP to provide protections for sensitive populations. Study Weblinks: NHLBI Trans-Omics for Precision Medicine Trans-Omics for Precision Medicine (TOPMed) Program Study Design: Prospective Longitudinal Cohort Study Type: Case Set Case-Control Cohort Family Longitudinal NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"NHLBI TOPMed: Genomic Summary Results for the Trans-Omics for Precision Medicine Program","short_name":"sumstats_GRU","commons":"BioData Catalyst","study_url":"","_subjects_count":0,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs002256.v1.p2.c1":{"gen3_discovery":{"authz":"/programs/dbGaP/projects/CRP_JHS_HMB-IRB-NPU","tags":[],"_unique_id":"phs002256.v1.p2.c1","study_id":"phs002256.v1.p2.c1","study_description":"This sub-study phs002256 Cardiometabolic Renal Proteomics study contains molecular data. Summary level phenotypes for the NHLBI JHS cohort participants can be viewed at the top-level study page phs000286 JHS Cohort. Individual level phenotype data and molecular data for all JHS Cohort top-level study and substudies are available by requesting Authorized Access to the NHLBI JHS Cohort phs000286 study. Study Design: Case Set Study Type: Case Set Total number of consented subjects: 2101 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Aptamer Proteomics of Cardiometabolic and Renal Traits in African Americans","short_name":"CRP_JHS_HMB-IRB-NPU","commons":"BioData Catalyst","study_url":"","_subjects_count":445,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs002256.v1.p2.c2":{"gen3_discovery":{"authz":"/programs/dbGaP/projects/CRP_JHS_DS-FDO-IRB-NPU","tags":[],"_unique_id":"phs002256.v1.p2.c2","study_id":"phs002256.v1.p2.c2","study_description":"This sub-study phs002256 Cardiometabolic Renal Proteomics study contains molecular data. Summary level phenotypes for the NHLBI JHS cohort participants can be viewed at the top-level study page phs000286 JHS Cohort. Individual level phenotype data and molecular data for all JHS Cohort top-level study and substudies are available by requesting Authorized Access to the NHLBI JHS Cohort phs000286 study. Study Design: Case Set Study Type: Case Set Total number of consented subjects: 2101 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Aptamer Proteomics of Cardiometabolic and Renal Traits in African Americans","short_name":"CRP_JHS_DS-FDO-IRB-NPU","commons":"BioData Catalyst","study_url":"","_subjects_count":109,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs002256.v1.p2.c3":{"gen3_discovery":{"authz":"/programs/dbGaP/projects/CRP_JHS_HMB-IRB","tags":[],"_unique_id":"phs002256.v1.p2.c3","study_id":"phs002256.v1.p2.c3","study_description":"This sub-study phs002256 Cardiometabolic Renal Proteomics study contains molecular data. Summary level phenotypes for the NHLBI JHS cohort participants can be viewed at the top-level study page phs000286 JHS Cohort. Individual level phenotype data and molecular data for all JHS Cohort top-level study and substudies are available by requesting Authorized Access to the NHLBI JHS Cohort phs000286 study. Study Design: Case Set Study Type: Case Set Total number of consented subjects: 2101 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Aptamer Proteomics of Cardiometabolic and Renal Traits in African Americans","short_name":"CRP_JHS_HMB-IRB","commons":"BioData Catalyst","study_url":"","_subjects_count":1254,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs002256.v1.p2.c4":{"gen3_discovery":{"authz":"/programs/dbGaP/projects/CRP_JHS_DS-FDO-IRB","tags":[],"_unique_id":"phs002256.v1.p2.c4","study_id":"phs002256.v1.p2.c4","study_description":"This sub-study phs002256 Cardiometabolic Renal Proteomics study contains molecular data. Summary level phenotypes for the NHLBI JHS cohort participants can be viewed at the top-level study page phs000286 JHS Cohort. Individual level phenotype data and molecular data for all JHS Cohort top-level study and substudies are available by requesting Authorized Access to the NHLBI JHS Cohort phs000286 study. Study Design: Case Set Study Type: Case Set Total number of consented subjects: 2101 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Aptamer Proteomics of Cardiometabolic and Renal Traits in African Americans","short_name":"CRP_JHS_DS-FDO-IRB","commons":"BioData Catalyst","study_url":"","_subjects_count":293,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs002299.v1.p1.c1":{"gen3_discovery":{"authz":"/programs/COVID19/projects/ORCHID_HMB","tags":[{"name":"COVID 19","category":"Program"},{"name":"dbGaP","category":"Study Registration"}],"_unique_id":"phs002299.v1.p1.c1","study_id":"phs002299.v1.p1.c1","study_description":"ORCHID was a multicenter, blinded, placebo-controlled randomized trial conducted at 34 hospitals in the US between April 2 and June 19, 2020. Adults hospitalized with respiratory symptoms from severe acute respiratory syndrome coronavirus 2 infection were enrolled, with the last outcome assessment on July 17, 2020. The planned sample size was 510 patients with five interim analyses; however, the trial was stopped at the fourth interim analysis for futility with a sample size of 479 patients.The distribution of the day 14 clinical status score (measured using a 7-category ordinal scale) was not significantly different for patients randomized to receive hydroxychloroquine compared with placebo.Instructions for requesting individual-level data are available on BioData Catalyst at https://biodatacatalyst.nhlbi.nih.gov/resources/data/. Apply for data access in dbGaP. Upon approval, users may begin accessing requested data in BioData Catalyst. For questions about availability, you may contact the BioData Catalyst team at https://biodatacatalyst.nhlbi.nih.gov/contact. Study Weblinks: PETAL Network ORCHID Study NHLBI BioLINCC (ORCHID) Study Design: Clinical Trial Study Type: Clinical Trial Controlled Trial Placebo-Controlled Randomized Randomized Controlled Clinical Trial Total number of consented subjects: 479 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"PETAL Network: Outcomes Related to COVID-19 Treated With Hydroxychloroquine Among Inpatients With Symptomatic Disease (ORCHID) Trial","short_name":"ORCHID_HMB","commons":"BioData Catalyst","study_url":"https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs002299.v1.p1","_subjects_count":479,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs002348.v1.p1.c1":{"gen3_discovery":{"authz":"/programs/BioLINCC/projects/MSH_GRU","tags":[{"name":"BioLINCC","category":"Program"},{"name":"dbGaP","category":"Study Registration"},{"name":"Clinical Phenotype","category":"Data Type"}],"_unique_id":"phs002348.v1.p1.c1","study_id":"phs002348.v1.p1.c1","study_description":"This study aimed to determine whether or not treatment with hydroxyurea titrated to maximum tolerated doses would reduce the frequency of vaso-occlusive (painful) crises by at least 50% in 299 men and women between 18 and 50 years old with a diagnosis of sickle cell anemia by gel electrophoresis conducted by a Core Laboratory. A secondary objective investigated correlations of fetal hemoglobin (HbF) levels and other patient or treatment characteristics with the occurrence of vaso-occlusive (painful) crises, and the effect of treatment on the quality of life.This controlled trial made hydroxyurea the first drug of proven benefit in preventing vaso-occlusive pain crisis and acute chest syndrome caused by sickle cell disease, with additional findings including reduced mortality in adult patients taking hydroxyurea for frequent painful sickle cell episodes after 9 of years follow-up. No significant side-effects of hydroxyurea therapy were noted.Instructions for requesting individual-level data are available on BioData Catalyst at https://biodatacatalyst.nhlbi.nih.gov/resources/data/. Apply for data access in dbGaP. Upon approval, users may begin accessing requested data in BioData Catalyst. For questions about availability, you may contact the BioData Catalyst team at https://biodatacatalyst.nhlbi.nih.gov/contact. Study Weblinks: ClinicalTrials.gov (MSH) NHLBI BioLINCC (MSH) Study Design: Clinical Trial Study Type: Double-Blind Randomized Controlled Clinical Trial Total number of consented subjects: 299 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Multicenter Study of Hydroxyurea (MSH)","short_name":"MSH_GRU","commons":"BioData Catalyst","study_url":"https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs002348.v1.p1","_subjects_count":357,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs002362.v1.p1.c1":{"gen3_discovery":{"authz":"/programs/BioLINCC/projects/CSSCD_GRU","tags":[{"name":"BioLINCC","category":"Program"},{"name":"dbGaP","category":"Study Registration"},{"name":"Clinical Phenotype","category":"Data Type"}],"_unique_id":"phs002362.v1.p1.c1","study_id":"phs002362.v1.p1.c1","study_description":"The Cooperative Study of Sickle Cell Disease was initiated in 1977 to determine the natural history of sickle cell disease (SCD) from birth to death in order to identify those factors contributing to the morbidity and mortality of the disease. Specific objectives included: 1) to study the effect of sickle cell disease on growth and development from birth through adolescence 2) to study the conditions or events that may be related to the onset of painful crises 3) to obtain data on the nature, duration, and outcome of major complications of SCD 4) determine the nature, prevalence, and age- related incidence of organ damage due to SCD, and 5) study the role of SCD and its interaction with selected health events.Phases 2 and 3 of the study involved followup of the infant cohort. A total of 709 infants (age less than 6 months) were enrolled during Phase 1 of the Cooperative Study of Sickle Cell Disease (CSSCD), and Phases 2 and 3 of the CSSCD was designed to follow these children for an additional 10 years. The study objectives included: 1) define prospectively the natural history of sickle cell disease; 2) determine the relationships between cognitive and academic functioning and brain status as determined by MRI; 3) determine the cognitive or behavioral markers of silent infarct; 4) determine the relationship of family functioning on the Family Environment Scale (FES) to brain status, cognitive functioning, and social and demographic factors; 5) continue studies that will enhance the state of knowledge on the influence of sickle cell disease on the psychosocial adjustment of children and adolescents. Phase 2A of the study sought to examine the progression of organ damage in the heart, lung, kidney, and liver in adult cohort patients (born before 1/1/56) enrolled in phase 1 of the study between 3/79 and 5/81. A total of 620 patients from 11 centers were eligible for phase 2A.Instructions for requesting individual-level data are available on BioData Catalyst at https://biodatacatalyst.nhlbi.nih.gov/resources/data/. Apply for data access in dbGaP. Upon approval, users may begin accessing requested data in BioData Catalyst. For questions about availability, you may contact the BioData Catalyst team at https://biodatacatalyst.nhlbi.nih.gov/contact. Study Weblinks: ClinicalTrials.gov (CSSCD) BioLINCC (CSSCD) - For biospecimen requests Study Design: Clinical Trial Study Type: Case-Control Clinical Trial Total number of consented subjects: 4085 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Cooperative Study of Sickle Cell Disease (CSSCD)","short_name":"CSSCD_GRU","commons":"BioData Catalyst","study_url":"https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs002386.v1.p1","_subjects_count":4085,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs002363.v1.p1.c1":{"gen3_discovery":{"authz":"/programs/COVID19/projects/RED_CORAL_HMB","tags":[{"name":"COVID 19","category":"Program"},{"name":"dbGaP","category":"Study Registration"},{"name":"Clinical Phenotype","category":"Data Type"}],"_unique_id":"phs002363.v1.p1.c1","study_id":"phs002363.v1.p1.c1","study_description":"To describe characteristics, treatment, and outcomes among patients hospitalized with COVID-19 early in the pandemic, 1480 consecutive adult inpatients with laboratory-confirmed, symptomatic SARS-CoV-2 infection admitted to 57 US hospitals from March 1 to April 1, 2020 were studied.It was found that in a geographically diverse early-pandemic COVID-19 cohort with complete hospital folllow-up, hospital mortality was associated with older age, comorbidity burden, and male sex. Intensive care unit admissions occurred early and were associated with protracted hospital stays. Survivors often required new health care services or respiratory support at discharge.The PETAL Network central institutional review board at Vanderbilt University and the institutional review boards at each participating hospital approved the study or determined that the study was exempt from review. Instructions for requesting individual-level data are available on BioData Catalyst at https://biodatacatalyst.nhlbi.nih.gov/resources/data/. Apply for data access in dbGaP. Upon approval, users may begin accessing requested data in BioData Catalyst. For questions about availability, you may contact the BioData Catalyst team at https://biodatacatalyst.nhlbi.nih.gov/contact. Study Weblinks: PETAL Network RED CORAL Study NHLBI BioLINCC (RED CORAL) Study Design: Control Set Study Type: Case-Cohort Clinical Cohort Cohort Multicenter Total number of consented subjects: 1480 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"PETAL Repository of Electronic Data COVID-19 Observational Study (RED CORAL)","short_name":"RED_CORAL_HMB","commons":"BioData Catalyst","study_url":"https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs002363.v1.p1","_subjects_count":1480,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs002369.v1.p2.c1":{"gen3_discovery":{"authz":"/programs/dbGaP/projects/MPIRD_JHS_HMB-IRB-NPU","tags":[],"_unique_id":"phs002369.v1.p2.c1","study_id":"phs002369.v1.p2.c1","study_description":"Our lab has identified and validated novel metabolite profiles of those destined to develop overt T2D. These metabolites were elevated up to 12 years before the onset of T2D in individuals who were initially glucose-tolerant; improved prediction of T2D beyond clinical risk factors and established biochemical markers; and have been validated by other groups. We have now extended our studies to participants in the Jackson Heart Study (JHS), an African American (AA) population with a high prevalence of T2D and its complications. We have also tested the predictive value of metabolites in a key clinical trial, the Diabetes Prevention Program (DPP). Our study has leveraged critical advances. Beyond the named metabolites that we have associated with incident T2D, our recent \"whole metabolome\" analyses of T2D and related traits in JHS have nominated hundreds of unknown compounds that are uncorrelated with existing biochemical markers for unambiguous identification. We have used novel, in-house mass spectrometry (MS) and bioinformatics tools to unambiguously identify these compounds. To complement the MS work, genome wide association studies (GWAS) and genetic correlation analyses of metabolites and proteins were used to assign metabolite peaks to pathways (e.g., based on association with known metabolites or with enzymes or solute carriers) that informed their identity. Available data will include metabolomics datasets and gwas summary statistics. Study Design: Prospective Longitudinal Cohort Study Type: Cohort Total number of consented subjects: 2706 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Metabolomic Predictors of Insulin Resistance and Diabetes","short_name":"MPIRD_JHS_HMB-IRB-NPU","commons":"BioData Catalyst","study_url":"","_subjects_count":617,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs002369.v1.p2.c2":{"gen3_discovery":{"authz":"/programs/dbGaP/projects/MPIRD_JHS_DS-FDO-IRB-NPU","tags":[],"_unique_id":"phs002369.v1.p2.c2","study_id":"phs002369.v1.p2.c2","study_description":"Our lab has identified and validated novel metabolite profiles of those destined to develop overt T2D. These metabolites were elevated up to 12 years before the onset of T2D in individuals who were initially glucose-tolerant; improved prediction of T2D beyond clinical risk factors and established biochemical markers; and have been validated by other groups. We have now extended our studies to participants in the Jackson Heart Study (JHS), an African American (AA) population with a high prevalence of T2D and its complications. We have also tested the predictive value of metabolites in a key clinical trial, the Diabetes Prevention Program (DPP). Our study has leveraged critical advances. Beyond the named metabolites that we have associated with incident T2D, our recent \"whole metabolome\" analyses of T2D and related traits in JHS have nominated hundreds of unknown compounds that are uncorrelated with existing biochemical markers for unambiguous identification. We have used novel, in-house mass spectrometry (MS) and bioinformatics tools to unambiguously identify these compounds. To complement the MS work, genome wide association studies (GWAS) and genetic correlation analyses of metabolites and proteins were used to assign metabolite peaks to pathways (e.g., based on association with known metabolites or with enzymes or solute carriers) that informed their identity. Available data will include metabolomics datasets and gwas summary statistics. Study Design: Prospective Longitudinal Cohort Study Type: Cohort Total number of consented subjects: 2706 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Metabolomic Predictors of Insulin Resistance and Diabetes","short_name":"MPIRD_JHS_DS-FDO-IRB-NPU","commons":"BioData Catalyst","study_url":"","_subjects_count":136,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs002369.v1.p2.c3":{"gen3_discovery":{"authz":"/programs/dbGaP/projects/MPIRD_JHS_HMB-IRB","tags":[],"_unique_id":"phs002369.v1.p2.c3","study_id":"phs002369.v1.p2.c3","study_description":"Our lab has identified and validated novel metabolite profiles of those destined to develop overt T2D. These metabolites were elevated up to 12 years before the onset of T2D in individuals who were initially glucose-tolerant; improved prediction of T2D beyond clinical risk factors and established biochemical markers; and have been validated by other groups. We have now extended our studies to participants in the Jackson Heart Study (JHS), an African American (AA) population with a high prevalence of T2D and its complications. We have also tested the predictive value of metabolites in a key clinical trial, the Diabetes Prevention Program (DPP). Our study has leveraged critical advances. Beyond the named metabolites that we have associated with incident T2D, our recent \"whole metabolome\" analyses of T2D and related traits in JHS have nominated hundreds of unknown compounds that are uncorrelated with existing biochemical markers for unambiguous identification. We have used novel, in-house mass spectrometry (MS) and bioinformatics tools to unambiguously identify these compounds. To complement the MS work, genome wide association studies (GWAS) and genetic correlation analyses of metabolites and proteins were used to assign metabolite peaks to pathways (e.g., based on association with known metabolites or with enzymes or solute carriers) that informed their identity. Available data will include metabolomics datasets and gwas summary statistics. Study Design: Prospective Longitudinal Cohort Study Type: Cohort Total number of consented subjects: 2706 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Metabolomic Predictors of Insulin Resistance and Diabetes","short_name":"MPIRD_JHS_HMB-IRB","commons":"BioData Catalyst","study_url":"","_subjects_count":1599,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs002369.v1.p2.c4":{"gen3_discovery":{"authz":"/programs/dbGaP/projects/MPIRD_JHS_DS-FDO-IRB","tags":[],"_unique_id":"phs002369.v1.p2.c4","study_id":"phs002369.v1.p2.c4","study_description":"Our lab has identified and validated novel metabolite profiles of those destined to develop overt T2D. These metabolites were elevated up to 12 years before the onset of T2D in individuals who were initially glucose-tolerant; improved prediction of T2D beyond clinical risk factors and established biochemical markers; and have been validated by other groups. We have now extended our studies to participants in the Jackson Heart Study (JHS), an African American (AA) population with a high prevalence of T2D and its complications. We have also tested the predictive value of metabolites in a key clinical trial, the Diabetes Prevention Program (DPP). Our study has leveraged critical advances. Beyond the named metabolites that we have associated with incident T2D, our recent \"whole metabolome\" analyses of T2D and related traits in JHS have nominated hundreds of unknown compounds that are uncorrelated with existing biochemical markers for unambiguous identification. We have used novel, in-house mass spectrometry (MS) and bioinformatics tools to unambiguously identify these compounds. To complement the MS work, genome wide association studies (GWAS) and genetic correlation analyses of metabolites and proteins were used to assign metabolite peaks to pathways (e.g., based on association with known metabolites or with enzymes or solute carriers) that informed their identity. Available data will include metabolomics datasets and gwas summary statistics. Study Design: Prospective Longitudinal Cohort Study Type: Cohort Total number of consented subjects: 2706 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Metabolomic Predictors of Insulin Resistance and Diabetes","short_name":"MPIRD_JHS_DS-FDO-IRB","commons":"BioData Catalyst","study_url":"","_subjects_count":354,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs002383.v1.p1.c1":{"gen3_discovery":{"authz":"/programs/BioLINCC/projects/Walk_PHaSST_DS-SCD-IRB-PUB-COL-NPU-MDS-RD","tags":[{"name":"dbGaP","category":"Study Registration"}],"_unique_id":"phs002383.v1.p1.c1","study_id":"phs002383.v1.p1.c1","study_description":"Pulmonary arterial hypertension (PAH) is a progressive condition characterized by narrowing or stiffening pulmonary arterioles resulting in increased pulmonary blood pressure and reduced delivery of oxygenated blood to the body. It is a common complication of sickle cell disease and initially presents with the symptom of shortness of breath (dyspnea) on exertion. As the condition worsens, other symptoms such as dizziness, lower extremity edema, and chest pain can develop. The drug, sildenafil, works by relaxing blood vessels in the lungs which reduces pulmonary blood pressure and allows more oxygenated blood to circulate. Increased levels of oxygenated blood allows individuals with PAH to tolerate more activity, but guidelines for using sildenafil in patients with PAH and sickle cell disease were unavailable at the time of the Walk-PHaSST trial.Participants were screened for the existence of pulmonary hypertension with a six minute walk test and a Doppler echocardiogram that assessed TRV, diastolic function, and valvular and systolic function. Subjects with TRV ≥ 2.7 m/s received further clinical evaluation for possible causes of pulmonary hypertension. Other screening data included medical history, a physical exam, and standard laboratory testing. For individuals with moderate to severe pulmonary hypertension (TRV ≥ 3.0), a cardiac catheterization was done at the baseline and week 16 data collection periods.Subjects eligible for the main intervention trial based on screening results were randomized in a 1:1 double blind fashion to receive sildenafil or placebo for 16 weeks. Subjects received 20 mg of oral sildenafil or matching placebo 3 times daily for 6 weeks, followed by 40 mg 3 times daily for 4 weeks, followed by 80 mg 3 times daily for 6 weeks, as tolerated. Participants could also receive other therapies as needed to manage sickle cell and related complications. The primary outcome measure of the trial was change in the six minute walk test, a standard indicator of a person's heart and lung function and exercise capacity, from baseline to week 16. After completing the study treatment (or placebo), participants could choose to be part of the open-label follow-up phase of the study and continue to be assessed for up to one year.The study was intended to screen about 1000 subjects and randomize 132 subjects, however it was terminated early due to the unforeseen increase in adverse events in participants treated with sildenafil as compared to placebo. When the study was stopped, 33 participants had completed the trial. Subjects continued to be monitored, but were instructed to taper sildenafil treatment over three to seven days.There was no evidence that treatment with sildenafil impacted the six minute walk distance from baseline to week 16. In addition, treatment with sildenafil appeared to increase rates of hospitalization due to sickle cell disease pain.Due to in part to the early termination of the trial, the majority of subject data was collected from the screening phase of the study (n=720), as opposed to the main intervention trial (n=74).Instructions for requesting individual-level data are available on BioData Catalyst at https://biodatacatalyst.nhlbi.nih.gov/resources/data/. Apply for data access in dbGaP. Upon approval, users may begin accessing requested data in BioData Catalyst. For questions about availability, you may contact the BioData Catalyst team at https://biodatacatalyst.nhlbi.nih.gov/contact. Study Weblinks: ClinicalTrials.gov (Walk-PHaSST) BioLINCC (Walk-PHaSST) Study Design: Clinical Trial Study Type: Clinical Trial Double-Blind Total number of consented subjects: 720 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Treatment of Pulmonary Hypertension and Sickle Cell Disease with Sildenafil Therapy (Walk-PHaSST)","short_name":"Walk_PHaSST_DS-SCD-IRB-PUB-COL-NPU-MDS-RD","commons":"BioData Catalyst","study_url":"https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs002383.v1.p1","_subjects_count":720,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs002385.v1.p1.c1":{"gen3_discovery":{"authz":"/programs/BioLINCC/projects/CIBMTR_GRU","tags":[{"name":"BioLINCC","category":"Program"},{"name":"dbGaP","category":"Study Registration"},{"name":"Clinical Phenotype","category":"Data Type"}],"_unique_id":"phs002385.v1.p1.c1","study_id":"phs002385.v1.p1.c1","study_description":"The Center for International Blood and Marrow Transplant Research (CIBMTR) is a hematopoietic cell transplant registry that was established in 1972 at the Medical College of Wisconsin. The overarching goal of the registry is to study trends in transplantations and to advance the understanding and application of allogeneic hematopoietic cell transplantation for malignant and non-malignant diseases. Included in this dataset are children, adolescents and young adults with severe sickle cell disease who received an allogeneic hematopoietic cell transplant in the United States and provided written informed consent for research.Hematopoietic cell transplant for sickle cell disease is curative. Offering this treatment for patients with severe disease is challenging as only about 20-25% of patients expected to benefit have an HLA-matched sibling. Consequently, several transplantations have utilized an HLA-matched or mismatched unrelated adult donor and HLA-mismatched relative. Transplantation strategies have also evolved over time that has included transplant conditioning regimens of varying intensity, grafts other than bone marrow and novel approaches to overcome the donor-recipient histocompatibility barrier and limit graft-versus-host disease. The data that is available for sickle cell disease transplants have been utilized to report on outcomes after transplantation and compare outcomes after transplantation of grafts HLA-matched related, HLA-mismatched related, HLA-matched and HLA-mismatched unrelated donors. Collectively, these data have advanced our knowledge and understanding of hematopoietic cell transplant for this disease. These data can also serve as \"contemporaneous controls\" for comparison with other more recent curative treatments like gene therapy and gene editing.Data available for request include allogeneic hematopoietic cell transplants for sickle cell disease (Hb SS and Hb Sβ thalassemia) in the United States from 1991 to 2019. Follow-up data through December 2020 are available.Instructions for requesting individual-level data are available on BioData Catalyst at https://biodatacatalyst.nhlbi.nih.gov/resources/data/. Apply for data access in dbGaP. Upon approval, users may begin accessing requested data in BioData Catalyst. For questions about availability, you may contact the BioData Catalyst team at https://biodatacatalyst.nhlbi.nih.gov/contact. Study Weblinks: ClinicalTrials.gov (HCT for SCD) BioLINCC (HCT for SCD) Study Design: Prospective Longitudinal Cohort Study Type: Clinical Cohort Cohort Control Set Longitudinal Longitudinal Cohort Multicenter Observational Total number of consented subjects: 1518 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Hematopoietic Cell Transplant for Sickle Cell Disease (HCT for SCD)","short_name":"CIBMTR_GRU","commons":"BioData Catalyst","study_url":"https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs002385.v1.p1","_subjects_count":1518,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs002386.v1.p1.c1":{"gen3_discovery":{"authz":"/programs/BioLINCC/projects/STOPII_GRU","tags":[{"name":"BioLINCC","category":"Program"},{"name":"dbGaP","category":"Study Registration"},{"name":"Clinical Phenotype","category":"Data Type"}],"_unique_id":"phs002386.v1.p1.c1","study_id":"phs002386.v1.p1.c1","study_description":"The STOP II trial evaluated whether prophylactic transfusion in patients with sickle cell disease and high risk of stroke can be safely halted after 30 months of treatment during which patients became low risk for stroke.Stroke causes substantial morbidity in children with sickle cell disease. To prevent first strokes, the Stroke Prevention Trial in Sickle Cell Anemia (STOP) used prophylactic transfusions in children who were identified by transcranial Doppler (TCD) ultrasonography as being at high risk for stroke. This strategy reduced the incidence of stroke among such children from 10% per year to less than 1% per year, leading to recommendations for TCD screening and prophylactic transfusion for children with abnormal velocities on ultrasonography. Despite the reduced risk of stroke, long-term use of transfusions can cause adverse side effects, such as iron overload or alloimmunization. However, cessation of transfusions is associated with recurrence of stroke, and at the time of the STOP II trial, there were no clinical or laboratory indicators to guide the duration of prophylaxis. Therefore the STOP II trial was initiated to determine whether transfusions could be limited by monitoring patients with TCD examinations after transfusions were halted and resuming transfusions if the examination indicated a high risk of stroke.The trial was halted for safety concerns after 79 of a planned 100 children were randomized. Discontinuation of transfusion for the prevention of stroke in children with sickle cell disease resulted in a high rate of reversion to abnormal blood-flow velocities on Doppler studies and stroke incidence.Instructions for requesting individual-level data are available on BioData Catalyst at https://biodatacatalyst.nhlbi.nih.gov/resources/data/. Apply for data access in dbGaP. Upon approval, users may begin accessing requested data in BioData Catalyst. For questions about availability, you may contact the BioData Catalyst team at https://biodatacatalyst.nhlbi.nih.gov/contact. Study Weblinks: BioLINCC (STOP II) ClinicalTrials.gov (STOP II) Study Design: Clinical Trial Study Type: Clinical Trial Randomized Total number of consented subjects: 79 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Optimizing Primary Stroke Prevention in Children with Sickle Cell Anemia (STOP II)","short_name":"STOPII_GRU","commons":"BioData Catalyst","study_url":"https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs002386.v1.p1","_subjects_count":77,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs002415.v1.p1.c1":{"gen3_discovery":{"authz":"/programs/BioLINCC/projects/BabyHug_DS-SCD-IRB-RD","tags":[{"name":"dbGaP","category":"Study Registration"},{"name":"Clinical Phenotype","category":"Data Type"}],"_unique_id":"phs002415.v1.p1.c1","study_id":"phs002415.v1.p1.c1","study_description":"Sickle cell anemia is associated with substantial morbidity from acute complications and organ dysfunction beginning in the first year of life. In 1995, the Multicenter Study of Hydroxyurea (MSH) (dbGaP phs002348) demonstrated that, in adults, hydroxyurea is effective in decreasing the frequency of painful crises, hospitalizations for crises, acute chest syndrome, and blood transfusions by 50%. The phase I/II study of hydroxyurea in children (HUG KIDS) demonstrated that children have a response to hydroxyurea similar to that seen in adults in terms of increasing fetal hemoglobin levels and total hemoglobin, and decreasing complications associated with sickle cell anemia. In addition, this study demonstrated that the drug does not adversely affect growth and development between the ages of 5 and 15. A pilot study of hydroxyurea (HUSOFT) given to children between the ages of 6 months and 24 months demonstrated that the drug was well tolerated and that the fetal hemoglobin levels rose and remained elevated compared to baseline with continued hydroxyurea administration. A Special Emphasis Panel (SEP) met on April 12, 1996 to review the results of the MSH trial and the progress to date of the HUG KIDS study. The SEP recommended that NHLBI undertake the BABY HUG trial. The BABY HUG Randomized Controlled Trial concluded that hydroxyurea treatment in very young children seemed to have an acceptable safety profile and to reduce complications of sickle cell anemia. However, more data were needed on the long-term safety of hydroxyurea use in very young children. As a result, follow-up studies were initiated. The Follow-Up Study II provided longer follow-up than Follow-Up Study I, and included more assessment types than Follow-Up Study I.The BABY HUG program consisted of three related studies, each of which has associated datasets and bio-specimens. A randomized controlled trial comparing hydroxyurea to placebo in very young children with sickle cell anemia (BABY HUG Randomized Controlled Trial) The first observational follow-up study of children from the randomized controlled trial (BABY HUG Follow-Up Study I). All children in Follow-Up Study I were offered the option of taking open-label hydroxyurea, with treatment decisions made by the family and the clinical team caring for the child. The second observational follow-up study of children from BABY HUG Follow-Up Study I. All children in Follow-Up Study II were offered the option of taking open-label hydroxyurea, with treatment decisions made by the family and the clinical team caring for the child.The purpose of the Randomized Controlled Trial was to determine if hydroxyurea can safely prevent early end organ damage in very young children with sickle cell anemia. The purpose of the BABY HUG Follow-up Study I was to provide structured follow-up of the children enrolled in the BABY HUG Randomized Controlled Trial, in order to characterize the long-term toxicities and unexpected risks (if any) associated with treatment with hydroxyurea at an early age. The objective of Follow-Up Study II was to obtain additional data about the long-term safety and efficacy of hydroxyurea use in children with Sickle Cell Anemia through at least the first decade of life.Instructions for requesting individual-level data are available on BioData Catalyst at https://biodatacatalyst.nhlbi.nih.gov/resources/data/. Apply for data access in dbGaP. Upon approval, users may begin accessing requested data in BioData Catalyst. For questions about availability, you may contact the BioData Catalyst team at https://biodatacatalyst.nhlbi.nih.gov/contact. Study Weblinks: Randomized Control Trial Follow-Up Study I Follow-Up Study II BioLINCC - BABY HUG Study Design: Clinical Trial Study Type: Clinical Cohort Clinical Trial Collection Controlled Trial Double-Blind Total number of consented subjects: 219 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Hydroxyurea to Prevent Organ Damage in Children with Sickle Cell Anemia (BABY HUG) Phase III Clinical Trial and Follow-Up Observational Studies I and II","short_name":"BabyHug_DS-SCD-IRB-RD","commons":"BioData Catalyst","study_url":"https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs002415.v1.p1","_subjects_count":204,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs002558.v3.p16.c1":{"gen3_discovery":{"authz":"/programs/dbGaP/projects/ADSP_FHS_HMB-IRB-MDS","tags":[],"_unique_id":"phs002558.v3.p16.c1","study_id":"phs002558.v3.p16.c1","study_description":"To identify novel genetic variation influencing AD risk and protection, the Alzheimer's Disease Sequencing Project (ADSP) was implemented as a collaborative effort of the National Institutes on Aging, the National Human Genome Research Institute, and the Alzheimer disease research community. Study design and sample selection were conducted to address issues of phenotypic heterogeneity and maximize statistical power. The study design includes 2 primary phases: a whole-genome sequencing (WGS) family-based study and a whole-exome sequencing (WES) case-control study. The WGS study was designed to target rarer variation through allelic segregation and linkage analyses in multiplex AD families. The WES case-control study was designed to target low-frequency coding variation in genes that contribute to AD risk or protection. The FHS ADSP WES samples are from the WES case-control study phase. Study Weblinks: ADSP Study Design: Case Set Study Type: Case-Control dbGaP estimated ancestry using GRAF-pop Total number of consented subjects: 581 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Framingham CHARGE Alzheimer's Disease Sequencing Project (ADSP)","short_name":"ADSP_FHS_HMB-IRB-MDS","commons":"BioData Catalyst","study_url":"","_subjects_count":352,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs002558.v3.p16.c2":{"gen3_discovery":{"authz":"/programs/dbGaP/projects/ADSP_FHS_HMB-IRB-NPU-MDS","tags":[],"_unique_id":"phs002558.v3.p16.c2","study_id":"phs002558.v3.p16.c2","study_description":"To identify novel genetic variation influencing AD risk and protection, the Alzheimer's Disease Sequencing Project (ADSP) was implemented as a collaborative effort of the National Institutes on Aging, the National Human Genome Research Institute, and the Alzheimer disease research community. Study design and sample selection were conducted to address issues of phenotypic heterogeneity and maximize statistical power. The study design includes 2 primary phases: a whole-genome sequencing (WGS) family-based study and a whole-exome sequencing (WES) case-control study. The WGS study was designed to target rarer variation through allelic segregation and linkage analyses in multiplex AD families. The WES case-control study was designed to target low-frequency coding variation in genes that contribute to AD risk or protection. The FHS ADSP WES samples are from the WES case-control study phase. Study Weblinks: ADSP Study Design: Case Set Study Type: Case-Control dbGaP estimated ancestry using GRAF-pop Total number of consented subjects: 581 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Framingham CHARGE Alzheimer's Disease Sequencing Project (ADSP)","short_name":"ADSP_FHS_HMB-IRB-NPU-MDS","commons":"BioData Catalyst","study_url":"","_subjects_count":229,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs002559.v3.p16.c1":{"gen3_discovery":{"authz":"/programs/dbGaP/projects/BRIDGET_FHS_HMB-IRB-MDS","tags":[],"_unique_id":"phs002559.v3.p16.c1","study_id":"phs002559.v3.p16.c1","study_description":"The BRIDGET study population comprises six large, richly phenotyped and genotyped prospective cohort studies of middle-aged and older community-dwelling persons: Austrian Stroke Prevention Study [ASPS], Rotterdam Study, Study of Health in Pomerania [SHIP], 3C-Dijon Study, Lothian Birth Cohort 1936 [LBC1936], and Framingham Heart Study (FHS). The FHS is an external partner participating in this project through independent funding.Alzheimer's disease (AD) begins many years before diagnosis and yet its etiology is still poorly understood. The BRIDGET consortium aims to identify genetic variants that are associated with structural brain aging, cognitive performance, and dementia risk in richly phenotyped population-based samples. This work aims to provide crucial information on the molecular pathways leading to AD, potentially leading to improved health outcomes for our aging population. This includes an innovative exploration of lifetime changes in methylation associated with structural brain alterations using a novel bisulfite sequencing technology, to help identify functional and disease relevant variants. Study Weblinks: BRIDGET Study Design: Prospective Longitudinal Cohort Study Type: Epigenetics Total number of consented subjects: 197 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Framingham BRain Imaging, cognition, Dementia and next generation GEnomics (BRIDGET)","short_name":"BRIDGET_FHS_HMB-IRB-MDS","commons":"BioData Catalyst","study_url":"","_subjects_count":186,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs002559.v3.p16.c2":{"gen3_discovery":{"authz":"/programs/dbGaP/projects/BRIDGET_FHS_HMB-IRB-NPU-MDS","tags":[],"_unique_id":"phs002559.v3.p16.c2","study_id":"phs002559.v3.p16.c2","study_description":"The BRIDGET study population comprises six large, richly phenotyped and genotyped prospective cohort studies of middle-aged and older community-dwelling persons: Austrian Stroke Prevention Study [ASPS], Rotterdam Study, Study of Health in Pomerania [SHIP], 3C-Dijon Study, Lothian Birth Cohort 1936 [LBC1936], and Framingham Heart Study (FHS). The FHS is an external partner participating in this project through independent funding.Alzheimer's disease (AD) begins many years before diagnosis and yet its etiology is still poorly understood. The BRIDGET consortium aims to identify genetic variants that are associated with structural brain aging, cognitive performance, and dementia risk in richly phenotyped population-based samples. This work aims to provide crucial information on the molecular pathways leading to AD, potentially leading to improved health outcomes for our aging population. This includes an innovative exploration of lifetime changes in methylation associated with structural brain alterations using a novel bisulfite sequencing technology, to help identify functional and disease relevant variants. Study Weblinks: BRIDGET Study Design: Prospective Longitudinal Cohort Study Type: Epigenetics Total number of consented subjects: 197 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Framingham BRain Imaging, cognition, Dementia and next generation GEnomics (BRIDGET)","short_name":"BRIDGET_FHS_HMB-IRB-NPU-MDS","commons":"BioData Catalyst","study_url":"","_subjects_count":11,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs002560.v3.p16.c1":{"gen3_discovery":{"authz":"/programs/dbGaP/projects/FHS_GutMicro_HMB-IRB-MDS","tags":[],"_unique_id":"phs002560.v3.p16.c1","study_id":"phs002560.v3.p16.c1","study_description":"The human gut harbors trillions of microbes that play dynamic roles in health. While the microbiome contributes to many cardiometabolic traits by modulating host inflammation and metabolism, there is an incomplete understanding regarding the extent and mechanisms by which individual microbes impact risk and development of cardiovascular disease (CVD). The Framingham Heart Study (FHS) is a multi-generational observational study following participants over decades to identify risk factors for CVD by correlating genetic and phenotypic factors with clinical outcomes. As a large-scale population-based cohort with extensive clinical phenotyping, FHS provides a rich landscape to explore the relationships between the gut microbiome and cardiometabolic traits Available Data sets Currently we have the following data set available in the 'Authorized Access' area of dbGaP. Cholesterol Metabolism by Uncultured Human Gut Bacteria Influences Host Cholesterol This data set, consisting of metagenome FASTQ data from 624 FHS participants, was released in conjunction with PMID: 32544460. Study Weblinks: Framingham Heart Study Study Design: Prospective Longitudinal Cohort Study Type: Cohort Total number of consented subjects: 1420 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Clinical and Genetic Correlates of the Gut Microbiome and Relation to Cardiometabolic Risk","short_name":"FHS_GutMicro_HMB-IRB-MDS","commons":"BioData Catalyst","study_url":"","_subjects_count":1352,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs002560.v3.p16.c2":{"gen3_discovery":{"authz":"/programs/dbGaP/projects/FHS_GutMicro_HMB-IRB-NPU-MDS","tags":[],"_unique_id":"phs002560.v3.p16.c2","study_id":"phs002560.v3.p16.c2","study_description":"The human gut harbors trillions of microbes that play dynamic roles in health. While the microbiome contributes to many cardiometabolic traits by modulating host inflammation and metabolism, there is an incomplete understanding regarding the extent and mechanisms by which individual microbes impact risk and development of cardiovascular disease (CVD). The Framingham Heart Study (FHS) is a multi-generational observational study following participants over decades to identify risk factors for CVD by correlating genetic and phenotypic factors with clinical outcomes. As a large-scale population-based cohort with extensive clinical phenotyping, FHS provides a rich landscape to explore the relationships between the gut microbiome and cardiometabolic traits Available Data sets Currently we have the following data set available in the 'Authorized Access' area of dbGaP. Cholesterol Metabolism by Uncultured Human Gut Bacteria Influences Host Cholesterol This data set, consisting of metagenome FASTQ data from 624 FHS participants, was released in conjunction with PMID: 32544460. Study Weblinks: Framingham Heart Study Study Design: Prospective Longitudinal Cohort Study Type: Cohort Total number of consented subjects: 1420 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Clinical and Genetic Correlates of the Gut Microbiome and Relation to Cardiometabolic Risk","short_name":"FHS_GutMicro_HMB-IRB-NPU-MDS","commons":"BioData Catalyst","study_url":"","_subjects_count":68,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs002611.v3.p16.c1":{"gen3_discovery":{"authz":"/programs/dbGaP/projects/FHS_RNA_Brain_HMB-IRB-MDS","tags":[],"_unique_id":"phs002611.v3.p16.c1","study_id":"phs002611.v3.p16.c1","study_description":"The biology of obesity is complex, involving both environmental and genetic factors and affecting metabolic and endocrine mechanisms in tissues of the gut, adipose, and brain. This study was conducted to identify transcripts in postmortem human brain tissue associated with obesity status. We conducted both large and small RNA sequencing of hypothalamus and nucleus accumbens from postmortem brain tissue samples from Framingham Heart Study participants defined as consistently obese, consistently normal weight as controls based on longitudinal BMI measures or selected without respect to BMI and falling within neither case nor control definition. Study Weblinks: RNA-sequencing of human post-mortem hypothalamus and nucleus accumbens identifies expression profiles associated with obesity Study Design: Case-Control Study Type: Transcriptome Sequencing Total number of consented subjects: 117 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Framingham Heart Study RNA Sequencing in Postmortem Brain Tissue","short_name":"FHS_RNA_Brain_HMB-IRB-MDS","commons":"BioData Catalyst","study_url":"","_subjects_count":94,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs002611.v3.p16.c2":{"gen3_discovery":{"authz":"/programs/dbGaP/projects/FHS_RNA_Brain_HMB-IRB-NPU-MDS","tags":[],"_unique_id":"phs002611.v3.p16.c2","study_id":"phs002611.v3.p16.c2","study_description":"The biology of obesity is complex, involving both environmental and genetic factors and affecting metabolic and endocrine mechanisms in tissues of the gut, adipose, and brain. This study was conducted to identify transcripts in postmortem human brain tissue associated with obesity status. We conducted both large and small RNA sequencing of hypothalamus and nucleus accumbens from postmortem brain tissue samples from Framingham Heart Study participants defined as consistently obese, consistently normal weight as controls based on longitudinal BMI measures or selected without respect to BMI and falling within neither case nor control definition. Study Weblinks: RNA-sequencing of human post-mortem hypothalamus and nucleus accumbens identifies expression profiles associated with obesity Study Design: Case-Control Study Type: Transcriptome Sequencing Total number of consented subjects: 117 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Framingham Heart Study RNA Sequencing in Postmortem Brain Tissue","short_name":"FHS_RNA_Brain_HMB-IRB-NPU-MDS","commons":"BioData Catalyst","study_url":"","_subjects_count":23,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs002694.v4.p1.c1":{"gen3_discovery":{"authz":"/programs/COVID19/projects/ACTIV4A_GRU","tags":[{"name":"COVID 19","category":"Program"},{"name":"dbGaP","category":"Study Registration"}],"_unique_id":"phs002694.v4.p1.c1","study_id":"phs002694.v4.p1.c1","study_description":"This is a randomized, open label, adaptive platform trial to compare the effectiveness of antithrombotic strategies for prevention of adverse outcomes in COVID-19 positive inpatients. Study Design: Interventional Study Type: Clinical Trial Controlled Trial Interventional Randomized Randomized Controlled Clinical Trial Total number of consented subjects: 3425 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"COVID-19 ACTIV-4 ACUTE: A Multicenter, Adaptive, Randomized Controlled Platform Trial of the Safety and Efficacy of Antithrombotic Strategies in Hospitalized Adults with COVID-19 (ACTIV4A)","short_name":"ACTIV4A_GRU","commons":"BioData Catalyst","study_url":"https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs002694.v4.p1","_subjects_count":3425,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs002710.v1.p1.c1":{"gen3_discovery":{"authz":"/programs/COVID19/projects/ACTIV4B_GRU","tags":[{"name":"COVID 19","category":"Program"},{"name":"dbGaP","category":"Study Registration"},{"name":"Clinical Phenotype","category":"Data Type"}],"_unique_id":"phs002710.v1.p1.c1","study_id":"phs002710.v1.p1.c1","study_description":"An adaptive randomized double-blind placebo-controlled platform trial to compare the effectiveness of anticoagulation with antiplatelet agents and with placebo to prevent thrombotic events in patients diagnosed with COVID-19 who are not admitted to hospital as COVID-19 related symptoms are currently stable. Study Design: Interventional Study Type: Clinical Trial Double-Blind Interventional Placebo-Controlled Randomized Randomized Controlled Clinical Trial Total number of consented subjects: 657 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"COVID-19 Outpatient Thrombosis Prevention Trial (ACTIV-4B)","short_name":"ACTIV4B_GRU","commons":"BioData Catalyst","study_url":"https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs002710.v1.p1","_subjects_count":657,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs002715.v1.p1.c1":{"gen3_discovery":{"authz":"/programs/NSRR/projects/NSRR-CFS_DS-HLBS-IRB-NPU","tags":[{"name":"dbGaP","category":"Study Registration"}],"_unique_id":"phs002715.v1.p1.c1","study_id":"phs002715.v1.p1.c1","study_description":"The Cleveland Family Study (CFS) is a family-based study of sleep apnea, consisting of 2,284 individuals (46% African American) from 361 families studied on up to 4 occasions over a period of 16 years. The study began in 1990 with the initial aims of quantifying the familial aggregation of sleep apnea. National Institutes of Health (NIH) renewals provided expansion of the original cohort, including increased minority recruitment, and longitudinal follow-up, with the last exam occurring in February 2006. The CFS was designed to provide fundamental epidemiological data on risk factors for sleep disordered breathing (SDB). The sample was selected by identifying affected probands who had laboratory diagnosed obstructive sleep apnea. All first-degree relatives, spouses and available second-degree relatives of affected probands were studied. In addition, during the first 5 study years, neighborhood control families were identified through a neighborhood proband, and his/her spouses and first-degree relatives. Each exam, occurring at approximately 4-year intervals, included new enrollment as well as follow up exams for previously enrolled subjects. For the first three visits, data, including an overnight sleep study, were collected in participants' homes while the last visit occurred in a general clinical research center (GCRC). Phenotypic characterization of the entire cohort included overnight sleep apnea studies, blood pressure, spirometry, anthropometry and questionnaires. Currently, data of 710 individuals are available for use through BioData Catalyst (with genotype data available through dbGaP).The National Sleep Research Resource (NSRR) is a NIH-supported sleep data repository that offers free access to large collections of de-identified physiological signals and related clinical data from a large range of cohort studies, clinical trials and other data sources from children and adults, including healthy individuals from the community and individuals with known sleep or other health disorders. The goals of NSRR are to facilitate rigorous research that requires access to large or more diverse data sets, including raw physiological signals, to promote a better understanding of risk factors for sleep and circadian disorders and/or the impact of sleep disturbances on health-related outcomes. Data from over 15 data sources and more than 40,000 individual sleep studies, many linked to dozens if not hundreds of clinical data elements, are available (as of Feb. 2022). Query tools are available to identify variables of interest, and their meta-data and provenance. Study Weblinks: Cleveland Family Study Study Design: Prospective Longitudinal Cohort Study Type: Longitudinal Cohort Total number of consented subjects: 710 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"National Sleep Research Resource (NSRR): Cleveland Family Study (CFS)","short_name":"NSRR-CFS_DS-HLBS-IRB-NPU","commons":"BioData Catalyst","study_url":"https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs002715.v1.p1","_subjects_count":710,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs002719.v1.p1.c1":{"gen3_discovery":{"authz":"/programs/heartfailure/projects/REGARDS_GWAS_HMB-IRB","tags":[],"_unique_id":"phs002719.v1.p1.c1","study_id":"phs002719.v1.p1.c1","study_description":"REGARDS is a national, population-based, longitudinal study of incident stroke and associated risk factors including over 30,000 Black and White adults aged 45 years or older from all 48 contiguous U.S. states and the District of Columbia. The study was designed to investigate reasons underlying the higher rate of stroke mortality among Black participants compared to White participants and among residents of the Southeastern U.S. compared to other U.S. regions. By design, Black adults and residents of the deep south were oversampled. Between 2003 and 2007 (baseline visit) participants completed a computer-assisted telephone interview to collect demographic information and medication adherence, and an in-home visit for blood pressure measurements and collection of blood and urine samples. Following the baseline visit, participants have been contacted by phone at six-month intervals to obtain information on incident stroke or secondary outcomes. Additionally, samples and data were collected on about 50% of the original cohort during a second study visit an average of 10 years after the baseline visit. Genotyping was performed as part of an ancillary study on 10,788 (84% Black) participants using Illumina MEGA arrays. Study Weblinks: REGARDS Study Study Design: Prospective Longitudinal Cohort Study Type: GWAS dbGaP estimated ancestry using GRAF-pop Total number of consented subjects: 10551 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Reasons for Geographic and Racial Differences in Stroke Cardiorenal GWAS","short_name":"REGARDS_GWAS_HMB-IRB","commons":"BioData Catalyst","study_url":"","_subjects_count":10551,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs002752.v1.p1.c1":{"gen3_discovery":{"authz":"/programs/COVID19/projects/C3PO_GRU","tags":[{"name":"COVID 19","category":"Program"},{"name":"dbGaP","category":"Study Registration"},{"name":"Clinical Phenotype","category":"Data Type"}],"_unique_id":"phs002752.v1.p1.c1","study_id":"phs002752.v1.p1.c1","study_description":"The Clinical Trial of COVID-19 Convalescent Plasma in Outpatients (C3PO) is a multicenter, randomized, single blind, two-arm, placebo controlled Phase III trial with blinded outcome assessments to establish the safety and efficacy of single dose of convalescent plasma for preventing the progression from mild to severe COVID-19 illness. Study Design: Clinical Trial Study Type: Clinical Trial Total number of consented subjects: 511 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Clinical Trial of COVID-19 Convalescent Plasma in Outpatients (C3PO)","short_name":"C3PO_GRU","commons":"BioData Catalyst","study_url":"https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs002752.v1.p1","_subjects_count":511,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs002770.v1.p1.c1":{"gen3_discovery":{"authz":"/programs/COVID19/projects/MUSIC_GRU","tags":[{"name":"COVID 19","category":"Program"},{"name":"dbGaP","category":"Study Registration"}],"_unique_id":"phs002770.v1.p1.c1","study_id":"phs002770.v1.p1.c1","study_description":"This study is an observational cohort study that will use routinely-collected clinical and cardiac (EKG, echocardiogram, CMR, exercise testing) data to assess the association between MIS-C (multisystem inflammatory syndrome in children) and cardiac outcomes within the first year after hospital discharge. Research funding will be available for EKGs, echocardiograms and MRIs in protocol windows that are not ordered by primary caregivers. Our principal goal is to determine the spectrum and early time course of coronary artery involvement, LV systolic function, and arrhythmias or conduction system abnormalities, and, using these data, to define associated clinical and laboratory factors. We will include all eligible patients, including retrospective cases beginning January 1, 2020, with follow-up (in-person or telehealth) up to one year and annual medical history forms until up to 5 years have elapsed since illness onset. Because many patients will have been identified by retrospective review, we will obtain consent at different times in their illness course. For this reason, it may be hard to reach some patients and their families. Waiver of consent will be obtained after three attempts have been made to locate the patient and family without success, as well as for the rare child who dies before informed consent can be obtained. We will include a HIPAA-compliant cryptographic algorithm to create a sharable “hashed” identifier from patient information. If blood work for research purposes is added to usual clinically-indicated blood work during follow-up visits, this will be covered by other informed consent forms. Our primary outcomes are the largest proximal Left Anterior Descending Coronary Artery (LAD) or Right Coronary Artery (RCA) z score and lowest Left Ventricular Ejection Fraction (LVEF). Study Weblinks: COVID MUSIC Study Study Design: Prospective Longitudinal Cohort Study Type: Observational Total number of consented subjects: 1114 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"MUSIC: Long-TerM OUtcomes after the Multisystem Inflammatory Syndrome In Children","short_name":"MUSIC_GRU","commons":"BioData Catalyst","study_url":"https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs002770.v1.p1","_subjects_count":1114,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs002808.v1.p1.c1":{"gen3_discovery":{"authz":"/programs/topmed/projects/nuMoM2b_GRU-IRB","tags":[{"name":"TOPMed","category":"Program"},{"name":"Genotype","category":"Data Type"},{"name":"dbGaP","category":"Study Registration"}],"_unique_id":"phs002808.v1.p1.c1","study_id":"phs002808.v1.p1.c1","study_description":"Participants from study sites that recruited during the original study funded by NICHD of pregnant people, called nuMoM2b, participated in this study. The nuMoM2b-HHS1 was a prospective observational follow-up study of the nuMoM2b cohort consisting of interval contacts via phone or web every 6 months to about a year, and an in-person visit 2 to 7 years after the end of the nuMoM2b pregnancy including: Demographics Self-administered questionnaires Clinical measurements Lab results An in-home sleep breathing assessment for the subset of participants with at least one valid sleep breathing assessment during nuMoM2b Abstraction of medical records for pregnancies subsequent to nuMoM2b involving self-reported adverse pregnancy outcomes or multiple births Abstraction of medical records of selected cardiovascular risk-related events or procedures reported by participants. The study capitalized on the rich and unique data prospectively collected during nuMoM2b (biomarkers, uterine artery Doppler studies, fetal growth, psychosocial determinants, sleep, and blood pressure) and rigorous definitions of adverse pregnancy outcomes. These data are stored in the NICHD repository DASH (https://dash.nichd.nih.gov/study/226675). A total of 8,838 nuMoM2b participants were targeted for contact during nuMoM2b-HHS and 7,872 participants were reached, of whom 7,003 completed one or more interval contacts. Of these, 5,206 agreed to the visit, and 4,508 attended an in-person visit. Study Weblinks: nuMoM2b website Study Design: Prospective Longitudinal Cohort Study Type: Longitudinal Cohort dbGaP estimated ancestry using GRAF-pop Total number of consented subjects: 8872 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Nulliparous Pregnancy Outcomes Study: Monitoring Mothers-to-be Heart Health Study (nuMoM2b Heart Health Study)","short_name":"nuMoM2b_GRU-IRB","commons":"BioData Catalyst","study_url":"https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs002808.v1.p1","_subjects_count":8872,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs002907.v1.p1.c1":{"gen3_discovery":{"authz":"/programs/COVID19/projects/C4R_JHS_HMB-NPU-IRB","tags":[],"_unique_id":"phs002907.v1.p1.c1","study_id":"phs002907.v1.p1.c1","study_description":"Adverse effects of the coronavirus disease 2019 (COVID19) pandemic on US society, health, and economy are widespread. The Collaborative Cohort of Cohorts for COVID-19 Research (C4R) aims to advance our knowledge on the impact of the COVID-19 pandemic in the United States. C4R is a diverse national prospective study comprising 14 long-standing prospective cohort studies and over 49,000 participants with extensive pre-COVID-19 phenotype data. C4R links pre-pandemic data on clinical and subclinical diseases and their risk factors, including behavior, cognition, biomarkers, and social determinants of health, to information on severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and acute and post-acute COVID-related illness. Ascertainment of COVID-19 infection occurs via standardized questionnaires, adjudication of COVID-related hospitalizations and deaths, and SARS-CoV-2 serosurvey via dried blood spot cards. C4R is investigating the following research questions: 1) how pre-existing health conditions affect risk of severe or prolonged COVID-19 related illness; 2) how SARS-CoV-2 infection and COVID-19 illness affect long-term health; and 3) how the pandemic has affected health-related behaviors and non-COVID health outcomes. This resource will allow evaluation of risk and resilience factors for COVID-19 severity and long-term health effects. Study Weblinks: https://www.jacksonheartstudy.org/ Study Design: Collection Study Type: Cohort Total number of consented subjects: 3883 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Collaborative Cohort of Cohorts for COVID-19 Research (C4R): Jackson Heart Study (JHS)","short_name":"C4R_JHS_HMB-NPU-IRB","commons":"BioData Catalyst","study_url":"","_subjects_count":312,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs002907.v1.p1.c2":{"gen3_discovery":{"authz":"/programs/COVID19/projects/C4R_JHS_DS-FDO-NPU-IRB","tags":[],"_unique_id":"phs002907.v1.p1.c2","study_id":"phs002907.v1.p1.c2","study_description":"Adverse effects of the coronavirus disease 2019 (COVID19) pandemic on US society, health, and economy are widespread. The Collaborative Cohort of Cohorts for COVID-19 Research (C4R) aims to advance our knowledge on the impact of the COVID-19 pandemic in the United States. C4R is a diverse national prospective study comprising 14 long-standing prospective cohort studies and over 49,000 participants with extensive pre-COVID-19 phenotype data. C4R links pre-pandemic data on clinical and subclinical diseases and their risk factors, including behavior, cognition, biomarkers, and social determinants of health, to information on severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and acute and post-acute COVID-related illness. Ascertainment of COVID-19 infection occurs via standardized questionnaires, adjudication of COVID-related hospitalizations and deaths, and SARS-CoV-2 serosurvey via dried blood spot cards. C4R is investigating the following research questions: 1) how pre-existing health conditions affect risk of severe or prolonged COVID-19 related illness; 2) how SARS-CoV-2 infection and COVID-19 illness affect long-term health; and 3) how the pandemic has affected health-related behaviors and non-COVID health outcomes. This resource will allow evaluation of risk and resilience factors for COVID-19 severity and long-term health effects. Study Weblinks: https://www.jacksonheartstudy.org/ Study Design: Collection Study Type: Cohort Total number of consented subjects: 3883 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Collaborative Cohort of Cohorts for COVID-19 Research (C4R): Jackson Heart Study (JHS)","short_name":"C4R_JHS_DS-FDO-NPU-IRB","commons":"BioData Catalyst","study_url":"","_subjects_count":81,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs002907.v1.p1.c3":{"gen3_discovery":{"authz":"/programs/COVID19/projects/C4R_JHS_HMB-IRB","tags":[],"_unique_id":"phs002907.v1.p1.c3","study_id":"phs002907.v1.p1.c3","study_description":"Adverse effects of the coronavirus disease 2019 (COVID19) pandemic on US society, health, and economy are widespread. The Collaborative Cohort of Cohorts for COVID-19 Research (C4R) aims to advance our knowledge on the impact of the COVID-19 pandemic in the United States. C4R is a diverse national prospective study comprising 14 long-standing prospective cohort studies and over 49,000 participants with extensive pre-COVID-19 phenotype data. C4R links pre-pandemic data on clinical and subclinical diseases and their risk factors, including behavior, cognition, biomarkers, and social determinants of health, to information on severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and acute and post-acute COVID-related illness. Ascertainment of COVID-19 infection occurs via standardized questionnaires, adjudication of COVID-related hospitalizations and deaths, and SARS-CoV-2 serosurvey via dried blood spot cards. C4R is investigating the following research questions: 1) how pre-existing health conditions affect risk of severe or prolonged COVID-19 related illness; 2) how SARS-CoV-2 infection and COVID-19 illness affect long-term health; and 3) how the pandemic has affected health-related behaviors and non-COVID health outcomes. This resource will allow evaluation of risk and resilience factors for COVID-19 severity and long-term health effects. Study Weblinks: https://www.jacksonheartstudy.org/ Study Design: Collection Study Type: Cohort Total number of consented subjects: 3883 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Collaborative Cohort of Cohorts for COVID-19 Research (C4R): Jackson Heart Study (JHS)","short_name":"C4R_JHS_HMB-IRB","commons":"BioData Catalyst","study_url":"","_subjects_count":1076,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs002907.v1.p1.c4":{"gen3_discovery":{"authz":"/programs/COVID19/projects/C4R_JHS_DS-FDO-IRB","tags":[],"_unique_id":"phs002907.v1.p1.c4","study_id":"phs002907.v1.p1.c4","study_description":"Adverse effects of the coronavirus disease 2019 (COVID19) pandemic on US society, health, and economy are widespread. The Collaborative Cohort of Cohorts for COVID-19 Research (C4R) aims to advance our knowledge on the impact of the COVID-19 pandemic in the United States. C4R is a diverse national prospective study comprising 14 long-standing prospective cohort studies and over 49,000 participants with extensive pre-COVID-19 phenotype data. C4R links pre-pandemic data on clinical and subclinical diseases and their risk factors, including behavior, cognition, biomarkers, and social determinants of health, to information on severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and acute and post-acute COVID-related illness. Ascertainment of COVID-19 infection occurs via standardized questionnaires, adjudication of COVID-related hospitalizations and deaths, and SARS-CoV-2 serosurvey via dried blood spot cards. C4R is investigating the following research questions: 1) how pre-existing health conditions affect risk of severe or prolonged COVID-19 related illness; 2) how SARS-CoV-2 infection and COVID-19 illness affect long-term health; and 3) how the pandemic has affected health-related behaviors and non-COVID health outcomes. This resource will allow evaluation of risk and resilience factors for COVID-19 severity and long-term health effects. Study Weblinks: https://www.jacksonheartstudy.org/ Study Design: Collection Study Type: Cohort Total number of consented subjects: 3883 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Collaborative Cohort of Cohorts for COVID-19 Research (C4R): Jackson Heart Study (JHS)","short_name":"C4R_JHS_DS-FDO-IRB","commons":"BioData Catalyst","study_url":"","_subjects_count":233,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs002908.v1.p1.c1":{"gen3_discovery":{"authz":"/programs/COVID19/projects/C4R_HCHS_SOL_HMB-NPU","tags":[{"name":"COVID 19","category":"Program"},{"name":"dbGaP","category":"Study Registration"}],"_unique_id":"phs002908.v1.p1.c1","study_id":"phs002908.v1.p1.c1","study_description":"Adverse effects of the coronavirus disease 2019 (COVID19) pandemic on US society, health, and economy are widespread. The Collaborative Cohort of Cohorts for COVID-19 Research (C4R) aims to advance our knowledge on the impact of the COVID-19 pandemic in the United States. C4R is a diverse national prospective study comprising 14 long-standing prospective cohort studies and over 49,000 participants with extensive pre-COVID-19 phenotype data. C4R links pre-pandemic data on clinical and subclinical diseases and their risk factors, including behavior, cognition, biomarkers, and social determinants of health, to information on severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and acute and post-acute COVID-related illness. Ascertainment of COVID-19 infection occurs via standardized questionnaires, adjudication of COVID-related hospitalizations and deaths, and SARS-CoV-2 serosurvey via dried blood spot cards. C4R is investigating the following research questions: 1) how pre-existing health conditions affect risk of severe or prolonged COVID-19 related illness; 2) how SARS-CoV-2 infection and COVID-19 illness affect long-term health; and 3) how the pandemic has affected health-related behaviors and non-COVID health outcomes. This resource will allow evaluation of risk and resilience factors for COVID-19 severity and long-term health effects. Cohort DescriptionHispanic Community Health Study/Study of Latinos (HCHS/SOL) is an ongoing population-based prospective cohort study of 16,415 community dwelling Hispanic/Latino adults aged 18-74 years at baseline, recruited from four urban field centers with large populations of Hispanics/ Latinos (Bronx, NY; Chicago, IL; Miami, FL; and San Diego, CA). The primary goals of the HCHS/SOL are to describe: (1) the prevalence and incidence of cardiovascular, pulmonary, and other major chronic conditions (2) the risk and/or protective factors associated with these conditions; and (3) the relationships between the initial sociodemographic and health profiles and future health events in the target population. Data Being Submitted Wave 1 questionnaire data includes 397 variables for up to 9817 HCHS/SOL participants in C4R. Wave 2 questionnaire data includes 448 variables for up to 7536 HCHS/SOL participants in C4R. Derived data includes 43 variables for up to 11182 HCHS/SOL participants in C4R. Phenotype data includes 113 variables for up to 11182 HCHS/SOL participants in C4R. Study Weblinks: C4R HCHS/SOL Study Design: Prospective Longitudinal Cohort Study Type: Total number of consented subjects: 11182 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Collaborative Cohort of Cohorts for COVID-19 Research (C4R): Hispanic Community Health Study/Study of Latinos (HCHS/SOL)","short_name":"C4R_HCHS_SOL_HMB-NPU","commons":"BioData Catalyst","study_url":"https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs002908.v1.p1","_subjects_count":1814,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs002908.v1.p1.c2":{"gen3_discovery":{"authz":"/programs/COVID19/projects/C4R_HCHS_SOL_HMB","tags":[{"name":"COVID 19","category":"Program"},{"name":"dbGaP","category":"Study Registration"}],"_unique_id":"phs002908.v1.p1.c2","study_id":"phs002908.v1.p1.c2","study_description":"Adverse effects of the coronavirus disease 2019 (COVID19) pandemic on US society, health, and economy are widespread. The Collaborative Cohort of Cohorts for COVID-19 Research (C4R) aims to advance our knowledge on the impact of the COVID-19 pandemic in the United States. C4R is a diverse national prospective study comprising 14 long-standing prospective cohort studies and over 49,000 participants with extensive pre-COVID-19 phenotype data. C4R links pre-pandemic data on clinical and subclinical diseases and their risk factors, including behavior, cognition, biomarkers, and social determinants of health, to information on severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and acute and post-acute COVID-related illness. Ascertainment of COVID-19 infection occurs via standardized questionnaires, adjudication of COVID-related hospitalizations and deaths, and SARS-CoV-2 serosurvey via dried blood spot cards. C4R is investigating the following research questions: 1) how pre-existing health conditions affect risk of severe or prolonged COVID-19 related illness; 2) how SARS-CoV-2 infection and COVID-19 illness affect long-term health; and 3) how the pandemic has affected health-related behaviors and non-COVID health outcomes. This resource will allow evaluation of risk and resilience factors for COVID-19 severity and long-term health effects. Cohort DescriptionHispanic Community Health Study/Study of Latinos (HCHS/SOL) is an ongoing population-based prospective cohort study of 16,415 community dwelling Hispanic/Latino adults aged 18-74 years at baseline, recruited from four urban field centers with large populations of Hispanics/ Latinos (Bronx, NY; Chicago, IL; Miami, FL; and San Diego, CA). The primary goals of the HCHS/SOL are to describe: (1) the prevalence and incidence of cardiovascular, pulmonary, and other major chronic conditions (2) the risk and/or protective factors associated with these conditions; and (3) the relationships between the initial sociodemographic and health profiles and future health events in the target population. Data Being Submitted Wave 1 questionnaire data includes 397 variables for up to 9817 HCHS/SOL participants in C4R. Wave 2 questionnaire data includes 448 variables for up to 7536 HCHS/SOL participants in C4R. Derived data includes 43 variables for up to 11182 HCHS/SOL participants in C4R. Phenotype data includes 113 variables for up to 11182 HCHS/SOL participants in C4R. Study Weblinks: C4R HCHS/SOL Study Design: Prospective Longitudinal Cohort Study Type: Total number of consented subjects: 11182 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Collaborative Cohort of Cohorts for COVID-19 Research (C4R): Hispanic Community Health Study/Study of Latinos (HCHS/SOL)","short_name":"C4R_HCHS_SOL_HMB","commons":"BioData Catalyst","study_url":"https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs002908.v1.p1","_subjects_count":9368,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs002909.v1.p1.c1":{"gen3_discovery":{"authz":"/programs/COVID19/projects/C4R_SPIROMICS_GRU","tags":[{"name":"COVID 19","category":"Program"},{"name":"dbGaP","category":"Study Registration"}],"_unique_id":"phs002909.v1.p1.c1","study_id":"phs002909.v1.p1.c1","study_description":"Adverse effects of the coronavirus disease 2019 (COVID19) pandemic on US society, health, and economy are widespread. The Collaborative Cohort of Cohorts for COVID-19 Research (C4R) aims to advance our knowledge on the impact of the COVID-19 pandemic in the United States. C4R is a diverse national prospective study comprising 14 long-standing prospective cohort studies and over 49,000 participants with extensive pre-COVID-19 phenotype data. C4R links pre-pandemic data on clinical and subclinical diseases and their risk factors, including behavior, cognition, biomarkers, and social determinants of health, to information on severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and acute and post-acute COVID-related illness. Ascertainment of COVID-19 infection occurs via standardized questionnaires, adjudication of COVID-related hospitalizations and deaths, and SARS-CoV-2 serosurvey via dried blood spot cards. C4R is investigating the following research questions: 1) how pre-existing health conditions affect risk of severe or prolonged COVID-19 related illness; 2) how SARS-CoV-2 infection and COVID-19 illness affect long-term health; and 3) how the pandemic has affected health-related behaviors and non-COVID health outcomes. This resource will allow evaluation of risk and resilience factors for COVID-19 severity and long-term health effects. Cohort Description The Subpopulations and Intermediate Outcome Measures in COPD Study (SPIROMICS) is a multi-center, observational, longitudinal case-control study designed to guide future development of therapies for COPD. SPIROMICS has recruited 2,983 COPD cases and controls, 40-80 years old with 20+ pack-years of smoking at 12 US sites in 2010–2015. Study Weblinks: C4R SPIROMICS Study Design: Prospective Longitudinal Cohort Study Type: Longitudinal Cohort Total number of consented subjects: 1579 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Collaborative Cohort of Cohorts for COVID-19 Research (C4R): Subpopulations and Intermediate Outcome Measures in COPD Study (SPIROMICS)","short_name":"C4R_SPIROMICS_GRU","commons":"BioData Catalyst","study_url":"https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs002909.v1.p1","_subjects_count":1191,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs002909.v1.p1.c2":{"gen3_discovery":{"authz":"/programs/COVID19/projects/C4R_SPIROMICS_GRU-NPU","tags":[{"name":"COVID 19","category":"Program"},{"name":"dbGaP","category":"Study Registration"}],"_unique_id":"phs002909.v1.p1.c2","study_id":"phs002909.v1.p1.c2","study_description":"Adverse effects of the coronavirus disease 2019 (COVID19) pandemic on US society, health, and economy are widespread. The Collaborative Cohort of Cohorts for COVID-19 Research (C4R) aims to advance our knowledge on the impact of the COVID-19 pandemic in the United States. C4R is a diverse national prospective study comprising 14 long-standing prospective cohort studies and over 49,000 participants with extensive pre-COVID-19 phenotype data. C4R links pre-pandemic data on clinical and subclinical diseases and their risk factors, including behavior, cognition, biomarkers, and social determinants of health, to information on severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and acute and post-acute COVID-related illness. Ascertainment of COVID-19 infection occurs via standardized questionnaires, adjudication of COVID-related hospitalizations and deaths, and SARS-CoV-2 serosurvey via dried blood spot cards. C4R is investigating the following research questions: 1) how pre-existing health conditions affect risk of severe or prolonged COVID-19 related illness; 2) how SARS-CoV-2 infection and COVID-19 illness affect long-term health; and 3) how the pandemic has affected health-related behaviors and non-COVID health outcomes. This resource will allow evaluation of risk and resilience factors for COVID-19 severity and long-term health effects. Cohort Description The Subpopulations and Intermediate Outcome Measures in COPD Study (SPIROMICS) is a multi-center, observational, longitudinal case-control study designed to guide future development of therapies for COPD. SPIROMICS has recruited 2,983 COPD cases and controls, 40-80 years old with 20+ pack-years of smoking at 12 US sites in 2010–2015. Study Weblinks: C4R SPIROMICS Study Design: Prospective Longitudinal Cohort Study Type: Longitudinal Cohort Total number of consented subjects: 1579 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Collaborative Cohort of Cohorts for COVID-19 Research (C4R): Subpopulations and Intermediate Outcome Measures in COPD Study (SPIROMICS)","short_name":"C4R_SPIROMICS_GRU-NPU","commons":"BioData Catalyst","study_url":"https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs002909.v1.p1","_subjects_count":197,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs002909.v1.p1.c3":{"gen3_discovery":{"authz":"/programs/COVID19/projects/C4R_SPIROMICS_DS-COPD","tags":[{"name":"COVID 19","category":"Program"},{"name":"dbGaP","category":"Study Registration"}],"_unique_id":"phs002909.v1.p1.c3","study_id":"phs002909.v1.p1.c3","study_description":"Adverse effects of the coronavirus disease 2019 (COVID19) pandemic on US society, health, and economy are widespread. The Collaborative Cohort of Cohorts for COVID-19 Research (C4R) aims to advance our knowledge on the impact of the COVID-19 pandemic in the United States. C4R is a diverse national prospective study comprising 14 long-standing prospective cohort studies and over 49,000 participants with extensive pre-COVID-19 phenotype data. C4R links pre-pandemic data on clinical and subclinical diseases and their risk factors, including behavior, cognition, biomarkers, and social determinants of health, to information on severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and acute and post-acute COVID-related illness. Ascertainment of COVID-19 infection occurs via standardized questionnaires, adjudication of COVID-related hospitalizations and deaths, and SARS-CoV-2 serosurvey via dried blood spot cards. C4R is investigating the following research questions: 1) how pre-existing health conditions affect risk of severe or prolonged COVID-19 related illness; 2) how SARS-CoV-2 infection and COVID-19 illness affect long-term health; and 3) how the pandemic has affected health-related behaviors and non-COVID health outcomes. This resource will allow evaluation of risk and resilience factors for COVID-19 severity and long-term health effects. Cohort Description The Subpopulations and Intermediate Outcome Measures in COPD Study (SPIROMICS) is a multi-center, observational, longitudinal case-control study designed to guide future development of therapies for COPD. SPIROMICS has recruited 2,983 COPD cases and controls, 40-80 years old with 20+ pack-years of smoking at 12 US sites in 2010–2015. Study Weblinks: C4R SPIROMICS Study Design: Prospective Longitudinal Cohort Study Type: Longitudinal Cohort Total number of consented subjects: 1579 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Collaborative Cohort of Cohorts for COVID-19 Research (C4R): Subpopulations and Intermediate Outcome Measures in COPD Study (SPIROMICS)","short_name":"C4R_SPIROMICS_DS-COPD","commons":"BioData Catalyst","study_url":"https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs002909.v1.p1","_subjects_count":95,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs002909.v1.p1.c4":{"gen3_discovery":{"authz":"/programs/COVID19/projects/C4R_SPIROMICS_DS-COPD-NPU","tags":[{"name":"COVID 19","category":"Program"},{"name":"dbGaP","category":"Study Registration"}],"_unique_id":"phs002909.v1.p1.c4","study_id":"phs002909.v1.p1.c4","study_description":"Adverse effects of the coronavirus disease 2019 (COVID19) pandemic on US society, health, and economy are widespread. The Collaborative Cohort of Cohorts for COVID-19 Research (C4R) aims to advance our knowledge on the impact of the COVID-19 pandemic in the United States. C4R is a diverse national prospective study comprising 14 long-standing prospective cohort studies and over 49,000 participants with extensive pre-COVID-19 phenotype data. C4R links pre-pandemic data on clinical and subclinical diseases and their risk factors, including behavior, cognition, biomarkers, and social determinants of health, to information on severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and acute and post-acute COVID-related illness. Ascertainment of COVID-19 infection occurs via standardized questionnaires, adjudication of COVID-related hospitalizations and deaths, and SARS-CoV-2 serosurvey via dried blood spot cards. C4R is investigating the following research questions: 1) how pre-existing health conditions affect risk of severe or prolonged COVID-19 related illness; 2) how SARS-CoV-2 infection and COVID-19 illness affect long-term health; and 3) how the pandemic has affected health-related behaviors and non-COVID health outcomes. This resource will allow evaluation of risk and resilience factors for COVID-19 severity and long-term health effects. Cohort Description The Subpopulations and Intermediate Outcome Measures in COPD Study (SPIROMICS) is a multi-center, observational, longitudinal case-control study designed to guide future development of therapies for COPD. SPIROMICS has recruited 2,983 COPD cases and controls, 40-80 years old with 20+ pack-years of smoking at 12 US sites in 2010–2015. Study Weblinks: C4R SPIROMICS Study Design: Prospective Longitudinal Cohort Study Type: Longitudinal Cohort Total number of consented subjects: 1579 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Collaborative Cohort of Cohorts for COVID-19 Research (C4R): Subpopulations and Intermediate Outcome Measures in COPD Study (SPIROMICS)","short_name":"C4R_SPIROMICS_DS-COPD-NPU","commons":"BioData Catalyst","study_url":"https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs002909.v1.p1","_subjects_count":40,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs002909.v1.p1.c5":{"gen3_discovery":{"authz":"/programs/COVID19/projects/C4R_SPIROMICS_GRU-COL","tags":[{"name":"COVID 19","category":"Program"},{"name":"dbGaP","category":"Study Registration"}],"_unique_id":"phs002909.v1.p1.c5","study_id":"phs002909.v1.p1.c5","study_description":"Adverse effects of the coronavirus disease 2019 (COVID19) pandemic on US society, health, and economy are widespread. The Collaborative Cohort of Cohorts for COVID-19 Research (C4R) aims to advance our knowledge on the impact of the COVID-19 pandemic in the United States. C4R is a diverse national prospective study comprising 14 long-standing prospective cohort studies and over 49,000 participants with extensive pre-COVID-19 phenotype data. C4R links pre-pandemic data on clinical and subclinical diseases and their risk factors, including behavior, cognition, biomarkers, and social determinants of health, to information on severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and acute and post-acute COVID-related illness. Ascertainment of COVID-19 infection occurs via standardized questionnaires, adjudication of COVID-related hospitalizations and deaths, and SARS-CoV-2 serosurvey via dried blood spot cards. C4R is investigating the following research questions: 1) how pre-existing health conditions affect risk of severe or prolonged COVID-19 related illness; 2) how SARS-CoV-2 infection and COVID-19 illness affect long-term health; and 3) how the pandemic has affected health-related behaviors and non-COVID health outcomes. This resource will allow evaluation of risk and resilience factors for COVID-19 severity and long-term health effects. Cohort Description The Subpopulations and Intermediate Outcome Measures in COPD Study (SPIROMICS) is a multi-center, observational, longitudinal case-control study designed to guide future development of therapies for COPD. SPIROMICS has recruited 2,983 COPD cases and controls, 40-80 years old with 20+ pack-years of smoking at 12 US sites in 2010–2015. Study Weblinks: C4R SPIROMICS Study Design: Prospective Longitudinal Cohort Study Type: Longitudinal Cohort Total number of consented subjects: 1579 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Collaborative Cohort of Cohorts for COVID-19 Research (C4R): Subpopulations and Intermediate Outcome Measures in COPD Study (SPIROMICS)","short_name":"C4R_SPIROMICS_GRU-COL","commons":"BioData Catalyst","study_url":"https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs002909.v1.p1","_subjects_count":7,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs002909.v1.p1.c6":{"gen3_discovery":{"authz":"/programs/COVID19/projects/C4R_SPIROMICS_GRU-COL-NPU","tags":[{"name":"COVID 19","category":"Program"},{"name":"dbGaP","category":"Study Registration"}],"_unique_id":"phs002909.v1.p1.c6","study_id":"phs002909.v1.p1.c6","study_description":"Adverse effects of the coronavirus disease 2019 (COVID19) pandemic on US society, health, and economy are widespread. The Collaborative Cohort of Cohorts for COVID-19 Research (C4R) aims to advance our knowledge on the impact of the COVID-19 pandemic in the United States. C4R is a diverse national prospective study comprising 14 long-standing prospective cohort studies and over 49,000 participants with extensive pre-COVID-19 phenotype data. C4R links pre-pandemic data on clinical and subclinical diseases and their risk factors, including behavior, cognition, biomarkers, and social determinants of health, to information on severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and acute and post-acute COVID-related illness. Ascertainment of COVID-19 infection occurs via standardized questionnaires, adjudication of COVID-related hospitalizations and deaths, and SARS-CoV-2 serosurvey via dried blood spot cards. C4R is investigating the following research questions: 1) how pre-existing health conditions affect risk of severe or prolonged COVID-19 related illness; 2) how SARS-CoV-2 infection and COVID-19 illness affect long-term health; and 3) how the pandemic has affected health-related behaviors and non-COVID health outcomes. This resource will allow evaluation of risk and resilience factors for COVID-19 severity and long-term health effects. Cohort Description The Subpopulations and Intermediate Outcome Measures in COPD Study (SPIROMICS) is a multi-center, observational, longitudinal case-control study designed to guide future development of therapies for COPD. SPIROMICS has recruited 2,983 COPD cases and controls, 40-80 years old with 20+ pack-years of smoking at 12 US sites in 2010–2015. Study Weblinks: C4R SPIROMICS Study Design: Prospective Longitudinal Cohort Study Type: Longitudinal Cohort Total number of consented subjects: 1579 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Collaborative Cohort of Cohorts for COVID-19 Research (C4R): Subpopulations and Intermediate Outcome Measures in COPD Study (SPIROMICS)","short_name":"C4R_SPIROMICS_GRU-COL-NPU","commons":"BioData Catalyst","study_url":"https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs002909.v1.p1","_subjects_count":26,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs002909.v1.p1.c7":{"gen3_discovery":{"authz":"/programs/COVID19/projects/C4R_SPIROMICS_DS-COPD-COL","tags":[{"name":"COVID 19","category":"Program"},{"name":"dbGaP","category":"Study Registration"}],"_unique_id":"phs002909.v1.p1.c7","study_id":"phs002909.v1.p1.c7","study_description":"Adverse effects of the coronavirus disease 2019 (COVID19) pandemic on US society, health, and economy are widespread. The Collaborative Cohort of Cohorts for COVID-19 Research (C4R) aims to advance our knowledge on the impact of the COVID-19 pandemic in the United States. C4R is a diverse national prospective study comprising 14 long-standing prospective cohort studies and over 49,000 participants with extensive pre-COVID-19 phenotype data. C4R links pre-pandemic data on clinical and subclinical diseases and their risk factors, including behavior, cognition, biomarkers, and social determinants of health, to information on severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and acute and post-acute COVID-related illness. Ascertainment of COVID-19 infection occurs via standardized questionnaires, adjudication of COVID-related hospitalizations and deaths, and SARS-CoV-2 serosurvey via dried blood spot cards. C4R is investigating the following research questions: 1) how pre-existing health conditions affect risk of severe or prolonged COVID-19 related illness; 2) how SARS-CoV-2 infection and COVID-19 illness affect long-term health; and 3) how the pandemic has affected health-related behaviors and non-COVID health outcomes. This resource will allow evaluation of risk and resilience factors for COVID-19 severity and long-term health effects. Cohort Description The Subpopulations and Intermediate Outcome Measures in COPD Study (SPIROMICS) is a multi-center, observational, longitudinal case-control study designed to guide future development of therapies for COPD. SPIROMICS has recruited 2,983 COPD cases and controls, 40-80 years old with 20+ pack-years of smoking at 12 US sites in 2010–2015. Study Weblinks: C4R SPIROMICS Study Design: Prospective Longitudinal Cohort Study Type: Longitudinal Cohort Total number of consented subjects: 1579 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Collaborative Cohort of Cohorts for COVID-19 Research (C4R): Subpopulations and Intermediate Outcome Measures in COPD Study (SPIROMICS)","short_name":"C4R_SPIROMICS_DS-COPD-COL","commons":"BioData Catalyst","study_url":"https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs002909.v1.p1","_subjects_count":6,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs002909.v1.p1.c8":{"gen3_discovery":{"authz":"/programs/COVID19/projects/C4R_SPIROMICS_DS-COPD-COL-NPU","tags":[{"name":"COVID 19","category":"Program"},{"name":"dbGaP","category":"Study Registration"}],"_unique_id":"phs002909.v1.p1.c8","study_id":"phs002909.v1.p1.c8","study_description":"Adverse effects of the coronavirus disease 2019 (COVID19) pandemic on US society, health, and economy are widespread. The Collaborative Cohort of Cohorts for COVID-19 Research (C4R) aims to advance our knowledge on the impact of the COVID-19 pandemic in the United States. C4R is a diverse national prospective study comprising 14 long-standing prospective cohort studies and over 49,000 participants with extensive pre-COVID-19 phenotype data. C4R links pre-pandemic data on clinical and subclinical diseases and their risk factors, including behavior, cognition, biomarkers, and social determinants of health, to information on severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and acute and post-acute COVID-related illness. Ascertainment of COVID-19 infection occurs via standardized questionnaires, adjudication of COVID-related hospitalizations and deaths, and SARS-CoV-2 serosurvey via dried blood spot cards. C4R is investigating the following research questions: 1) how pre-existing health conditions affect risk of severe or prolonged COVID-19 related illness; 2) how SARS-CoV-2 infection and COVID-19 illness affect long-term health; and 3) how the pandemic has affected health-related behaviors and non-COVID health outcomes. This resource will allow evaluation of risk and resilience factors for COVID-19 severity and long-term health effects. Cohort Description The Subpopulations and Intermediate Outcome Measures in COPD Study (SPIROMICS) is a multi-center, observational, longitudinal case-control study designed to guide future development of therapies for COPD. SPIROMICS has recruited 2,983 COPD cases and controls, 40-80 years old with 20+ pack-years of smoking at 12 US sites in 2010–2015. Study Weblinks: C4R SPIROMICS Study Design: Prospective Longitudinal Cohort Study Type: Longitudinal Cohort Total number of consented subjects: 1579 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Collaborative Cohort of Cohorts for COVID-19 Research (C4R): Subpopulations and Intermediate Outcome Measures in COPD Study (SPIROMICS)","short_name":"C4R_SPIROMICS_DS-COPD-COL-NPU","commons":"BioData Catalyst","study_url":"https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs002909.v1.p1","_subjects_count":17,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs002910.v1.p1.c1":{"gen3_discovery":{"authz":"/programs/COVID19/projects/C4R_COPDGene_HMB","tags":[{"name":"COVID 19","category":"Program"},{"name":"dbGaP","category":"Study Registration"}],"_unique_id":"phs002910.v1.p1.c1","study_id":"phs002910.v1.p1.c1","study_description":"Adverse effects of the coronavirus disease 2019 (COVID19) pandemic on US society, health, and economy are widespread. The Collaborative Cohort of Cohorts for COVID-19 Research (C4R) aims to advance our knowledge on the impact of the COVID-19 pandemic in the United States. C4R is a diverse national prospective study comprising 14 long-standing prospective cohort studies and over 49,000 participants with extensive pre-COVID-19 phenotype data. C4R links pre-pandemic data on clinical and subclinical diseases and their risk factors, including behavior, cognition, biomarkers, and social determinants of health, to information on severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and acute and post-acute COVID-related illness. Ascertainment of COVID-19 infection occurs via standardized questionnaires, adjudication of COVID-related hospitalizations and deaths, and SARS-CoV-2 serosurvey via dried blood spot cards. C4R is investigating the following research questions: 1) how pre-existing health conditions affect risk of severe or prolonged COVID-19 related illness; 2) how SARS-CoV-2 infection and COVID-19 illness affect long-term health; and 3) how the pandemic has affected health-related behaviors and non-COVID health outcomes. This resource will allow evaluation of risk and resilience factors for COVID-19 severity and long-term health effects. Cohort Description The Genetic Epidemiology of COPD (COPDGene) study is a non-interventional, multicenter, longitudinal, case-control study at 21 US sites of smokers with a ≥10 pack-year history of smoking, with and without COPD, and healthy never smokers. The initial goal was to characterize disease-related phenotypes and explore associations with susceptibility genes. Data Being Submitted Wave 1 questionnaire data includes 397 variables for up to 3683 COPDGene participants in C4R. Wave 2 questionnaire data includes 447 variables for up to 2191 COPDGene participants in C4R. Dried Blood Spot/Serosurvey data includes 7 variables for up to 1692 COPDGene participants in C4R. Derived data includes 43 variables for up to 4082 COPDGene participants in C4R. Phenotype data includes 113 variables for up to 4082 COPDGene participants in C4R. Study Weblinks: C4R COPDGene Study Design: Prospective Longitudinal Cohort Study Type: Longitudinal Cohort Prospective Total number of consented subjects: 4191 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Collaborative Cohort of Cohorts for COVID-19 Research (C4R): Genetic Epidemiology of COPD Study (COPDGene)","short_name":"C4R_COPDGene_HMB","commons":"BioData Catalyst","study_url":"https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs002910.v1.p1","_subjects_count":4075,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs002910.v1.p1.c2":{"gen3_discovery":{"authz":"/programs/COVID19/projects/C4R_COPDGene_DS-CS","tags":[{"name":"COVID 19","category":"Program"},{"name":"dbGaP","category":"Study Registration"}],"_unique_id":"phs002910.v1.p1.c2","study_id":"phs002910.v1.p1.c2","study_description":"Adverse effects of the coronavirus disease 2019 (COVID19) pandemic on US society, health, and economy are widespread. The Collaborative Cohort of Cohorts for COVID-19 Research (C4R) aims to advance our knowledge on the impact of the COVID-19 pandemic in the United States. C4R is a diverse national prospective study comprising 14 long-standing prospective cohort studies and over 49,000 participants with extensive pre-COVID-19 phenotype data. C4R links pre-pandemic data on clinical and subclinical diseases and their risk factors, including behavior, cognition, biomarkers, and social determinants of health, to information on severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and acute and post-acute COVID-related illness. Ascertainment of COVID-19 infection occurs via standardized questionnaires, adjudication of COVID-related hospitalizations and deaths, and SARS-CoV-2 serosurvey via dried blood spot cards. C4R is investigating the following research questions: 1) how pre-existing health conditions affect risk of severe or prolonged COVID-19 related illness; 2) how SARS-CoV-2 infection and COVID-19 illness affect long-term health; and 3) how the pandemic has affected health-related behaviors and non-COVID health outcomes. This resource will allow evaluation of risk and resilience factors for COVID-19 severity and long-term health effects. Cohort Description The Genetic Epidemiology of COPD (COPDGene) study is a non-interventional, multicenter, longitudinal, case-control study at 21 US sites of smokers with a ≥10 pack-year history of smoking, with and without COPD, and healthy never smokers. The initial goal was to characterize disease-related phenotypes and explore associations with susceptibility genes. Data Being Submitted Wave 1 questionnaire data includes 397 variables for up to 3683 COPDGene participants in C4R. Wave 2 questionnaire data includes 447 variables for up to 2191 COPDGene participants in C4R. Dried Blood Spot/Serosurvey data includes 7 variables for up to 1692 COPDGene participants in C4R. Derived data includes 43 variables for up to 4082 COPDGene participants in C4R. Phenotype data includes 113 variables for up to 4082 COPDGene participants in C4R. Study Weblinks: C4R COPDGene Study Design: Prospective Longitudinal Cohort Study Type: Longitudinal Cohort Prospective Total number of consented subjects: 4191 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Collaborative Cohort of Cohorts for COVID-19 Research (C4R): Genetic Epidemiology of COPD Study (COPDGene)","short_name":"C4R_COPDGene_DS-CS","commons":"BioData Catalyst","study_url":"https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs002910.v1.p1","_subjects_count":116,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs002911.v1.p1.c1":{"gen3_discovery":{"authz":"/programs/COVID19/projects/C4R_FHS_HMB-IRB-MDS","tags":[{"name":"COVID 19","category":"Program"},{"name":"dbGaP","category":"Study Registration"}],"_unique_id":"phs002911.v1.p1.c1","study_id":"phs002911.v1.p1.c1","study_description":"Adverse effects of the coronavirus disease 2019 (COVID19) pandemic on US society, health, and economy are widespread. The Collaborative Cohort of Cohorts for COVID-19 Research (C4R) aims to advance our knowledge on the impact of the COVID-19 pandemic in the United States. C4R is a diverse national prospective study comprising 14 long-standing prospective cohort studies and over 49,000 participants with extensive pre-COVID-19 phenotype data. C4R links pre-pandemic data on clinical and subclinical diseases and their risk factors, including behavior, cognition, biomarkers, and social determinants of health, to information on severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and acute and post-acute COVID-related illness. Ascertainment of COVID-19 infection occurs via standardized questionnaires, adjudication of COVID-related hospitalizations and deaths, and SARS-CoV-2 serosurvey via dried blood spot cards. C4R is investigating the following research questions: 1) how pre-existing health conditions affect risk of severe or prolonged COVID-19 related illness; 2) how SARS-CoV-2 infection and COVID-19 illness affect long-term health; and 3) how the pandemic has affected health-related behaviors and non-COVID health outcomes. This resource will allow evaluation of risk and resilience factors for COVID-19 severity and long-term health effects. Cohort DescriptionIn 1948, the researchers recruited 5,209 men and women between the ages of 30 and 62 from the town of Framingham, Massachusetts, and began the first round of extensive physical examinations and lifestyle interviews that they would later analyze for common patterns related to CVD development. Since 1948, the subjects have returned to the study every two years for an examination consisting of a detailed medical history, physical examination, and laboratory tests, and in 1971, the study enrolled a second-generation cohort -- 5,124 of the original participants' adult children and their spouses -- to participate in similar examinations. The second examination of the Offspring cohort occurred eight years after the first examination, and subsequent examinations have occurred approximately every four years thereafter. In 1994, the need to establish a new study reflecting a more diverse community of Framingham was recognized, and the first Omni cohort of the Framingham Heart Study, consisting of 506 participants, was enrolled. In April 2002 4095 third generation of participants, the grandchildren of the original cohort, were added. In 2003, 103 spouses of the offspring Cohort (NOS), and a second group of 410 Omni participants were enrolled. Through 2019, the original cohort has completed a total of 32 exams, the Offspring cohort 9 exams, the OMNI1 cohort 4 exams, and GEN3, NOS and OMNI2 cohorts each have completed 3 exams. The FHS is a joint project of the National Heart, Lung and Blood Institute and Boston University.Data Being Submitted Wave 1 questionnaire data includes 3967 variables for up to 3112 FHS participants in C4R.Wave 2 questionnaire data includes 448 variables for up to 2337 FHS participants in C4R.Dried Blood Spot/Serosurvey data includes 7 variables for up to 2189 FHS participants in C4R.Derived data includes 43 variables for up to 3151 FHS participants in C4R.Phenotype data includes 113 variables for up to 3151 FHS participants in C4R. Study Weblinks: Collaborative Cohort of Cohorts for COVID-19 Research, (C4R) Framingham Heart Study (FHS) Study Design: Prospective Longitudinal Cohort Study Type: Longitudinal Cohort Total number of consented subjects: 7270 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Collaborative Cohort of Cohorts for COVID-19 Research (C4R): Framingham Heart Study (FHS)","short_name":"C4R_FHS_HMB-IRB-MDS","commons":"BioData Catalyst","study_url":"https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs002911.v1.p1","_subjects_count":3097,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs002911.v1.p1.c2":{"gen3_discovery":{"authz":"/programs/COVID19/projects/C4R_FHS_HMB-IRB-NPU-MDS","tags":[{"name":"COVID 19","category":"Program"},{"name":"dbGaP","category":"Study Registration"}],"_unique_id":"phs002911.v1.p1.c2","study_id":"phs002911.v1.p1.c2","study_description":"Adverse effects of the coronavirus disease 2019 (COVID19) pandemic on US society, health, and economy are widespread. The Collaborative Cohort of Cohorts for COVID-19 Research (C4R) aims to advance our knowledge on the impact of the COVID-19 pandemic in the United States. C4R is a diverse national prospective study comprising 14 long-standing prospective cohort studies and over 49,000 participants with extensive pre-COVID-19 phenotype data. C4R links pre-pandemic data on clinical and subclinical diseases and their risk factors, including behavior, cognition, biomarkers, and social determinants of health, to information on severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and acute and post-acute COVID-related illness. Ascertainment of COVID-19 infection occurs via standardized questionnaires, adjudication of COVID-related hospitalizations and deaths, and SARS-CoV-2 serosurvey via dried blood spot cards. C4R is investigating the following research questions: 1) how pre-existing health conditions affect risk of severe or prolonged COVID-19 related illness; 2) how SARS-CoV-2 infection and COVID-19 illness affect long-term health; and 3) how the pandemic has affected health-related behaviors and non-COVID health outcomes. This resource will allow evaluation of risk and resilience factors for COVID-19 severity and long-term health effects. Cohort DescriptionIn 1948, the researchers recruited 5,209 men and women between the ages of 30 and 62 from the town of Framingham, Massachusetts, and began the first round of extensive physical examinations and lifestyle interviews that they would later analyze for common patterns related to CVD development. Since 1948, the subjects have returned to the study every two years for an examination consisting of a detailed medical history, physical examination, and laboratory tests, and in 1971, the study enrolled a second-generation cohort -- 5,124 of the original participants' adult children and their spouses -- to participate in similar examinations. The second examination of the Offspring cohort occurred eight years after the first examination, and subsequent examinations have occurred approximately every four years thereafter. In 1994, the need to establish a new study reflecting a more diverse community of Framingham was recognized, and the first Omni cohort of the Framingham Heart Study, consisting of 506 participants, was enrolled. In April 2002 4095 third generation of participants, the grandchildren of the original cohort, were added. In 2003, 103 spouses of the offspring Cohort (NOS), and a second group of 410 Omni participants were enrolled. Through 2019, the original cohort has completed a total of 32 exams, the Offspring cohort 9 exams, the OMNI1 cohort 4 exams, and GEN3, NOS and OMNI2 cohorts each have completed 3 exams. The FHS is a joint project of the National Heart, Lung and Blood Institute and Boston University.Data Being Submitted Wave 1 questionnaire data includes 3967 variables for up to 3112 FHS participants in C4R.Wave 2 questionnaire data includes 448 variables for up to 2337 FHS participants in C4R.Dried Blood Spot/Serosurvey data includes 7 variables for up to 2189 FHS participants in C4R.Derived data includes 43 variables for up to 3151 FHS participants in C4R.Phenotype data includes 113 variables for up to 3151 FHS participants in C4R. Study Weblinks: Collaborative Cohort of Cohorts for COVID-19 Research, (C4R) Framingham Heart Study (FHS) Study Design: Prospective Longitudinal Cohort Study Type: Longitudinal Cohort Total number of consented subjects: 7270 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Collaborative Cohort of Cohorts for COVID-19 Research (C4R): Framingham Heart Study (FHS)","short_name":"C4R_FHS_HMB-IRB-NPU-MDS","commons":"BioData Catalyst","study_url":"https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs002911.v1.p1","_subjects_count":238,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs002913.v1.p1.c1":{"gen3_discovery":{"authz":"/programs/COVID19/projects/C4R_SARP_GRU-PUB-NPU","tags":[{"name":"COVID 19","category":"Program"},{"name":"dbGaP","category":"Study Registration"}],"_unique_id":"phs002913.v1.p1.c1","study_id":"phs002913.v1.p1.c1","study_description":"Adverse effects of the coronavirus disease 2019 (COVID19) pandemic on US society, health, and economy are widespread. The Collaborative Cohort of Cohorts for COVID-19 Research (C4R) aims to advance our knowledge on the impact of the COVID-19 pandemic in the United States. C4R is a diverse national prospective study comprising 14 long-standing prospective cohort studies and over 49,000 participants with extensive pre-COVID-19 phenotype data. C4R links pre-pandemic data on clinical and subclinical diseases and their risk factors, including behavior, cognition, biomarkers, and social determinants of health, to information on severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and acute and post-acute COVID-related illness. Ascertainment of COVID-19 infection occurs via standardized questionnaires, adjudication of COVID-related hospitalizations and deaths, and SARS-CoV-2 serosurvey via dried blood spot cards. C4R is investigating the following research questions: 1) how pre-existing health conditions affect risk of severe or prolonged COVID-19 related illness; 2) how SARS-CoV-2 infection and COVID-19 illness affect long-term health; and 3) how the pandemic has affected health-related behaviors and non-COVID health outcomes. This resource will allow evaluation of risk and resilience factors for COVID-19 severity and long-term health effects. Cohort Description The Severe Asthma Research Program (SARP) has been investigating the clinical, physiologic and molecular phenotypes of asthma since 2000. It is currently following ~400 deeply phenotyped asthma patients. Data Being Submitted Wave 1 questionnaire data includes 397 variables for up to 375 SARP participants in C4R.Wave 2 questionnaire data includes 448 variables for up to 289 SARP participants in C4R.Dried Blood Spot/Serosurvey data includes 7 variables for up to 290 SARP participants in C4R.Derived data includes 43 variables for up to 463 SARP participants in C4R.Phenotype data includes 113 variables for up to 463 SARP participants in C4R. Study Weblinks: C4R SARP Study Design: Prospective Longitudinal Cohort Study Type: Longitudinal Cohort Total number of consented subjects: 479 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Collaborative Cohort of Cohorts for COVID-19 Research (C4R): Severe Asthma Research Program (SARP)","short_name":"C4R_SARP_GRU-PUB-NPU","commons":"BioData Catalyst","study_url":"https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs002913.v1.p1","_subjects_count":23,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs002913.v1.p1.c2":{"gen3_discovery":{"authz":"/programs/COVID19/projects/C4R_SARP_GRU-PUB","tags":[{"name":"COVID 19","category":"Program"},{"name":"dbGaP","category":"Study Registration"}],"_unique_id":"phs002913.v1.p1.c2","study_id":"phs002913.v1.p1.c2","study_description":"Adverse effects of the coronavirus disease 2019 (COVID19) pandemic on US society, health, and economy are widespread. The Collaborative Cohort of Cohorts for COVID-19 Research (C4R) aims to advance our knowledge on the impact of the COVID-19 pandemic in the United States. C4R is a diverse national prospective study comprising 14 long-standing prospective cohort studies and over 49,000 participants with extensive pre-COVID-19 phenotype data. C4R links pre-pandemic data on clinical and subclinical diseases and their risk factors, including behavior, cognition, biomarkers, and social determinants of health, to information on severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and acute and post-acute COVID-related illness. Ascertainment of COVID-19 infection occurs via standardized questionnaires, adjudication of COVID-related hospitalizations and deaths, and SARS-CoV-2 serosurvey via dried blood spot cards. C4R is investigating the following research questions: 1) how pre-existing health conditions affect risk of severe or prolonged COVID-19 related illness; 2) how SARS-CoV-2 infection and COVID-19 illness affect long-term health; and 3) how the pandemic has affected health-related behaviors and non-COVID health outcomes. This resource will allow evaluation of risk and resilience factors for COVID-19 severity and long-term health effects. Cohort Description The Severe Asthma Research Program (SARP) has been investigating the clinical, physiologic and molecular phenotypes of asthma since 2000. It is currently following ~400 deeply phenotyped asthma patients. Data Being Submitted Wave 1 questionnaire data includes 397 variables for up to 375 SARP participants in C4R.Wave 2 questionnaire data includes 448 variables for up to 289 SARP participants in C4R.Dried Blood Spot/Serosurvey data includes 7 variables for up to 290 SARP participants in C4R.Derived data includes 43 variables for up to 463 SARP participants in C4R.Phenotype data includes 113 variables for up to 463 SARP participants in C4R. Study Weblinks: C4R SARP Study Design: Prospective Longitudinal Cohort Study Type: Longitudinal Cohort Total number of consented subjects: 479 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Collaborative Cohort of Cohorts for COVID-19 Research (C4R): Severe Asthma Research Program (SARP)","short_name":"C4R_SARP_GRU-PUB","commons":"BioData Catalyst","study_url":"https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs002913.v1.p1","_subjects_count":105,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs002913.v1.p1.c3":{"gen3_discovery":{"authz":"/programs/COVID19/projects/C4R_SARP_DS-AAI-PUB-NPU","tags":[{"name":"COVID 19","category":"Program"},{"name":"dbGaP","category":"Study Registration"}],"_unique_id":"phs002913.v1.p1.c3","study_id":"phs002913.v1.p1.c3","study_description":"Adverse effects of the coronavirus disease 2019 (COVID19) pandemic on US society, health, and economy are widespread. The Collaborative Cohort of Cohorts for COVID-19 Research (C4R) aims to advance our knowledge on the impact of the COVID-19 pandemic in the United States. C4R is a diverse national prospective study comprising 14 long-standing prospective cohort studies and over 49,000 participants with extensive pre-COVID-19 phenotype data. C4R links pre-pandemic data on clinical and subclinical diseases and their risk factors, including behavior, cognition, biomarkers, and social determinants of health, to information on severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and acute and post-acute COVID-related illness. Ascertainment of COVID-19 infection occurs via standardized questionnaires, adjudication of COVID-related hospitalizations and deaths, and SARS-CoV-2 serosurvey via dried blood spot cards. C4R is investigating the following research questions: 1) how pre-existing health conditions affect risk of severe or prolonged COVID-19 related illness; 2) how SARS-CoV-2 infection and COVID-19 illness affect long-term health; and 3) how the pandemic has affected health-related behaviors and non-COVID health outcomes. This resource will allow evaluation of risk and resilience factors for COVID-19 severity and long-term health effects. Cohort Description The Severe Asthma Research Program (SARP) has been investigating the clinical, physiologic and molecular phenotypes of asthma since 2000. It is currently following ~400 deeply phenotyped asthma patients. Data Being Submitted Wave 1 questionnaire data includes 397 variables for up to 375 SARP participants in C4R.Wave 2 questionnaire data includes 448 variables for up to 289 SARP participants in C4R.Dried Blood Spot/Serosurvey data includes 7 variables for up to 290 SARP participants in C4R.Derived data includes 43 variables for up to 463 SARP participants in C4R.Phenotype data includes 113 variables for up to 463 SARP participants in C4R. Study Weblinks: C4R SARP Study Design: Prospective Longitudinal Cohort Study Type: Longitudinal Cohort Total number of consented subjects: 479 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Collaborative Cohort of Cohorts for COVID-19 Research (C4R): Severe Asthma Research Program (SARP)","short_name":"C4R_SARP_DS-AAI-PUB-NPU","commons":"BioData Catalyst","study_url":"https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs002913.v1.p1","_subjects_count":26,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs002913.v1.p1.c4":{"gen3_discovery":{"authz":"/programs/COVID19/projects/C4R_SARP_DS-AAI-PUB","tags":[{"name":"COVID 19","category":"Program"},{"name":"dbGaP","category":"Study Registration"}],"_unique_id":"phs002913.v1.p1.c4","study_id":"phs002913.v1.p1.c4","study_description":"Adverse effects of the coronavirus disease 2019 (COVID19) pandemic on US society, health, and economy are widespread. The Collaborative Cohort of Cohorts for COVID-19 Research (C4R) aims to advance our knowledge on the impact of the COVID-19 pandemic in the United States. C4R is a diverse national prospective study comprising 14 long-standing prospective cohort studies and over 49,000 participants with extensive pre-COVID-19 phenotype data. C4R links pre-pandemic data on clinical and subclinical diseases and their risk factors, including behavior, cognition, biomarkers, and social determinants of health, to information on severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and acute and post-acute COVID-related illness. Ascertainment of COVID-19 infection occurs via standardized questionnaires, adjudication of COVID-related hospitalizations and deaths, and SARS-CoV-2 serosurvey via dried blood spot cards. C4R is investigating the following research questions: 1) how pre-existing health conditions affect risk of severe or prolonged COVID-19 related illness; 2) how SARS-CoV-2 infection and COVID-19 illness affect long-term health; and 3) how the pandemic has affected health-related behaviors and non-COVID health outcomes. This resource will allow evaluation of risk and resilience factors for COVID-19 severity and long-term health effects. Cohort Description The Severe Asthma Research Program (SARP) has been investigating the clinical, physiologic and molecular phenotypes of asthma since 2000. It is currently following ~400 deeply phenotyped asthma patients. Data Being Submitted Wave 1 questionnaire data includes 397 variables for up to 375 SARP participants in C4R.Wave 2 questionnaire data includes 448 variables for up to 289 SARP participants in C4R.Dried Blood Spot/Serosurvey data includes 7 variables for up to 290 SARP participants in C4R.Derived data includes 43 variables for up to 463 SARP participants in C4R.Phenotype data includes 113 variables for up to 463 SARP participants in C4R. Study Weblinks: C4R SARP Study Design: Prospective Longitudinal Cohort Study Type: Longitudinal Cohort Total number of consented subjects: 479 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Collaborative Cohort of Cohorts for COVID-19 Research (C4R): Severe Asthma Research Program (SARP)","short_name":"C4R_SARP_DS-AAI-PUB","commons":"BioData Catalyst","study_url":"https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs002913.v1.p1","_subjects_count":307,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs002919.v1.p1.c1":{"gen3_discovery":{"authz":"/programs/COVID19/projects/C4R_REGARDS_HMB-IRB","tags":[{"name":"COVID 19","category":"Program"},{"name":"dbGaP","category":"Study Registration"}],"_unique_id":"phs002919.v1.p1.c1","study_id":"phs002919.v1.p1.c1","study_description":"Adverse effects of the coronavirus disease 2019 (COVID19) pandemic on US society, health, and economy are widespread. The Collaborative Cohort of Cohorts for COVID-19 Research (C4R) aims to advance our knowledge on the impact of the COVID-19 pandemic in the United States. C4R is a diverse national prospective study comprising 14 long-standing prospective cohort studies and over 49,000 participants with extensive pre-COVID-19 phenotype data. C4R links pre-pandemic data on clinical and subclinical diseases and their risk factors, including behavior, cognition, biomarkers, and social determinants of health, to information on severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and acute and post-acute COVID-related illness. Ascertainment of COVID-19 infection occurs via standardized questionnaires, adjudication of COVID-related hospitalizations and deaths, and SARS-CoV-2 serosurvey via dried blood spot cards. C4R is investigating the following research questions: 1) how pre-existing health conditions affect risk of severe or prolonged COVID-19 related illness; 2) how SARS-CoV-2 infection and COVID-19 illness affect long-term health; and 3) how the pandemic has affected health-related behaviors and non-COVID health outcomes. This resource will allow evaluation of risk and resilience factors for COVID-19 severity and long-term health effects. Cohort DescriptionThe REasons for Geographic and Racial Differences in Stroke (REGARDS) cohort is one of the nation's largest, most comprehensive population-based cohorts, and it uses innovative home- and telephone-based data collection. REGARDS centrally recruited and initially examined 30,239 Black and White men and women aged ≥45 years in 2003-7 to understand why Southerners and Black Americans have a higher incidence of stroke and related diseases that affect brain health.Data Being Submitted Wave 1 questionnaire data includes 397 variables for 8109 REGARDS participants in C4R. Wave 2 questionnaire data includes 448 variables for 6421 REGARDS participants in C4R. Dried Blood Spot/Serosurvey data includes 7 variables for 4058 REGARDS participants in C4R. Derived data includes 43 variables for 8606 REGARDS participants in C4R. Phenotype data includes 113 variables for 7880 REGARDS participants in C4R. Study Weblinks: 1) C4R: www.c4r-nih.org 2) REGARDS: https://www.uab.edu/soph/regardsstudy/ Study Design: Prospective Longitudinal Cohort Study Type: Longitudinal Cohort Total number of consented subjects: 8707 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Collaborative Cohort of Cohorts for COVID-19 Research (C4R): REasons for Geographic and Racial Differences in Stroke (REGARDS)","short_name":"C4R_REGARDS_HMB-IRB","commons":"BioData Catalyst","study_url":"https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs002919.v1.p1","_subjects_count":8707,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs002975.v1.p1.c1":{"gen3_discovery":{"authz":"/programs/COVID19/projects/C4R_PREPF_DS-PMD-IRB","tags":[{"name":"COVID 19","category":"Program"},{"name":"dbGaP","category":"Study Registration"}],"_unique_id":"phs002975.v1.p1.c1","study_id":"phs002975.v1.p1.c1","study_description":"Adverse effects of the coronavirus disease 2019 (COVID19) pandemic on US society, health, and economy are widespread. The Collaborative Cohort of Cohorts for COVID-19 Research (C4R) aims to advance our knowledge on the impact of the COVID-19 pandemic in the United States. C4R is a diverse national prospective study comprising 14 long-standing prospective cohort studies and over 49,000 participants with extensive pre-COVID-19 phenotype data. C4R links pre-pandemic data on clinical and subclinical diseases and their risk factors, including behavior, cognition, biomarkers, and social determinants of health, to information on severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and acute and post-acute COVID-related illness. Ascertainment of COVID-19 infection occurs via standardized questionnaires, adjudication of COVID-related hospitalizations and deaths, and SARS-CoV-2 serosurvey via dried blood spot cards. C4R is investigating the following research questions: 1) how pre-existing health conditions affect risk of severe or prolonged COVID-19 related illness; 2) how SARS-CoV-2 infection and COVID-19 illness affect long-term health; and 3) how the pandemic has affected health-related behaviors and non-COVID health outcomes. This resource will allow evaluation of risk and resilience factors for COVID-19 severity and long-term health effects. Cohort Description Prevent Pulmonary Fibrosis (PrePF) has been investigating the clinical, physiologic and genetic phenotypes of interstitial lung disease (ILD) by focusing on families with two or more cases of ILD and individuals with sporadic IPF. It has recruited over 1,200 families with two or more cases of pulmonary fibrosis. These families with pulmonary fibrosis include 2,837 individuals with probable or definite idiopathic interstitial pneumonia (IIP) and 2,404 unaffected FDRs. In addition, PrePF recruited over 10,000 individuals with sporadic idiopathic pulmonary fibrosis (IPF). Data Being Submitted Wave 1 questionnaire data includes 397 variables for up to 585 PrePF participants in C4R Wave 2 questionnaire data includes 448 variables for up to 370 PrePF participants in C4R Dried Blood Spot/Serosurvey data includes 7 variables for up to 206 PrePF participants in C4R Derived data includes 43 variables for up to 585 PrePF participants in C4R Phenotype data includes 113 variables for up to 585 PrePF participants in C4R Study Weblinks: C4R Study Design: Prospective Longitudinal Cohort Study Type: Total number of consented subjects: 628 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Collaborative Cohort of Cohorts for COVID-19 Research (C4R): Prevent Pulmonary Fibrosis (PrePF)","short_name":"C4R_PREPF_DS-PMD-IRB","commons":"BioData Catalyst","study_url":"https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs002975.v1.p1","_subjects_count":628,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs002980.v1.p1.c1":{"gen3_discovery":{"authz":"/programs/COVID19/projects/C4R_MASALA_HMB-IRB-COL","tags":[{"name":"COVID 19","category":"Program"},{"name":"dbGaP","category":"Study Registration"}],"_unique_id":"phs002980.v1.p1.c1","study_id":"phs002980.v1.p1.c1","study_description":"Adverse effects of the coronavirus disease 2019 (COVID19) pandemic on US society, health, and economy are widespread. The Collaborative Cohort of Cohorts for COVID-19 Research (C4R) aims to advance our knowledge on the impact of the COVID-19 pandemic in the United States. C4R is a diverse national prospective study comprising 14 long-standing prospective cohort studies and over 49,000 participants with extensive pre-COVID-19 phenotype data. C4R links pre-pandemic data on clinical and subclinical diseases and their risk factors, including behavior, cognition, biomarkers, and social determinants of health, to information on severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and acute and post-acute COVID-related illness. Ascertainment of COVID-19 infection occurs via standardized questionnaires, adjudication of COVID-related hospitalizations and deaths, and SARS-CoV-2 serosurvey via dried blood spot cards. C4R is investigating the following research questions: 1) how pre-existing health conditions affect risk of severe or prolonged COVID-19 related illness; 2) how SARS-CoV-2 infection and COVID-19 illness affect long-term health; and 3) how the pandemic has affected health-related behaviors and non-COVID health outcomes. This resource will allow evaluation of risk and resilience factors for COVID-19 severity and long-term health effects. Cohort Description The Mediators of Atherosclerosis in South Asians Living in America (MASALA) study is a prospective cohort of South Asians that aims to identify risk factors for heart disease in a large, growing Asian American subgroup. MASALA enrolled 906 South Asians in 2010-2013 and then added a new wave of 258 South Asian participants from 2017-2018, for a full cohort size of 1,164. Data Being Submitted Wave 1 questionnaire data includes 3967 variables for up to 431 MASALA participants in C4R. Wave 2 questionnaire data includes 448 variables for up to 313 MASALA participants in C4R. Dried Blood Spot/Serosurvey data includes 7 variables for up to 248 MASALA participants in C4R. Derived data includes 43 variables for up to 528 MASALA participants in C4R. Phenotype data includes 113 variables for up to 429 MASALA participants in C4R. Study Weblinks: C4R MASALA Study Design: Prospective Longitudinal Cohort Study Type: Cohort Observational Prospective Total number of consented subjects: 571 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Collaborative Cohort of Cohorts for COVID-19 Research (C4R): Mediators of Atherosclerosis in South Asians Living in America Study (MASALA)","short_name":"C4R_MASALA_HMB-IRB-COL","commons":"BioData Catalyst","study_url":"https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs002980.v1.p1","_subjects_count":571,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs002988.v1.p1.c1":{"gen3_discovery":{"authz":"/programs/COVID19/projects/C4R_ARIC_HMB-IRB","tags":[{"name":"COVID 19","category":"Program"},{"name":"dbGaP","category":"Study Registration"}],"_unique_id":"phs002988.v1.p1.c1","study_id":"phs002988.v1.p1.c1","study_description":"Adverse effects of the coronavirus disease 2019 (COVID19) pandemic on US society, health, and economy are widespread. The Collaborative Cohort of Cohorts for COVID-19 Research (C4R) aims to advance our knowledge on the impact of the COVID-19 pandemic in the United States. C4R is a diverse national prospective study comprising 14 long-standing prospective cohort studies and over 49,000 participants with extensive pre-COVID-19 phenotype data. C4R links pre-pandemic data on clinical and subclinical diseases and their risk factors, including behavior, cognition, biomarkers, and social determinants of health, to information on severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and acute and post-acute COVID-related illness. Ascertainment of COVID-19 infection occurs via standardized questionnaires, adjudication of COVID-related hospitalizations and deaths, and SARS-CoV-2 serosurvey via dried blood spot cards. C4R is investigating the following research questions: 1) how pre-existing health conditions affect risk of severe or prolonged COVID-19 related illness; 2) how SARS-CoV-2 infection and COVID-19 illness affect long-term health; and 3) how the pandemic has affected health-related behaviors and non-COVID health outcomes. This resource will allow evaluation of risk and resilience factors for COVID-19 severity and long-term health effects. Cohort Description The Atherosclerosis Risk in Communities (ARIC) study began in the mid-1980s with the initial aims being to describe the presence of subclinical atherosclerosis, the progression of atherosclerosis to clinical cardiovascular disease (CVD), and the association of novel risk factors with CVD. ARIC recruited its cohort of men and women aged 45-64 in 1987-89 from four communities (Forsyth County, NC; Jackson, MS; suburban Minneapolis, MN; and Washington County, MD). As of 2020, ARIC counts over 6,000 participants.Data Submitted Wave 1 questionnaire data includes 397 variables for up to 5326 ARIC participants in C4R. Wave 2 questionnaire data includes 448 variables for up to 4619 ARIC participants in C4R. Dried Blood Spot/Serosurvey data includes 7 variables for up to 2083 ARIC participants in C4R. Derived data includes 43 variables for up to 5449 ARIC participants in C4R. Phenotype data includes 113 variables for up to 5449 ARIC participants in C4R. Study Weblinks: C4R:https://c4r-nih.org/ ARIC:https://sites.cscc.unc.edu/aric/desc_pub Study Design: Prospective Longitudinal Cohort Study Type: Longitudinal Cohort Total number of consented subjects: 6523 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Collaborative Cohort of Cohorts for COVID-19 Research (C4R): Atherosclerosis Risk in Communities Study (ARIC)","short_name":"C4R_ARIC_HMB-IRB","commons":"BioData Catalyst","study_url":"https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs002988.v1.p1","_subjects_count":5254,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs002988.v1.p1.c2":{"gen3_discovery":{"authz":"/programs/COVID19/projects/C4R_ARIC_DS-CVD-IRB","tags":[{"name":"COVID 19","category":"Program"},{"name":"dbGaP","category":"Study Registration"}],"_unique_id":"phs002988.v1.p1.c2","study_id":"phs002988.v1.p1.c2","study_description":"Adverse effects of the coronavirus disease 2019 (COVID19) pandemic on US society, health, and economy are widespread. The Collaborative Cohort of Cohorts for COVID-19 Research (C4R) aims to advance our knowledge on the impact of the COVID-19 pandemic in the United States. C4R is a diverse national prospective study comprising 14 long-standing prospective cohort studies and over 49,000 participants with extensive pre-COVID-19 phenotype data. C4R links pre-pandemic data on clinical and subclinical diseases and their risk factors, including behavior, cognition, biomarkers, and social determinants of health, to information on severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and acute and post-acute COVID-related illness. Ascertainment of COVID-19 infection occurs via standardized questionnaires, adjudication of COVID-related hospitalizations and deaths, and SARS-CoV-2 serosurvey via dried blood spot cards. C4R is investigating the following research questions: 1) how pre-existing health conditions affect risk of severe or prolonged COVID-19 related illness; 2) how SARS-CoV-2 infection and COVID-19 illness affect long-term health; and 3) how the pandemic has affected health-related behaviors and non-COVID health outcomes. This resource will allow evaluation of risk and resilience factors for COVID-19 severity and long-term health effects. Cohort Description The Atherosclerosis Risk in Communities (ARIC) study began in the mid-1980s with the initial aims being to describe the presence of subclinical atherosclerosis, the progression of atherosclerosis to clinical cardiovascular disease (CVD), and the association of novel risk factors with CVD. ARIC recruited its cohort of men and women aged 45-64 in 1987-89 from four communities (Forsyth County, NC; Jackson, MS; suburban Minneapolis, MN; and Washington County, MD). As of 2020, ARIC counts over 6,000 participants.Data Submitted Wave 1 questionnaire data includes 397 variables for up to 5326 ARIC participants in C4R. Wave 2 questionnaire data includes 448 variables for up to 4619 ARIC participants in C4R. Dried Blood Spot/Serosurvey data includes 7 variables for up to 2083 ARIC participants in C4R. Derived data includes 43 variables for up to 5449 ARIC participants in C4R. Phenotype data includes 113 variables for up to 5449 ARIC participants in C4R. Study Weblinks: C4R:https://c4r-nih.org/ ARIC:https://sites.cscc.unc.edu/aric/desc_pub Study Design: Prospective Longitudinal Cohort Study Type: Longitudinal Cohort Total number of consented subjects: 6523 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Collaborative Cohort of Cohorts for COVID-19 Research (C4R): Atherosclerosis Risk in Communities Study (ARIC)","short_name":"C4R_ARIC_DS-CVD-IRB","commons":"BioData Catalyst","study_url":"https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs002988.v1.p1","_subjects_count":200,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs003017.v1.p1.c1":{"gen3_discovery":{"authz":"/programs/COVID19/projects/C4R_MESA_HMB","tags":[{"name":"COVID 19","category":"Program"},{"name":"dbGaP","category":"Study Registration"}],"_unique_id":"phs003017.v1.p1.c1","study_id":"phs003017.v1.p1.c1","study_description":"Adverse effects of the coronavirus disease 2019 (COVID19) pandemic on US society, health, and economy are widespread. The Collaborative Cohort of Cohorts for COVID-19 Research (C4R) aims to advance our knowledge on the impact of the COVID-19 pandemic in the United States. C4R is a diverse national prospective study comprising 14 long-standing prospective cohort studies and over 49,000 participants with extensive pre-COVID-19 phenotype data. C4R links pre-pandemic data on clinical and subclinical diseases and their risk factors, including behavior, cognition, biomarkers, and social determinants of health, to information on severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and acute and post-acute COVID-related illness. Ascertainment of COVID-19 infection occurs via standardized questionnaires, adjudication of COVID-related hospitalizations and deaths, and SARS-CoV-2 serosurvey via dried blood spot cards. C4R is investigating the following research questions: 1) how pre-existing health conditions affect risk of severe or prolonged COVID-19 related illness; 2) how SARS-CoV-2 infection and COVID-19 illness affect long-term health; and 3) how the pandemic has affected health-related behaviors and non-COVID health outcomes. This resource will allow evaluation of risk and resilience factors for COVID-19 severity and long-term health effects. Cohort Description The Multi-Ethnic Study of Atherosclerosis (MESA) is a study of the characteristics of subclinical cardiovascular disease (CVD) and the risk factors that predict progression to clinically overt CVD or progression of the subclinical disease. MESA researchers study a diverse, population-based sample of 6,814 asymptomatic men and women aged 45-84. Participants were recruited from six field centers across the United States: Wake Forest University, Columbia University, Johns Hopkins University, University of Minnesota, Northwestern University and University of California - Los Angeles. Participants of this study are limited to MESA Classic participants. MESA Family and MESA Air Pollution cohorts are excluded from C4R. Data Being Submitted Wave 1 questionnaire data includes 397 variables for up to 3119 MESA participants in C4R. Wave 2 questionnaire data includes 448 variables for up to 1933 MESA participants in C4R. Dried Blood Spot/Serosurvey data includes 7 variables for up to 1058 MESA participants in C4R. Derived data includes 43 variables for up to 3283 MESA participants in C4R. Phenotype data includes 113 variables for up to 3136 MESA participants in C4R. Study Weblinks: C4R MESA Study Design: Prospective Longitudinal Cohort Study Type: Longitudinal Cohort Total number of consented subjects: 3337 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Collaborative Cohort of Cohorts for COVID-19 Research (C4R): Multi-Ethnic Study of Atherosclerosis (MESA)","short_name":"C4R_MESA_HMB","commons":"BioData Catalyst","study_url":"https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs003017.v1.p1","_subjects_count":3043,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs003017.v1.p1.c2":{"gen3_discovery":{"authz":"/programs/COVID19/projects/C4R_MESA_HMB-NPU","tags":[{"name":"COVID 19","category":"Program"},{"name":"dbGaP","category":"Study Registration"}],"_unique_id":"phs003017.v1.p1.c2","study_id":"phs003017.v1.p1.c2","study_description":"Adverse effects of the coronavirus disease 2019 (COVID19) pandemic on US society, health, and economy are widespread. The Collaborative Cohort of Cohorts for COVID-19 Research (C4R) aims to advance our knowledge on the impact of the COVID-19 pandemic in the United States. C4R is a diverse national prospective study comprising 14 long-standing prospective cohort studies and over 49,000 participants with extensive pre-COVID-19 phenotype data. C4R links pre-pandemic data on clinical and subclinical diseases and their risk factors, including behavior, cognition, biomarkers, and social determinants of health, to information on severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and acute and post-acute COVID-related illness. Ascertainment of COVID-19 infection occurs via standardized questionnaires, adjudication of COVID-related hospitalizations and deaths, and SARS-CoV-2 serosurvey via dried blood spot cards. C4R is investigating the following research questions: 1) how pre-existing health conditions affect risk of severe or prolonged COVID-19 related illness; 2) how SARS-CoV-2 infection and COVID-19 illness affect long-term health; and 3) how the pandemic has affected health-related behaviors and non-COVID health outcomes. This resource will allow evaluation of risk and resilience factors for COVID-19 severity and long-term health effects. Cohort Description The Multi-Ethnic Study of Atherosclerosis (MESA) is a study of the characteristics of subclinical cardiovascular disease (CVD) and the risk factors that predict progression to clinically overt CVD or progression of the subclinical disease. MESA researchers study a diverse, population-based sample of 6,814 asymptomatic men and women aged 45-84. Participants were recruited from six field centers across the United States: Wake Forest University, Columbia University, Johns Hopkins University, University of Minnesota, Northwestern University and University of California - Los Angeles. Participants of this study are limited to MESA Classic participants. MESA Family and MESA Air Pollution cohorts are excluded from C4R. Data Being Submitted Wave 1 questionnaire data includes 397 variables for up to 3119 MESA participants in C4R. Wave 2 questionnaire data includes 448 variables for up to 1933 MESA participants in C4R. Dried Blood Spot/Serosurvey data includes 7 variables for up to 1058 MESA participants in C4R. Derived data includes 43 variables for up to 3283 MESA participants in C4R. Phenotype data includes 113 variables for up to 3136 MESA participants in C4R. Study Weblinks: C4R MESA Study Design: Prospective Longitudinal Cohort Study Type: Longitudinal Cohort Total number of consented subjects: 3337 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Collaborative Cohort of Cohorts for COVID-19 Research (C4R): Multi-Ethnic Study of Atherosclerosis (MESA)","short_name":"C4R_MESA_HMB-NPU","commons":"BioData Catalyst","study_url":"https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs003017.v1.p1","_subjects_count":294,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs003028.v1.p1.c1":{"gen3_discovery":{"authz":"/programs/COVID19/projects/C4R_NOMAS_GRU","tags":[{"name":"COVID 19","category":"Program"},{"name":"dbGaP","category":"Study Registration"}],"_unique_id":"phs003028.v1.p1.c1","study_id":"phs003028.v1.p1.c1","study_description":"Adverse effects of the coronavirus disease 2019 (COVID19) pandemic on US society, health, and economy are widespread. The Collaborative Cohort of Cohorts for COVID-19 Research (C4R) aims to advance our knowledge on the impact of the COVID-19 pandemic in the United States. C4R is a diverse national prospective study comprising 14 long-standing prospective cohort studies and over 49,000 participants with extensive pre-COVID-19 phenotype data. C4R links pre-pandemic data on clinical and subclinical diseases and their risk factors, including behavior, cognition, biomarkers, and social determinants of health, to information on severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and acute and post-acute COVID-related illness. Ascertainment of COVID-19 infection occurs via standardized questionnaires, adjudication of COVID-related hospitalizations and deaths, and SARS-CoV-2 serosurvey via dried blood spot cards. C4R is investigating the following research questions: 1) how pre-existing health conditions affect risk of severe or prolonged COVID-19 related illness; 2) how SARS-CoV-2 infection and COVID-19 illness affect long-term health; and 3) how the pandemic has affected health-related behaviors and non-COVID health outcomes. This resource will allow evaluation of risk and resilience factors for COVID-19 severity and long-term health effects. Cohort Description The Northern Manhattan Study (NOMAS) is a study of the population of Washington Heights in Northern Manhattan. The ongoing study, which began in 1990, has enrolled over 4,400 people, some of whom have suffered a stroke or related neurological syndromes. As the cohort aged, the specific aims grew to include not only vascular determinants of stroke but also cognitive decline, mild cognitive impairment (MCI) and dementia. The overall goal of NOMAS is to investigate stroke risk factors in different race-ethnic groups. NOMAS is also committed to developing better stroke prevention programs to improve the health of the community. The Hispanic population in Northern Manhattan is largely Dominican, along with Puerto Rican, Cuban, and Central and South American components.Data Being Submitted Wave 1 questionnaire data includes 397 variables for up to 887 NOMAS participants in C4R Wave 2 questionnaire data includes 448 variables for up to 815 NOMAS participants in C4R Derived data includes 43 variables for up to 995 NOMAS participants in C4R Phenotype data includes 113 variables for up to 995 NOMAS participants in C4R Study Weblinks: C4R NOMAS Study Design: Prospective Longitudinal Cohort Study Type: Total number of consented subjects: 995 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Collaborative Cohort of Cohorts for COVID-19 Research (C4R): Northern Manhattan Study (NOMAS)","short_name":"C4R_NOMAS_GRU","commons":"BioData Catalyst","study_url":"https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs003028.v1.p1","_subjects_count":999,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs003045.v1.p1.c1":{"gen3_discovery":{"authz":"/programs/COVID19/projects/C4R_CARDIA_HMB","tags":[],"_unique_id":"phs003045.v1.p1.c1","study_id":"phs003045.v1.p1.c1","study_description":"Adverse effects of the coronavirus disease 2019 (COVID19) pandemic on US society, health, and economy are widespread. The Collaborative Cohort of Cohorts for COVID-19 Research (C4R) aims to advance our knowledge on the impact of the COVID-19 pandemic in the United States. C4R is a diverse national prospective study comprising 14 long-standing prospective cohort studies and over 49,000 participants with extensive pre-COVID-19 phenotype data. C4R links pre-pandemic data on clinical and subclinical diseases and their risk factors, including behavior, cognition, biomarkers, and social determinants of health, to information on severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and acute and post-acute COVID-related illness. Ascertainment of COVID-19 infection occurs via standardized questionnaires, adjudication of COVID-related hospitalizations and deaths, and SARS-CoV-2 serosurvey via dried blood spot cards. C4R is investigating the following research questions: 1) how pre-existing health conditions affect risk of severe or prolonged COVID-19 related illness; 2) how SARS-CoV-2 infection and COVID-19 illness affect long-term health; and 3) how the pandemic has affected health-related behaviors and non-COVID health outcomes. This resource will allow evaluation of risk and resilience factors for COVID-19 severity and long-term health effects. Cohort Description The Coronary Artery Risk Development in Young Adults (CARDIA) study is a study examining the development and determinants of clinical and subclinical cardiovascular disease and their risk factors. It began in 1985-6 with a group of 5115 black and white men and women aged 18-30 years. The participants were selected so that there would be approximately the same number of people in subgroups of race, gender, education (high school or less and more than high school), and age (18-24 and 25-30 years) in each of 4 centers: Birmingham, AL; Chicago, IL; Minneapolis, MN; and Oakland, CA. These same participants were asked to participate in follow-up examinations during 1987-1988 (Year 2), 1990-1991 (Year 5), 1992-1993 (Year 7), 1995-1996 (Year 10), 2000-2001 (Year 15), 2005-2006 (Year 20), 2010-2011 (Year 25), 2015-2016 (Year 30), and 2021-2022 (Year 35). Data Being Submitted Wave 1 questionnaire data includes 397 variables for up to 2434 CARDIA participants in C4RWave 2 questionnaire data includes 448 variables for up to 1901 CARDIA participants in C4RDried Blood Spot/Serosurvey data includes 7 variables for up to 1332 CARDIA participants in C4RDerived data includes 43 variables for up to 2723 CARDIA participants in C4RPhenotype data includes 113 variables for up to 2723 CARDIA participants in C4R Study Weblinks: C4R CARDIA Study Design: Prospective Longitudinal Cohort Study Type: Longitudinal Total number of consented subjects: 2374 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Collaborative Cohort of Cohorts for COVID-19 Research (C4R): Coronary Artery Risk Development in Young Adults Study (CARDIA)","short_name":"C4R_CARDIA_HMB","commons":"BioData Catalyst","study_url":"","_subjects_count":0,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs003045.v1.p1.c2":{"gen3_discovery":{"authz":"/programs/COVID19/projects/C4R_CARDIA_HMB-NPU","tags":[],"_unique_id":"phs003045.v1.p1.c2","study_id":"phs003045.v1.p1.c2","study_description":"Adverse effects of the coronavirus disease 2019 (COVID19) pandemic on US society, health, and economy are widespread. The Collaborative Cohort of Cohorts for COVID-19 Research (C4R) aims to advance our knowledge on the impact of the COVID-19 pandemic in the United States. C4R is a diverse national prospective study comprising 14 long-standing prospective cohort studies and over 49,000 participants with extensive pre-COVID-19 phenotype data. C4R links pre-pandemic data on clinical and subclinical diseases and their risk factors, including behavior, cognition, biomarkers, and social determinants of health, to information on severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and acute and post-acute COVID-related illness. Ascertainment of COVID-19 infection occurs via standardized questionnaires, adjudication of COVID-related hospitalizations and deaths, and SARS-CoV-2 serosurvey via dried blood spot cards. C4R is investigating the following research questions: 1) how pre-existing health conditions affect risk of severe or prolonged COVID-19 related illness; 2) how SARS-CoV-2 infection and COVID-19 illness affect long-term health; and 3) how the pandemic has affected health-related behaviors and non-COVID health outcomes. This resource will allow evaluation of risk and resilience factors for COVID-19 severity and long-term health effects. Cohort Description The Coronary Artery Risk Development in Young Adults (CARDIA) study is a study examining the development and determinants of clinical and subclinical cardiovascular disease and their risk factors. It began in 1985-6 with a group of 5115 black and white men and women aged 18-30 years. The participants were selected so that there would be approximately the same number of people in subgroups of race, gender, education (high school or less and more than high school), and age (18-24 and 25-30 years) in each of 4 centers: Birmingham, AL; Chicago, IL; Minneapolis, MN; and Oakland, CA. These same participants were asked to participate in follow-up examinations during 1987-1988 (Year 2), 1990-1991 (Year 5), 1992-1993 (Year 7), 1995-1996 (Year 10), 2000-2001 (Year 15), 2005-2006 (Year 20), 2010-2011 (Year 25), 2015-2016 (Year 30), and 2021-2022 (Year 35). Data Being Submitted Wave 1 questionnaire data includes 397 variables for up to 2434 CARDIA participants in C4RWave 2 questionnaire data includes 448 variables for up to 1901 CARDIA participants in C4RDried Blood Spot/Serosurvey data includes 7 variables for up to 1332 CARDIA participants in C4RDerived data includes 43 variables for up to 2723 CARDIA participants in C4RPhenotype data includes 113 variables for up to 2723 CARDIA participants in C4R Study Weblinks: C4R CARDIA Study Design: Prospective Longitudinal Cohort Study Type: Longitudinal Total number of consented subjects: 2374 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Collaborative Cohort of Cohorts for COVID-19 Research (C4R): Coronary Artery Risk Development in Young Adults Study (CARDIA)","short_name":"C4R_CARDIA_HMB-NPU","commons":"BioData Catalyst","study_url":"","_subjects_count":0,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs003045.v2.p2.c1":{"gen3_discovery":{"authz":"/programs/COVID19/projects/C4R_CARDIA_HMB-IRB","tags":[],"_unique_id":"phs003045.v2.p2.c1","study_id":"phs003045.v2.p2.c1","study_description":"Adverse effects of the coronavirus disease 2019 (COVID19) pandemic on US society, health, and economy are widespread. The Collaborative Cohort of Cohorts for COVID-19 Research (C4R) aims to advance our knowledge on the impact of the COVID-19 pandemic in the United States. C4R is a diverse national prospective study comprising 14 long-standing prospective cohort studies and over 49,000 participants with extensive pre-COVID-19 phenotype data. C4R links pre-pandemic data on clinical and subclinical diseases and their risk factors, including behavior, cognition, biomarkers, and social determinants of health, to information on severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and acute and post-acute COVID-related illness. Ascertainment of COVID-19 infection occurs via standardized questionnaires, adjudication of COVID-related hospitalizations and deaths, and SARS-CoV-2 serosurvey via dried blood spot cards. C4R is investigating the following research questions: 1) how pre-existing health conditions affect risk of severe or prolonged COVID-19 related illness; 2) how SARS-CoV-2 infection and COVID-19 illness affect long-term health; and 3) how the pandemic has affected health-related behaviors and non-COVID health outcomes. This resource will allow evaluation of risk and resilience factors for COVID-19 severity and long-term health effects. Cohort Description The Coronary Artery Risk Development in Young Adults (CARDIA) study is a study examining the development and determinants of clinical and subclinical cardiovascular disease and their risk factors. It began in 1985-6 with a group of 5115 black and white men and women aged 18-30 years. The participants were selected so that there would be approximately the same number of people in subgroups of race, gender, education (high school or less and more than high school), and age (18-24 and 25-30 years) in each of 4 centers: Birmingham, AL; Chicago, IL; Minneapolis, MN; and Oakland, CA. These same participants were asked to participate in follow-up examinations during 1987-1988 (Year 2), 1990-1991 (Year 5), 1992-1993 (Year 7), 1995-1996 (Year 10), 2000-2001 (Year 15), 2005-2006 (Year 20), 2010-2011 (Year 25), 2015-2016 (Year 30), and 2021-2022 (Year 35). Data Being Submitted Wave 1 questionnaire data includes 397 variables for up to 2434 CARDIA participants in C4RWave 2 questionnaire data includes 448 variables for up to 1901 CARDIA participants in C4RDried Blood Spot/Serosurvey data includes 7 variables for up to 1332 CARDIA participants in C4RDerived data includes 43 variables for up to 2723 CARDIA participants in C4RPhenotype data includes 113 variables for up to 2723 CARDIA participants in C4R Study Weblinks: C4R CARDIA Study Design: Prospective Longitudinal Cohort Study Type: Longitudinal Total number of consented subjects: 2714 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Collaborative Cohort of Cohorts for COVID-19 Research (C4R): Coronary Artery Risk Development in Young Adults Study (CARDIA)","short_name":"C4R_CARDIA_HMB-IRB","commons":"BioData Catalyst","study_url":"","_subjects_count":2533,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs003045.v2.p2.c2":{"gen3_discovery":{"authz":"/programs/COVID19/projects/C4R_CARDIA_HMB-IRB-NPU","tags":[],"_unique_id":"phs003045.v2.p2.c2","study_id":"phs003045.v2.p2.c2","study_description":"Adverse effects of the coronavirus disease 2019 (COVID19) pandemic on US society, health, and economy are widespread. The Collaborative Cohort of Cohorts for COVID-19 Research (C4R) aims to advance our knowledge on the impact of the COVID-19 pandemic in the United States. C4R is a diverse national prospective study comprising 14 long-standing prospective cohort studies and over 49,000 participants with extensive pre-COVID-19 phenotype data. C4R links pre-pandemic data on clinical and subclinical diseases and their risk factors, including behavior, cognition, biomarkers, and social determinants of health, to information on severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and acute and post-acute COVID-related illness. Ascertainment of COVID-19 infection occurs via standardized questionnaires, adjudication of COVID-related hospitalizations and deaths, and SARS-CoV-2 serosurvey via dried blood spot cards. C4R is investigating the following research questions: 1) how pre-existing health conditions affect risk of severe or prolonged COVID-19 related illness; 2) how SARS-CoV-2 infection and COVID-19 illness affect long-term health; and 3) how the pandemic has affected health-related behaviors and non-COVID health outcomes. This resource will allow evaluation of risk and resilience factors for COVID-19 severity and long-term health effects. Cohort Description The Coronary Artery Risk Development in Young Adults (CARDIA) study is a study examining the development and determinants of clinical and subclinical cardiovascular disease and their risk factors. It began in 1985-6 with a group of 5115 black and white men and women aged 18-30 years. The participants were selected so that there would be approximately the same number of people in subgroups of race, gender, education (high school or less and more than high school), and age (18-24 and 25-30 years) in each of 4 centers: Birmingham, AL; Chicago, IL; Minneapolis, MN; and Oakland, CA. These same participants were asked to participate in follow-up examinations during 1987-1988 (Year 2), 1990-1991 (Year 5), 1992-1993 (Year 7), 1995-1996 (Year 10), 2000-2001 (Year 15), 2005-2006 (Year 20), 2010-2011 (Year 25), 2015-2016 (Year 30), and 2021-2022 (Year 35). Data Being Submitted Wave 1 questionnaire data includes 397 variables for up to 2434 CARDIA participants in C4RWave 2 questionnaire data includes 448 variables for up to 1901 CARDIA participants in C4RDried Blood Spot/Serosurvey data includes 7 variables for up to 1332 CARDIA participants in C4RDerived data includes 43 variables for up to 2723 CARDIA participants in C4RPhenotype data includes 113 variables for up to 2723 CARDIA participants in C4R Study Weblinks: C4R CARDIA Study Design: Prospective Longitudinal Cohort Study Type: Longitudinal Total number of consented subjects: 2714 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Collaborative Cohort of Cohorts for COVID-19 Research (C4R): Coronary Artery Risk Development in Young Adults Study (CARDIA)","short_name":"C4R_CARDIA_HMB-IRB-NPU","commons":"BioData Catalyst","study_url":"","_subjects_count":181,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs003063.v1.p1.c1":{"gen3_discovery":{"authz":"/programs/COVID19/projects/ACTIV4C_GRU","tags":[{"name":"COVID 19","category":"Program"},{"name":"dbGaP","category":"Study Registration"}],"_unique_id":"phs003063.v1.p1.c1","study_id":"phs003063.v1.p1.c1","study_description":"This study is an adaptive, prospective, randomized trial designed to compare the effectiveness and safety of antithrombotic therapy with no antithrombotic therapy after hospitalization for 48 hours or longer for COVID-19. For Stage 1 of this study, participants will be randomized to either prophylactic anticoagulation or no anticoagulant therapy for 30 days, and then followed for an additional 60 days after the completion of treatment (total duration of follow-up, approximately 90 days). Biobanking of samples for future biomarker and mechanistic studies will be available for centers able to participate and collect samples from eligible participants. Samples will be collected at the time of enrollment and after the completion of 30 days of therapy. Study Weblinks: Clinical Trials Study Design: Interventional Study Type: Clinical Trial Double-Blind Interventional Placebo-Controlled Randomized Randomized Controlled Clinical Trial Total number of consented subjects: 1217 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"COVID-19: Post-Hospital Thromboprophylaxis A Multicenter, Adaptive, Prospective, Randomized Trial Evaluating the Efficacy and Safety of Antithrombotic Strategies in Patients with COVID-19 Following Hospital Discharge (ACTIV-4C)","short_name":"ACTIV4C_GRU","commons":"BioData Catalyst","study_url":"https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs003063.v1.p1","_subjects_count":1217,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs003212.v1.p1.c1":{"gen3_discovery":{"authz":"/programs/DIR/projects/Eculizumab_GRU","tags":[{"name":"dbGaP","category":"Study Registration"}],"_unique_id":"phs003212.v1.p1.c1","study_id":"phs003212.v1.p1.c1","study_description":"Platelet transfusion can be a life-saving procedure in preventing or treating serious bleeding in patients who have low and/or dysfunctional platelets. Heavily transfused patients frequently develop human leukocyte antigen (HLA) allo-immunization resulting in platelet transfusion refractoriness and a high risk for life-threatening thrombocytopenia. Data suggest complement activation leading to the destruction of platelets bound by HLA allo-antibodies may play a pathophysiologic role in platelet refractoriness. We conducted a pilot trial to investigate the use of eculizumab to treat platelet transfusion refractoriness in allo-immunized patients with severe thrombocytopenia. We hypothesized that when we treated patients having platelet refractoriness with eculizumab, platelet counts would increase to higher numbers after platelet transfusions, decreasing the risk of bleeding complications associated with having a low platelet count. The response of the treatment was assessed by the corrected platelet count increment (CCI) 10 - 60 min and 18 - 24 h post transfusion, and any requirement for subsequent platelet transfusions following eculizumab. Reference 1 (PMID: 32086819) contains the main results for this trial. Study Design: Clinical Trial Study Type: Clinical Trial Total number of consented subjects: 10 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"A Pilot Trial of Complement Inhibition Using Eculizumab to Overcome Platelet Transfusion Refractoriness in HLA Allo-Immunized Patients","short_name":"Eculizumab_GRU","commons":"BioData Catalyst","study_url":"https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs003212.v1.p1","_subjects_count":10,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs003231.v1.p1.c1":{"gen3_discovery":{"authz":"/programs/DIR/projects/ApoA-1_Atherosclerosis_in_Psoriasis_GRU","tags":[{"name":"dbGaP","category":"Study Registration"}],"_unique_id":"phs003231.v1.p1.c1","study_id":"phs003231.v1.p1.c1","study_description":"Apolipoprotein A-1 is a protein localized to high-density lipoprotein that functions to remove cholesterol from tissues for transport back to the liver. Psoriasis is a systemic inflammatory disease associated with poor high-density lipoprotein function and accelerated non-calcified burden by coronary computed tomographic angiography. In this study, 310 psoriasis patients from The Psoriasis, Atherosclerosis, and Cardiometabolic Disease Initiative (PACI) were studied at baseline to determine if levels of circulating apolipoprotein A-1 predict early onset coronary artery disease in inflammatory conditions. Of the 310 participants, 124 were followed for four years to determine if apolipoprotein A-1 predicts non-calcified coronary burden over time. The primary outcome of this study was non-calcified coronary burden by coronary computed tomography angiography. To assess non-calcified coronary burden, participants underwent coronary computed tomography angiography using the same scanner (320-detector row Aquilion ONE ViSION, Toshiba, Japan). For ApoA-1 quantification, fasting blood draw was performed the same day as the coronary computed tomography angiography. The 400MHz proton Vantera Clinical Analyzer was used to quantify Plasma apolipoprotein A-1. The study determined that low levels of apolipoprotein A-1 are associated with increased coronary artery burden and that this relationship persists over time. The data are available through dbGaP and the dataset includes all variables reported in the manuscript. Study Design: Prospective Longitudinal Cohort Study Type: Longitudinal Longitudinal Cohort Prospective Total number of consented subjects: 310 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"ApoA-1 and Atherosclerosis in Psoriasis","short_name":"ApoA-1_Atherosclerosis_in_Psoriasis_GRU","commons":"BioData Catalyst","study_url":"https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs003231.v1.p1","_subjects_count":310,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs003288.v1.p1.c1":{"gen3_discovery":{"authz":"/programs/BioLINCC/projects/BL_MESA_HMB","tags":[],"_unique_id":"phs003288.v1.p1.c1","study_id":"phs003288.v1.p1.c1","study_description":"The Multi-Ethnic Study of Atherosclerosis (MESA) is a study of the characteristics of subclinical cardiovascular disease (disease detected non-invasively before it has produced clinical signs and symptoms) and the risk factors that predict progression to clinically overt cardiovascular disease or progression of the subclinical disease. MESA researchers study a diverse, population-based sample of 6,814 asymptomatic men and women aged 45-84. Thirty-eight percent of the recruited participants are white, 28 percent African-American, 22 percent Hispanic, and 12 percent Asian, predominantly of Chinese descent. Data available for request include phenotypic data previously released on BioLINCC as well as raw images (E.g. Echocardiogram) and raw tracing data files (e.g. Electrocardiogram). These new data are intended to be made available to interested researchers via BioData Catalyst, will include participants irrespective of participation in genetics (i.e. the full MESA cohort), and may be merged with currently posted (to dbGaP) phenotype and molecular datasets (WGS, GWA, RNA Seq, Methylation, Metabolomics, and Proteomics). Study Weblinks: MESA BioLINCC Publications Study Design: Prospective Longitudinal Cohort Study Type: Family Longitudinal Total number of consented subjects: 6814 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Multi-Ethnic Study of Atherosclerosis (BioLINCC)","short_name":"BL_MESA_HMB","commons":"BioData Catalyst","study_url":"","_subjects_count":6043,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs003288.v1.p1.c2":{"gen3_discovery":{"authz":"/programs/BioLINCC/projects/BL_MESA_HMB-NPU","tags":[],"_unique_id":"phs003288.v1.p1.c2","study_id":"phs003288.v1.p1.c2","study_description":"The Multi-Ethnic Study of Atherosclerosis (MESA) is a study of the characteristics of subclinical cardiovascular disease (disease detected non-invasively before it has produced clinical signs and symptoms) and the risk factors that predict progression to clinically overt cardiovascular disease or progression of the subclinical disease. MESA researchers study a diverse, population-based sample of 6,814 asymptomatic men and women aged 45-84. Thirty-eight percent of the recruited participants are white, 28 percent African-American, 22 percent Hispanic, and 12 percent Asian, predominantly of Chinese descent. Data available for request include phenotypic data previously released on BioLINCC as well as raw images (E.g. Echocardiogram) and raw tracing data files (e.g. Electrocardiogram). These new data are intended to be made available to interested researchers via BioData Catalyst, will include participants irrespective of participation in genetics (i.e. the full MESA cohort), and may be merged with currently posted (to dbGaP) phenotype and molecular datasets (WGS, GWA, RNA Seq, Methylation, Metabolomics, and Proteomics). Study Weblinks: MESA BioLINCC Publications Study Design: Prospective Longitudinal Cohort Study Type: Family Longitudinal Total number of consented subjects: 6814 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Multi-Ethnic Study of Atherosclerosis (BioLINCC)","short_name":"BL_MESA_HMB-NPU","commons":"BioData Catalyst","study_url":"","_subjects_count":771,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs003419.v2.p1.c1":{"gen3_discovery":{"authz":"/programs/COVID19/projects/BLUE_CORAL_HMB","tags":[],"_unique_id":"phs003419.v2.p1.c1","study_id":"phs003419.v2.p1.c1","study_description":"Data Access NOTE: Please refer to the “Authorized Access” section below for information about how access to the data from this accession differs from many other dbGaP accessions.Available Data: Long Term Follow-up data has been added with version 2. Biospecimens: Access to Biospecimens is through the NHLBI Biologic Specimen and Data Repository Information Coordinating Center (BioLINCC). Biospecimens from PETAL BLUE CORAL include: Bronchial Lavage, Plasma, Tracheal Aspirate, Urine, Whole Blood Buffy Coat, DNA, Plasma, Serum, Urine, and Whole Blood. Please note that use of biospecimens is tiered for both non-genetic and genetic research.Objectives: To measure the incidence and changes over time in symptoms, disability, and financial status after COVID-19–related hospitalization.Background: For many individuals, the effects of COVID-19 persist after the acute phase and result in prolonged symptoms and disability. This has led to widespread efforts to characterize the epidemiologic characteristics of such post-COVID-19 sequelae. However, accurate data were limited, hindering the ability to counsel patients, caregivers, and policy makers and to plan relevant recovery-focused clinical research. Thus, the BLUE CORAL study was intended to address the knowledge gaps and provide critical data to help guide clinical care, public health, and scientific efforts.Participants: A total of 1376 COVID-19 patents were enrolled, with 825 (444 male, and 379 female) that completed at least one follow-up survey.A subset of the BLUE CORAL adult participants were enrolled in the extension study, FIRE CORAL. FIRE CORAL was a multicenter prospective cohort study of participants recovering from COVID-19 disease after discharge from the hospital. Design: BLUE CORAL was a prospective cohort study. Participants were enrolled between August 24, 2020, and July 20, 2021, with follow-up occurring through March 30, 2022. Posthospital surveys were administered by trained interviewers in English or Spanish to patients or their proxies at 1, 3, and 6 months after enrollment. Cardiopulmonary symptoms were assessed using the Airways Questionnaire 20, the Kansas City Cardiomyopathy Questionnaire, and the Seattle Angina Questionnaire. Fatigue was assessed using the Patient Health Questionnaire-9. Disability was assessed by self-report of limitations in activities of daily living (ADLs) or instrumental activities of daily living (IADLs). Financial problems were assessed using the World Health Organization Disability Assessment Schedule 2.0 question and questions regarding job changes, time off work, and insurance coverage developed with the Mi-COVID-19 study using qualitative interviews. Quality of life was measured using the European Quality of Life 5-dimension 5-level instrument.The primary outcomes were new or worsened cardiopulmonary symptoms, financial problems, functional impairments, perceived return to baseline health, and quality of life. Symptoms that were not present before hospitalization or specifically reported as increased in severity were counted as new or worsened. Conclusions: The findings of this cohort study of people discharged after COVID-19 hospitalization suggest that recovery in symptoms, functional status, and fatigue was limited at 6 months, and some participants reported new problems 6 months after hospital discharge. Study Weblinks: PETAL Network BioLINCC: Prevention and Early Treatment of Acute Lung Injury (PETAL) Network – Biology and Longitudinal Epidemiology of P Study Design: Prospective Longitudinal Cohort Study Type: Longitudinal Observational Total number of consented subjects: 1376 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"BLUE CORAL: Biology and Longitudinal Epidemiology of PETAL COVID-19 Observational Study","short_name":"BLUE_CORAL_HMB","commons":"BioData Catalyst","study_url":"","_subjects_count":1376,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs003461.v1.p1.c1":{"gen3_discovery":{"authz":null,"tags":null,"_unique_id":"phs003461.v1.p1.c1","study_id":"phs003461.v1.p1.c1","study_description":null,"full_name":null,"short_name":null,"commons":"BioData Catalyst","study_url":null,"_subjects_count":0,"__manifest":null,"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs003461.v2.p2.c1":{"gen3_discovery":{"authz":null,"tags":null,"_unique_id":"phs003461.v2.p2.c1","study_id":"phs003461.v2.p2.c1","study_description":null,"full_name":null,"short_name":null,"commons":"BioData Catalyst","study_url":null,"_subjects_count":0,"__manifest":null,"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs003461.v3.p3.c1":{"gen3_discovery":{"authz":"/programs/RECOVER/projects/RC_Pediatrics_GRU","tags":[],"_unique_id":"phs003461.v3.p3.c1","study_id":"phs003461.v3.p3.c1","study_description":"The NIH Researching COVID to Enhance Recovery (RECOVER) initiative comprises a set of three combined retrospective and prospective, longitudinal and observational meta-cohort studies with nested case-control studies designed to define and characterize the epidemiology, natural history, clinical spectrum, and underlying mechanisms of post-acute effects of SARS-CoV-2 infection (PASC or Post-COVID syndrome) in a diverse study population representative of the general COVID-19 population in the US. Enrolled patients, with and without known SARS-CoV-2 infection, will be observed for clinical signs and symptoms of PASC and will be assessed for risk and resiliency factors and potential mediating factors associated with the severity and progression of PASC. The objective of the RECOVER initiative is to enhance knowledge of recovery from SARS-CoV-2 infections in order to support development of novel diagnostic and therapeutic interventions. Overarching scientific objectives are as follows:Characterize the incidence and prevalence of sequelae of SARS-CoV-2 infection.Characterize the spectrum of clinical symptoms, subclinical organ dysfunction, natural history, and distinct phenotypes identified as sequelae of SARS-CoV-2 infection. Define the biological mechanisms underlying pathogenesis of the sequelae of SARS-CoV-2 infection. The RECOVER observational studies comprise three cohorts across the lifespan (adult, pediatric, and tissue pathology (autopsy)). The data collection and data analysis plans for each cohort have been harmonized to use common data elements where feasible. Brief descriptions of each cohort are provided in the following paragraphs: 1) NIH RECOVER: A Multi-site Observational Study of Post-Acute Sequelae of SARS-CoV-2 Infection in Adults (see phs003463)The RECOVER adult cohort study is a combined retrospective and prospective, longitudinal, observational meta-cohort of individuals who will enter the cohort with and without SARS-CoV-2 infection and at varying stages before and after infection. Individuals with and without SARS-CoV-2 infection, and with or without PASC symptoms, will be followed to identify risk factors and occurrence of PASC. This study will be conducted in the United States and subjects will be recruited through inpatient, outpatient, and community-based settings. Study data including age, demographics, social determinants of health, medical history, vaccination history, details of acute SARS-CoV-2 infection, overall health and physical function, and PASC symptom screen will be reported by subjects or collected from the electronic health record using a case report form at specified intervals. Biologic specimens will be collected at specified intervals, with some tests performed in local clinical laboratories and others performed by centralized research centers or banked in the Biospecimen Repository. Advanced clinical examinations and radiologic examinations will be performed at local study sites with cross-site standardization. 2) A Multi-Center Observational Study: The RECOVER Post Acute Sequelae of SARS-CoV-2 (PASC) Pediatric Cohort Study (this study)The RECOVER pediatric study is a combined retrospective and prospective, longitudinal, observational meta-cohort of individuals ages newborn-25 years who will enter the cohort with and without SARS-CoV-2 infection at varying stages before and after infection. Individuals with and without SARS-CoV-2 infection and with or without PASC symptoms will be followed to identify risk factors and occurrence of PASC. This study recruit participants inpatient, outpatient, and community-based settings in the United States. Study data including age, demographics, social determinants of health, medical history, vaccination history, details of acute SARS-CoV-2 infection, overall health and physical function, and PASC symptoms will be reported by participants or collected from the electronic health record using a case report form at specified intervals. Biologic specimens will be collected at specified intervals, with some tests performed in local clinical laboratories and others performed by centralized research centers or banked in the Biospecimen Repository. Advanced clinical and radiologic examinations will be performed at local study sites with cross-site standardization. 3) NIH RECOVER: A Multi-site Pathology Study of Post-Acute Sequelae of SARS-CoV-2 Infection The RECOVER tissue pathology study is a cross-sectional study designed to define and characterize the epidemiology, natural history, clinical spectrum, and underlying mechanisms of post-acute effects of SARS-CoV-2 infection in a diverse population representative of the general COVID-19 population in the US. The autopsy study will characterize the pathology of PASC in (i) non-hospitalized patients who die 30 days or later from symptom onset of COVID-19, and (ii) hospitalized patients who die 30 days or later after discharge from a hospitalization for COVID-19. The study will include decedents who had previously fully recovered from SARS-CoV-2 infection (i.e., >30 days from onset in non-hospitalized, or >30 days from discharge in hospitalized patients), and decedents who meet clinical criteria of PASC as defined by the recent World Health Organization publication (see Section 5.4 below). The autopsy study will also explore the pathology of acute SARS-CoV-2 infection in a smaller subset of patients who died 15-30 days from symptom onset. This protocol defines the common set of clinical data elements, autopsy procedures for tissue collection, core measures, pathology protocols, shared pathology tissues, data elements, and methodology. Each investigator site is expected to perform autopsies on the decedents to address the pathophysiology of the potential long-term effects of SARS-CoV-2 infection on human health. The Consortium analysis plan aims to address research questions by incorporating: 1) tissue obtained from autopsies performed at each Phase II participant's site; and 2) tissue available from other pathology investigators/autopsy sites within the Consortium. Study Weblinks: NIH RECOVER NIH RECOVER Release Notes Study Design: Prospective Longitudinal Cohort Study Type: Longitudinal Cohort Total number of consented subjects: 25155 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"NIH RECOVER-Pediatric: Understanding the Long-Term Impact of COVID on Children and Families","short_name":"RC_Pediatrics_GRU","commons":"BioData Catalyst","study_url":"","_subjects_count":25155,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs003463.v1.p1.c1":{"gen3_discovery":{"authz":"","tags":[],"_unique_id":"phs003463.v1.p1.c1","study_id":"phs003463.v1.p1.c1","study_description":"","full_name":"","short_name":"","commons":"BioData Catalyst","study_url":"","_subjects_count":0,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs003463.v2.p2.c1":{"gen3_discovery":{"authz":null,"tags":null,"_unique_id":"phs003463.v2.p2.c1","study_id":"phs003463.v2.p2.c1","study_description":null,"full_name":null,"short_name":null,"commons":"BioData Catalyst","study_url":null,"_subjects_count":0,"__manifest":null,"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs003463.v3.p2.c1":{"gen3_discovery":{"authz":"","tags":[],"_unique_id":"phs003463.v3.p2.c1","study_id":"phs003463.v3.p2.c1","study_description":"","full_name":"","short_name":"","commons":"BioData Catalyst","study_url":"","_subjects_count":0,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs003463.v4.p3.c1":{"gen3_discovery":{"authz":null,"tags":null,"_unique_id":"phs003463.v4.p3.c1","study_id":"phs003463.v4.p3.c1","study_description":null,"full_name":null,"short_name":null,"commons":"BioData Catalyst","study_url":null,"_subjects_count":0,"__manifest":null,"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs003463.v5.p3.c1":{"gen3_discovery":{"authz":null,"tags":null,"_unique_id":"phs003463.v5.p3.c1","study_id":"phs003463.v5.p3.c1","study_description":null,"full_name":null,"short_name":null,"commons":"BioData Catalyst","study_url":null,"_subjects_count":0,"__manifest":null,"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs003463.v5.p4.c1":{"gen3_discovery":{"authz":"/programs/RECOVER/projects/RC_Adult_GRU","tags":[],"_unique_id":"phs003463.v5.p4.c1","study_id":"phs003463.v5.p4.c1","study_description":"The NIH Researching COVID to Enhance Recovery (RECOVER) initiative comprises a set of three combined retrospective and prospective, longitudinal, observational meta-cohort studies with nested case-control studies designed to define and characterize the epidemiology, natural history, clinical spectrum, and underlying mechanisms of post-acute effects of SARS-CoV-2 infection (PASC or Post-COVID syndrome) in a diverse study population representative of the general COVID-19 population in the US. Enrolled patients with and without known SARS-CoV-2 infection will be observed for clinical signs and symptoms of PASC and will be assessed for risk and resiliency factors and potential mediating factors associated with the severity and progression of PASC. The objective of the RECOVER initiative is to enhance knowledge of recovery from SARS-CoV-2 infections in order to support development of novel diagnostic and therapeutic interventions. Overarching scientific objectives are as follows: Characterize the incidence and prevalence of sequelae of SARS-CoV-2 infection. Characterize the spectrum of clinical symptoms, subclinical organ dysfunction, natural history, and distinct phenotypes identified as sequelae of SARS-CoV-2 infection.Define the biological mechanisms underlying pathogenesis of the sequelae of SARS-CoV-2 infection. The RECOVER observational studies comprise three cohorts across the lifespan (adult, pediatric, and tissue pathology (autopsy)). The data collection and data analysis plans for each cohort have been harmonized to use common data elements where feasible. Brief descriptions of each cohort are provided in the following paragraphs:1) NIH RECOVER: A Multi-site Observational Study of Post-Acute Sequelae of SARS-CoV-2 Infection in Adults (this study)The RECOVER adult cohort study is a combined retrospective and prospective, longitudinal, observational meta-cohort of individuals who will enter the cohort with and without SARS-CoV-2 infection and at varying stages before and after infection. Individuals with and without SARS-CoV-2 infection and with or without PASC symptoms will be followed to identify risk factors and occurrence of PASC. This study will be conducted in the United States and subjects will be recruited through inpatient, outpatient, and community-based settings. Study data including age, demographics, social determinants of health, medical history, vaccination history, details of acute SARS-CoV-2 infection, overall health and physical function, and PASC symptom screen will be reported by subjects or collected from the electronic health record using a case report form at specified intervals. Biologic specimens will be collected at specified intervals, with some tests performed in local clinical laboratories and others performed by centralized research centers or banked in the Biospecimen Repository. Advanced clinical examinations and radiologic examinations will be performed at local study sites with cross-site standardization. A summary of information available by request in the RECOVER Adult Cohort (this study) can be reviewed via the \"Adult Cohort Dataset Release Notes\" and the \"REDCap Codebook for the Adult Cohort\" documents.2) The RECOVER Post Acute Sequelae of SARS-CoV-2 (PASC) Pediatric Cohort Study: A Multi-Center Observational Study (data not yet released)The RECOVER pediatric study is a combined retrospective and prospective, longitudinal, observational meta-cohort of individuals ages newborn-25 years who will enter the cohort with and without SARS-CoV-2 infection at varying stages before and after infection. Individuals with and without SARS-CoV-2 infection and with or without PASC symptoms will be followed to identify risk factors and occurrence of PASC. This study recruit participants inpatient, outpatient, and community-based settings in the United States. Study data including age, demographics, social determinants of health, medical history, vaccination history, details of acute SARS-CoV-2 infection, overall health and physical function, and PASC symptoms will be reported by participants or collected from the electronic health record using a case report form at specified intervals. Biologic specimens will be collected at specified intervals, with some tests performed in local clinical laboratories and others performed by centralized research centers or banked in the Biospecimen Repository. Advanced clinical and radiologic examinations will be performed at local study sites with cross-site standardization.3) NIH RECOVER: A Multi-site Pathology Study of Post-Acute Sequelae of SARS-CoV-2 Infection (data not yet released)The RECOVER tissue pathology study is a cross-sectional study designed to define and characterize the epidemiology, natural history, clinical spectrum, and underlying mechanisms of post-acute effects of SARS-CoV-2 infection in a diverse population representative of the general COVID-19 population in the US. The autopsy study will characterize the pathology of PASC in (i) non-hospitalized patients who die 30 days or later from symptom onset of COVID-19, and (ii) hospitalized patients who die 30 days or later after discharge from a hospitalization for COVID-19. The study will include decedents who had previously fully recovered from SARS-CoV-2 infection (i.e., >30 days from onset in non-hospitalized, or >30 days from discharge in hospitalized patients), and decedents who meet clinical criteria of PASC as defined by the recent World Health Organization publication (see Section 5.4 below). The autopsy study will also explore the pathology of acute SARS-CoV-2 infection in a smaller subset of patients who died 15-30 days from symptom onset. This protocol defines the common set of clinical data elements, autopsy procedures for tissue collection, core measures, pathology protocols, shared pathology tissues, data elements, and methodology. Each investigator site is expected to perform autopsies on the decedents to address the pathophysiology of the potential long-term effects of SARS-CoV-2 infection on human health. The Consortium analysis plan aims to address research questions by incorporating: 1) tissue obtained from autopsies performed at each Phase II participant's site; and 2) tissue available from other pathology investigators/autopsy sites within the Consortium. Study Weblinks: NIH RECOVER NIH RECOVER Release Notes Study Design: Prospective Longitudinal Cohort Study Type: Longitudinal Cohort Total number of consented subjects: 15156 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"NIH RECOVER: A Multi-Site Observational Study of Post-Acute Sequelae of SARS-CoV-2 Infection in Adults","short_name":"RC_Adult_GRU","commons":"BioData Catalyst","study_url":"","_subjects_count":2356,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs003470.v1.p1.c1":{"gen3_discovery":{"authz":"/programs/BioLINCC/projects/BMT_CTN-0601_GRU","tags":[{"name":"dbGaP","category":"Study Registration"}],"_unique_id":"phs003470.v1.p1.c1","study_id":"phs003470.v1.p1.c1","study_description":"ObjectivesThe primary objective is to determine event-free survival (EFS) at 1 year after unrelated donor (URD) hematopoietic stem cell transplantation (HCT) using bone marrow (BM) in patients with sickle cell disease (SCD).BackgroundSickle cell disease (SCD), also known as sickle cell anemia, is an inherited blood disease that can cause organ damage, stroke, and intense pain episodes. Children with sickle cell disease experience organ damage, impaired quality of life, and premature mortality. A blood stem cell transplant is a treatment option for someone with a severe form of the disease. Prior to undergoing a transplant, people typically receive a conditioning regimen of high doses of chemotherapy and other medications to prepare the body to accept the transplant. This type of conditioning regimen is known as a myeloablative conditioning regimen, but it can result in toxicities and sterility. A conditioning regimen that uses lower doses of chemotherapy and medications may be safer for transplant recipients. This type of regimen is known as reduced intensity conditioning (RIC) regimen. RIC has a more favorable toxicity profile but is associated with higher rates of graft rejection (GR), especially with graft sources such as umbilical cord blood This study evaluated the safety and effectiveness of blood stem cell transplants, using bone marrow from unrelated donors, in children with severe SCD who receive a RIC regimen prior to the transplant.SubjectsPatients 3.0-19.75 years old with symptomatic SCD AND one or more of the following complications: (1)-(i) a clinically significant neurologic event (stroke) or any neurologic defect lasting > 24 hours and accompanied by an infarct on cerebral magnetic resonance imaging (MRI); OR, (ii) patients who have a Transcranial Doppler (TCD) velocity that exceeds 200 cm/sec by the non-imaging technique (or TCD measurement of >185 cm/sec by the imaging technique) measured at a minimum of 2 separate occasions one month or more apart; OR, (2) Minimum of two episodes of acute chest syndrome within the preceding 2-year period defined as new pulmonary alveolar consolidation involving at least one complete lung segment (associated with acute symptoms including fever, chest pain, tachypnea, wheezing, rales, or cough that is not attributed to asthma or bronchiolitis) despite adequate supportive care measures; OR, (3) History of 3 or more severe pain events (defined as new onset of pain that lasts for at least 2 hours for which there is no other explanation) per year in the 2 years prior to enrollment despite adequate supportive care measures (if patients are receiving hydroxyurea and compliant with therapy, being symptomatic is an indication for transplantation; however, if patients decline hydroxyurea or non-compliant with this therapy, they would still remain eligible for study if pain criteria as described above are met). Lansky/Karnofsky performance score must be ≥ 40. Hemoglobin S must be ≤ 45%. Patients must have an unrelated adult bone marrow donor who is HLA-matched at 8 of 8 HLA-A, -B, -C and -DRB1 at high resolution using DNA-based typing. Patients with bridging fibrosis or cirrhosis of the liver, with uncontrolled bacterial, viral, or fungal infection in the past month, or seropositivity for HIV are excluded. Patients with HLA-matched family donors, or who have received prior HCT, and females who are pregnant or breast feeding are excluded. Thirty patients were enrolled on this study and of these, 29 patients met the criteria and proceeded to the study transplant.DesignParticipants attended a study visit prior to the transplant to undergo a blood collection, neurocognitive testing to measure learning and brain function, magnetic resonance angiogram (MRA) and magnetic resonance imaging (MRI) scans. Questionnaires to assess quality of life were also completed. All patients received erythrocyte transfusions before transplant. Twenty-two days (-22) before the transplant, participants began receiving a reduced intensity conditioning regimen of chemotherapy and medications. On days -21, -20, and -19 participants weighing 10 kg or more received 10 mg, 15 mg, and then 20 mg of Alemtuzumab intravenously (IV) followed by 30 mg/m2/day IV on days -8 through -4 of Fludarabine. Eight days (-8) before the transplant, participants were admitted to the hospital to continue the conditioning regimen which included 140 mg/m2 IV of Melphalan on day -3. Participants received the bone marrow transplant on day 0. Prophylaxis for GVHD consisted of a calcineurin inhibitor (tacrolimus or cyclosporine) administered from day -3 through day 100 after graft infusion, with subsequent taper through day 180; methotrexate 7.5 mg/m2 on days 1, 3, and 6; and methylprednisolone 1 mg/kg per day from days 7 through 28, with subsequent taper by 20% per week. One week after the transplant continuing until the WBC is normal, participants received granulocyte-colony-stimulating factor (G-CSF). After leaving the hospital, participants attended study visits weekly during weeks 1 to 8, at day 60, weekly during weeks 9 to 14, at Day 100, at month 6, and at years 1 and 2. At all study visits, a blood collection, medical history review, and physical exam occurred. In addition, at day 100, month 6, and years 1 and 2, questionnaires to assess quality of life were completed. At select visits the following procedures were conducted: lung function testing, heart function testing, MRA and MRI scans, and neurocognitive testing.The primary outcome was 1-year EFS. Death, disease recurrence or graft rejection by 1 year were considered events for this endpoint.ConclusionsThe trial met its prespecified 1-year EFS, and significantly improved HRQL was reported posttransplant. However, although the Reduced-intensity conditioning (RIC) provided successful engraftment in most patients, the regimen cannot be considered safe for widespread adoption without modification due to the regimen-related toxicity (RRT) and high rate of chronic GVHD, which was the predominant cause of mortality. Study Weblinks: BMT CTN Study Design: Clinical Trial Study Type: Clinical Trial Total number of consented subjects: 55 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Unrelated Donor Reduced Intensity Bone Marrow Transplant for Children with Severe Sickle Cell Disease (BMT CTN-0601-BioLINCC)","short_name":"BMT_CTN-0601_GRU","commons":"BioData Catalyst","study_url":"https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs003470.v1.p1","_subjects_count":55,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs003483.v1.p1.c1":{"gen3_discovery":{"authz":"/programs/BioLINCC/projects/BL_SPRINT_GRU","tags":[],"_unique_id":"phs003483.v1.p1.c1","study_id":"phs003483.v1.p1.c1","study_description":"Available DataThe available data include all elements of the previously released SPRINT Primary Outcome Paper (SPRINT-POP) data, the full SPRINT clinical data including the MRI and MIND data, and select ancillary study data (Ambulatory Blood Pressure Monitoring, APOL1, Acute Kidney Injury, ASK, Heart, FAST, PWV, Renal Resistance, Biomarkers, Plasma AD).ObjectiveThe Systolic Blood Pressure Trial (SPRINT) was conducted to test the hypothesis that treating systolic blood pressure to a target of less than 120 mm Hg, as compared to a target of less than 140 mm Hg, would reduce the incidence of cardiovascular disease.BackgroundHypertension is a highly prevalent condition among adults and is a leading risk factor for myocardial infarction and stroke. Further, isolated systolic hypertension is the most common form of hypertension in adults over 50 years of age. Observational studies have shown a monotonic increase in cardiovascular risk with systolic blood pressures above 115 mm Hg; however, general population clinical trials have only documented the benefits of lowering systolic blood pressure to a target of 150 mm Hg. A 2007 expert panel sponsored by the National Heart, Lung, and Blood Institute designated the hypothesis that lowering the systolic blood pressure goal to a level <120 mm Hg as the most important hypothesis to test in reducing hypertension related complications in those without diabetes.SubjectsA total of 9361 participants were enrolled, with 4,678 randomized to the intensive-treatment group and 4,683 randomized to the standard-treatment group.DesignSPRINT was a randomized, single blinded (outcome adjudicators were blinded to treatment assignment) treatment trial with participants randomized to a systolic blood-pressure target of either less than 140 mm Hg (the standard-treatment group) or less than 120 mm Hg (the intensive-treatment group). Following randomization, baseline hypertensive regimens were adjusted in accordance with study treatment algorithms established for each group. The study formulary included all major classes of antihypertensive agents. Investigators could prescribe other antihypertensive medications, but the use of drug classes with the strongest evidence for reduction in cardiovascular outcomes was encouraged. This included thiazide-type diuretics as the first-line agent, loop diuretics for participants with advanced chronic kidney disease, and beta-adrenergic blockers for participants with coronary artery disease. Medications for participants in the intensive-treatment group were adjusted on a monthly basis to target a systolic blood pressure of less than 120 mm Hg. Medications for participants in the standard-treatment group were adjusted to target a systolic blood pressure of 135 to 139 mm Hg, and the dose was reduced if systolic blood pressure was less than 130 mm Hg on a single visit or less than 135 mm Hg on two consecutive visits. Lifestyle modification was encouraged as part of the management strategy.Participants were seen monthly for the first 3 months and every 3 months thereafter. Demographic data were collected at baseline. Clinical and laboratory data were obtained at baseline and every 3 months thereafter. A structured interview was used in both groups every 3 months to obtain self-reported cardiovascular disease outcomes. Medical records and electrocardiograms were obtained for documentation of events. Incidences of hypotension, syncope, injurious falls, electrolyte abnormalities, and bradycardia that were evaluated in an emergency department were included in adverse event reporting. Occurrences of acute kidney injury or acute renal failure requiring hospitalization were also monitored. The primary outcome was a composite outcome of myocardial infarction, other acute coronary syndromes, stroke, heart failure, or death from cardiovascular causes.ConclusionsThe blood pressure intervention was stopped in August of 2015 (median follow-up of 3.26 years) after the cardiovascular outcome results exceeded the boundary for efficacy at two consecutive time points. Compared with a systolic blood pressure target of less than 140 mm Hg, an intensive systolic blood pressure target of 120 mm Hg resulted in lower rates of fatal and nonfatal major cardiovascular events and death from any cause. Significantly higher rates of some adverse events were observed in the intensive-treatment group. Study Weblinks: Systolic Blood Pressure Intervention Trial (SPRINT) Study BioLINCC study page Study Design: Clinical Trial Study Type: Clinical Trial Total number of consented subjects: 9361 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Systolic Blood Pressure Intervention Trial (SPRINT-BioLINCC)","short_name":"BL_SPRINT_GRU","commons":"BioData Catalyst","study_url":"","_subjects_count":9361,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs003493.v1.p1.c1":{"gen3_discovery":{"authz":"/programs/BioLINCC/projects/BL_STICH_GRU","tags":[],"_unique_id":"phs003493.v1.p1.c1","study_id":"phs003493.v1.p1.c1","study_description":"Data Access NOTE: Please refer to the “Authorized Access” section below for information about how access to the data from this accession differs from many other dbGaP accessions. ObjectiveTo compare medical therapy with coronary bypass surgery and/or surgical ventricular reconstruction for patients with congestive heart failure and coronary artery disease.BackgroundCoronary artery disease (CAD) is the most common cause of heart failure, which in turn is a major cause of death and disability globally. Evidence from previous clinical trials supports the use of coronary-artery bypass grafting (CABG) to relieve disabling symptoms of angina, particularly among high-risk subgroups with extensive CAD. However, the studies did not include patients with severe left ventricular dysfunction, and developments in medical therapy have since led to updated guidelines. In addition, the benefits of CABG in patients with ischemic cardiomyopathy had still not been clearly established at the time of this study. STICH sought to evaluate the role of CABG in the treatment of patients with CAD and left ventricular systolic dysfunction.Reduced left ventricular function may occur after myocardial infarction, often in conjunction with left ventricular remodeling, including left ventricular enlargement and changes in chamber geometry. Left ventricular remodeling is correlated with progression of heart failure and a poor prognosis. Therefore, a surgical approach to remodeling through left ventricular volume reduction could improve outcomes for patients with CAD and heart failure. Surgical ventricular reconstruction (SVR) has been shown to reduce the left ventricular volume, increase the ejection fraction, and improve ventricular function. There is also evidence that SVR performed with CABG may reduce the rate of hospitalization and improve ventricular function, as compared to CABG alone. As part of a second hypothesis, STICH additionally investigated whether SVR when added to CABG would improve outcomes in patients with heart failure and CAD.ParticipantsA total of 2,136 participants were enrolled in STICH. 1,212 were enrolled in the hypothesis 1 component of the trial, with 602 participants assigned to receive medical therapy alone, and 610 participants assigned to receive medical therapy plus CABG. 1,000 were enrolled in the hypothesis 2 component, with 499 participants assigned to receive medical therapy plus CABG, and 501 participants assigned to receive medical therapy plus CABG and SVR. 76 participants that were assigned to the CABG with medical therapy treatment were enrolled in both hypothesis components.DesignAfter initial determination of overall eligibility, participants were evaluated to determine which component of the STICH program was appropriate for them on the basis of suitable therapeutic options. All participants underwent cardiac imaging for assessment of left ventricular function and wall motion. Participants in the hypothesis 1 component were randomly assigned to receive either medical therapy alone or medical therapy plus CABG. Participants in the hypothesis 2 component were randomly assigned to receive either medical therapy plus CABG or medical therapy plus CABG and SVR.At baseline, demographic factors and clinical characteristics were assessed, including current medications and prior diagnostic and other cardiovascular procedures, and a physical examination was performed. Guideline-based recommendations for drug and device use were emphasized for all participants. All participants underwent follow-up evaluations at the time of discharge or at 30 days for participants still hospitalized, every 4 months for the first year, and every 6 months thereafter. The median length of follow-up was 56 months for hypothesis 1 and 48 months for hypothesis 2.For participants receiving CABG, arterial grafting for stenosis of the left anterior descending coronary artery was required for all participants without specific contraindications. The use of additional arterial conduits supplemented by vein grafts was recommended for revascularization of all major vessels with clinically significant stenoses. Concurrent mitral-valve surgery for regurgitation was performed at the discretion of the surgeon. For participants receiving SVR, the operation was most commonly performed during a single period of cardioplegic arrest after construction of bypass grafts. However, the procedure could also be performed with the heart beating in order to facilitate identification of the noncontractile zone of scarring. After an anterior left ventriculotomy was centered in the zone of anterior asynergy, a suture was placed in the interior of the ventricle to encircle the scar at the boundary between the akinetic and viable tissue. Visual inspection and palpation facilitated the judgment of whether a patch was needed to optimize the chamber size without deforming the left ventricle during closure of the ventriculotomy.The primary outcome for hypothesis 1 was the rate of death from any cause. The primary outcome for hypothesis two was a composite of death from any cause and hospitalization for cardiac causes.ConclusionsThere was no significant difference between medical therapy alone and medical therapy plus CABG for death from any cause, though participants that underwent CABG had lower rates of death from cardiovascular causes, death from any cause, or hospitalization for cardiovascular causes. Adding SVR to CABG reduced the left ventricular volume, as compared with CABG alone. However, this anatomical change was not associated with a greater improvement in symptoms or exercise tolerance, or with a reduction in the rate of death or hospitalization for cardiac causes. Study Weblinks: BioLINCC study page Study Design: Clinical Trial Study Type: Clinical Trial Total number of consented subjects: 2621 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Surgical Treatment for Ischemic Heart Failure (STICH-BioLINCC)","short_name":"BL_STICH_GRU","commons":"BioData Catalyst","study_url":"","_subjects_count":2621,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs003506.v1.p1.c1":{"gen3_discovery":{"authz":"/programs/BioLINCC/projects/BL_HFN_ATHENA_GRU","tags":[],"_unique_id":"phs003506.v1.p1.c1","study_id":"phs003506.v1.p1.c1","study_description":"ObjectiveTo assess whether high-dose spironolactone treatment for patients with acute heart failure lowers natriuretic peptide levels and improves outcomes better than usual care.BackgroundAcute heart failure (AHF) accounts for more than a million hospitalizations in the United States annually. The role of low-dose mineralocorticoid receptors antagonists (MRAs) therapy as a neurohormonal antagonist is well established for the treatment of chronic heart failure and reduced ejection fraction. However, the role of high-dose MRA therapy in AHF remained uncertain. A previous clinical trial suggested that the benefits of high-dose MRA therapy in AHF included lower natriuretic peptide levels, less congestion, better renal function, and less need for an intravenous diuretic. The use of intravenous loop diuretics can intensify secondary hyperaldosteronism among AHF patients, and hyperaldosteronism directly contributes to diuretic resistance in AHF. Elevated aldosterone levels in AHF are associated with an increased risk of cardiovascular mortality and HF readmission. Hospitalizations for heart failure are associated with increased risk of mortality and/or readmission.The HFN-ATHENA trial was conducted to determine if mineralocorticoid receptor antagonists administered at high doses relieved congestion, decreased diuretic resistance, and mitigated the effects of adverse neurohormonal activation in AHF.SubjectsThe ATHENA trial enrolled 360 participants. Of these, 178 participants were randomized to usual care treatment (placebo or low-dose spironolactone) and 182 participants were randomized to high-dose spironolactone.DesignThe study intervention was initiated within 24 hours of patients receiving the first dose of intravenous diuretics. Participants not taking spironolactone at enrollment were randomized to 100 mg spironolactone or a placebo. Participants taking low-dose spironolactone before their hospital admission were randomized to 100 mg or 25 mg per day in the usual care treatment arm. Prescription of all other medications, including diuretics, was left at the discretion of the treating physician. The study drug was discontinued after 96 hours and further MRA use was left to the treating physician's discretion. The primary end point was the proportional change in the log NT-proBNP levels from randomization to 96 hours (or at the hospital discharge if the discharge occurred earlier than 96 hours). Secondary endpoints included: (1) a clinical congestion score; (2) dyspnea relief; (3) daily cumulative net urine output for up to 96 hours; (4) net weight change from baseline to 96 hours or discharge (whichever came first); (5) furosemide equivalents of the loop diuretic dosage at discharge; and (6) the development of in-hospital worsening HF, with signs and symptoms requiring additional therapy.ConclusionsThere was no significant difference in the primary or secondary endpoints between the high-dose treatment arm and the usual care treatment arm. Study Weblinks: BioLINCC Repository Study Design: Clinical Trial Study Type: Clinical Trial Total number of consented subjects: 360 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Heart Failure Network Aldosterone Targeted Neurohormonal Combined with Natriuresis Therapy - (HFN ATHENA-BioLINCC)","short_name":"BL_HFN_ATHENA_GRU","commons":"BioData Catalyst","study_url":"","_subjects_count":360,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs003510.v1.p1.c1":{"gen3_discovery":{"authz":"/programs/BioLINCC/projects/BL_HFN_CARRESS_GRU","tags":[],"_unique_id":"phs003510.v1.p1.c1","study_id":"phs003510.v1.p1.c1","study_description":"ObjectiveThe CARRESS trial examined the effectiveness of ultrafiltration compared with a strategy of diuretic-based stepped pharmacologic therapy on renal function and weight loss in patients with heart failure who have worsening renal function and persistent congestion.BackgroundAcute cardiorenal syndrome is defined as worsening renal function in patients with acute decompensated heart failure. It occurs in 25 to 33% of patients and is associated with poor outcomes. Current heart failure treatments focus on removing excess fluid buildup, however administration of intravenous diuretics may contribute to worsening renal function. Venovenous ultrafiltration is one alternative therapy that may be effective in patients with acute decompensated heart failure complicated by acute cardiorenal syndrome and persistent congestionSubjectsA total of 188 patients were randomized.DesignHospitalized subjects were randomly assigned to receive either ultrafiltration therapy or pharmacologic therapy. Ultrafiltration was performed at a fluid-removal rate of 200 ml per hour and loop diuretics were discontinued for the duration of the intervention. The addition of intravenous vasodilators or positive inotropic agents was prohibited, unless they were deemed to be necessary as rescue therapy. Patients assigned to stepped pharmacologic therapy received intravenous diuretics to manage congestion and maintain a urine output of 3 to 5 liters per day. In both groups, the assigned treatment strategy was to be continued until the signs and symptoms of congestion in the patient were reduced as much as possible. The primary end points were baseline changes in serum creatinine and weight as assessed at 96 hours after treatment assignment.ConclusionsThe use of a stepped pharmacologic-therapy algorithm was superior to a strategy of ultrafiltration for the preservation of renal function, and there was a similar amount of weight loss between the two groups. Ultrafiltration was associated with a higher rate of adverse events (Bart, et al., 2012, PMID: 23131078). Study Weblinks: BioLINCC Repository Study Design: Clinical Trial Study Type: Clinical Trial Total number of consented subjects: 188 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Heart Failure Network - Effectiveness of Ultrafiltration in Treating People with Acute Decompensated Heart Failure and Cardiorenal Syndrome (HFN CARRESS - BioLINCC)","short_name":"BL_HFN_CARRESS_GRU","commons":"BioData Catalyst","study_url":"","_subjects_count":188,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs003524.v1.p1.c1":{"gen3_discovery":{"authz":"/programs/BioLINCC/projects/BL_HFN_DOSE_AHF_GRU","tags":[{"name":"dbGaP","category":"Study Registration"}],"_unique_id":"phs003524.v1.p1.c1","study_id":"phs003524.v1.p1.c1","study_description":"ObjectivesThe DOSE study sought to evaluate the most effective dosing (high vs. low) and administration (continuous infusion vs. intermittent boluses) combination of the diuretic Furosemide in the treatment of patients with acute decompensated heart failure.BackgroundAcute decompensated heart failure is the most common cause of hospital admissions among patients older than 65 years of age and is responsible for more than 1 million hospitalizations annually in the United States. Intravenous loop diuretics are an essential component of current treatment and are administered to approximately 90% of patients who are hospitalized with heart failure. Despite decades of clinical experience with these agents, prospective data to guide the use of loop diuretics are sparse, and current guidelines are based primarily on expert opinion. As a result, clinical practice varies widely with regard to both the mode of administration and the dosing.SubjectsA total of 308 patients were enrolled between March 2008 and November 2009 at 26 clinical sites in the United States and Canada. DesignThe DOSE study was a prospective, randomized, double-blind, controlled trial with a 2-by-2 factorial design. Patients were randomly assigned to either a low-dose strategy (total intravenous furosemide dose equal to their total daily oral loop diuretic dose in furosemide equivalents) or a high-dose strategy (total daily intravenous furosemide dose 2.5 times their total daily oral loop diuretic dose in furosemide equivalents) and to administration of furosemide either by intravenous bolus every 12 hours or by continuous intravenous infusion.The study treatment, with group assignments concealed, was continued for up to 72 hours. At 48 hours, the treating physician had the option of adjusting the diuretic strategy on the basis of the clinical response. An assessment of biomarkers, including creatinine, cystatin C, and N-terminal pro-brain natriuretic peptide, was performed at a central core laboratory at baseline, 72 hours, and 60 days. Patients were followed for clinical events to day 60. The coprimary end points were patients' global assessment of symptoms, quantified as the area under the curve (AUC) of the score on a visual-analogue scale over the course of 72 hours, and the change in the serum creatinine level from baseline to 72 hours.ConclusionsAmong patients with acute decompensated heart failure, there were no significant differences in patients' global assessment of symptoms or in the change in renal function when diuretic therapy was administered by bolus as compared with continuous infusion or at a high dose as compared with a low dose. (Felker et. al., 2011, PMID: 21366472) Study Weblinks: BioLINCC HFN-DOSE study page Study Design: Clinical Trial Study Type: Clinical Trial Total number of consented subjects: 308 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Heart Failure Network: Diuretic Optimization Strategies Evaluation in Acute Heart Failure (HFN DOSE-BioLINCC)","short_name":"BL_HFN_DOSE_AHF_GRU","commons":"BioData Catalyst","study_url":"https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs003524.v1.p1","_subjects_count":308,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs003529.v1.p1.c1":{"gen3_discovery":{"authz":null,"tags":null,"_unique_id":"phs003529.v1.p1.c1","study_id":"phs003529.v1.p1.c1","study_description":null,"full_name":null,"short_name":null,"commons":"BioData Catalyst","study_url":null,"_subjects_count":0,"__manifest":null,"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs003529.v2.p2.c1":{"gen3_discovery":{"authz":"/programs/CureSC/projects/SCD_NHDR_GRU","tags":[],"_unique_id":"phs003529.v2.p2.c1","study_id":"phs003529.v2.p2.c1","study_description":"Data Access NOTE Please refer to the “Authorized Access” section below for information about how access to the data from this accession differs from many other dbGaP accessions. BackgroundThe NHLBI initiated the Sickle Cell Disease Natural History Data Resource (SCD NHDR) to leverage existing SCD studies to build a data resource to provide phenotypic data on contemporaneous control cohorts for gene therapy trials and other studies. The potential uses of the NHDR are broad, including providing matched controls for clinical trials, observing a cohort of untreated patients as part of a natural history study, or conducting comparative effectiveness research on a subpopulation with selected co-morbidities or drug treatment profiles. The SCD NHDR includes two multi-center SCD longitudinal cohort studies with extensive annual clinical data and patient surveys, the Sickle Cell Disease Implementation Consortium (SCDIC-I and SCDIC-II) and the Globin Research Network for Data and Discovery (GRNDaD). The SCDIC-I, initiated in 2017 and concluded in June 2022, enrolled over 2400 patients with SCD from 8 US treatment centers. The SCDIC-II reconsented 1220 of the SCDIC-I patients as well as enrolling an additional 450 new patients from the same 8 centers between September 2022 and October 2023, for a total of 1670 in SCDIC-II. Only two of the many GRNDaD centers are submitting data to the SCD NHDR for deposit into BDC (approximately 122 patients). Data submissions from the SCD NHDR to BDC will be annually starting in early 2024. Description of the Study Data All data obtained for the SCD NHDR are considered common data elements (CDEs) important for studies of SCD. These CDEs were identified from several workgroups of SCD experts convened under the NHLBI's Cure-SC Initiative (https://curesickle.org/cde-catalog). The following types of data elements were abstracted from the medical record – variables that describe the SCD diagnosis, SCD co-morbidities and other clinical complications, elements from the physical examination, medications and transfusions, insurance type, laboratory measurements, healthcare utilization, history of SCD-related procedures, and measurements from cardiac procedures. The following types of data were self-reported on the patient survey – demographics, diagnosis information, pain experience, social and mental health information, other patient reported outcome domains (e.g., sleep, fatigue), and alcohol and smoking history. Standard PRO measures were used from ASCQ-Me, PROMIS and Neuro-QoL. Patient surveys were completed approximately annually. Under SCDIC-I, two medical record abstractions and labs were reported at enrollment and approximately 3 years later. Under SCDIC-II and GRNDaD, all data are collected annually. Patients may refuse to complete the survey. Study Design: Prospective Longitudinal Cohort Study Type: Clinical Cohort Total number of consented subjects: 1792 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Sickle Cell Disease Natural History Data Resource (SCD NHDR)","short_name":"SCD_NHDR_GRU","commons":"BioData Catalyst","study_url":"","_subjects_count":1792,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs003533.v1.p1.c1":{"gen3_discovery":{"authz":"/programs/BioLINCC/projects/BL_HFN_EXACT-HF_GRU","tags":[{"name":"dbGaP","category":"Study Registration"}],"_unique_id":"phs003533.v1.p1.c1","study_id":"phs003533.v1.p1.c1","study_description":"ObjectivesTo determine the effect of allopurinol after 24 weeks on a composite clinical endpoint that classifies subject's clinical status (improved, worsened, unchanged) in patients with heart failure and high uric acid levels.BackgroundMorbidity and mortality rates for patients with heart failure are high, despite guideline-recommended therapy. Heart failure is characterized by an imbalance between left ventricular (LV) performance and myocardial energy consumption. There is a growing body of evidence that suggests oxidative stress contributes to ventricular and vascular remodeling, and disease progression in heart failure. Targeting potential source(s) of oxidative stress, e.g. Xanthine oxidase (XO), was the focus of recent clinical trials and epidemiological studies. Increased XO activity has been shown to lead to production of superoxide and uric acid (UA). Serum uric acid levels are included in heart failure risk scores, and hyperuricemia is present in about 25% of patients with heart failure. Hyperuricemia is associated with exercise intolerance, reduced survival, and worsening symptoms. The EXACT-HF trial tested allopurinol, an inhibitor of XO, as a potential target therapy for hyperuricemic heart failure patients.Subjects253 subjects were enrolled in the EXACT-HF study. 128 participants were randomized to the allopurinol arm, and of those participants, 119 completed the trial and 9 did not. 125 participants were randomized to the placebo arm, and of those participants, 116 completed the trial and 9 did not.DesignEXACT-HF was a multi-center, double-blind, placebo controlled, 24-week trial of allopurinol. Eligible participants had to be receiving a stable regimen for at least two weeks (3 months for beta-blockers) prior to randomization. Participants were randomized by an automated system to either the allopurinol or placebo arm, and started treatment within 12 hours of completing the baseline visit. During the first week, participants in both treatment arms received 300mg daily of the respective medications. For the following 23 weeks, participants in both treatment arms received 600mg daily of the respective medications. Patients unable to tolerate 600 mg were maintained on 300 mg.The primary endpoint was a composite clinical endpoint (CCE) that classified a subject's clinical status as improved, worsened, or unchanged at 24 weeks. The CCE was determined based on the following: death; hospitalization, emergency room visit or emergent clinic visit for worsening HF; medication change for worsening HF; and Patient Global Assessment using a 7-point scale. Secondary endpoints at 12 and 24 weeks included changes in quality of life as assessed by the Kansas City Cardiomyopathy Questionnaire, and submaximal exercise capacity as assessed by a 6-minute walk test.ConclusionsParticipants who received allopurinol had significantly less serum uric acid laboratory levels after 24 weeks; however, no significant difference was observed in the primary and secondary endpoints between the allopurinol and placebo-treated patients. Therefore, in high-risk HF patients with reduced ejection fraction and elevated uric acid levels, xanthine oxidase inhibition with allopurinol failed to improve clinical status, exercise capacity, quality of life, or LVEF at 24 weeks (Circulation. 2015 May 19; 131(20):1763-71). Study Weblinks: BioLINCC Repository Study Design: Clinical Trial Study Type: Clinical Trial Total number of consented subjects: 253 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Heart Failure Network - Xanthine Oxidase Inhibition for Hyperuricemic Heart Failure Patients (HFN EXACT-BioLINCC)","short_name":"BL_HFN_EXACT-HF_GRU","commons":"BioData Catalyst","study_url":"https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs003533.v1.p1","_subjects_count":253,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs003542.v1.p1.c1":{"gen3_discovery":{"authz":"/programs/BioLINCC/projects/BL_HFN-FIGHT_GRU","tags":[{"name":"dbGaP","category":"Study Registration"}],"_unique_id":"phs003542.v1.p1.c1","study_id":"phs003542.v1.p1.c1","study_description":"Objectives To test whether therapy with a GLP-1 agonist improves clinical stability following hospitalization for acute heart failure. Background Heart failure was the leading cause of hospitalization in the United States with more than 4 million admissions per year from 2003–2009. Abnormal cardiac metabolism contributes to the pathophysiology of advanced heart failure with reduced left ventricular ejection fraction (LVEF). As heart failure progresses, these abnormalities become more pronounced and are observed in both patients with and without type 2 diabetes. At this time of this study, there was no heart failure therapy that targeted these metabolic abnormalities; however, in earlier clinical studies, glucagon-like peptide 1 (GLP-1) agonists showed cardioprotective effects in patients with advanced heart failure, irrespective of type 2 diabetes status. Glucagon-like peptide 1 is an endogenous incretin hormone that improves insulin sensitivity with minimal risk of hypoglycemia. This study was created to determine if use of GLP-1 agonists improved clinical stability in recently hospitalized patients with acute heart failure and reduced LVEF. Participants There were 300 participants. Design Participants were identified by hospital admission records and were enrolled during either the last 24 hours of his or her hospitalization for heart failure or the 2-week interval after the hospitalization. Baseline evaluations were conducted, which included echocardiographic measures, the 6-minute walk test, the Kansas City Cardiomyopathy Questionnaire (KCCQ), and blood tests. After the baseline evaluation, patients were randomized in a 1:1 ratio to receive either the GLP-1 agonist liraglutide or placebo as a daily subcutaneous injection. The protocol involved titration of study drug dosage as tolerated every 14 days from 0.6 mg/d to 1.2 mg/d to 1.8 mg/d during the first 30 days of the trial (as tolerated). Follow-up testing was performed at 30-, 90-, and 180-day study visits. The primary end point was a global rank score in which all participants, regardless of treatment assignment, were ranked across 3 hierarchical tiers: time to death, time to rehospitalization for heart failure, and time-averaged proportional change in N-terminal pro-B-type natriuretic peptide (NT-proBNP) level from baseline to 180 days. Conclusions The GLP-1 agonist liraglutide did not improve post-hospitalization clinical stability in patients with advanced heart failure and reduced LVEF. There was no significant between-group difference in the global rank scores and furthermore, there were no significant differences detected in any of the secondary endpoints. Study Weblinks: HFN FIGHT on BioLINCC Study Design: Clinical Trial Study Type: Clinical Trial Total number of consented subjects: 300 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Heart Failure Network: Functional Impact of GLP-1 for Heart Failure Treatment (HFN FIGHT-BioLINCC)","short_name":"BL_HFN-FIGHT_GRU","commons":"BioData Catalyst","study_url":"https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs003542.v1.p1","_subjects_count":300,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs003543.v1.p1.c1":{"gen3_discovery":{"authz":"/programs/NSRR/projects/SR_HCHS_HMB-NPU","tags":[{"name":"dbGaP","category":"Study Registration"}],"_unique_id":"phs003543.v1.p1.c1","study_id":"phs003543.v1.p1.c1","study_description":"The Hispanic Community Health Study / Study of Latinos (HCHS/SOL) is a multi-center epidemiologic study in Hispanic/Latino populations to determine the role of acculturation in the prevalence and development of disease, and to identify risk factors playing a protective or harmful role in Hispanics/Latinos. The study is sponsored by the National Heart, Lung, and Blood Institute (NHLBI) and six other institutes, centers, and offices of the National Institutes of Health (NIH) contributed to the first phase of the project. Raw polysomnography data are available from the HCHS/SOL Baseline visit and raw actigraphy data are available from the Sueño Ancillary visit. Primary HCHS/SOL data can be requested through dbGaP phs000810 Hispanic Community Health Study /Study of Latinos (HCHS/SOL). Study Weblinks: Hispanic Community Health Study / Study of Latinos Website National Sleep Research Resource: Hispanic Community Health Study / Study of Latinos Study Design: Prospective Longitudinal Cohort Study Type: Cohort Total number of consented subjects: 12121 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"National Sleep Research Resource (NSRR): Hispanic Community Health Study/Study of Latinos","short_name":"SR_HCHS_HMB-NPU","commons":"BioData Catalyst","study_url":"https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs003543.v1.p1","_subjects_count":2304,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs003543.v1.p1.c2":{"gen3_discovery":{"authz":"/programs/NSRR/projects/SR_HCHS_HMB","tags":[{"name":"dbGaP","category":"Study Registration"}],"_unique_id":"phs003543.v1.p1.c2","study_id":"phs003543.v1.p1.c2","study_description":"The Hispanic Community Health Study / Study of Latinos (HCHS/SOL) is a multi-center epidemiologic study in Hispanic/Latino populations to determine the role of acculturation in the prevalence and development of disease, and to identify risk factors playing a protective or harmful role in Hispanics/Latinos. The study is sponsored by the National Heart, Lung, and Blood Institute (NHLBI) and six other institutes, centers, and offices of the National Institutes of Health (NIH) contributed to the first phase of the project. Raw polysomnography data are available from the HCHS/SOL Baseline visit and raw actigraphy data are available from the Sueño Ancillary visit. Primary HCHS/SOL data can be requested through dbGaP phs000810 Hispanic Community Health Study /Study of Latinos (HCHS/SOL). Study Weblinks: Hispanic Community Health Study / Study of Latinos Website National Sleep Research Resource: Hispanic Community Health Study / Study of Latinos Study Design: Prospective Longitudinal Cohort Study Type: Cohort Total number of consented subjects: 12121 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"National Sleep Research Resource (NSRR): Hispanic Community Health Study/Study of Latinos","short_name":"SR_HCHS_HMB","commons":"BioData Catalyst","study_url":"https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs003543.v1.p1","_subjects_count":9817,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs003548.v1.p1.c1":{"gen3_discovery":{"authz":"/programs/BioLINCC/projects/BL_HFN-NEAT_GRU","tags":[],"_unique_id":"phs003548.v1.p1.c1","study_id":"phs003548.v1.p1.c1","study_description":"Data Access NOTE: Please refer to the \"Authorized Access\" section below for information about how access to the data from this accession differs from many other dbGaP accessions. Related StudiesEcho images are available with HFN-NEAT Imaging.ObjectivesTo determine the effect of isosorbide mononitrate on daily activity in patients with heart failure and preserved ejection fraction.Background Nitrates are commonly prescribed for symptom relief in patients with heart failure. Early studies in patients with heart failure with a reduced ejection fraction concluded that long-acting nitrates improve activity tolerance; however, approximately half of heart failure patients have preserved ejection fraction. The effects of nitrates in patients with heart failure and a preserved ejection fraction have not been extensively studied and the overall effect of nitrates on activity tolerance in such patients is uncertain. ParticipantsThere were a total of 110 participants enrolled with 51 participants assigned to receive isosorbide mono-nitrate first and placebo second, and 59 participants assigned to receive placebo first and isosorbide mononitrate second. Design Enrolled participants underwent baseline assessments, including echocardiography, quality-of-life scores, 6-minute walk test distance, and NT-proBNP levels. participants were also supplied with two kinetic activity monitors containing high-sensitivity triaxis accelerometers, to be worn 24 hours per day. The accelerometer measurements were expressed as arbitrary accelerometer units and stored every 15 minutes equaling 96 data points per day. The 15-minute cumulative accelerometer units were totaled over a 24-hour period to provide daily accelerometer units. Participants were assigned to one of two treatment groups: 6 weeks of placebo first with crossover to 6 weeks of isosorbide mononitrate, or 6 weeks of isosorbide mononitrate first with crossover to 6 weeks of placebo. The study drugs were prepared as 30-mg tablets of isosorbide mononitrate and matching placebo. During each 6-week period, participants were instructed to take no study drug for the first 2 weeks followed by one tablet (30 mg daily) for 1 week, two tablets (60 mg once daily) for 1 week, and four tablets (120 mg once daily) until the next study visit, for a treatment duration of at least 2 weeks and up to 4 weeks. After each 6-week period, participants returned to the study center to repeat end-point assessments. The primary outcome for the study was the comparison of average daily accelerometer units during the period in which participants were receiving the 120-mg dose of isosorbide mononitrate compared to the period in which participants received the placebo. Other secondary end points included the 6-minute walk distance and the post-walk Borg dyspnea score, scores on the Kansas City Cardiomyopathy Questionnaire and the Minnesota Living with Heart Failure Questionnaire, and NT-proBNP levels. In addition, participants completed a questionnaire indicating in which period (first, second, no preference) they felt better. Conclusions Participants were active for fewer hours of the day during the 120-mg phase of receipt of isosorbide mononitrate as compared with placebo. Furthermore, during all study-drug regimens combined (30 mg to 120 mg), participants were less active during receipt of isosorbide mononitrate as compared with placebo. There was no significant effect of isosorbide mononitrate on secondary outcomes. Study Weblinks: BioLINCC Repository Study Design: Clinical Trial Study Type: Clinical Trial Total number of consented subjects: 110 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Heart Failure Network - Nitrate's Effect on Activity Tolerance in Heart Failure with Preserved Ejection Fraction (HFN NEAT-BioLINCC)","short_name":"BL_HFN-NEAT_GRU","commons":"BioData Catalyst","study_url":"","_subjects_count":110,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs003551.v1.p1.c1":{"gen3_discovery":{"authz":"/programs/BioLINCC/projects/BL_ACCORD_GRU","tags":[{"name":"dbGaP","category":"Study Registration"}],"_unique_id":"phs003551.v1.p1.c1","study_id":"phs003551.v1.p1.c1","study_description":"Related StudiesWhole genome and whole exome data is available on a subset of participants with phs001411. ECG signal data is available with phs003562.ObjectivesThe purpose of this study was to determine if intensive glycemic control, multiple lipid management and intensive blood pressure control could prevent major cardiovascular events (myocardial infarction, stroke or cardiovascular death) in adults with type 2 diabetes mellitus. Secondary hypotheses included treatment differences in other cardiovascular outcomes, total mortality, microvascular outcomes, health-related quality of life and cost-effectiveness. BackgroundGlycemia Trial:Patients with type 2 diabetes mellitus die of cardiovascular disease (CVD) at rates two to four times higher than non-diabetic populations of similar demographic characteristics. They also experience increased rates of nonfatal myocardial infarction and stroke. With the growing prevalence of obesity in the United States, CVD associated with type 2 diabetes is expected to become an even greater public health challenge in the coming decades than it is now. Expected increases in event rates will be associated with a concomitant rise in suffering and resource utilization.The ACCORD study investigated whether intensive therapy to target normal glycated hemoglobin (HbA1c) levels would reduce cardiovascular events in patients with type 2 diabetes who had either established cardiovascular disease or additional cardiovascular risk factors when compared to standard therapy (HbA1c between 7.0% and 7.9%). A separate analysis investigated whether reduction of blood glucose concentration decreases the rate of microvascular complications in these patients. Lipid Therapy Trial: Patients with type 2 diabetes mellitus have an increased incidence of atherosclerotic cardiovascular disease attributable, in part, to associated risk factors such as dyslipidemia. This is characterized by elevated plasma triglyceride levels, low levels of high-density lipoprotein (HDL) cholesterol and small, dense low-density lipoprotein (LDL) particles. The ACCORD Lipid Therapy trial was designed to test the effect of a therapeutic strategy that uses a fibrate to raise HDL-C and lower triglyceride levels and uses a statin for treatment of LDL-C reduce the rate of CVD events compared to a strategy that only uses a statin for treatment of LDL-C on cardiovascular outcomes in patients with type 2 diabetes that were at high risk for cardiovascular disease. Blood Pressure Trial: Diabetes mellitus increases the risk of cardiovascular disease at every level of systolic blood pressure. Because cardiovascular risk in patients with diabetes is graded and continuous across the entire range of levels of systolic blood pressure, even at prehypertensive levels, the Seventh Report of the Joint National Committee on Prevention, Detection, Evaluation, and Treatment of High Blood Pressure (JNC 7) recommended beginning drug treatment in patients with diabetes who have systolic blood pressures of 130 mm Hg or higher, with a treatment goal of reducing systolic blood pressure to below 130 mm Hg. There is, however, a paucity of evidence from randomized clinical trials to support these recommendations. The ACCORD Blood Pressure trial tested the effect of a target systolic blood pressure below 120 mm Hg on major cardiovascular events among high-risk persons with type 2 diabetes compared to a strategy that targeted a SBP of < 140 mm Hg. EYE Substudy: Diabetic retinopathy, an important microvascular complication of diabetes, is a leading cause of blindness in the United States. Randomized, controlled clinical trials in cohorts of patients with type 1 diabetes and those with type 2 diabetes have shown the beneficial effects of intensive glycemic control and intensive treatment of elevated blood pressure on the progression of diabetic retinopathy. Elevated serum cholesterol and triglyceride levels have been implicated, in observational studies and small trials, as additional risk factors for the development of diabetic retinopathy and visual loss. The ACCORD EYE Substudy evaluated the effects of the ACCORD medical strategies on the progression of diabetic retinopathy in a subgroup of trial patients. MIND Substudy: Studies suggest that older persons with type 2 diabetes have at least twice the likelihood of developing late-life cognitive impairment or dementia compared to those without. The mechanisms underlying these cognitive disorders are increasingly thought to reflect a mixed pathology pattern with contributions from vascular, neurodegenerative and neurovascular processes. Pathophysiological mechanisms that have been described include inflammation, oxidative stress, energy imbalance, protein misfolding, glucocorticoid-mediated effects and differences in genetic susceptibilities. The ACCORD MIND substudy took as a premise that early intervention with the ACCORD therapeutic strategies to improve glycemic control could mitigate the adverse effects of type 2 diabetes on the brain. Participants10,251 participants with type 2 diabetes and HbA1c concentrations of 7.5% or more participated in the trial. Of these patients, 5518 were assigned to the lipid therapy arm and 4733 to the blood pressure arm. EYE Substudy: A subgroup of 2856 participants was evaluated for the effects of the ACCORD interventions at 4 years on the progression of diabetic retinopathy. Participants who, at baseline, had a history of proliferative diabetic retinopathy that had been treated with laser photocoagulation or vitrectomy were excluded. MIND Substudy: A subgroup of 2977 participants was evaluated for cognitive function and brain volume. The ACCORD MIND substudy excluded participants aged <55 years and those in the Veteran's Administration CCN (to retain the overall sex balance reflected in the other CCNs). Within ACCORD MIND a group of 632 participants participated in the MRI sub-study. Design Participants were randomly assigned to undergo either intensive glycemic control (targeting a glycated hemoglobin level <6.0%) or standard therapy (targeting a glycated hemoglobin level of 7.0 to 7.9%). Of these participants, 5518 with dyslipidemia were also randomly assigned, in a 2-by-2 factorial design, to receive simvastatin (to reduce low-density lipoprotein [LDL] cholesterol levels) in combination with either fenofibrate (to reduce triglyceride levels and increase high-density lipoprotein [HDL] cholesterol levels) or matching placebo. The remaining 4733 participants were randomly assigned, in a 2-by-2 factorial design, to undergo either intensive blood-pressure control (targeting a systolic blood pressure <120 mm Hg) or standard therapy (targeting a systolic blood pressure <140 mm Hg). The primary outcome was a composite of nonfatal myocardial infarction, nonfatal stroke or death from cardiovascular causes. Clinic staff and participants were not blinded to treatment arm. The finding of higher mortality in the intensive-therapy group led to a discontinuation of intensive therapy after a mean of 3.5 years of follow-up. Analysis was done for all participants who were assessed for microvascular outcomes, on the basis of treatment assignment, irrespective of treatments received or compliance to therapies. EYE Substudy: EYE Substudy participants were evaluated at two standardized and comprehensive eye examinations for the effects of the ACCORD interventions at 4 years on the progression of diabetic retinopathy by 3 or more steps on the Early Treatment Diabetic Retinopathy Study Severity Scale (as assessed from seven-field stereoscopic fundus photographs, with 17 possible steps and a higher number of steps indicating greater severity) or the development of diabetic retinopathy necessitating laser photocoagulation or vitrectomy. MIND Substudy: The cognitive primary outcome, the Digit Symbol Substitution Test (DSST) score, was assessed at baseline, 20 and 40 months. Total brain volume (TBV), the primary brain structure outcome, was assessed with MRI at baseline and 40 months in a sub-set of 632 patients. All patients with follow-up data were included in the primary analyses. Conclusions Glycemia Trial: As compared with standard therapy, the use of intensive therapy to target normal glycated hemoglobin levels for 3.5 years increased mortality and did not significantly reduce major cardiovascular events. (Action to Control Cardiovascular Risk in Diabetes Study Group, et al.,2008, PMID:18539917). Microvascular Outcomes of the Glycemia Trial: Intensive therapy did not reduce the risk of advanced measures of microvascular outcomes, but delayed the onset of albuminuria and some measures of eye complications and neuropathy. Microvascular benefits of intensive therapy should be weighed against the risk of increased total and cardiovascular disease-related mortality, increased weight gain, and higher risk for severe hypoglycemia. (Ismail-Beigi et al., 2010, PMID: 20594588) Lipid Therapy Trial: The combination of fenofibrate and simvastatin did not reduce the rate of fatal cardiovascular events, nonfatal myocardial infarction or nonfatal stroke, as compared with simvastatin alone. These results do not support the routine use of combination therapy with fenofibrate and simvastatin to reduce cardiovascular risk in the majority of high-risk patients with type 2 diabetes (ACCORD Study Group, et al., 2010, PMID: 20228404). Blood Pressure Trial: In patients with type 2 diabetes at high risk for cardiovascular events, targeting a systolic blood pressure of less than 120 mm Hg, as compared with less than 140 mm Hg, did not reduce the rate of a composite outcome of fatal and nonfatal major cardiovascular events (ACCORD Study Group, et al., 2010, PMID: 20228401). EYE Substudy: Intensive glycemic control and intensive combination treatment of dyslipidemia, but not intensive blood-pressure control, reduced the rate of progression of diabetic retinopathy (ACCORD Study Group, et al., 2010, PMID: 20587587). MIND Substudy: Although significant differences in TBV favored the intensive therapy, cognitive outcomes were not different. Combined with the unfavorable effects on other ACCORD outcomes, MIND findings do not support using intensive therapy to reduce the adverse effects of diabetes on the brain in patients similar to MIND patients (Launer et al., 2011, PMID: 21958949). Study Weblinks: ACCORD on BioLINCC Study Design: Clinical Trial Study Type: Clinical Trial Total number of consented subjects: 10251 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Action to Control Cardiovascular Risk in Diabetes (ACCORD-BioLINCC)","short_name":"BL_ACCORD_GRU","commons":"BioData Catalyst","study_url":"https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs003551.v1.p1","_subjects_count":10251,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs003557.v1.p1.c1":{"gen3_discovery":{"authz":"/programs/BioLINCC/projects/BL_HFN_IRONOUT_GRU","tags":[{"name":"dbGaP","category":"Study Registration"}],"_unique_id":"phs003557.v1.p1.c1","study_id":"phs003557.v1.p1.c1","study_description":"ObjectivesTo test the hypothesis that, compared to placebo, oral iron repletion in heart failure patients with iron deficiency improves exercise capacity after 16 weeks of therapy.Background Iron deficiency affects approximately one half of patients with symptomatic heart failure. The presence of iron deficiency in patients with heart failure is associated with reduced functional capacity, poorer quality of life, and increased mortality. Despite growing recognition of the significance of iron deficiency, randomized multicenter trials exploring the utility of oral iron supplementation, a therapy that is inexpensive, readily available, and safe, have not been performed in patients with heart failure. Moreover, patient characteristics and biochemical profiles that may influence responsiveness to oral iron in patients with heart failure have not been defined. Results of intravenous iron repletion trials have been favorable, but regularly treating patients with intravenous iron products is expensive and poses logistical challenges for outpatients. Therefore, the HFN-IRONOUT study was initiated to investigate the efficacy of oral iron in patients with heart failure with reduced ejection fraction (HFrEF). ParticipantsA total of 225 participants were enrolled, 111 randomized to receive oral iron and 114 randomized to receive the placebo. Design The HFN-IRONOUT study was a phase 2, double-blind, placebo-controlled randomized clinical trial that enrolled participants at 23 sites in the United States. Participants were randomly assigned, in a 1:1 ratio, to receive either oral iron polysaccharide or placebo with the use of an automated web-based system. A permuted block randomization method (with 4 participants per block) was stratified by enrolling site and anemia status (defined as hemoglobin < 12 g/dL). Study drug was administered orally at 150 mg, twice daily for 16 weeks. At baseline, 8 weeks, and 16 weeks participants underwent studies including history and physical examination, cardiopulmonary exercise testing (CPET), Kansas City Cardiomyopathy Questionnaire (KCCQ), and 6-minute walk test. CPETs were performed using a 10 Watt/minute incremental ramp protocol and breath-by-breath measures of oxygen uptake were uniformly analyzed by the CPET Core Lab. Participants also underwent phlebotomy for biomarkers. Iron studies, including iron, total iron binding capacity, and ferritin, were measured at baseline and after 16 weeks to determine the extent to which oral iron led to iron repletion. The primary end point was the change in peak oxygen uptake (peak VO2) after 16 weeks of therapy. Conclusions Among participants with HFrEF with iron deficiency, high-dose oral iron did not improve exercise capacity over 16 weeks. Study Weblinks: BioLINCC Repository Study Design: Clinical Trial Study Type: Clinical Trial Total number of consented subjects: 225 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Heart Failure Network Oral Iron Repletion Effects on Oxygen Uptake in Heart Failure (HFN IRONOUT-BioLINCC)","short_name":"BL_HFN_IRONOUT_GRU","commons":"BioData Catalyst","study_url":"https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs003557.v1.p1","_subjects_count":225,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs003562.v1.p1.c1":{"gen3_discovery":{"authz":"/programs/imaging/projects/ACCORD_GRU","tags":[{"name":"dbGaP","category":"Study Registration"}],"_unique_id":"phs003562.v1.p1.c1","study_id":"phs003562.v1.p1.c1","study_description":"Available DataAction to Control Cardiovascular Risk in Diabetes (ACCORD-Imaging), provides access to ECG signals data from the ACCORD clinical trial. The clinical phenotyping and outcomes data from the trial are associated with ACCORD-BioLINCC, phs003551.ObjectivesThe purpose of this study was to determine if intensive glycemic control, multiple lipid management and intensive blood pressure control could prevent major cardiovascular events (myocardial infarction, stroke or cardiovascular death) in adults with type 2 diabetes mellitus. Secondary hypotheses included treatment differences in other cardiovascular outcomes, total mortality, microvascular outcomes, health-related quality of life and cost-effectiveness.BackgroundGlycemia Trial:Patients with type 2 diabetes mellitus die of cardiovascular disease (CVD) at rates two to four times higher than non-diabetic populations of similar demographic characteristics. They also experience increased rates of nonfatal myocardial infarction and stroke. With the growing prevalence of obesity in the United States, CVD associated with type 2 diabetes is expected to become an even greater public health challenge in the coming decades than it is now. Expected increases in event rates will be associated with a concomitant rise in suffering and resource utilization.The ACCORD study investigated whether intensive therapy to target normal glycated hemoglobin (HbA1c) levels would reduce cardiovascular events in patients with type 2 diabetes who had either established cardiovascular disease or additional cardiovascular risk factors when compared to standard therapy (HbA1c between 7.0% and 7.9%). A separate analysis investigated whether reduction of blood glucose concentration decreases the rate of microvascular complications in these patients.Lipid Therapy Trial:Patients with type 2 diabetes mellitus have an increased incidence of atherosclerotic cardiovascular disease attributable, in part, to associated risk factors such as dyslipidemia. This is characterized by elevated plasma triglyceride levels, low levels of high-density lipoprotein (HDL) cholesterol and small, dense low-density lipoprotein (LDL) particles. The ACCORD Lipid Therapy trial was designed to test the effect of a therapeutic strategy that uses a fibrate to raise HDL-C and lower triglyceride levels and uses a statin for treatment of LDL-C reduce the rate of CVD events compared to a strategy that only uses a statin for treatment of LDL-C on cardiovascular outcomes in patients with type 2 diabetes that were at high risk for cardiovascular disease.Blood Pressure Trial:Diabetes mellitus increases the risk of cardiovascular disease at every level of systolic blood pressure. Because cardiovascular risk in patients with diabetes is graded and continuous across the entire range of levels of systolic blood pressure, even at prehypertensive levels, the Seventh Report of the Joint National Committee on Prevention, Detection, Evaluation, and Treatment of High Blood Pressure (JNC 7) recommended beginning drug treatment in patients with diabetes who have systolic blood pressures of 130 mm Hg or higher, with a treatment goal of reducing systolic blood pressure to below 130 mm Hg. There is, however, a paucity of evidence from randomized clinical trials to support these recommendations. The ACCORD Blood Pressure trial tested the effect of a target systolic blood pressure below 120 mm Hg on major cardiovascular events among high-risk persons with type 2 diabetes compared to a strategy that targeted a SBP of < 140 mm Hg.EYE Substudy:Diabetic retinopathy, an important microvascular complication of diabetes, is a leading cause of blindness in the United States. Randomized, controlled clinical trials in cohorts of patients with type 1 diabetes and those with type 2 diabetes have shown the beneficial effects of intensive glycemic control and intensive treatment of elevated blood pressure on the progression of diabetic retinopathy. Elevated serum cholesterol and triglyceride levels have been implicated, in observational studies and small trials, as additional risk factors for the development of diabetic retinopathy and visual loss. The ACCORD EYE Substudy evaluated the effects of the ACCORD medical strategies on the progression of diabetic retinopathy in a subgroup of trial patients.MIND Substudy:Studies suggest that older persons with type 2 diabetes have at least twice the likelihood of developing late-life cognitive impairment or dementia compared to those without. The mechanisms underlying these cognitive disorders are increasingly thought to reflect a mixed pathology pattern with contributions from vascular, neurodegenerative and neurovascular processes. Pathophysiological mechanisms that have been described include inflammation, oxidative stress, energy imbalance, protein misfolding, glucocorticoid-mediated effects and differences in genetic susceptibilities. The ACCORD MIND substudy took as a premise that early intervention with the ACCORD therapeutic strategies to improve glycemic control could mitigate the adverse effects of type 2 diabetes on the brain.Subjects10,251 patients with type 2 diabetes and HbA1c concentrations of 7.5% or more participated in the trial. Of these patients, 5518 were assigned to the lipid therapy arm and 4733 to the blood pressure arm. EYE Substudy:A subgroup of 2856 patients was evaluated for the effects of the ACCORD interventions at 4 years on the progression of diabetic retinopathy. Patients who, at baseline, had a history of proliferative diabetic retinopathy that had been treated with laser photocoagulation or vitrectomy were excluded.MIND Substudy:A subgroup of 2977 patients was evaluated for cognitive function and brain volume. The ACCORD MIND substudy excluded patients aged <55 years and those in the Veteran's Administration CCN (to retain the overall sex balance reflected in the other CCNs). Within ACCORD MIND a group of 632 patients participated in the MRI sub-study.DesignPatients were randomly assigned to undergo either intensive glycemic control (targeting a glycated hemoglobin level <6.0%) or standard therapy (targeting a glycated hemoglobin level of 7.0 to 7.9%). Of these patients, 5518 with dyslipidemia were also randomly assigned, in a 2-by-2 factorial design, to receive simvastatin (to reduce low-density lipoprotein [LDL] cholesterol levels) in combination with either fenofibrate (to reduce triglyceride levels and increase high-density lipoprotein [HDL] cholesterol levels) or matching placebo. The remaining 4733 patients were randomly assigned, in a 2-by-2 factorial design, to undergo either intensive blood-pressure control (targeting a systolic blood pressure <120 mm Hg) or standard therapy (targeting a systolic blood pressure <140 mm Hg). The primary outcome was a composite of nonfatal myocardial infarction, nonfatal stroke or death from cardiovascular causes. Clinic staff and patients were not blinded to treatment arm. The finding of higher mortality in the intensive-therapy group led to a discontinuation of intensive therapy after a mean of 3.5 years of follow-up. Analysis was done for all patients who were assessed for microvascular outcomes, on the basis of treatment assignment, irrespective of treatments received or compliance to therapies.EYE Substudy:EYE Substudy patients were evaluated at two standardized and comprehensive eye examinations for the effects of the ACCORD interventions at 4 years on the progression of diabetic retinopathy by 3 or more steps on the Early Treatment Diabetic Retinopathy Study Severity Scale (as assessed from seven-field stereoscopic fundus photographs, with 17 possible steps and a higher number of steps indicating greater severity) or the development of diabetic retinopathy necessitating laser photocoagulation or vitrectomy.MIND Substudy:The cognitive primary outcome, the Digit Symbol Substitution Test (DSST) score, was assessed at baseline, 20 and 40 months. Total brain volume (TBV), the primary brain structure outcome, was assessed with MRI at baseline and 40 months in a sub-set of 632 patients. All patients with follow-up data were included in the primary analyses.ConclusionsGlycemia Trial:As compared with standard therapy, the use of intensive therapy to target normal glycated hemoglobin levels for 3.5 years increased mortality and did not significantly reduce major cardiovascular events. (NEJM. 2008; 358(24): 2545-59).Microvascular Outcomes of the Glycemia Trial:Intensive therapy did not reduce the risk of advanced measures of microvascular outcomes, but delayed the onset of albuminuria and some measures of eye complications and neuropathy. Microvascular benefits of intensive therapy should be weighed against the risk of increased total and cardiovascular disease-related mortality, increased weight gain, and higher risk for severe hypoglycemia. (Lancet. 2010; 376(9739): 419-30)Lipid Therapy Trial:The combination of fenofibrate and simvastatin did not reduce the rate of fatal cardiovascular events, nonfatal myocardial infarction or nonfatal stroke, as compared with simvastatin alone. These results do not support the routine use of combination therapy with fenofibrate and simvastatin to reduce cardiovascular risk in the majority of high-risk patients with type 2 diabetes (NEJM. 2010; 362(17): 1563–1574).Blood Pressure Trial:In patients with type 2 diabetes at high risk for cardiovascular events, targeting a systolic blood pressure of less than 120 mm Hg, as compared with less than 140 mm Hg, did not reduce the rate of a composite outcome of fatal and nonfatal major cardiovascular events (NEJM. 2010; 362: 1575-1585).EYE Substudy:Intensive glycemic control and intensive combination treatment of dyslipidemia, but not intensive blood-pressure control, reduced the rate of progression of diabetic retinopathy (NEJM. 2010; 363: 233-244).MIND Substudy:Although significant differences in TBV favored the intensive therapy, cognitive outcomes were not different. Combined with the unfavorable effects on other ACCORD outcomes, MIND findings do not support using intensive therapy to reduce the adverse effects of diabetes on the brain in patients similar to MIND patients (Lancet Neurol. 2011; 10(11): 969–977). Study Weblinks: ACCORD BioLINCC ACCORD SNP Genotypes Study Design: Clinical Trial Study Type: Clinical Trial Total number of consented subjects: 10251 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Action to Control Cardiovascular Risk in Diabetes (ACCORD - Imaging)","short_name":"ACCORD_GRU","commons":"BioData Catalyst","study_url":"https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs003562.v1.p1","_subjects_count":10150,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs003562.v2.p1.c1":{"gen3_discovery":{"authz":null,"tags":null,"_unique_id":null,"study_id":null,"study_description":null,"full_name":null,"short_name":null,"commons":"BioData Catalyst","study_url":null,"_subjects_count":0,"__manifest":null,"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs003565.v1.p1.c1":{"gen3_discovery":{"authz":"/programs/BioLINCC/projects/BL_HFN-RELAX_GRU","tags":[],"_unique_id":"phs003565.v1.p1.c1","study_id":"phs003565.v1.p1.c1","study_description":"Data Access NOTE: Please refer to the “Authorized Access” section below for information about how access to the data from this accession differs from many other dbGaP accessions. Related StudyEcho images are available through HFN RELAX-ImagingObjectivesThe RELAX trial tested the hypothesis that chronic phosphodiesterase type-5 inhibitor therapy with sildenafil would improve exercise capacity and clinical status in heart failure patients with normal ejection fraction, as compared to placebo. Background Heart failure (HF) with preserved ejection fraction (HFpEF) is a common and highly morbid condition that is characterized by chronic exercise intolerance, progressive functional decline and a high rate of readmission. At the time of the RELAX trial, clinical trials of renin-angiotensin system antagonists had not demonstrated improvement in outcomes or clinical status in HFpEF, and effective therapies were needed. Phosphodiesterase type-5 (PDE-5) metabolizes the nitric oxide (NO) and natriuretic peptide (NP) systems' second messenger cyclic guanosine monophosphate (cGMP), and thus may limit beneficial NO and NP actions in the heart, vasculature and kidney. Pre-clinical studies suggest that inhibition of PDE-5 reverses adverse cardiac structural and functional remodeling and enhances vascular, neuroendocrine and renal function. In clinical studies, PDE-5 inhibitor therapy improved exercise tolerance and clinical status in patients with idiopathic pulmonary arterial hypertension and in patients with HF and reduced ejection fraction (HFrEF). A small, single-center study in HFpEF observed improved hemodynamics, left ventricular (LV) diastolic function, right ventricular (RV) systolic function, LV hypertrophy and lung function with chronic PDE-5 inhibition as compared to placebo. In aggregate, these studies suggested the potential for PDE-5 inhibition to ameliorate several key pathophysiological perturbations in HFpEF, and thus improve exercise capacity and clinical status. ParticipantsA total of 216 participants were enrolled in the trial with 113 in the Sildenafil group and 103 in the placebo group. Design Participants who met screening criteria underwent baseline studies including a history and physical examination, cardiopulmonary exercise test (CPXT), six-minute walk distance, Minnesota Living with Heart Failure Questionnaire (MLWHFQ), echocardiography, cardiac magnetic resonance imaging, and phlebotomy for biomarkers. Subjects were then randomly assigned, in a 1:1 ratio, to either the sildenafil or placebo intervention group. The study drug was administered orally at 20 mg three times daily (TID) for 12 weeks. If the dose was well tolerated at 12 weeks, it was increased to 60 mg TID for another 12 weeks. If side effects developed, study staff could recommend discontinuation or return to a lower or previously tolerated dose of study drug. Sildenafil levels 2 hours after a scheduled dose of study drug were obtained at 12 and 24 weeks. The primary endpoint was exercise capacity determined by change in peak oxygen consumption during the CPXT after 24 weeks of therapy. Secondary endpoints included change in six-minute walk distance at 12 and 24 weeks, change in peak oxygen consumption at 12 weeks, and a three tier score reflective of clinical status where patients were ranked based on time to death (lowest tier), time to cardiovascular or cardiorenal hospitalization (middle tier), and change in the MLWHFQ for patients alive without cardiovascular or cardiorenal hospitalization after 24 weeks (highest tier). Conclusions Chronic phosphodiesterase type-5 inhibitor therapy with sildenafil for 24 weeks did not alter exercise capacity or clinical status compared to placebo in patients with heart failure and preserved ejection fraction. Study Weblinks: BioLINCC Repository Study Design: Clinical Trial Study Type: Clinical Trial Total number of consented subjects: 216 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Heart Failure Network - Phosphodiesterase-5 Inhibition to Improve Clinical Status and Exercise Capacity in Diastolic Heart Failure (HFN RELAX-BioLINCC)","short_name":"BL_HFN-RELAX_GRU","commons":"BioData Catalyst","study_url":"","_subjects_count":216,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs003566.v1.p1.c1":{"gen3_discovery":{"authz":"/programs/imaging/projects/SPRINT_GRU","tags":[{"name":"dbGaP","category":"Study Registration"}],"_unique_id":"phs003566.v1.p1.c1","study_id":"phs003566.v1.p1.c1","study_description":"Available DataSystolic Blood Pressure Intervention Trial, SPRINT-Imaging, provides access to ECG signals data from the SPRINT clinical trial. The clinical phenotyping and outcomes data from the trial are associated with SPRINT-BioLINCC, phs003483.ObjectiveThe Systolic Blood Pressure Trial (SPRINT) was conducted to test the hypothesis that treating systolic blood pressure to a target of less than 120 mm Hg, as compared to a target of less than 140 mm Hg, would reduce the incidence of cardiovascular disease. BackgroundHypertension is a highly prevalent condition among adults and is a leading risk factor for myocardial infarction and stroke. Further, isolated systolic hypertension is the most common form of hypertension in adults over 50 years of age. Observational studies have shown a monotonic increase in cardiovascular risk with systolic blood pressures above 115 mm Hg; however, general population clinical trials have only documented the benefits of lowering systolic blood pressure to a target of 150 mm Hg. A 2007 expert panel sponsored by the National Heart, Lung, and Blood Institute designated the hypothesis that lowering the systolic blood pressure goal to a level <120 mm Hg as the most important hypothesis to test in reducing hypertension related complications in those without diabetes. SubjectsA total of 9361 participants were enrolled, with 4,678 randomized to the intensive-treatment group and 4,683 randomized to the standard-treatment group. DesignSPRINT was a randomized, single blinded (outcome adjudicators were blinded to treatment assignment) treatment trial with participants randomized to a systolic blood-pressure target of either less than 140 mm Hg (the standard-treatment group) or less than 120 mm Hg (the intensive-treatment group). Following randomization, baseline hypertensive regimens were adjusted in accordance with study treatment algorithms established for each group. The study formulary included all major classes of antihypertensive agents. Investigators could prescribe other antihypertensive medications, but the use of drug classes with the strongest evidence for reduction in cardiovascular outcomes was encouraged. This included thiazide-type diuretics as the first-line agent, loop diuretics for participants with advanced chronic kidney disease, and beta-adrenergic blockers for participants with coronary artery disease. Medications for participants in the intensive-treatment group were adjusted on a monthly basis to target a systolic blood pressure of less than 120 mm Hg. Medications for participants in the standard-treatment group were adjusted to target a systolic blood pressure of 135 to 139 mm Hg, and the dose was reduced if systolic blood pressure was less than 130 mm Hg on a single visit or less than 135 mm Hg on two consecutive visits. Lifestyle modification was encouraged as part of the management strategy. Participants were seen monthly for the first 3 months and every 3 months thereafter. Demographic data were collected at baseline. Clinical and laboratory data were obtained at baseline and every 3 months thereafter. A structured interview was used in both groups every 3 months to obtain self-reported cardiovascular disease outcomes. Medical records and electrocardiograms were obtained for documentation of events. Incidences of hypotension, syncope, injurious falls, electrolyte abnormalities, and bradycardia that were evaluated in an emergency department were included in adverse event reporting. Occurrences of acute kidney injury or acute renal failure requiring hospitalization were also monitored. The primary outcome was a composite outcome of myocardial infarction, other acute coronary syndromes, stroke, heart failure, or death from cardiovascular causes. ConclusionsThe blood pressure intervention was stopped in August of 2015 (median follow-up of 3.26 years) after the cardiovascular outcome results exceeded the boundary for efficacy at two consecutive time points. Compared with a systolic blood pressure target of less than 140 mm Hg, an intensive systolic blood pressure target of 120 mm Hg resulted in lower rates of fatal and nonfatal major cardiovascular events and death from any cause. Significantly higher rates of some adverse events were observed in the intensive-treatment group. Study Design: Clinical Trial Study Type: Clinical Trial Total number of consented subjects: 9361 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Systolic Blood Pressure Intervention Trial (SPRINT-Imaging)","short_name":"SPRINT_GRU","commons":"BioData Catalyst","study_url":"https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs003566.v1.p1","_subjects_count":9320,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs003566.v2.p1.c1":{"gen3_discovery":{"authz":null,"tags":null,"_unique_id":null,"study_id":null,"study_description":null,"full_name":null,"short_name":null,"commons":"BioData Catalyst","study_url":null,"_subjects_count":0,"__manifest":null,"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs003578.v1.p1.c1":{"gen3_discovery":{"authz":"/programs/REDS/projects/RESPONSE_GRU","tags":[{"name":"dbGaP","category":"Study Registration"}],"_unique_id":"phs003578.v1.p1.c1","study_id":"phs003578.v1.p1.c1","study_description":"Leveraging access to the blood supply and blood donors, the REDS-IV-P program began conducting the RESPONSE study (REDS-IV-P Epidemiology, Surveillance and Preparedness of the Novel SARS-CoV-2 Epidemic) in early 2020 in order to 1) evaluate if SARS-CoV-2 RNA was found in blood donations in the U.S. using an assay that could potentially be used to screen the blood supply if evidence of SARS-CoV-2 transfusion-transmission became apparent 2) conduct serosurveys using optimized assays/algorithms to monitor antibody reactivity in blood donor populations over time, 3) enroll SARS-CoV-2 positive donors and others into a longitudinal cohort study to answer fundamental questions about the evolution of viremia and immune responses, and 4) establish a sharable biorepository that includes specimens collected early on in the infection and potentially large volumes of plasma from infected/convalescent donors.Screening for SARS-CoV-2 RNAemia was completed using a SARS-CoV-2 nucleic acid test (NAT) performed on retained blood donor minipool samples from six geographic regions in the US. The study also included serosurveillance (i.e. testing for antibody directed against the SARS-CoV2 spike protein) of donations from the same six regions to document accruing seroincidence in blood donor populations and to project these rates in the general population. To enrich for donors with acute SARS-CoV-2 infection, another part of the study focused on donors reporting post-donation information (PDI) consistent with COVID-19 by testing plasma from all available PDI donations for SARS-CoV-2 RNA by NAT. Subjects who were diagnosed with COVID-19 based on PDI reports or who tested positive by SARS-CoV-2 NAT on index donation plasma were enrolled into a longitudinal follow-up study which collected multiple samples for up to one-year post-infection. The longitudinal follow-up study also enrolled community members who reported a new positive SARS-CoV-2 NAT test in the prior 7-14 days. The specific aims of the RESPONSE study were to: Establish the incidence of SARS-CoV-2 RNAemia in blood donations from the American Red Cross (ARC) regions in Los Angeles, Boston, and Minneapolis metropolitan areas, Bloodworks Northwest (BWNW), New York Blood Center (NYBC), and Vitalant San Francisco Bay Area, monthly between March and September of 2020 Conduct serosurveys to study antibody reactivity in same six areas as above monthly for March to August 2020 Document rates of Post Donation Information (PDI) reports to determine PDI rates relevant to SARS-CoV-2 clinical disease and test index donation plasma from PDI donors for SARS-CoV-2 RNA Enroll SARS-CoV-2 infected subjects into a longitudinal cohort study to answer fundamental questions on the evolution of viremia, early immune responses and waning of immunity over 3-12 months of follow-up Establish a sharable biorepository of samples from all of the above Aims for future research The data from Aims 3 and 4 above is being made available in BioData Catalyst.Biospecimens for these Aims are managed by Vitalant Research Institute (VRI). More information on biospecimens is available. Study Weblinks: REDS-IV-P RESPONSE Study Design: Prospective Longitudinal Cohort Study Type: Cohort Longitudinal Longitudinal Cohort Observational Total number of consented subjects: 4729 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"REDS-IV-P Epidemiology, Surveillance and Preparedness of the Novel SARS-CoV-2 Epidemic (RESPONSE)","short_name":"RESPONSE_GRU","commons":"BioData Catalyst","study_url":"https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs003578.v1.p1","_subjects_count":4729,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs003589.v1.p1.c1":{"gen3_discovery":{"authz":"/programs/BioLINCC/projects/BL_HFN-ROSE_GRU","tags":[],"_unique_id":"phs003589.v1.p1.c1","study_id":"phs003589.v1.p1.c1","study_description":"ObjectivesTo test the two independent hypotheses that when compared to placebo, addition of: (1) low dose dopamine; or (2) low dose nesiritide to diuretic therapy will enhance decongestion and preserve renal function in patients with acute heart failure and renal dysfunction.Background A primary treatment goal in acute heart failure is to achieve adequate decongestion while avoiding renal dysfunction and other side effects. Patients with acute heart failure and moderate or severe renal dysfunction are at risk for inadequate decongestion and worsening renal function - both of which are associated with worse outcomes. Renal adjuvant therapies that enhance decongestion and preserve renal function during treatment of acute heart failure are needed. Dopamine is an endogenous catecholamine which, at low doses, may selectively activate dopamine receptors and promote renal vasodilatation. Previous studies have suggested that the addition of low dose dopamine to diuretic therapy enhances decongestion and preserves renal function during diuretic therapy in acute heart failure; however, these studies were small with variable study designs and dopamine doses. B-type natriuretic peptide (BNP) is a cardiac peptide with vasodilating, renin and aldosterone inhibiting, natriuretic and diuretic properties. Nesiritide is human recombinant BNP approved for management of acute heart failure. The recommended dose lowers blood pressure and atrial pressures and produces modest improvement in dyspnea, but does not favorably impact clinical outcomes or renal function, potentially due to its hypotensive effects. Small studies using low dose nesiritide in acute heart failure and cardiac surgery patients have demonstrated favorable effects on urine output and renal function. Therefore, the Renal Optimization Strategies Evaluation (ROSE) trial was initiated to determine the benefits and safety of intravenous administration of low dose nesiritide or low dose dopamine in patients with congestive heart failure and kidney dysfunction. ParticipantsA total of 360 participants were enrolled. Design Participants were enrolled within 24 hours of hospital admission and randomized in a 1:1 ratio to the nesiritide or dopamine strategies. Participants randomized to the dopamine strategy were randomized in a double-blind 2:1 ratio to low dose dopamine (2 µg/kg/min for 72 hours infused via local guideline stipulated vascular access) or placebo. Participants randomized to the nesiritide strategy were randomized in a double-blind 2:1 ratio to low dose nesiritide (0.005 μg/kg/min for 72 hours infused via peripheral intravenous access without initial bolus) or placebo. All participants received open-label, intravenous loop diuretic treatment with a recommended total daily dose equal to 2.5x the total daily oral outpatient furosemide (or equivalent) dose at 7 days prior to admission up to a maximum of 600 mg/day. Participants naive to outpatient loop diuretics received 80 mg/day of intravenous furosemide. One-half of the total daily diuretic dose was administered as a bolus twice daily for at least 24 hours. Use of other medications and diuretic dosing after 24 hours were at the discretion of the clinician. All participants were placed on a 2000 mg sodium diet and 2000 cc fluid restriction. After the primary endpoint assessment at 72 hours, study drug was discontinued and subsequent treatment was at the clinician's discretion. The two co-primary endpoints were the 72-hour cumulative urinary volume as an index of decongestion efficacy and the change in cystatin-C from randomization to 72 hours as a measure of renal function preservation. Conclusions In participants with acute heart failure and renal dysfunction, neither low-dose dopamine nor low-dose nesiritide enhanced decongestion or improved renal function when added to diuretic therapy. Study Weblinks: BioLINCC Repository Study Design: Clinical Trial Study Type: Clinical Trial Total number of consented subjects: 360 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Heart Failure Network - Renal Optimization Strategies Evaluation in Acute Heart Failure and Reliable Evaluation of Dyspnea (HFN ROSE-BioLINCC)","short_name":"BL_HFN-ROSE_GRU","commons":"BioData Catalyst","study_url":"","_subjects_count":360,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs003593.v1.p1.c1":{"gen3_discovery":{"authz":null,"tags":null,"_unique_id":"phs003593.v1.p1.c1","study_id":"phs003593.v1.p1.c1","study_description":null,"full_name":null,"short_name":null,"commons":"BioData Catalyst","study_url":null,"_subjects_count":0,"__manifest":null,"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs003593.v1.p1.c2":{"gen3_discovery":{"authz":null,"tags":null,"_unique_id":"phs003593.v1.p1.c2","study_id":"phs003593.v1.p1.c2","study_description":null,"full_name":null,"short_name":null,"commons":"BioData Catalyst","study_url":null,"_subjects_count":0,"__manifest":null,"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs003593.v2.p1.c1":{"gen3_discovery":{"authz":"/programs/imaging/projects/img_FHS_HMB-IRB-MDS","tags":[],"_unique_id":"phs003593.v2.p1.c1","study_id":"phs003593.v2.p1.c1","study_description":"The Framingham Heart Study (FHS) is a population-based, observational cohort study initiated in 1948 to prospectively investigate the determinants of cardiovascular disease to guide public health prevention. The FHS began by recruiting an Original Cohort of 5,209 men and women between the ages of 30 and 62 from the town of Framingham, Massachusetts, who had not yet developed overt symptoms of cardiovascular disease or suffered a heart attack or stroke. The Original cohort Exam 1 took place between 1948 and 1953. Since that time the cohort has had a total of 32 biennial exams (ending in 2014) and event follow-up through 2022. In 1971, the FHS added the Offspring cohort, comprising 5124 children whose parents were enrolled in the Original cohort and the spouses of the children. This cohort on average has been examined every three to four years. However, there was an eight year gap between Exam 1 and Exam 2 and a seven year gap between Exam 7 and Exam 8. The latest exam (10) was completed in 2022. In 2002, the transgenerational FHS design was facilitated with the recruitment of 4095 children of the Offspring cohort (Third Generation), and 103 spouses of the Offspring who were not previously enrolled in the study (New Offspring Spouses, NOS). These cohorts have completed 3 exams through 2019. To reflect the changing demographic characteristics of the greater Framingham community, the FHS additionally recruited and enrolled 2 cohorts comprising racial and ethnic minority groups, termed Omni-1 and Omni-2, (n = 506 and 410, respectively) in 1995 and 2002, respectively. These cohorts included individuals of African American, Hispanic, Asian, Indian, Native American, and Pacific Islander descent. The OMNI-1 cohort have completed 5 exams through 2022. The OMNI-2 cohort have completed 3 exams through 2019. Data available for request include Echocardiogram images, available from the following exams in each cohort. Original Cohort: exams 18-32; Offspring cohort: exams 3-10; Third Generation, NOS and OMNI-2 cohorts: exams 1-3; OMNI-1 cohort: exams 1-5.CT image data at one or two timepoints were added for 4427 participants in the offspring, third generation, and OMNI1 and OMNI2 cohorts.Summary level phenotypes for the Framingham Cohort study participants can be viewed at the top-level study page phs000007 Framingham Cohort. Individual level phenotype data and molecular data for all Framingham top-level study and substudies are available by requesting Authorized Access to the Framingham Cohort study phs000007. Study Weblinks: The Framingham Heart Study NHLBI Framingham Heart Study Study Design: Prospective Longitudinal Cohort Study Type: Longitudinal Total number of consented subjects: 15448 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Framingham Heart Study-Cohort (FHS-Cohort) - Imaging","short_name":"img_FHS_HMB-IRB-MDS","commons":"BioData Catalyst","study_url":"","_subjects_count":13169,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs003593.v2.p1.c2":{"gen3_discovery":{"authz":"/programs/imaging/projects/img_FHS_HMB-IRB-NPU-MDS","tags":[],"_unique_id":"phs003593.v2.p1.c2","study_id":"phs003593.v2.p1.c2","study_description":"The Framingham Heart Study (FHS) is a population-based, observational cohort study initiated in 1948 to prospectively investigate the determinants of cardiovascular disease to guide public health prevention. The FHS began by recruiting an Original Cohort of 5,209 men and women between the ages of 30 and 62 from the town of Framingham, Massachusetts, who had not yet developed overt symptoms of cardiovascular disease or suffered a heart attack or stroke. The Original cohort Exam 1 took place between 1948 and 1953. Since that time the cohort has had a total of 32 biennial exams (ending in 2014) and event follow-up through 2022. In 1971, the FHS added the Offspring cohort, comprising 5124 children whose parents were enrolled in the Original cohort and the spouses of the children. This cohort on average has been examined every three to four years. However, there was an eight year gap between Exam 1 and Exam 2 and a seven year gap between Exam 7 and Exam 8. The latest exam (10) was completed in 2022. In 2002, the transgenerational FHS design was facilitated with the recruitment of 4095 children of the Offspring cohort (Third Generation), and 103 spouses of the Offspring who were not previously enrolled in the study (New Offspring Spouses, NOS). These cohorts have completed 3 exams through 2019. To reflect the changing demographic characteristics of the greater Framingham community, the FHS additionally recruited and enrolled 2 cohorts comprising racial and ethnic minority groups, termed Omni-1 and Omni-2, (n = 506 and 410, respectively) in 1995 and 2002, respectively. These cohorts included individuals of African American, Hispanic, Asian, Indian, Native American, and Pacific Islander descent. The OMNI-1 cohort have completed 5 exams through 2022. The OMNI-2 cohort have completed 3 exams through 2019. Data available for request include Echocardiogram images, available from the following exams in each cohort. Original Cohort: exams 18-32; Offspring cohort: exams 3-10; Third Generation, NOS and OMNI-2 cohorts: exams 1-3; OMNI-1 cohort: exams 1-5.CT image data at one or two timepoints were added for 4427 participants in the offspring, third generation, and OMNI1 and OMNI2 cohorts.Summary level phenotypes for the Framingham Cohort study participants can be viewed at the top-level study page phs000007 Framingham Cohort. Individual level phenotype data and molecular data for all Framingham top-level study and substudies are available by requesting Authorized Access to the Framingham Cohort study phs000007. Study Weblinks: The Framingham Heart Study NHLBI Framingham Heart Study Study Design: Prospective Longitudinal Cohort Study Type: Longitudinal Total number of consented subjects: 15448 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Framingham Heart Study-Cohort (FHS-Cohort) - Imaging","short_name":"img_FHS_HMB-IRB-NPU-MDS","commons":"BioData Catalyst","study_url":"","_subjects_count":2279,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs003594.v1.p1.c1":{"gen3_discovery":{"authz":"/programs/BioLINCC/projects/BL_FHS_HMB-IRB-MDS","tags":[],"_unique_id":"phs003594.v1.p1.c1","study_id":"phs003594.v1.p1.c1","study_description":"Data Access NOTE Please refer to the \"Authorized Access\" section below for information about how access to the data from this accession differs from many other dbGaP accessions. Related Studies Other Framingham data available include: Imaging studies (Framingham Heart Study-Cohort (FHS-Cohort)-Imaging, phs003593), Genetics and genomics (Framingham Cohort, phs000007), Collaborative Cohort of Cohorts for COVID-19 Research (C4R): (Framingham Heart Study, phs002911), and as a component of the Sleep Heart Health Study (SHHS-BioLINCC, phs003637). Available Data Original cohort: data now include examination data from the first 32 clinical exams, selected ancillary data, and event follow-up through 2018. Offspring/Omni1 cohort: Data available include Framingham Offspring examination data from the first 9 clinical exams and selected ancillary data and event follow-up through 2019. Also included are the first 4 exams from the OMNI 1 cohort. Third Generation/Omni2/New Offspring Cohort: Data available include Framingham Generation 3 examination data from the first 3 clinical exams, selected ancillary data and event follow-up through 2019. Also included are the OMNI 2 and New Offspring (NOS) cohorts. A genetic pedigree is not provided for the Framingham phenotype only data. Objectives The objectives of the Framingham Study are to study the incidence and prevalence of cardiovascular disease (CVD) and its risk factors, trends in CVD incidence and its risk factors over time, and familial patterns of CVD and risk factors. Other important objectives include the estimation of incidence rates of disease and description of the natural history of cardiovascular disease, including the sequence of clinical signs and systems that precede the clinically recognizable syndrome and the consequences and course of clinically manifest disease. Background Original cohort: The original cohort of the Framingham Study began in 1948 under the U.S. Public Health Service and was transferred under the direct operations of the new National Heart Institute, NIH, in 1949. Participants were sampled from Framingham, Massachusetts, including both men and women. This was the first prospective study of cardiovascular disease and identified the concept of risk factors and their joint effects. Offspring/Omni1 cohort: With the aging of the Framingham cohort and with interest in familiar aggregation and heritability, a new cohort consisting of the offspring of the original cohort was sampled. Spouses of offspring were also included. This new sample, began enrollment in 1971 and constituted a second generation of participants, permitting new assessment of risk factors and outcomes, and provided a resource for the genetic analyses which were yet to come. The Offspring participants have had repeated examinations, though at typically longer intervals than the original cohort. Third Generation/Omni2/New Offspring Cohort: Thirty-one years after enrollment began for the second generation of the Framingham Heart Study (Framingham Offspring Study), Framingham investigators began enrolling adults with at least one parent enrolled in the Offspring study into the Framingham Generation 3 cohort. The addition of the third generation was expected to facilitate investigation of secular trends in risk factors and indicators of health and disease within families, to enhance statistical power to detect genetic and environmental determinants of complex diseases, and to clarify how subclinical cardiovascular disease predicts occurrence of overt clinical events. Participants Original cohort: At entry to the study in 1948-1952, the study recruited 5,209 men and women, ages 28-62 years, living in Framingham, MA. Offspring/Omni1 cohort: 5,124 men and women, ages 5-70 years at entry consisting of offspring of the original Framingham cohort (and spouses of the offspring). In 1994, the Omni Cohort 1 enrolled 507 men and women of African-American, Hispanic, Asian, Indian, Pacific Islander and Native American origins, who at the time of enrollment were residents of Framingham and the surrounding towns. Third Generation/Omni2/New Offspring Cohort: 4095 men and women, almost all who self reported their ethnicity as white, ages 19+ years at entry, with at least one parent in the Framingham Offspring study, participated in the Gen III cohort. The New Offspring Cohort enrolled spouses of Offspring participants that were not otherwise enrolled and had at least two biological children participating in Gen III. 103 New Offspring Spouses (47 men and 56 women) participated. The OMNI 2 cohort enrolled additional ethnically diverse participants, including many individuals related to the participants of Omni Cohort 1 and also individuals unrelated to Omni Cohort 1 members for a total of 410 new participants. Design The cardiovascular disease conditions under investigation include coronary heart disease (angina pectoris, myocardial infarction, coronary insufficiency and sudden and non-sudden death), stroke, hypertension, peripheral arterial disease and congestive heart failure. Original cohort: The Framingham Study is a longitudinal investigation of constitutional and environmental factors influencing the development of CVD in men and women. Examination of participants has taken place every two years and the cohort has been followed for morbidity and mortality over that time period. Offspring/Omni1 cohort: By 1975, a sample of 5,124 men and women, consisting of offspring of the original Framingham cohort (and spouses of the offspring) had participated in the study. Additional studies of these subjects have continued under research contracts. Third Generation/Omni2/New Offspring Cohort: The children of Offspring Cohort participants were initially identified who would be 20 years of age or older by the end of the enrollment period. A higher priority for recruitment was assigned to individuals who belonged to large extended families, in order to complement phenotypic and genotypic information already obtained from prior generations. The baseline examination was begun in 2002 and completed in 2005. Study Weblinks: Framingham Heart Study Framingham original cohort-BioLINCC Framingham Offspring/Omni1 cohort-BioLINCC Framingham third generation/Omni2/New Offspring cohort-BioLINCC Study Design: Prospective Longitudinal Cohort Study Type: Cohort Longitudinal Cohort Observational Population Total number of consented subjects: 15447 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Framingham Heart Study-Cohort (FHS-Cohort) - BioLINCC","short_name":"BL_FHS_HMB-IRB-MDS","commons":"BioData Catalyst","study_url":"","_subjects_count":13168,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs003594.v1.p1.c2":{"gen3_discovery":{"authz":"/programs/BioLINCC/projects/BL_FHS_HMB-IRB-NPU-MDS","tags":[],"_unique_id":"phs003594.v1.p1.c2","study_id":"phs003594.v1.p1.c2","study_description":"Data Access NOTE Please refer to the \"Authorized Access\" section below for information about how access to the data from this accession differs from many other dbGaP accessions. Related Studies Other Framingham data available include: Imaging studies (Framingham Heart Study-Cohort (FHS-Cohort)-Imaging, phs003593), Genetics and genomics (Framingham Cohort, phs000007), Collaborative Cohort of Cohorts for COVID-19 Research (C4R): (Framingham Heart Study, phs002911), and as a component of the Sleep Heart Health Study (SHHS-BioLINCC, phs003637). Available Data Original cohort: data now include examination data from the first 32 clinical exams, selected ancillary data, and event follow-up through 2018. Offspring/Omni1 cohort: Data available include Framingham Offspring examination data from the first 9 clinical exams and selected ancillary data and event follow-up through 2019. Also included are the first 4 exams from the OMNI 1 cohort. Third Generation/Omni2/New Offspring Cohort: Data available include Framingham Generation 3 examination data from the first 3 clinical exams, selected ancillary data and event follow-up through 2019. Also included are the OMNI 2 and New Offspring (NOS) cohorts. A genetic pedigree is not provided for the Framingham phenotype only data. Objectives The objectives of the Framingham Study are to study the incidence and prevalence of cardiovascular disease (CVD) and its risk factors, trends in CVD incidence and its risk factors over time, and familial patterns of CVD and risk factors. Other important objectives include the estimation of incidence rates of disease and description of the natural history of cardiovascular disease, including the sequence of clinical signs and systems that precede the clinically recognizable syndrome and the consequences and course of clinically manifest disease. Background Original cohort: The original cohort of the Framingham Study began in 1948 under the U.S. Public Health Service and was transferred under the direct operations of the new National Heart Institute, NIH, in 1949. Participants were sampled from Framingham, Massachusetts, including both men and women. This was the first prospective study of cardiovascular disease and identified the concept of risk factors and their joint effects. Offspring/Omni1 cohort: With the aging of the Framingham cohort and with interest in familiar aggregation and heritability, a new cohort consisting of the offspring of the original cohort was sampled. Spouses of offspring were also included. This new sample, began enrollment in 1971 and constituted a second generation of participants, permitting new assessment of risk factors and outcomes, and provided a resource for the genetic analyses which were yet to come. The Offspring participants have had repeated examinations, though at typically longer intervals than the original cohort. Third Generation/Omni2/New Offspring Cohort: Thirty-one years after enrollment began for the second generation of the Framingham Heart Study (Framingham Offspring Study), Framingham investigators began enrolling adults with at least one parent enrolled in the Offspring study into the Framingham Generation 3 cohort. The addition of the third generation was expected to facilitate investigation of secular trends in risk factors and indicators of health and disease within families, to enhance statistical power to detect genetic and environmental determinants of complex diseases, and to clarify how subclinical cardiovascular disease predicts occurrence of overt clinical events. Participants Original cohort: At entry to the study in 1948-1952, the study recruited 5,209 men and women, ages 28-62 years, living in Framingham, MA. Offspring/Omni1 cohort: 5,124 men and women, ages 5-70 years at entry consisting of offspring of the original Framingham cohort (and spouses of the offspring). In 1994, the Omni Cohort 1 enrolled 507 men and women of African-American, Hispanic, Asian, Indian, Pacific Islander and Native American origins, who at the time of enrollment were residents of Framingham and the surrounding towns. Third Generation/Omni2/New Offspring Cohort: 4095 men and women, almost all who self reported their ethnicity as white, ages 19+ years at entry, with at least one parent in the Framingham Offspring study, participated in the Gen III cohort. The New Offspring Cohort enrolled spouses of Offspring participants that were not otherwise enrolled and had at least two biological children participating in Gen III. 103 New Offspring Spouses (47 men and 56 women) participated. The OMNI 2 cohort enrolled additional ethnically diverse participants, including many individuals related to the participants of Omni Cohort 1 and also individuals unrelated to Omni Cohort 1 members for a total of 410 new participants. Design The cardiovascular disease conditions under investigation include coronary heart disease (angina pectoris, myocardial infarction, coronary insufficiency and sudden and non-sudden death), stroke, hypertension, peripheral arterial disease and congestive heart failure. Original cohort: The Framingham Study is a longitudinal investigation of constitutional and environmental factors influencing the development of CVD in men and women. Examination of participants has taken place every two years and the cohort has been followed for morbidity and mortality over that time period. Offspring/Omni1 cohort: By 1975, a sample of 5,124 men and women, consisting of offspring of the original Framingham cohort (and spouses of the offspring) had participated in the study. Additional studies of these subjects have continued under research contracts. Third Generation/Omni2/New Offspring Cohort: The children of Offspring Cohort participants were initially identified who would be 20 years of age or older by the end of the enrollment period. A higher priority for recruitment was assigned to individuals who belonged to large extended families, in order to complement phenotypic and genotypic information already obtained from prior generations. The baseline examination was begun in 2002 and completed in 2005. Study Weblinks: Framingham Heart Study Framingham original cohort-BioLINCC Framingham Offspring/Omni1 cohort-BioLINCC Framingham third generation/Omni2/New Offspring cohort-BioLINCC Study Design: Prospective Longitudinal Cohort Study Type: Cohort Longitudinal Cohort Observational Population Total number of consented subjects: 15447 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Framingham Heart Study-Cohort (FHS-Cohort) - BioLINCC","short_name":"BL_FHS_HMB-IRB-NPU-MDS","commons":"BioData Catalyst","study_url":"","_subjects_count":2279,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs003599.v1.p1.c1":{"gen3_discovery":{"authz":"/programs/BioLINCC/projects/BL_HF-ACTION_HMB","tags":[],"_unique_id":"phs003599.v1.p1.c1","study_id":"phs003599.v1.p1.c1","study_description":"Accessing Data Please refer to “Authorized Access” below regarding accessing data through the BioData Catalyst ecosystem. The data from this accession is not available for download through dbGaP.ObjectivesThe HF-ACTION study examined whether exercise training reduces a composite endpoint of all-cause mortality or all-cause hospitalization for patients with left ventricular systolic dysfunction and heart failure symptoms. Background Heart failure (HF) is a major and growing cardiovascular syndrome that is the end result of many cardiovascular disorders. Although evidence-based drug and device therapies decrease mortality, hospitalizations, and HF symptoms and improve quality of life, many patients treated with these regimens often remain burdened by dyspnea and fatigue, diminished exercise tolerance, reduced quality of life, recurrent hospitalizations, and early mortality. Whereas rest was traditionally recommended for HF patients, there has been evidence that physical deconditioning may play a key role in the progression of symptoms and poor outcomes. Previous studies have shown positive effects of exercise training on exercise capacity, quality of life, and biomarkers and suggest that exercise training might improve survival and decrease HF hospitalizations. Nonetheless, there remains a safety concern regarding exercise training in HF and a large scale, multicenter, controlled clinical trial was needed to provide definitive clinical outcome data. Participants A total of 2,331 participants were randomized. 2,130 consented to share data with non-commercial entities, and 1,753 consented to share for commercial purposes. Design All participants underwent baseline cardiopulmonary exercise testing. Test results were reviewed by investigators to identify significant arrhythmias or ischemia that would prevent safe exercise training, to determine appropriate levels of exercise training, and to establish training heart rate ranges. Demographics, socioeconomic status, past medical history, current medications, physical exam, and the most recent laboratory tests were obtained prior to randomization. All participants received detailed self-management educational materials which included information on medications, fluid management, symptom exacerbation, sodium intake, and physical activity. Participants randomized to the exercise training arm first participated in a structured, group-based, supervised exercise program, with a goal of 3 sessions per week for a total of 36 sessions in 3 months. The primary exercises were walking, treadmill, or stationary cycling. Exercise was initiated at 15 to 30 minutes per session at a heart rate corresponding to 60% of heart rate reserve, and was increased after 6 sessions to 30 to 35 minutes duration and 70% of heart rate reserve. Participants began home-based exercise after completing 18 supervised sessions and were to fully transition to home exercise after 36 supervised sessions. The target training regimen for home exercise was 5 times per week for 40 minutes at a heart rate of 60% to 70% of heart rate reserve. Participants randomized to the usual care group were not provided with a formal exercise prescription. To provide comparable levels of attention from study personnel, all participants were called every 2 weeks for the first 9 months, monthly until 24 months of follow-up, and quarterly thereafter. Participants returned for clinic visits every 3 months for the first 2 years of participation and yearly thereafter for up to 4 years. Follow-up assessments included cardiopulmonary exercise testing, a 6-minute walk test, and a physical activity questionnaire. The primary end point was a composite of all-cause mortality or all-cause hospitalization. Secondary end points included all-cause mortality, the composite of cardiovascular mortality or cardiovascular hospitalization, and the composite of cardiovascular mortality or HF hospitalization. Conclusions After adjustment for highly prognostic predictors of the primary end point, exercise training was associated with modestly significant reductions for both all-cause mortality or hospitalization and cardiovascular mortality or heart failure hospitalization. Study Weblinks: BioLINCC Repository Study Design: Clinical Trial Study Type: Clinical Trial Total number of consented subjects: 2130 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Heart Failure: A Controlled Trial Investigating Outcomes of Exercise Training (HF-ACTION-BioLINCC)","short_name":"BL_HF-ACTION_HMB","commons":"BioData Catalyst","study_url":"","_subjects_count":1753,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs003599.v1.p1.c2":{"gen3_discovery":{"authz":"/programs/BioLINCC/projects/BL_HF-ACTION_HMB-NPU","tags":[],"_unique_id":"phs003599.v1.p1.c2","study_id":"phs003599.v1.p1.c2","study_description":"Accessing Data Please refer to “Authorized Access” below regarding accessing data through the BioData Catalyst ecosystem. The data from this accession is not available for download through dbGaP.ObjectivesThe HF-ACTION study examined whether exercise training reduces a composite endpoint of all-cause mortality or all-cause hospitalization for patients with left ventricular systolic dysfunction and heart failure symptoms. Background Heart failure (HF) is a major and growing cardiovascular syndrome that is the end result of many cardiovascular disorders. Although evidence-based drug and device therapies decrease mortality, hospitalizations, and HF symptoms and improve quality of life, many patients treated with these regimens often remain burdened by dyspnea and fatigue, diminished exercise tolerance, reduced quality of life, recurrent hospitalizations, and early mortality. Whereas rest was traditionally recommended for HF patients, there has been evidence that physical deconditioning may play a key role in the progression of symptoms and poor outcomes. Previous studies have shown positive effects of exercise training on exercise capacity, quality of life, and biomarkers and suggest that exercise training might improve survival and decrease HF hospitalizations. Nonetheless, there remains a safety concern regarding exercise training in HF and a large scale, multicenter, controlled clinical trial was needed to provide definitive clinical outcome data. Participants A total of 2,331 participants were randomized. 2,130 consented to share data with non-commercial entities, and 1,753 consented to share for commercial purposes. Design All participants underwent baseline cardiopulmonary exercise testing. Test results were reviewed by investigators to identify significant arrhythmias or ischemia that would prevent safe exercise training, to determine appropriate levels of exercise training, and to establish training heart rate ranges. Demographics, socioeconomic status, past medical history, current medications, physical exam, and the most recent laboratory tests were obtained prior to randomization. All participants received detailed self-management educational materials which included information on medications, fluid management, symptom exacerbation, sodium intake, and physical activity. Participants randomized to the exercise training arm first participated in a structured, group-based, supervised exercise program, with a goal of 3 sessions per week for a total of 36 sessions in 3 months. The primary exercises were walking, treadmill, or stationary cycling. Exercise was initiated at 15 to 30 minutes per session at a heart rate corresponding to 60% of heart rate reserve, and was increased after 6 sessions to 30 to 35 minutes duration and 70% of heart rate reserve. Participants began home-based exercise after completing 18 supervised sessions and were to fully transition to home exercise after 36 supervised sessions. The target training regimen for home exercise was 5 times per week for 40 minutes at a heart rate of 60% to 70% of heart rate reserve. Participants randomized to the usual care group were not provided with a formal exercise prescription. To provide comparable levels of attention from study personnel, all participants were called every 2 weeks for the first 9 months, monthly until 24 months of follow-up, and quarterly thereafter. Participants returned for clinic visits every 3 months for the first 2 years of participation and yearly thereafter for up to 4 years. Follow-up assessments included cardiopulmonary exercise testing, a 6-minute walk test, and a physical activity questionnaire. The primary end point was a composite of all-cause mortality or all-cause hospitalization. Secondary end points included all-cause mortality, the composite of cardiovascular mortality or cardiovascular hospitalization, and the composite of cardiovascular mortality or HF hospitalization. Conclusions After adjustment for highly prognostic predictors of the primary end point, exercise training was associated with modestly significant reductions for both all-cause mortality or hospitalization and cardiovascular mortality or heart failure hospitalization. Study Weblinks: BioLINCC Repository Study Design: Clinical Trial Study Type: Clinical Trial Total number of consented subjects: 2130 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Heart Failure: A Controlled Trial Investigating Outcomes of Exercise Training (HF-ACTION-BioLINCC)","short_name":"BL_HF-ACTION_HMB-NPU","commons":"BioData Catalyst","study_url":"","_subjects_count":377,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs003621.v1.p1.c1":{"gen3_discovery":{"authz":"/programs/BioLINCC/projects/BL_GUIDE-IT_GRU","tags":[{"name":"dbGaP","category":"Study Registration"}],"_unique_id":"phs003621.v1.p1.c1","study_id":"phs003621.v1.p1.c1","study_description":"Accessing Data: Please refer to “Authorized Access” below regarding accessing data through the BioData Catalyst ecosystem. The data from this accession is not available for download through dbGaP.Objective: To determine whether an amino-terminal pro-B-type natriuretic peptide (NT-pro-BNP)-guided treatment strategy improves clinical outcomes vs usual care in high-risk patients with heart failure (HF) and reduced ejection fraction (HFrEF).Background: Heart failure is a common disorder. Standard treatment for HF includes diuretics to control fluid, and drugs called \"neurohormonal antagonists\" (such as beta-blockers and ACE-inhibitors) to help the heart work more efficiently. The natriuretic peptides, specifically NT-pro-BNP, are biomarkers that reflect HF severity and are significantly associated with adverse outcomes in HF. Smaller studies have evaluated adjusting HF therapy based on natriuretic peptide levels (“guided therapy”) with inconsistent results.Participants: A total of 894 participants were enrolled at 45 sites in the United States and Canada, with 446 randomized to the NT-pro-BNP-guided strategy treatment group and 448 randomized to the usual care treatment group.Design: GUIDE-IT was a multicenter randomized clinical trial with participants randomized to either the NT-pro-BNP-guided therapy strategy or usual care. Given the nature of the study intervention, treatment assignment was not blinded. For participants randomized to the NT-pro-BNP-guided strategy, clinicians were instructed to titrate HF therapy to target an NT-pro-BNP level <1,000 pg/mL. Specific adjustments of therapy for individual participants were at the discretion of the treating physician, but sites were encouraged to prioritize titration of neurohormonal antagonists over diuretics unless there was clinical evidence of congestion or volume overload. For participants in either group, investigators were provided with the most recent American Heart Association (AHA)/American College of Cardiology (ACC) practice guidelines for the management of HF and specific information on target doses of proven medical therapies.After an initial visit at 2 and 6 weeks, visits occurred every 3 months throughout the remainder of the study. After therapy adjustment for HF (whether driven by NT-pro-BNP levels or clinical reasons), participants had a 2-week follow-up visit for reassessment. All participants in either group also had blinded NT-pro-BNP concentrations measured in a core laboratory at each study visit. The primary end point was the composite of time-to-first HF hospitalization or cardiovascular mortality. Secondary end points included all-cause mortality, total hospitalizations for HF, days alive and not hospitalized for cardiovascular reasons, the individual components on the primary end point, and adverse events. Conclusions: The guided strategy intervention was stopped in July of 2016 (median follow-up of 15 months) after the study met prespecified inefficacy criteria. Compared to usual care, a strategy of NT-pro-BNP-guided therapy was not more effective in improving time-to-first HF hospitalization or cardiovascular mortality in high-risk participants with HFrEF. Study Weblinks: BioLINCC Repository Study Design: Clinical Trial Study Type: Clinical Trial Total number of consented subjects: 894 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Guiding Evidence Based Therapy Using Biomarker Intensified Treatment in Heart Failure (GUIDE-IT-BioLINCC)","short_name":"BL_GUIDE-IT_GRU","commons":"BioData Catalyst","study_url":"https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs003621.v1.p1","_subjects_count":894,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs003637.v1.p1.c1":{"gen3_discovery":{"authz":null,"tags":null,"_unique_id":"phs003637.v1.p1.c1","study_id":"phs003637.v1.p1.c1","study_description":null,"full_name":null,"short_name":null,"commons":"BioData Catalyst","study_url":null,"_subjects_count":0,"__manifest":null,"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs003637.v2.p1.c1":{"gen3_discovery":{"authz":"/programs/BioLINCC/projects/BL_SHHS_NSRR_HMB-MDS","tags":[],"_unique_id":"phs003637.v2.p1.c1","study_id":"phs003637.v2.p1.c1","study_description":"Data Access NOTE: Please refer to the “Authorized Access” section below for information about how access to the data from this accession differs from many other dbGaP accessions.Related StudiesParent cohort phenotype data can be accessed through ARIC-BioLINCC, Framingham-BioLINCC, and CHS-BioLINCC. Objectives To determine the cardiovascular and other consequences of sleep-disordered breathing and to test whether sleep-disordered breathing is associated with an increased risk of coronary heart disease, stroke, all-cause mortality and hypertension by examining subjects from well-characterized and established epidemiologic cohorts. Background Obstructive sleep apnea syndrome (OSA) is a potentially debilitating condition characterized by repetitive episodes of apnea while asleep, nocturnal oxygen desaturation, excessive daytime sleepiness, and loud disruptive snoring. Epidemiologic data from middle-aged adults indicate that OSA is common, with prevalence rates of 4% in men and 2% in women. Prior studies implicated OSA as a risk factor for the development of hypertension, ischemic heart disease, congestive heart failure, stroke and consequently premature death. Questions arose as to whether an increased propensity for cardiovascular and cerebrovascular diseases was limited to only those with frank OSA or whether more subtle forms of sleep-disordered breathing (SDB) would also confer elevated risk. Further evidence was also needed to clarify whether, SDB, including OSA, is an independent risk factor for the development of cardiovascular or cerebrovascular disease. Known cardiovascular and cerebrovascular disease risk factors such as obesity and smoking are commonly present in those with SDB; therefore, apparent associations between SDB and cardiovascular and cerebrovascular diseases may have resulted from the effects of these concomitant risk factors. Moreover, there was no understanding as to whether such factors as race, age, gender, and prevalent cardiovascular or cerebrovascular disease might interact with SDB to alter future cardiovascular and cerebrovascular disease risk. Mechanisms underlying any propensity to develop cardiovascular or cerebrovascular disease with SDB had not been firmly established (Quan, et al., 1997, PMID: 9493915). Participants Participants in SHHS were recruited from nine existing NHLBI epidemiological studies in which data on cardiovascular risk factors had been collected previously. The “parent” cohorts included: Two sites of the Atherosclerosis Risk in Communities Study (ARIC) Three sites of the Cardiovascular Health Study (CHS) The Framingham Offspring Cohort The Strong Heart Study (SHS) sites in South Dakota, Oklahoma, and Arizona The New York Hypertension Cohorts The Tucson Epidemiologic Study of Airways Obstructive Diseases and the Health and Environment Study From these parent cohorts, a sample of participants who met the inclusion criteria (age 40 years or older; no history of treatment of sleep apnea; no tracheostomy; no current home oxygen therapy) was invited to participate in the baseline examination of the SHHS, which included an initial polysomnogram (SHHS-1). Several cohorts over-sampled snorers in order to increase the study-wide prevalence of sleep-disordered breathing. In all, 6441 individuals were enrolled between November 1, 1995 and January 31, 1998. During exam cycle 3 (January 2001-June 2003), a second polysomnogram (SHHS-2) was obtained in 3295 of the participants. Due to sovereignty issues, Strong Heart Study participants are not included in the shared SHHS data. Data from a total of 5839 participants (1920 ARIC, 1249 CHS, 997 Framingham Offspring and OMNI 1, and 1673 from other studies), consenting to share data are available. Design The Sleep Heart Health Study added in-home polysomnography to the data collected in each of the parent studies at a baseline SHHS exam and a follow-up approximately 4 years later. Using the Compumedics PS polysomnograph, sleep studies were obtained in an unattended setting, usually in the homes of the participants, by trained and certified technicians. The recording montage consisted of: C3/A2 and C4/A1 EEGs, sampled at 125 Hz right and left electrooculograms (EOGs), sampled at 50 Hz a bipolar submental electromyogram (EMG), sampled at 125 Hz thoracic and abdominal excursions (THOR and ABDO), recorded by inductive plethysmography bands and sampled at 10 Hz \"airflow\" detected by a nasal-oral thermocouple (Protec, Woodinville, WA), sampled at 10 Hz finger-tip pulse oximetry (Nonin, Minneapolis, MN) sampled at 1 Hz ECG from a bipolar lead, sampled at 125 Hz for most SHHS-1 studies and 250 Hz for SHHS-2 studies Heart rate (PR) derived from the ECG and sampled at 1 Hz body position (using a mercury gauge sensor) ambient light (on/off, by a light sensor secured to the recording garment)This montage provides data on the occurrence of sleep-disordered breathing, sleep stages, heart rate, oximetry and on arousals. Each participant in the parent studies was also asked to complete the Sleep Habits Questionnaire which covers usual sleep pattern, snoring, and sleepiness. Study Weblinks: BioLINCC Sleep Heart Health Study Study Design: Prospective Longitudinal Cohort Study Type: Observational Total number of consented subjects: 5839 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Sleep Heart Health Study (SHHS-BioLINCC-NSRR)","short_name":"BL_SHHS_NSRR_HMB-MDS","commons":"BioData Catalyst","study_url":"","_subjects_count":5839,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs003639.v1.p1.c1":{"gen3_discovery":{"authz":"/programs/imaging/projects/img_CHS_HMB-MDS","tags":[{"name":"dbGaP","category":"Study Registration"}],"_unique_id":"phs003639.v1.p1.c1","study_id":"phs003639.v1.p1.c1","study_description":"The Cardiovascular Health Study (CHS) is a prospective study of risk factors for development and progression of coronary heart disease (CHD) and stroke in people aged 65 years and older. The 5,888 study participants were recruited from four U.S. communities and have undergone extensive clinic examinations for evaluation of markers of subclinical cardiovascular disease. The original cohort, enrolled in 1989-90, totaled 5,201 participants. A supplemental cohort of 687 predominantly African-American participants was enrolled in 1992-93. Clinic examinations were performed at study baseline and at annual visits through 1998-1999, and again in 2005-2006. Examination components included medical and personal history, medication inventory, ECG, blood pressure, anthropometry, assessment of physical and cognitive function, and depression screening. Other components done less frequently included phlebotomy, spirometry, echocardiography, carotid ultrasound, cerebral magnetic resonance imaging, measurement of ankle-brachial index and retinal exam. Participants were contacted by telephone annually between exams to collect information about hospitalizations and potential cardiovascular events. Since 1999, participants have been contacted every six months by phone, primarily to identify cardiovascular events and to assess physical and cognitive health. Standard protocols for the identification and adjudication of events were implemented during follow-up. The adjudicated events are myocardial infarction, angina, heart failure (HF), stroke, transient ischemic attack (TIA), claudication, and mortality. Study Weblinks: Cardiovascular Health Study Study Design: Prospective Longitudinal Cohort Study Type: Cohort Total number of consented subjects: 5539 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Cardiovascular Health Study (CHS) - Imaging","short_name":"img_CHS_HMB-MDS","commons":"BioData Catalyst","study_url":"https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs003639.v1.p1","_subjects_count":5350,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs003639.v1.p1.c2":{"gen3_discovery":{"authz":"/programs/imaging/projects/img_CHS_HMB-NPU-MDS","tags":[{"name":"dbGaP","category":"Study Registration"}],"_unique_id":"phs003639.v1.p1.c2","study_id":"phs003639.v1.p1.c2","study_description":"The Cardiovascular Health Study (CHS) is a prospective study of risk factors for development and progression of coronary heart disease (CHD) and stroke in people aged 65 years and older. The 5,888 study participants were recruited from four U.S. communities and have undergone extensive clinic examinations for evaluation of markers of subclinical cardiovascular disease. The original cohort, enrolled in 1989-90, totaled 5,201 participants. A supplemental cohort of 687 predominantly African-American participants was enrolled in 1992-93. Clinic examinations were performed at study baseline and at annual visits through 1998-1999, and again in 2005-2006. Examination components included medical and personal history, medication inventory, ECG, blood pressure, anthropometry, assessment of physical and cognitive function, and depression screening. Other components done less frequently included phlebotomy, spirometry, echocardiography, carotid ultrasound, cerebral magnetic resonance imaging, measurement of ankle-brachial index and retinal exam. Participants were contacted by telephone annually between exams to collect information about hospitalizations and potential cardiovascular events. Since 1999, participants have been contacted every six months by phone, primarily to identify cardiovascular events and to assess physical and cognitive health. Standard protocols for the identification and adjudication of events were implemented during follow-up. The adjudicated events are myocardial infarction, angina, heart failure (HF), stroke, transient ischemic attack (TIA), claudication, and mortality. Study Weblinks: Cardiovascular Health Study Study Design: Prospective Longitudinal Cohort Study Type: Cohort Total number of consented subjects: 5539 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Cardiovascular Health Study (CHS) - Imaging","short_name":"img_CHS_HMB-NPU-MDS","commons":"BioData Catalyst","study_url":"https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs003639.v1.p1","_subjects_count":171,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs003639.v1.p1.c3":{"gen3_discovery":{"authz":"/programs/imaging/projects/img_CHS_DS-CVD-MDS","tags":[{"name":"dbGaP","category":"Study Registration"}],"_unique_id":"phs003639.v1.p1.c3","study_id":"phs003639.v1.p1.c3","study_description":"The Cardiovascular Health Study (CHS) is a prospective study of risk factors for development and progression of coronary heart disease (CHD) and stroke in people aged 65 years and older. The 5,888 study participants were recruited from four U.S. communities and have undergone extensive clinic examinations for evaluation of markers of subclinical cardiovascular disease. The original cohort, enrolled in 1989-90, totaled 5,201 participants. A supplemental cohort of 687 predominantly African-American participants was enrolled in 1992-93. Clinic examinations were performed at study baseline and at annual visits through 1998-1999, and again in 2005-2006. Examination components included medical and personal history, medication inventory, ECG, blood pressure, anthropometry, assessment of physical and cognitive function, and depression screening. Other components done less frequently included phlebotomy, spirometry, echocardiography, carotid ultrasound, cerebral magnetic resonance imaging, measurement of ankle-brachial index and retinal exam. Participants were contacted by telephone annually between exams to collect information about hospitalizations and potential cardiovascular events. Since 1999, participants have been contacted every six months by phone, primarily to identify cardiovascular events and to assess physical and cognitive health. Standard protocols for the identification and adjudication of events were implemented during follow-up. The adjudicated events are myocardial infarction, angina, heart failure (HF), stroke, transient ischemic attack (TIA), claudication, and mortality. Study Weblinks: Cardiovascular Health Study Study Design: Prospective Longitudinal Cohort Study Type: Cohort Total number of consented subjects: 5539 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Cardiovascular Health Study (CHS) - Imaging","short_name":"img_CHS_DS-CVD-MDS","commons":"BioData Catalyst","study_url":"https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs003639.v1.p1","_subjects_count":2,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs003639.v1.p1.c4":{"gen3_discovery":{"authz":"/programs/imaging/projects/img_CHS_DS-CVD-NPU-MDS","tags":[{"name":"dbGaP","category":"Study Registration"}],"_unique_id":"phs003639.v1.p1.c4","study_id":"phs003639.v1.p1.c4","study_description":"The Cardiovascular Health Study (CHS) is a prospective study of risk factors for development and progression of coronary heart disease (CHD) and stroke in people aged 65 years and older. The 5,888 study participants were recruited from four U.S. communities and have undergone extensive clinic examinations for evaluation of markers of subclinical cardiovascular disease. The original cohort, enrolled in 1989-90, totaled 5,201 participants. A supplemental cohort of 687 predominantly African-American participants was enrolled in 1992-93. Clinic examinations were performed at study baseline and at annual visits through 1998-1999, and again in 2005-2006. Examination components included medical and personal history, medication inventory, ECG, blood pressure, anthropometry, assessment of physical and cognitive function, and depression screening. Other components done less frequently included phlebotomy, spirometry, echocardiography, carotid ultrasound, cerebral magnetic resonance imaging, measurement of ankle-brachial index and retinal exam. Participants were contacted by telephone annually between exams to collect information about hospitalizations and potential cardiovascular events. Since 1999, participants have been contacted every six months by phone, primarily to identify cardiovascular events and to assess physical and cognitive health. Standard protocols for the identification and adjudication of events were implemented during follow-up. The adjudicated events are myocardial infarction, angina, heart failure (HF), stroke, transient ischemic attack (TIA), claudication, and mortality. Study Weblinks: Cardiovascular Health Study Study Design: Prospective Longitudinal Cohort Study Type: Cohort Total number of consented subjects: 5539 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Cardiovascular Health Study (CHS) - Imaging","short_name":"img_CHS_DS-CVD-NPU-MDS","commons":"BioData Catalyst","study_url":"https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs003639.v1.p1","_subjects_count":5,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs003654.v1.p1.c1":{"gen3_discovery":{"authz":"/programs/BioLINCC/projects/BL_SCD-HeFT_GRU","tags":[{"name":"dbGaP","category":"Study Registration"}],"_unique_id":"phs003654.v1.p1.c1","study_id":"phs003654.v1.p1.c1","study_description":"Data Access NOTE: Please refer to the “Authorized Access” section below for information about how access to the data from this accession differs from many other dbGaP accessions. Objectives The Sudden Cardiac Death in Heart Failure Trial (SCD-HeFT) was designed to evaluate the hypothesis that amiodarone or a conservatively programmed shock-only, single-lead implantable cardioverter defibrillator (ICD) would decrease the risk of death from any cause in a broad population of patients with mild-to-moderate heart failure. Background Patients with congestive heart failure (CHF) can die suddenly and unpredictably from arrhythmia despite the use of proven medical therapies, such as beta-blockade. Two approaches have been developed to prevent sudden death among patients with CHF: therapy with amiodarone and therapy with an ICD. However, most of the mortality data on amiodarone and ICD therapy at the time of the study had been obtained in clinical trials performed after myocardial infarction in patients without CHF or those with ventricular arrhythmias. Thus, more data was needed to guide these therapies in patients who did not meet these criteria. Participants There were a total of 2521 participants. 847 were randomly assigned to placebo, 845 to amiodarone, and 829 to ICD therapy. Design Before randomization, participants underwent electrocardiography, a 6-minute walk test, 24-hour ambulatory electrocardiography, liver and thyroid function studies, and chest radiography. Participants were required, if clinically reasonable, to receive treatment with a beta-blocker and an angiotensin-converting-enzyme inhibitor, as well as an aldosterone antagonist, aspirin, and statins, when appropriate. Participants were randomly assigned in equal proportions to receive placebo, amiodarone, or a single-chamber ICD programmed to shock-only mode. Participants assigned to amiodarone or matching placebo began therapy as outpatients immediately after randomization. Placebo and amiodarone were administered as a loading dose of 800 mg/day for one week, 400 mg/day for three weeks, and then as a daily maintenance dosage according to weight and bradycardia status. Participants assigned to ICD therapy received their device a median of three days after randomization. The goal of ICD therapy was to treat only rapid, sustained ventricular tachycardia or ventricular fibrillation. Dual-chamber or biventricular devices, or antitachycardia or rate-response pacing therapies were not permitted. The ICD was uniformly programmed to have a detection rate of 187 beats per minute or more. Antibradycardia pacing was initiated only if the intrinsic rate decreased to less than 34 beats per minute. Median follow-up was 45.5 months. The primary end point was death from any cause. Secondary outcome measures included cardiac mortality, arrhythmic mortality, morbidity, quality of life, and incremental cost-effectiveness of the interventions. Each active treatment arm was compared to the placebo drug arm. Conclusions In participants with NYHA class II or III CHF and LVEF of 35% or less, amiodarone had no favorable effect on survival, whereas single-lead, shock-only ICD therapy reduced overall mortality by 23%. Study Weblinks: BioLINCC Repository Study Design: Clinical Trial Study Type: Clinical Trial Total number of consented subjects: 2521 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Sudden Cardiac Death in Heart Failure Trial (SCD-HeFT-BioLINCC)","short_name":"BL_SCD-HeFT_GRU","commons":"BioData Catalyst","study_url":"https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs003654.v1.p1","_subjects_count":2521,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs003665.v1.p1.c1":{"gen3_discovery":{"authz":"/programs/BioLINCC/projects/BL_TOPCAT_HMB-MDS","tags":[],"_unique_id":"phs003665.v1.p1.c1","study_id":"phs003665.v1.p1.c1","study_description":"Data Access NOTEPlease refer to the \"Authorized Access\" section below for information about how access to the data from this accession. Access differs from many other dbGaP accessions. BiospecimensAccess to Biospecimens is through the NHLBI Biologic Specimen and Data Repository Information Coordinating Center (BioLINCC). Biospecimens from TOPCAT include Buffy Coat, DNA, Plasma, Serum, Urine, and Whole Blood. Please note that use of biospecimens in genetic research is subject to a tiered consent. Objectives The TOPCAT trial evaluated the effectiveness of aldosterone antagonist therapy in reducing cardiovascular mortality, aborted cardiac arrest, and heart failure hospitalization in patients who have heart failure with preserved systolic function. Background Many patients with heart failure have a normal, or near-normal, left ventricular ejection fraction (LVEF). Such patients share similar signs and symptoms as patients who have heart failure and a reduced LVEF, as well as an impaired quality of life and a poor prognosis. However, at the time of TOPCAT, the benefit of medical therapies for heart failure were limited to those with a reduced LVEF. Due to a lack of favorable evidence from clinical trials, clinical guidelines offered no specific recommendations for the management of heart failure in patients with preserved LVEF, except for attention to coexisting conditions. Among patients with heart failure and a reduced LVEF and those with myocardial infarction complicated by heart failure and left ventricular dysfunction, mineralocorticoid receptor antagonists have been shown to be effective in reducing overall mortality and hospitalizations for heart failure. In small mechanistic studies involving patients with heart failure and preserved left ventricular function, mineralocorticoid receptor antagonists improved measures of diastolic function. However, rigorous testing was needed regarding their effect on clinical outcomes in patients with preserved LVEF. Therefore, the TOPCAT trial was initiated to determine whether treatment with spironolactone, an aldosterone antagonist, would improve clinical outcomes in patients with symptomatic heart failure and a relatively preserved LVEF. Participants A total of 3445 participants were enrolled, with 1722 assigned to the spironolactone group and 1723 assigned to the placebo group. Among these, 2464 participants were enrolled via the hospitalization stratum and 981 were enrolled via the BNP stratum. Design TOPCAT was a phase 3, multicenter, international, randomized, double-blind, and placebo controlled trial. Eligible participants were randomly assigned to receive either spironolactone or placebo in a 1:1 ratio. Randomization was stratified according to whether the patient met the criterion for previous hospitalization or BNP elevation. The baseline visit included assessment of socio-demographics, physical characteristics, medical history, lifestyle factors, laboratory measures, electrocardiography variables and health-related quality of life and functional status. Study drugs were initially administered at a dose of 15 mg once daily, which was increased as tolerated to a maximum of 45 mg daily during the first four months after randomization. Subsequent dose adjustments were made as required and subjects continued to receive other treatments for heart failure and co-existing illnesses. Measurement of potassium and creatinine levels was required within 1 week after a change in the study-drug dose and at each scheduled study visit. Follow-up visits to monitor symptoms, medications, and events and to dispense study drug were scheduled every four months during the subject's first year on the study, and every six months thereafter. The mean follow-up interval was 3.3 years in each study group. Repository blood and urine samples were collected at the baseline and 1 year visits from consenting subjects. The primary endpoint was a composite of cardiovascular mortality, aborted cardiac arrest or hospitalization for the management of heart failure. Secondary endpoints included all-cause mortality, hospitalization for heart failure management, new onset of diabetes mellitus or atrial fibrillation, and quality of life. A subset of subjects also participated in the Echocardiography or Echocardiography and Vascular Stiffness ancillary studies. Echocardiography, and additionally tonometry in the Echocardiography and Vascular Stiffness study, were performed at baseline and at either 12 or 18 months following randomization. If the subject was already enrolled in the TOPCAT trial at the time the ancillary study was initiated, but had not yet reached the 18 month visit, baseline was determined via a retrospective analysis performed on any echocardiographic images completed within 60 days prior to TOPCAT enrollment and no tonometry was performed if applicable. Conclusions In patients with heart failure and a preserved ejection fraction, treatment with spironolactone did not significantly reduce the incidence of the primary composite outcome of death from cardiovascular causes, aborted cardiac arrest, or hospitalization for the management of heart failure. However, the drug reduced the secondary endpoint of heart failure hospitalization incidence. Study Weblinks: BioLINCC Repository Study Design: Clinical Trial Study Type: Clinical Trial Total number of consented subjects: 3445 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Treatment of Preserved Cardiac Function Heart Failure with an Aldosterone Antagonist (TOPCAT-BioLINCC)","short_name":"BL_TOPCAT_HMB-MDS","commons":"BioData Catalyst","study_url":"","_subjects_count":3445,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs003667.v1.p1.c1":{"gen3_discovery":{"authz":"/programs/BioLINCC/projects/BL_HFN-INDIE_GRU","tags":[],"_unique_id":"phs003667.v1.p1.c1","study_id":"phs003667.v1.p1.c1","study_description":"Data Access NOTEPlease refer to the “Authorized Access” section below for information about how access to the data from this accession differs from many other dbGaP accessions.ObjectiveTo determine the effect of inhaled, nebulized inorganic nitrite on exercise capacity in patients with heart failure with preserved ejection fraction. Background Approximately half of patients with heart failure have a preserved ejection fraction (HFpEF). However, there are no proven effective medical treatments for this syndrome. Evidence suggests that impairments in nitric oxide availability have a potentially important role in the pathophysiology of HFpEF. Unlike organic nitrates, inorganic nitrite is converted to nitric oxide in the presence of hypoxia and acidosis, conditions that develop during exercise. Because the cardiac, vascular, and skeletal muscle abnormalities that limit physical capacity and contribute to symptoms in patients with HFpEF characteristically develop during exercise, inorganic nitrite may provide the best way to target nitric oxide delivery precisely at the time of greatest need. The HFN-INDIE trial was initiated to test the hypothesis that compared to placebo, longer-term use of inhaled, nebulized inorganic nitrite would enhance peak exercise capacity in patients with HFpEF. Participants A total of 105 participants were randomized. 53 were randomized to receive nitrite first and 52 were randomized to receive placebo first. Design HFN-INDIE was a multicenter, randomized, double-blind, placebo-controlled, crossover study. After enrollment, patients underwent baseline studies to determine eligibility. All patients were required to display objective exercise limitation, evidenced by reduced peak oxygen consumption (V̇O2) on cardiopulmonary exercise testing of less than 75% predicted, with a respiratory exchange ratio indicative of maximal effort (≥1.0). Following qualifying exercise testing, eligible participants received an open-label, single-dose run-in of inhaled, nebulized sodium nitrite (80 mg) to assess tolerability, symptoms, and orthostatic vital signs. Patients developing hypotension (systolic blood pressure <90 mm Hg seated or standing), light-headedness, or any other intolerance were categorized as a run-in failure and were not randomized. Following the baseline studies, eligible patients were randomly assigned to either receive nitrite first or to receive placebo first. Study drug was administered 3 times a day by nebulizer. During each 6-week period, patients were instructed to take no study drug for the first 2 weeks (baseline phase during the first period and washout phase during the second period), followed by 46 mg 3 times daily for 1 week, and then 80 mg 3 times daily for 3 weeks. After the first period, patients returned to the study center to receive the crossover study drug. The prespecified primary end point was peak V̇o2, measured as the highest 30-second average during upright cycle ergometry, during the 4-week period in which patients were receiving inorganic nitrite as compared with placebo. Accelerometry, health-related quality-of-life scores on the self-administered Kansas City Cardiomyopathy Questionnaire (score range, 0-100, with higher scores indicating better quality of life), echocardiographic indicators of cardiac filling pressures measured at trough drug levels (E/e' ratio, estimated pulmonary artery systolic pressure, and left atrial volume index; lower scores indicate better health for all), ventilatory efficiency (VE/V̇co2, lower indicating better health), exercise time (higher indicating better health), and NT-proBNP levels (lower indicating better health) were also collected. Conclusions Among patients with HFpEF, administration of inhaled inorganic nitrite for 4 weeks, compared with placebo, did not result in significant improvement in exercise capacity. Borlaug et al., 2018, PMID: 30398602. Study Weblinks: BioLINCC Repository Study Design: Clinical Trial Study Type: Clinical Trial Total number of consented subjects: 105 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Heart Failure Network: Inorganic Nitrite Delivery to Improve Exercise Capacity in HFpEF (HFN INDIE-BioLINCC)","short_name":"BL_HFN-INDIE_GRU","commons":"BioData Catalyst","study_url":"","_subjects_count":105,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs003668.v1.p1.c1":{"gen3_discovery":{"authz":"/programs/BioLINCC/projects/BL_SOLVD_GRU","tags":[],"_unique_id":"phs003668.v1.p1.c1","study_id":"phs003668.v1.p1.c1","study_description":"Data Access NOTE:Please refer to the \"Authorized Access\" section below for information about how access to the data from this accession. Access differs from many other dbGaP accessions. ObjectivesThis study was initiated in 1986, primarily to evaluate the effects of enalapril, an ACE inhibitor, on long-term mortality and major morbidity in a group of participants with left ventricular dysfunction. Two large separate trials were run concurrently as part of SOLVD: 1) a prevention trial of participants with low ejection fraction but no overt symptoms of CHF and, 2) a treatment trial of participants with low ejection fraction and symptoms of CHF. In addition, participants at selected sites were entered into substudies to evaluate the effect of enalapril on a number of intermediate outcomes such as right and left ventricular function and hemodynamics, LV mass and wall stress, hormones, arrhythmias, exercise capacity, and quality of life in subsets of participants. Lastly, a registry of 6,336 participants with congestive heart failure of LV dysfunction was designed to describe the clinical course of an unselected group of participants. Background Congestive Heart Failure (CHF) is a major and increasingly recognized public health problem. The recognition that participants with CHF often have elevated peripheral vascular resistance has led to the introduction of vasodilator therapy, which has emerged as an important component of its treatment. Of the vasodilators, the angiotensin-converting enzyme (ACE) inhibitors appeared to be the most promising. In 1985, little was known about the impact of any long-term drug treatment on survival. SOLVD Registry: The SOLVD Registry is a hospital-based observational study, conducted at selected SOLVD hospitals, of participants with at least moderate left-ventricular dysfunction (EF ≤ 45%) and/or radiologically confirmed heart failure. It consists of a main study (n=6,273) and a substudy (n=898). Although there is overlap between the Registry and the SOLVD trials, the Registry sample is not a subset of SOLVD nor is it the pool of participants eligible for both trials. Participants A total of 2,569 participants were enrolled into the treatment study and 4,228 participants were enrolled in the prevention study. The dataset available through the NHLBI contains the prevention and treatment study data as well as the registry data. Conclusions In the prevention trial, a significant reduction in the incidence of heart failure and the rate of related hospitalizations was observed for participants in the enalapril arm. A statistically significant reduction in mortality was not observed in the enalapril treatment arm; however, there was a trend toward fewer total deaths and deaths due to cardiovascular causes among the enalapril participants (SOLVD Investigators, et al., 1992, PMID: 1463530). Study Weblinks: BioLINCC Repository Study Design: Clinical Trial Study Type: Clinical Trial Observational Total number of consented subjects: 11939 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Studies of Left Ventricular Dysfunction (SOLVD-BioLINCC)","short_name":"BL_SOLVD_GRU","commons":"BioData Catalyst","study_url":"","_subjects_count":11939,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs003702.v1.p1.c1":{"gen3_discovery":{"authz":"/programs/imaging/projects/img_MESA_ECHO_HMB","tags":[],"_unique_id":"phs003702.v1.p1.c1","study_id":"phs003702.v1.p1.c1","study_description":"The Multi-Ethnic Study of Atherosclerosis (MESA) is a study of the characteristics of subclinical cardiovascular disease (disease detected non-invasively before it has produced clinical signs and symptoms) and the risk factors that predict progression to clinically overt cardiovascular disease or progression of the subclinical disease. MESA researchers study a diverse, population-based sample of 6,814 asymptomatic men and women aged 45-84. Thirty-eight percent of the recruited participants are white, 28 percent African-American, 22 percent Hispanic, and 12 percent Asian, predominantly of Chinese descent. Echocardiogram Image Repository includes Echocardiogram Images performed during MESA Exam 6 conducted between 2016 and 2018. Study Weblinks: The Multi-Ethnic Study of Atherosclerosis Study Design: Prospective Longitudinal Cohort Study Type: Cohort Total number of consented subjects: 6814 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Multi-Ethnic Study of Atherosclerosis (Echocardiogram Image Repository)","short_name":"img_MESA_ECHO_HMB","commons":"BioData Catalyst","study_url":"","_subjects_count":2471,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs003702.v1.p1.c2":{"gen3_discovery":{"authz":"/programs/imaging/projects/img_MESA_ECHO_HMB-NPU","tags":[],"_unique_id":"phs003702.v1.p1.c2","study_id":"phs003702.v1.p1.c2","study_description":"The Multi-Ethnic Study of Atherosclerosis (MESA) is a study of the characteristics of subclinical cardiovascular disease (disease detected non-invasively before it has produced clinical signs and symptoms) and the risk factors that predict progression to clinically overt cardiovascular disease or progression of the subclinical disease. MESA researchers study a diverse, population-based sample of 6,814 asymptomatic men and women aged 45-84. Thirty-eight percent of the recruited participants are white, 28 percent African-American, 22 percent Hispanic, and 12 percent Asian, predominantly of Chinese descent. Echocardiogram Image Repository includes Echocardiogram Images performed during MESA Exam 6 conducted between 2016 and 2018. Study Weblinks: The Multi-Ethnic Study of Atherosclerosis Study Design: Prospective Longitudinal Cohort Study Type: Cohort Total number of consented subjects: 6814 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Multi-Ethnic Study of Atherosclerosis (Echocardiogram Image Repository)","short_name":"img_MESA_ECHO_HMB-NPU","commons":"BioData Catalyst","study_url":"","_subjects_count":771,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs003703.v1.p1.c1":{"gen3_discovery":{"authz":"/programs/imaging/projects/img_MESA_ECG_HMB","tags":[{"name":"dbGaP","category":"Study Registration"}],"_unique_id":"phs003703.v1.p1.c1","study_id":"phs003703.v1.p1.c1","study_description":"The Multi-Ethnic Study of Atherosclerosis (MESA) is a study of the characteristics of subclinical cardiovascular disease (disease detected non-invasively before it has produced clinical signs and symptoms) and the risk factors that predict progression to clinically overt cardiovascular disease or progression of the subclinical disease. MESA researchers study a diverse, population-based sample of 6,814 asymptomatic men and women aged 45-84. Thirty-eight percent of the recruited participants are white, 28 percent African-American, 22 percent Hispanic, and 12 percent Asian, predominantly of Chinese descent. Electrocardiogram Tracing Repository includes ECG tracings performed during MESA Exam 1 conducted between 2000 and 2002 and during MESA Exam 5 conducted between 2010 and 2012. Study Weblinks: The Multi-Ethnic Study of Atherosclerosis Study Design: Prospective Longitudinal Cohort Study Type: Cohort Total number of consented subjects: 6814 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Multi-Ethnic Study of Atherosclerosis (Electrocardiogram Tracing Repository)","short_name":"img_MESA_ECG_HMB","commons":"BioData Catalyst","study_url":"https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs003703.v1.p1","_subjects_count":6203,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs003703.v1.p1.c2":{"gen3_discovery":{"authz":"/programs/imaging/projects/img_MESA_ECG_HMB-NPU","tags":[{"name":"dbGaP","category":"Study Registration"}],"_unique_id":"phs003703.v1.p1.c2","study_id":"phs003703.v1.p1.c2","study_description":"The Multi-Ethnic Study of Atherosclerosis (MESA) is a study of the characteristics of subclinical cardiovascular disease (disease detected non-invasively before it has produced clinical signs and symptoms) and the risk factors that predict progression to clinically overt cardiovascular disease or progression of the subclinical disease. MESA researchers study a diverse, population-based sample of 6,814 asymptomatic men and women aged 45-84. Thirty-eight percent of the recruited participants are white, 28 percent African-American, 22 percent Hispanic, and 12 percent Asian, predominantly of Chinese descent. Electrocardiogram Tracing Repository includes ECG tracings performed during MESA Exam 1 conducted between 2000 and 2002 and during MESA Exam 5 conducted between 2010 and 2012. Study Weblinks: The Multi-Ethnic Study of Atherosclerosis Study Design: Prospective Longitudinal Cohort Study Type: Cohort Total number of consented subjects: 6814 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Multi-Ethnic Study of Atherosclerosis (Electrocardiogram Tracing Repository)","short_name":"img_MESA_ECG_HMB-NPU","commons":"BioData Catalyst","study_url":"https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs003703.v1.p1","_subjects_count":794,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs003708.v1.p1.c1":{"gen3_discovery":{"authz":"/programs/COVID19/projects/ACTIV4_HostTissue_GRU","tags":[],"_unique_id":"phs003708.v1.p1.c1","study_id":"phs003708.v1.p1.c1","study_description":"ACTIV 4 Host Tissue is a shared-placebo clinical trial platform evaluating therapies targeting the host response to COVID-19 in hospitalized patients. The overarching goal of the platform was to find effective strategies for inpatient management of patients with COVID-19. Therapeutic goals for patients hospitalized for COVID-19 include hastening recovery and preventing progression to critical illness, multiorgan failure, or death. Our objective is to determine whether modulating the host tissue response improves clinical outcomes among patients with COVID-19. Three trials were implemented to investigate three agents: TXA-127, TRV-027, and Fostamatinib. These agents all impact the host tissue response in COVID-19 via a number of unique mechanisms, including potential beneficial effects on the RAAS system and formation of neutrophil extracellular traps (NETs). Each trial evaluated the efficacy of these agents' ability to impact the host tissue response and improve outcomes in patients hospitalized with COVID-19. We found no evidence that any of the three agents significantly improved clinical outcomes as measured by the primary outcome, oxygen free days through day 28. Study Design: Clinical Trial Study Type: Clinical Trial Interventional Longitudinal Multicenter Phase III Placebo-Controlled Randomized Randomized Controlled Clinical Trial Total number of consented subjects: 899 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"CONNECTS Master Protocol for Clinical Trials targeting Macro- and Micro-Immuno-Thrombosis, Vascular Hyperinflammation, and Hypercoagulability and Renin-Angiotensin-Aldosterone System (RAAS) in Hospitalized Patients with COVID-19 (ACTIV-4 Host Tissue)","short_name":"ACTIV4_HostTissue_GRU","commons":"BioData Catalyst","study_url":"","_subjects_count":899,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs003714.v1.p1.c1":{"gen3_discovery":{"authz":"/programs/BioLINCC/projects/BL_ARDSNet_ALVEOLI_GRU","tags":[],"_unique_id":"phs003714.v1.p1.c1","study_id":"phs003714.v1.p1.c1","study_description":"Data Access NOTE: Please refer to the \"Authorized Access\" section below for information about how access to the data from this accession differs from many other dbGaP accessions. BiospecimensAccess to Biospecimens is through the NHLBI Biologic Specimen and Data Repository Information Coordinating Center (BioLINCC). Biospecimens from ARDSNet-ALVEOLI include Plasma and DNA. Please note that use of biospecimens in genetic research is subject to a tiered consent. Available Data Outcome data regarding organ failure free days are not available. Objectives The ARDS Network is a consortium of clinical centers and a coordinating center to design and test novel therapies for the treatment of Acute Lung Injury (ALI) and Acute Respiratory Distress Syndrome (ARDS). The ARDS Network 01/03 trials included an investigation of the efficacy and safety of Ketoconazole and Respiratory Management in the treatment of ALI and ARDS (KARMA). The Ketoconazole arm of the KARMA study was later stopped due to an inability to show efficacy. Participants continued to be randomized to the respiratory management arms of the study (ARMA), which compared two ventilator strategies: a tidal volume of 6 mL/kg versus 12 mL/kg. The LARMA phase of the study investigated the efficacy of Lisofylline and Respiratory Management. The objective of the ALVEOLI study was to compare clinical outcomes of participants with ALI and ARDS treated with a higher end-expiratory lung volume/lower FiO2 versus a lower end-expiratory lung volume/higher FiO2 ventilation strategy. The ALVEOLI study tested the hypothesis that mortality from ALI and ARDS would be reduced with a mechanical ventilation strategy designed to prevent lung injury from repeated collapse of bronchioles and alveoli at end-expiration. Background Most participants requiring mechanical ventilation for ALI and ARDS receive positive end-expiratory pressure (PEEP) of 5 to 12 cm of water. Higher PEEP levels may improve oxygenation and reduce ventilator-induced lung injury but may also cause circulatory depression and lung injury from overdistention. PEEP levels higher than traditional levels may reduce ventilator-induced lung injury by decreasing the proportion of nonaerated lung and higher PEEP levels may allow arterial-oxygenation goals to be met at a lower level of inspired oxygen (FiO2). Participants A total of 550 participants were randomized to receive mechanical ventilation with either lower or higher PEEP levels, which were set according to different tables of predetermined combinations of PEEP and fraction of inspired oxygen. Conclusions Participants with acute lung injury and ARDS who receive mechanical ventilation with a tidal-volume goal of 6 ml per kilogram of predicted body weight and an end-inspiratory plateau-pressure limit of 30 cm of water, clinical outcomes were statistically similar whether lower or higher PEEP levels are used. (Brower, et al., 1004; PMID: 15269312). Study Weblinks: BioLINCC Repository Study Design: Clinical Trial Study Type: Clinical Trial Total number of consented subjects: 550 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Acute Respiratory Distress Network (ARDSNet) Study 04 Assessment of Low Tidal Volume and Elevated End-Expiratory Volume to Obviate Lung Injury (ALVEOLI-BioLINCC)","short_name":"BL_ARDSNet_ALVEOLI_GRU","commons":"BioData Catalyst","study_url":"","_subjects_count":550,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs003726.v1.p1.c1":{"gen3_discovery":{"authz":"/programs/BioLINCC/projects/BL_ROC_Cardiac_Epistry_3_GRU","tags":[],"_unique_id":"phs003726.v1.p1.c1","study_id":"phs003726.v1.p1.c1","study_description":"Data Access NOTE: Please refer to the “Authorized Access” section below for information about how access to the data from this accession differs from many other dbGaP accessions. Available Data The ROC Cardiac Epistry version 3 include all cardiac arrest cases entered into the ROC database from April 1, 2011 to June 30, 2015. This is separate from versions 1 and 2 because of the major changes in how and which data were collected. Version 3 represents the following major changes to the structure and data collection: separate ED Arrival and Hospital Admits forms, mandatory ED and Hospital elements and a revamped CPR Process form. For ROC traumatic injury Epistry data please see: ROC-Trauma Epistry Objectives To build a prospective population-based registry of participants with out-of-hospital cardiac arrest responded to by Emergency Medical Services (EMS). Specific aims included: to establish whether the results of Resuscitation Outcomes Consortium (ROC) trials can be generalized to the larger population of participants that experience cardiac arrest; to more fully establish the burden of cardiac arrest; and to examine the relationships between variation in EMS structure and process, regional and periodic factors, and participant outcomes. Background Cardiac arrest is a common, serious, debilitating and costly public health problem. Although there has been a steady decline in morbidity and mortality from most cardiovascular diseases, high mortality rates for out-of-hospital cardiac arrests continue to pose a challenge for healthcare providers and a significant public health burden. The Resuscitation Outcomes Consortium (ROC) was established in 2004 to conduct clinical research in the areas of cardiopulmonary arrest and life-threatening traumatic injury with the overall goal of improving resuscitation outcomes. Participant and care characteristics can predict favorable outcomes in cardiac arrests, but there is still a wide variation in outcomes that is not well understood. EMS factors such as service level, number of responding providers, use of procedures or drugs in the field, training, quality assurance/feedback, and response time intervals also vary significantly by region. Variations in geographic, socioeconomic and periodic factors may also be associated with differences in outcomes. Prior to ROC Cardiac Epistry, there were no North American population-based registries for out-of-hospital cardiac arrests. Therefore there was a need for standardized data collection of out-of-hospital cardiac arrests in diverse geographic locations in order to identify the independent effects of prognostic or treatment factors accounting for variations in survival. Participants There were 120,306 participants. Design ROC Epistry collected standardized data regarding episode-specific factors, participant demographics, clinical information, pre-hospital interventions and disposition, hospital information, and participant outcome for all out-of-hospital cardiac arrests in the ROC regions. Each ROC site had to ensure capture of all eligible cases within the EMS service areas. Out-of-hospital data were extracted from existing databases whenever possible and augmented with targeted review of EMS reports. Hospital data were abstracted directly from the hospital file in most cases. Alternative methods included linkage to death registries and obituaries if the death occurred within 30 days. Sites submitted data using a web-based interface or batch uploads. Participants were not contacted directly. Study Weblinks: BioLINCC Repository Study Design: Prospective Longitudinal Cohort Study Type: Observational Total number of consented subjects: 120306 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Resuscitation Outcomes Consortium (ROC) Cardiac Epidemiologic Registry (Cardiac Epistry) Version 3 (ROC-Cardiac Epistry 3-BioLINCC)","short_name":"BL_ROC_Cardiac_Epistry_3_GRU","commons":"BioData Catalyst","study_url":"","_subjects_count":120306,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs003730.v1.p1.c1":{"gen3_discovery":{"authz":"/programs/BioLINCC/projects/BL_BEST_GRU","tags":[],"_unique_id":"phs003730.v1.p1.c1","study_id":"phs003730.v1.p1.c1","study_description":"Data Access NOTE: Please refer to the “Authorized Access” section below for information about how access to the data from this accession differs from many other dbGaP accessions. Objectives The Beta-Blocker Evaluation of Survival Trial was designed to determine whether bucindolol hydrochloride- a nonselective beta-adrenergic blocker and mild vasodilator- would reduce the rate of death from any cause among patients with advanced heart failure and to assess its effects in various subgroups defined by ethnic background and demographic criteria- specifically women and members of minority groups. Background Although beta-adrenergic-receptor antagonists reduce morbidity and Mortality in participants with mild-to-moderate chronic heart failure, their effort on survival in participants with more advanced heart failure is unknown. Participants There were 2,708 participants. Conclusions Bucindolol resulted in no significant overall survival benefit. (Krause-Steinrauf et al., 2001, PMID: 11386264). Study Weblinks: BioLINCC Repository Study Design: Clinical Trial Study Type: Clinical Trial Total number of consented subjects: 2707 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Beta-Blocker Evaluation in Survival Trial (BEST-BioLINCC)","short_name":"BL_BEST_GRU","commons":"BioData Catalyst","study_url":"","_subjects_count":2707,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs003734.v1.p1.c1":{"gen3_discovery":{"authz":"/programs/BioLINCC/projects/BL_ARDSNet_ARMA_KARMA_LARMA_GRU","tags":[],"_unique_id":"phs003734.v1.p1.c1","study_id":"phs003734.v1.p1.c1","study_description":"Data Access NOTE: Please refer to the “Authorized Access” section below for information about how access to the data from this accession differs from many other dbGaP accessions. Biospecimens Access to Biospecimens is through the NHLBI Biologic Specimen and Data Repository Information Coordinating Center (BioLINCC). Biospecimens from ARDSNet-ARMA/KARMA/LARMA include plasma, serum and urine. Please note that use of biospecimens in genetic research is subject to a tiered consent. Objectives The ARDS Network is a consortium of clinical centers and a coordinating center to design and test novel therapies for the treatment of Acute Lung Injury (ALI) and Acute Respiratory Distress Syndrome (ARDS). The primary objective of the KARMA trial was to investigate the efficacy and safety of Ketoconazole and Respiratory Management in the treatment of ALI and ARDS. The Ketoconazole arm of the study was later stopped due to an inability to show efficacy. Participants continued to be randomized to the respiratory management arms of the study (ARMA), which compared two ventilator strategies: a tidal volume of 6 mL/kg versus 12 mL/kg. The LARMA phase of the study investigated the efficacy of Lisofylline and Respiratory Management. Background Participants suffering from ARDS are extremely ill, require mechanical ventilation and, despite improvements in medical care and technology, had a mortality rate as high as 50 percent. An excessive inflammatory response is characteristic of ALI of which ARDS represents the most severe end of the pathophysiologic spectrum. The inflammatory response includes increased numbers of neutrophils activated to produce cytokines, proteases, and reactive oxygen intermediates. Pulmonary injury may also be enhanced by alveolar and tissue macrophages as a producer of vasoactive substances, neutrophil chemoattractants, and procoagulant substances. Ketoconazole, a synthetic antifungal imidazole, also has anti-inflammatory activities and may inhibit neutrophil recruitment via several different pathways known to be involved in the development of ALI and ARDS. Lisofylline causes a marked decrease in the circulating levels of the major oxidizable species of free fatty acids and also inhibits proinflammatory intracellular signaling. Mechanical ventilation in participants with ALI and ARDS have traditionally used tidal volumes of 10 to 15 ml per kilogram of body weight. These large tidal volumes are often necessary to achieve normal partial pressure of arterial carbon dioxide and pH, but may induce inflammatory responses through disruption of pulmonary epithelium and endothelium. Mechanical ventilation at lower tidal volumes may reduce injurious lung stretch and decrease the inflammatory response. Participants The Ketoconazole and Lisofylline trials were designed as 2 x 2 factorials and included 220 participants in each trial. A total of 860 participants were randomized into the ventilator management trial. Participants enrolled in the Lisofylline or Ketoconozole studies had to be concurrently enrolled in the ventilator management study and were first randomized into a ventilator strategy and then to drug or placebo. Conclusions Ketoconazole was found to be safe but did not reduce mortality, duration of mechanical ventilation, or improve lung function. Lisofylline was also found to be safe and to have no beneficial effect for participants with ALI or ARDS. Ventilation at lower tidal volumes resulted in reduced mortality and an increase in the number of days without ventilator support. (PMIDs: 10789668, 11902249, 10793162). Study Weblinks: BioLINCC Repository Study Design: Clinical Trial Study Type: Clinical Trial Total number of consented subjects: 902 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Acute Respiratory Distress Network (ARDSNet) Studies 01 and 03 Lower Versus Higher Tidal Volume, Ketoconazole Treatment and Lisofylline Treatment (ARMA/KARMA/LARMA) (ARDSNet-ARMA/KARMA/LARMA-BioLINCC)","short_name":"BL_ARDSNet_ARMA_KARMA_LARMA_GRU","commons":"BioData Catalyst","study_url":"","_subjects_count":902,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs003736.v1.p1.c1":{"gen3_discovery":{"authz":"/programs/BioLINCC/projects/BL_ARDSNet_SAILS_HMB-MDS","tags":[],"_unique_id":"phs003736.v1.p1.c1","study_id":"phs003736.v1.p1.c1","study_description":"Data Access NOTE: Please refer to the “Authorized Access” section below for information about how access to the data from this accession differs from many other dbGaP accessions. Biospecimens Access to Biospecimens is through the NHLBI Biologic Specimen and Data Repository Information Coordinating Center (BioLINCC). Biospecimens from ARDSNet-SAILS include Plasma, DNA, and Urine. Please note that use of biospecimens in genetic research is subject to a tiered consent. Objectives The SAILS trial was intended to assess the efficacy and safety of oral rosuvastatin in participants with sepsis-induced Acute Lung Injury (ALI) and test the hypothesis that rosuvastatin therapy would improve the clinical outcomes of critically ill participants with sepsis-associated acute respiratory distress syndrome (ARDS). Background In ARDS, inflammation in the lungs and other organs can cause life-threatening organ failure. Inhibitors of 3-hydroxy-3-methylglutaryl coenzyme A reductase (statins) can modulate inflammatory responses. Previous observational studies suggested that statins improved clinical outcomes in participants with sepsis. Participants There were 745 participants. Design Participants were randomly assigned in permuted blocks to receive either enteral rosuvastatin or placebo. A 40 mg loading dose of the study drug was administered within four hours after randomization. Subsequently, maintenance doses of 20 mg were administered daily until the third day after discharge from the intensive care unit, study day 28, hospital discharge, or death, whichever came first. The primary outcome measure was mortality before hospital discharge home or until study day 60 if the participant was still in a health care facility. Secondary outcome measures included the number of ventilator-free days to day 28, organ-failure-free days to day 14, and ICU-free days to day 28. Conclusions The study was stopped because of futility after 745 of an estimated 1000 participants had been enrolled. There was no significant difference between study groups in 60 day in-hospital mortality or in mean ventilator-free days. The rosuvastatin group had fewer days free of hepatic or renal failure. Thus, rosuvastatin therapy did not improve clinical outcomes in participants with sepsis-associated ARDS and may have contributed to hepatic and renal organ dysfunction. Study Weblinks: BioLINCC Repository Study Design: Clinical Trial Study Type: Clinical Trial Total number of consented subjects: 745 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Acute Respiratory Distress Network (ARDSNet) Studies 10 and 12 Statins for Acutely Injured Lungs from Sepsis (SAILS) (ARDSNet-SAILS-BioLINCC)","short_name":"BL_ARDSNet_SAILS_HMB-MDS","commons":"BioData Catalyst","study_url":"","_subjects_count":745,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs003737.v1.p1.c1":{"gen3_discovery":{"authz":"/programs/Individual_Study/projects/UTMB_HeLP_GRU","tags":[],"_unique_id":"phs003737.v1.p1.c1","study_id":"phs003737.v1.p1.c1","study_description":"Data Access NOTE: Please refer to the “Authorized Access” section below for information about how access to the data from this study.Objectives: The HeLP study assessed how early case management, financial incentives contingent on cardiac-rehabilitation attendance, or both impacted adherence to cardiac rehabilitation among patients with lower socioeconomic status (SES) who had a cardiac-rehabilitation-qualifying diagnosis. Background:Cardiovascular disease (CVD) is the leading cause of death in the United States. Regular attendance at cardiac rehabilitation (CR) is the number one recommendation for patients who have experienced a recent cardiac event. CR is a secondary prevention outpatient program involving an individually tailored structured exercise program along with counseling and encouragement regarding lifestyle changes to reduce the recurrence of major cardiac events.Despite the benefits of CR attendance, enrollment and adherence to the program are low. This is particularly true of individuals of lower socioeconomic status (SES), who also generally suffer a higher burden from CVD on account of higher-risk cardiac profiles. As these profiles are the result of modifiable behavior targeted by CR (i.e., smoking, obesity, lack of physical activity), methods of increasing CR attendance among this population are necessary.Case management and financial incentives contingent on CR attendance are two potential strategies for addressing this issue. Previous studies have shown how trained case managers can support and assist patients with attending CR and improving their cardiac health, and how financial incentives can promote various types of health-related behavior. The purpose of the present study was to evaluate how these two interventions, individually and in tandem, fared at improving CR adherence among individuals of lower SES specifically. Participants:A total of 314 participants were screened, and 209 were randomized. All consented to have their data shared for research purposes. Design:Eligible patients were approached either while still in the hospital or during initial visits to CR. After obtaining informed consent, clinical and demographic characteristics (i.e., age, sex, education, race and ethnicity, smoking status, and CR-qualifying diagnosis) and depressive symptoms were collected. Participants then were randomized 2:3:3:3 to usual care (UC), case management starting in hospital (CM), financial incentives for attending CR (FI), or financial incentives plus case management (FICM). For all participants regardless of condition, an appropriate referral for CR was confirmed after randomization. Over the course of the study participants completed three assessments – one at intake, one after four months, and one after one year. Clinical (i.e., cardiorespiratory fitness, body composition, and cardiac-related quality of life) and sociocognitive (i.e., Beck Depression Inventory, Achenbach System of Empirically Based Assessment, and Behavior Rating Inventory of Executive Function) measures were obtained at each assessment. Participants randomized to the UC condition were contacted weekly by study staff for adverse event checks, but received no additional intervention. Participants randomized to the CM condition were immediately assigned a case manager. Case managers met with their participants, usually within 24 hours of consent while they were still in the hospital, to introduce themselves during an initial check-in. Within the first week of consent they completed a longer, more thorough initial needs assessment with their participant and established behavioral goals. For the next 16 weeks, case managers met with their participants at least once a week, typically over the phone, to discuss progress on these goals and address any problems or barriers that had arisen. Case managers also were available via phone outside of these regular meetings during normal working hours and Saturday mornings. Participants randomized to the FI condition could earn money for completing an initial CR orientation and attending CR sessions. Twenty dollars could be earned for completing the CR orientation session. CR attendance was reinforced on an escalating schedule starting at $10. Payments increased by $2 for each successive session attended, and capped out at a maximum of $40 per session. Unexcused absences resulted in the incentives for that session not being earned, and the potential earnings for the next scheduled session being reset to $10. Successful participation of two consecutive sessions following the reset resulted in the incentives being returned to the amount prior to the reset. In total, participants could earn $1220 for attending the initial orientation and all 36 sessions of CR. The primary outcome of interest was the percentage of participants who completed at least 30 sessions of CR. Secondary outcomes included the number of sessions completed, cardiorespiratory fitness (peak VO2 and estimated metabolic equivalents (METs)), body composition (waist circumference and BMI), depression scores, and both general and cardiac-related qualify of life. Conclusions:The two interventions involving financial incentives (i.e., financial incentives alone and financial incentives plus case management) significantly improved CR adherence compared to usual care. Subsequent analyses revealed that the combination of financial incentives and case management led to greater improvements in CR attendance than financial incentives alone. Study Design: Clinical Trial Study Type: Clinical Trial Total number of consented subjects: 192 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Incentives and Case Management to Improve Cardiac Care: Healthy Lifestyle Program (HeLP)","short_name":"UTMB_HeLP_GRU","commons":"BioData Catalyst","study_url":"","_subjects_count":192,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs003738.v1.p1.c1":{"gen3_discovery":{"authz":"/programs/BioLINCC/projects/BL_ARIC_HMB-NPU-MDS","tags":[],"_unique_id":"phs003738.v1.p1.c1","study_id":"phs003738.v1.p1.c1","study_description":"Data Access NOTE:Please refer to the “Authorized Access” section below for information about how access to the data from this accession differs from many other dbGaP accessions. At present, the ARIC sIRB has determined that ARIC data cannot be shared with for-profit entities.Related Studies Other ARIC data available include: Imaging studies (ARIC-Imaging), Genetics and genomics (ARIC, phs000280.v8.p2), Collaborative Cohort of Cohorts for COVID-19 Research (C4R): ARIC (phs002988.v1.p1), and as a component of the Sleep Heart Health Study (SHHS-BioLINCC, phs003637.v1.p1). Available Data Data available for request include ARIC v1-v8 examination cycles, collated annual follow-up communication data for contact years 2-32, and follow-up for mortality, heart disease, and stroke events through 2019. Also included are data from ancillary studies. Objectives The objectives of ARIC are to: 1) investigate associations of factors, including those not previously measured in cohort studies, with prevalence of atherosclerosis and incidence of CHD, clinical stroke and other cardiovascular diseases; and 2) measure cardiovascular disease occurrence and trends and relate these to community levels of, and changes in, risk factors, medical care and atherosclerosis. Background At the time of project initiation, the NHLBI had long recognized the need for longitudinal studies to identify the biochemical and physiological markers and specific environmental factors which place individuals at high risk for the major atherosclerosis diseases. The development of reliable ultrasound examination of peripheral arteries enhanced the expected benefit of such studies. Community surveillance planning began for ARIC in response to recommendations of the 1978 NHLBI Workshop on the Decline in CHD Mortality and has been extended in its purpose to evaluate the large geographic differences in U.S. mortality. Participants Black and white men and women, age 45-64 at entry; sample size: 15,792. Design ARIC is a large-scale, long-term prospective study that measures associations of established and suspected coronary heart disease risk factors with both atherosclerosis and new CHD events in men and women from four geographically diverse communities. The project has two components: community surveillance of morbidity and mortality; and repeated examinations of a representative cohort of men and women in each community. The community surveillance involves abstracting hospital records and death certificates and investigating out-of-hospital deaths. The representative cohorts include approximately 4,000 persons from each community. Community surveillance data includes detailed hospital record abstraction, ECG tracings, and event adjudication. Data from out-of-hospital events in the community include physician, informant, and coroner questionnaires as well as death certificate data and event adjudication. Community surveillance ended in 2014.Cohort participants were examined four times at three year intervals between 1987 and 1998, and have been continuously contacted annually to update their medical histories. Atherosclerosis was measured by carotid ultrasonography. Risk factors studied include: blood lipids, lipoprotein cholesterols, and apolipoproteins; plasma hemostatic factors; blood chemistries and hematology; sitting, supine and standing blood pressures; anthropometry; fasting blood glucose and insulin levels; ECG findings; cigarette and alcohol use; physical activity levels; dietary aspects; and family history. Clinic visits were restarted in 2011 with ARIC visit 5. Study Weblinks: ARIC BioLINCC Study Design: Prospective Longitudinal Cohort Study Type: Cohort Longitudinal Cohort Observational Population Total number of consented subjects: 15277 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Atherosclerosis Risk in Communities Study (ARIC-BioLINCC)","short_name":"BL_ARIC_HMB-NPU-MDS","commons":"BioData Catalyst","study_url":"","_subjects_count":15277,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs003739.v1.p1.c1":{"gen3_discovery":{"authz":"/programs/BioLINCC/projects/BL_CARDIA_HMB-MDS","tags":[],"_unique_id":"phs003739.v1.p1.c1","study_id":"phs003739.v1.p1.c1","study_description":"Data Access NOTE: Please refer to the “Authorized Access” section below for information about how access to the data from this accession differs from many other dbGaP accessions.Related Studies: Other CARDIA data available include:phs000236.v2.p2 PAGE: CALiCo: Coronary Artery Risk Development in Young Adults(CARDIA) phs000309.v3.p2 The CARDIA-GENEVA Study phs000399.v1.p2 NHLBI GO-ESP: Heart Cohorts Exome Sequencing Project (CARDIA) phs000613.v1.p2 NHLBI CARDIA Candidate Gene Association Resource (CARe) phs003675.v1.p1 CARDIA Multi-omics Obesity & CVD Substudy – Year 20 Untargeted Metabolomics Data phs001612.v3.p2 NHLBI TOPMed: CARDIA (Coronary Artery Risk Development in Young Adults) phs003045.v1.p1 Collaborative Cohort of Cohorts for COVID-19 Research (C4R): Coronary Artery Risk Development in Young Adults Study (CARDIA) phs000285.v4.p3 CARDIA_Cohort Available Data: Available data for request include exam data through Year 30 and outcomes and death data through 2022. Additionally, data from 28 ancillary studies are available for request.Objectives: The original objectives of CARDIA were to document levels of risk factors for coronary artery disease and potential determinants of these risk factors in young adults; to study the interrelationships of risk factors and lifestyles and to document behavioral and environmental changes during the transition from young adulthood to middle age; to compare cross-sectional and longitudinal data on age-related trends in cardiovascular disease risk factors; and to compare levels and evolution of risk factors between men and women, blacks and whites, and in groups of differing socioeconomic status. Goals of the study have evolved to emphasize understanding determinants of left ventricular mass, emerging obesity and hypertension, and sequelae of hypertension in pregnancy.Background: CARDIA is designed to increase understanding of contributors to changes in cardiovascular disease (CVD) risk factors during the critical years of transition from young adulthood to middle age. CARDIA was funded initially in 1983 for a five-year cycle that included two rounds of examinations. Contract renewals have allowed for subsequent re-examinations.Participants: Black and white men and women; ages 18-30 years at entry with a range of attained education; original sample size: 5,115.Design: CARDIA is a population-based observational study of 5,115 participants aged 18-30 years recruited in 1985-1986. The sample was designed to achieve approximately balanced subgroups of race, gender, education (high school or less and more than high school) and age (18-24 and 25-30). Forty percent of the cohort had no more than a high school education. A total of nine examinations have been completed in the cohort with examination cycles at year 2 of the project and years 5, 7, 10 , 15, 20, 25, and 30.In addition to standard measurements of blood pressure, anthropometry, blood lipids, smoking behavior, physical activity, diet, pulmonary function, and many psychological factors, CARDIA has other included measurements (in subsets or in the full cohort) to obtain unique information on other aspects of risk factor development and early morbidity. These have included: graded exercise treadmill testing; echocardiography, particularly for measurement of left ventricular mass; cardiovascular reactivity; serum cotinine; Lp(a), apoE phenotype, apolipoprotein A1 and B; homocysteine; skin reflectance; body composition by dual X-ray absorptiometry; glucose tolerance testing; vascular resistance and compliance; and plasma renin activity and sympathetic nervous system activity. Study Weblinks: CARDIA BioLINCC Study Design: Prospective Longitudinal Cohort Study Type: Longitudinal Longitudinal Cohort Observational Population Total number of consented subjects: 4544 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Coronary Artery Risk Development in Young Adults (CARDIA-BioLINCC)","short_name":"BL_CARDIA_HMB-MDS","commons":"BioData Catalyst","study_url":"","_subjects_count":4411,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs003739.v1.p1.c2":{"gen3_discovery":{"authz":"/programs/BioLINCC/projects/BL_CARDIA_HMB-NPU-MDS","tags":[],"_unique_id":"phs003739.v1.p1.c2","study_id":"phs003739.v1.p1.c2","study_description":"Data Access NOTE: Please refer to the “Authorized Access” section below for information about how access to the data from this accession differs from many other dbGaP accessions.Related Studies: Other CARDIA data available include:phs000236.v2.p2 PAGE: CALiCo: Coronary Artery Risk Development in Young Adults(CARDIA) phs000309.v3.p2 The CARDIA-GENEVA Study phs000399.v1.p2 NHLBI GO-ESP: Heart Cohorts Exome Sequencing Project (CARDIA) phs000613.v1.p2 NHLBI CARDIA Candidate Gene Association Resource (CARe) phs003675.v1.p1 CARDIA Multi-omics Obesity & CVD Substudy – Year 20 Untargeted Metabolomics Data phs001612.v3.p2 NHLBI TOPMed: CARDIA (Coronary Artery Risk Development in Young Adults) phs003045.v1.p1 Collaborative Cohort of Cohorts for COVID-19 Research (C4R): Coronary Artery Risk Development in Young Adults Study (CARDIA) phs000285.v4.p3 CARDIA_Cohort Available Data: Available data for request include exam data through Year 30 and outcomes and death data through 2022. Additionally, data from 28 ancillary studies are available for request.Objectives: The original objectives of CARDIA were to document levels of risk factors for coronary artery disease and potential determinants of these risk factors in young adults; to study the interrelationships of risk factors and lifestyles and to document behavioral and environmental changes during the transition from young adulthood to middle age; to compare cross-sectional and longitudinal data on age-related trends in cardiovascular disease risk factors; and to compare levels and evolution of risk factors between men and women, blacks and whites, and in groups of differing socioeconomic status. Goals of the study have evolved to emphasize understanding determinants of left ventricular mass, emerging obesity and hypertension, and sequelae of hypertension in pregnancy.Background: CARDIA is designed to increase understanding of contributors to changes in cardiovascular disease (CVD) risk factors during the critical years of transition from young adulthood to middle age. CARDIA was funded initially in 1983 for a five-year cycle that included two rounds of examinations. Contract renewals have allowed for subsequent re-examinations.Participants: Black and white men and women; ages 18-30 years at entry with a range of attained education; original sample size: 5,115.Design: CARDIA is a population-based observational study of 5,115 participants aged 18-30 years recruited in 1985-1986. The sample was designed to achieve approximately balanced subgroups of race, gender, education (high school or less and more than high school) and age (18-24 and 25-30). Forty percent of the cohort had no more than a high school education. A total of nine examinations have been completed in the cohort with examination cycles at year 2 of the project and years 5, 7, 10 , 15, 20, 25, and 30.In addition to standard measurements of blood pressure, anthropometry, blood lipids, smoking behavior, physical activity, diet, pulmonary function, and many psychological factors, CARDIA has other included measurements (in subsets or in the full cohort) to obtain unique information on other aspects of risk factor development and early morbidity. These have included: graded exercise treadmill testing; echocardiography, particularly for measurement of left ventricular mass; cardiovascular reactivity; serum cotinine; Lp(a), apoE phenotype, apolipoprotein A1 and B; homocysteine; skin reflectance; body composition by dual X-ray absorptiometry; glucose tolerance testing; vascular resistance and compliance; and plasma renin activity and sympathetic nervous system activity. Study Weblinks: CARDIA BioLINCC Study Design: Prospective Longitudinal Cohort Study Type: Longitudinal Longitudinal Cohort Observational Population Total number of consented subjects: 4544 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Coronary Artery Risk Development in Young Adults (CARDIA-BioLINCC)","short_name":"BL_CARDIA_HMB-NPU-MDS","commons":"BioData Catalyst","study_url":"","_subjects_count":133,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs003740.v1.p1.c1":{"gen3_discovery":{"authz":"/programs/BioLINCC/projects/BL_JHS_HMB-MDS","tags":[],"_unique_id":"phs003740.v1.p1.c1","study_id":"phs003740.v1.p1.c1","study_description":"Accessing Data: Please refer to “Authorized Access” below regarding accessing data through the BioData Catalyst ecosystem. The data from this accession is not available for download through dbGaP.Related Studies: Other Jackson Heart Study data available include: Imaging studies (JHS-Imaging), Genetics and genomics (The Jackson Heart Study, phs000286.v7.p2), and Collaborative Cohort of Cohorts for COVID-19 Research (C4R-JHS, phs002907.v1.p1): Jackson Heart Study (phs002907.v1.p1).Available Data: Data available for request include Jackson Heart Study visit 1-3 examination cycles, collated annual follow-up communication data through 2016, and follow-up for mortality, heart disease, and stroke events through 2014.Objectives: The objectives of the Jackson Heart Study are to: 1) investigate the associations of biological, psychosocial, and behavioral factors with the incidence atherosclerotic events and health outcomes in an African American cohort; and 2) increase access to and the participation of African American populations and scientists in biomedical research and professions.Background: It has long been recognized that African Americans share a disproportionate burden of deleterious health outcomes including diabetes, hypertension, kidney disease and early onset of cardiovascular disease. The Jackson Heart Study was initiated in 2000 to explore potential mechanisms and mediators of health outcomes in a large African American cohort. In addition, the JHS conducts a variety of community education and outreach activities to promote healthy lifestyles to reduce disease risk burden and student training programs to promote and support public health research.Participants: African American men and women, age 35-84 at entry. Of the 5306 cohort members enrolled in the study, the data repository contains data from 3,883 that provided informed consent to share their data with investigators not affiliated with the study.Design: Participants were enrolled in the study from 2000-2004 from urban and rural areas of three counties (Hinds, Madison and Rankin) in the Jackson, MS metropolitan statistical area. Participants were enrolled from each of 4 recruitment pools: a random sample component (17%), volunteer component (30%), currently enrolled in the Atherosclerosis Risk in Communities (ARIC) Study (31%), and secondary family members (22%). Recruitment was limited to non-institutionalized adult African Americans age 35-84 years, except in the family cohort where those age ≥21 years were eligible. The final cohort of 5,306 participants includes 6.59% of all African American residents aged 35-84 (N=76,426, US Census 2000). Data collection at the baseline exam included a medical history, physical examination, blood/urine analytes and interview questions on areas such as: physical activity; stress, coping and spirituality; racism and discrimination; socioeconomic status; and health care access.The current release of the Jackson Heart Study includes data collected at baseline, exam 2 (2005-2008), and exam 3 (2009-2013). Annual follow-up and surveillance of clinical cardiovascular events is ongoing. Study Weblinks: BioLINCC Repository Study Design: Prospective Longitudinal Cohort Study Type: Cohort Total number of consented subjects: 3883 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Jackson Heart Study (JHS-BioLINCC)","short_name":"BL_JHS_HMB-MDS","commons":"BioData Catalyst","study_url":"","_subjects_count":2567,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs003740.v1.p1.c2":{"gen3_discovery":{"authz":"/programs/BioLINCC/projects/BL_JHS_HMB-NPU-MDS","tags":[],"_unique_id":"phs003740.v1.p1.c2","study_id":"phs003740.v1.p1.c2","study_description":"Accessing Data: Please refer to “Authorized Access” below regarding accessing data through the BioData Catalyst ecosystem. The data from this accession is not available for download through dbGaP.Related Studies: Other Jackson Heart Study data available include: Imaging studies (JHS-Imaging), Genetics and genomics (The Jackson Heart Study, phs000286.v7.p2), and Collaborative Cohort of Cohorts for COVID-19 Research (C4R-JHS, phs002907.v1.p1): Jackson Heart Study (phs002907.v1.p1).Available Data: Data available for request include Jackson Heart Study visit 1-3 examination cycles, collated annual follow-up communication data through 2016, and follow-up for mortality, heart disease, and stroke events through 2014.Objectives: The objectives of the Jackson Heart Study are to: 1) investigate the associations of biological, psychosocial, and behavioral factors with the incidence atherosclerotic events and health outcomes in an African American cohort; and 2) increase access to and the participation of African American populations and scientists in biomedical research and professions.Background: It has long been recognized that African Americans share a disproportionate burden of deleterious health outcomes including diabetes, hypertension, kidney disease and early onset of cardiovascular disease. The Jackson Heart Study was initiated in 2000 to explore potential mechanisms and mediators of health outcomes in a large African American cohort. In addition, the JHS conducts a variety of community education and outreach activities to promote healthy lifestyles to reduce disease risk burden and student training programs to promote and support public health research.Participants: African American men and women, age 35-84 at entry. Of the 5306 cohort members enrolled in the study, the data repository contains data from 3,883 that provided informed consent to share their data with investigators not affiliated with the study.Design: Participants were enrolled in the study from 2000-2004 from urban and rural areas of three counties (Hinds, Madison and Rankin) in the Jackson, MS metropolitan statistical area. Participants were enrolled from each of 4 recruitment pools: a random sample component (17%), volunteer component (30%), currently enrolled in the Atherosclerosis Risk in Communities (ARIC) Study (31%), and secondary family members (22%). Recruitment was limited to non-institutionalized adult African Americans age 35-84 years, except in the family cohort where those age ≥21 years were eligible. The final cohort of 5,306 participants includes 6.59% of all African American residents aged 35-84 (N=76,426, US Census 2000). Data collection at the baseline exam included a medical history, physical examination, blood/urine analytes and interview questions on areas such as: physical activity; stress, coping and spirituality; racism and discrimination; socioeconomic status; and health care access.The current release of the Jackson Heart Study includes data collected at baseline, exam 2 (2005-2008), and exam 3 (2009-2013). Annual follow-up and surveillance of clinical cardiovascular events is ongoing. Study Weblinks: BioLINCC Repository Study Design: Prospective Longitudinal Cohort Study Type: Cohort Total number of consented subjects: 3883 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Jackson Heart Study (JHS-BioLINCC)","short_name":"BL_JHS_HMB-NPU-MDS","commons":"BioData Catalyst","study_url":"","_subjects_count":711,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs003740.v1.p1.c3":{"gen3_discovery":{"authz":"/programs/BioLINCC/projects/BL_JHS_DS-CVD-MDS","tags":[],"_unique_id":"phs003740.v1.p1.c3","study_id":"phs003740.v1.p1.c3","study_description":"Accessing Data: Please refer to “Authorized Access” below regarding accessing data through the BioData Catalyst ecosystem. The data from this accession is not available for download through dbGaP.Related Studies: Other Jackson Heart Study data available include: Imaging studies (JHS-Imaging), Genetics and genomics (The Jackson Heart Study, phs000286.v7.p2), and Collaborative Cohort of Cohorts for COVID-19 Research (C4R-JHS, phs002907.v1.p1): Jackson Heart Study (phs002907.v1.p1).Available Data: Data available for request include Jackson Heart Study visit 1-3 examination cycles, collated annual follow-up communication data through 2016, and follow-up for mortality, heart disease, and stroke events through 2014.Objectives: The objectives of the Jackson Heart Study are to: 1) investigate the associations of biological, psychosocial, and behavioral factors with the incidence atherosclerotic events and health outcomes in an African American cohort; and 2) increase access to and the participation of African American populations and scientists in biomedical research and professions.Background: It has long been recognized that African Americans share a disproportionate burden of deleterious health outcomes including diabetes, hypertension, kidney disease and early onset of cardiovascular disease. The Jackson Heart Study was initiated in 2000 to explore potential mechanisms and mediators of health outcomes in a large African American cohort. In addition, the JHS conducts a variety of community education and outreach activities to promote healthy lifestyles to reduce disease risk burden and student training programs to promote and support public health research.Participants: African American men and women, age 35-84 at entry. Of the 5306 cohort members enrolled in the study, the data repository contains data from 3,883 that provided informed consent to share their data with investigators not affiliated with the study.Design: Participants were enrolled in the study from 2000-2004 from urban and rural areas of three counties (Hinds, Madison and Rankin) in the Jackson, MS metropolitan statistical area. Participants were enrolled from each of 4 recruitment pools: a random sample component (17%), volunteer component (30%), currently enrolled in the Atherosclerosis Risk in Communities (ARIC) Study (31%), and secondary family members (22%). Recruitment was limited to non-institutionalized adult African Americans age 35-84 years, except in the family cohort where those age ≥21 years were eligible. The final cohort of 5,306 participants includes 6.59% of all African American residents aged 35-84 (N=76,426, US Census 2000). Data collection at the baseline exam included a medical history, physical examination, blood/urine analytes and interview questions on areas such as: physical activity; stress, coping and spirituality; racism and discrimination; socioeconomic status; and health care access.The current release of the Jackson Heart Study includes data collected at baseline, exam 2 (2005-2008), and exam 3 (2009-2013). Annual follow-up and surveillance of clinical cardiovascular events is ongoing. Study Weblinks: BioLINCC Repository Study Design: Prospective Longitudinal Cohort Study Type: Cohort Total number of consented subjects: 3883 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Jackson Heart Study (JHS-BioLINCC)","short_name":"BL_JHS_DS-CVD-MDS","commons":"BioData Catalyst","study_url":"","_subjects_count":404,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs003740.v1.p1.c4":{"gen3_discovery":{"authz":"/programs/BioLINCC/projects/BL_JHS_DS-CVD-NPU-MDS","tags":[],"_unique_id":"phs003740.v1.p1.c4","study_id":"phs003740.v1.p1.c4","study_description":"Accessing Data: Please refer to “Authorized Access” below regarding accessing data through the BioData Catalyst ecosystem. The data from this accession is not available for download through dbGaP.Related Studies: Other Jackson Heart Study data available include: Imaging studies (JHS-Imaging), Genetics and genomics (The Jackson Heart Study, phs000286.v7.p2), and Collaborative Cohort of Cohorts for COVID-19 Research (C4R-JHS, phs002907.v1.p1): Jackson Heart Study (phs002907.v1.p1).Available Data: Data available for request include Jackson Heart Study visit 1-3 examination cycles, collated annual follow-up communication data through 2016, and follow-up for mortality, heart disease, and stroke events through 2014.Objectives: The objectives of the Jackson Heart Study are to: 1) investigate the associations of biological, psychosocial, and behavioral factors with the incidence atherosclerotic events and health outcomes in an African American cohort; and 2) increase access to and the participation of African American populations and scientists in biomedical research and professions.Background: It has long been recognized that African Americans share a disproportionate burden of deleterious health outcomes including diabetes, hypertension, kidney disease and early onset of cardiovascular disease. The Jackson Heart Study was initiated in 2000 to explore potential mechanisms and mediators of health outcomes in a large African American cohort. In addition, the JHS conducts a variety of community education and outreach activities to promote healthy lifestyles to reduce disease risk burden and student training programs to promote and support public health research.Participants: African American men and women, age 35-84 at entry. Of the 5306 cohort members enrolled in the study, the data repository contains data from 3,883 that provided informed consent to share their data with investigators not affiliated with the study.Design: Participants were enrolled in the study from 2000-2004 from urban and rural areas of three counties (Hinds, Madison and Rankin) in the Jackson, MS metropolitan statistical area. Participants were enrolled from each of 4 recruitment pools: a random sample component (17%), volunteer component (30%), currently enrolled in the Atherosclerosis Risk in Communities (ARIC) Study (31%), and secondary family members (22%). Recruitment was limited to non-institutionalized adult African Americans age 35-84 years, except in the family cohort where those age ≥21 years were eligible. The final cohort of 5,306 participants includes 6.59% of all African American residents aged 35-84 (N=76,426, US Census 2000). Data collection at the baseline exam included a medical history, physical examination, blood/urine analytes and interview questions on areas such as: physical activity; stress, coping and spirituality; racism and discrimination; socioeconomic status; and health care access.The current release of the Jackson Heart Study includes data collected at baseline, exam 2 (2005-2008), and exam 3 (2009-2013). Annual follow-up and surveillance of clinical cardiovascular events is ongoing. Study Weblinks: BioLINCC Repository Study Design: Prospective Longitudinal Cohort Study Type: Cohort Total number of consented subjects: 3883 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Jackson Heart Study (JHS-BioLINCC)","short_name":"BL_JHS_DS-CVD-NPU-MDS","commons":"BioData Catalyst","study_url":"","_subjects_count":201,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs003743.v1.p1.c1":{"gen3_discovery":{"authz":"/programs/BioLINCC/projects/BL_ARDSNet_ALTA_HMB-MDS","tags":[],"_unique_id":"phs003743.v1.p1.c1","study_id":"phs003743.v1.p1.c1","study_description":"Data Access NOTE: Please refer to the “Authorized Access” section below for information about how access to the data from this accession differs from many other dbGaP accessions. Biospecimens Access to Biospecimens is through the NHLBI Biologic Specimen and Data Repository Information Coordinating Center (BioLINCC). Biospecimens from ARDSNet-ALTA include Plasma, DNA, Urine, and BAL. Please note that use of biospecimens in genetic research is subject to a tiered consent. Objectives This clinical trial was designed to test the hypothesis that an aerosolized beta-2-agonist, albuterol, would improve clinical outcomes in participants with acute lung injury (ALI) and acute respiratory distress syndrome (ARDS). Background In participants with acute lung injury and acute respiratory distress syndrome (ALI/ARDS), inflammation of the pulmonary circulation increases vascular permeability. Fluid leaks from blood vessels into the pulmonary interstitium and alveoli. Recovery from this form of acute respiratory failure requires that the pulmonary edema resolve. The resolution of alveolar edema is driven by active transport of sodium and chloride ions from the luminal space across both type I and type II alveolar epithelial cells, creating an osmotic gradient for the reabsorption of water. In the ex vivo human lung, the rate of alveolar fluid clearance can be doubled by treatment with a cyclic AMP beta-2 adrenergic receptor agonist. On the basis of the preclinical observations that treatment with beta-2-agonists could reduce pulmonary edema and accelerate the rate of alveolar fluid clearance, the ALTA study was designed and undertaken with the hypothesis that treatment of participants with ALI/ARDS with beta-agonist therapy would accelerate the resolution of alveolar edema and improve clinical outcomes. Participants There were 282 participants. Design Study staff conducted a multicenter, randomized, placebo-controlled clinical trial in which participants were randomized to receive aerosolized albuterol (5 mg) or saline placebo every 4 hours for up to 10 days. The primary outcome variable for the trial was ventilator-free days. Conclusions Ventilator-free days were not significantly different between the albuterol and placebo groups. The results suggest that aerosolized albuterol does not improve clinical outcomes in participants with ALI. Routine use of beta-2 agonist therapy in mechanically ventilated participants with ALI cannot be recommended (Matthay, et al., 2011, PMID: 21562125). Study Weblinks: BioLINCC Repository Study Design: Clinical Trial Study Type: Clinical Trial Total number of consented subjects: 282 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Acute Respiratory Distress Network (ARDSNet) Studies 06 and 08 Prospective, Randomized, Multicenter Trial of Aerosolized Albuterol Versus Placebo for the Treatment of Acute Lung Injury (ALTA) (ARDSNet-ALTA-BioLINCC)","short_name":"BL_ARDSNet_ALTA_HMB-MDS","commons":"BioData Catalyst","study_url":"","_subjects_count":282,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs003744.v1.p1.c1":{"gen3_discovery":{"authz":"/programs/BioLINCC/projects/BL_ARDSNet_Omega_HMB-MDS","tags":[],"_unique_id":"phs003744.v1.p1.c1","study_id":"phs003744.v1.p1.c1","study_description":"Data Access NOTE: Please refer to the “Authorized Access” section below for information about how access to the data from this accession differs from many other dbGaP accessions. Biospecimens: Access to Biospecimens is through the NHLBI Biologic Specimen and Data Repository Information Coordinating Center (BioLINCC). Biospecimens from ARDSNet-Omega include bronchial lavage, plasma, urine, and DNA. Please note that use of biospecimens in genetic research is subject to a tiered consent.Objectives: To determine if dietary supplementation of omega-3 (n-3) fatty acids, γ-linolenic acid and antioxidants to participants with acute lung injury would increase ventilator-free days to study day 28.Background: Early acute lung injury (ALI) is characterized by neutrophilic lung inflammation, permeability, and intravascular and alveolar fibrin deposition. The type and inflammatory activity of eicosanoids liberated during inflammation depends on the membrane phospholipid composition: omega 6 (n-6) fatty acid arachidonate yields highly reactive and inflammatory dienoic prostaglandins and series 4 leukotrienes, whereas omega-3 (n-3) fatty acids favor production of less active and potentially anti-inflammatory trienoic prostaglandins and series 5 leukotrienes. Participants at risk of developing ALI have n-3 levels approximately 25% of normal and those with established ALI have n-3 levels as low as 6% of normal, suggesting a potential role for n-3 dietary supplementation in participants with ALI.Three randomized controlled studies, conducted in participants with ALI or sepsis-induced respiratory failure, demonstrated an association between the administration of an enteral formula enriched in n-3 fatty acids, GLA, and antioxidants and improved oxygenation and respiratory physiology compared with an unenriched, high-fat formula. However, interpretation of these results is limited by the small sample sizes and as-treated analyses of only those participants who tolerated full enteral nutrition. Participants: The total number of participants in the study was 272.Design: Participants were stratified by hospital and the presence of shock at baseline and then randomized to receive either twice-daily enteral supplementation of n-3 fatty acids, GLA, and antioxidants (n-3 supplement) or an isocaloric-isovolemic carbohydrate-rich control. Participants were also simultaneously randomized to a separate ongoing trial (the EDEN study) comparing low- vs full-calorie enteral nutrition in a 2×2 factorial design.The n-3 or control supplement was administered enterally as twice-daily boluses of 120 mL beginning within 6 hours of randomization. Dosing continued until the earliest of 21 days, 48 hours of unassisted breathing, or extubation. The energy provided by the boluses supplemented that provided by each primary physician's choice of standard continuous non–n-3-enriched enteral formula. The rate of continuous enteral feeding was managed by a protocol with an algorithm for gastrointestinal intolerances. The supplement was administered even if enteral nutrition was interrupted, as long as the patient was tolerating enteral medications. Conclusions: The study was stopped by the DSMB for futility at the first interim analysis after 143 participants had been randomized to receive the n-3 supplement and 129 to receive the isocaloric control. Despite an 8-fold increase in plasma eicosapentaenoic acid levels, participants receiving the n-3 supplement had fewer ventilator-free days, intensive care unit–free days, and nonpulmonary organ failure-free days. Study Weblinks: BioLINCC Repository Study Design: Clinical Trial Study Type: Clinical Trial Total number of consented subjects: 272 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"ARDSNet 07-08: Randomized, Blinded, Placebo-Controlled, Multi-Center Trial of Omega-3 Fatty Acid, Gamma-Linolenic Acid, and Antioxidants in Acute Lung Injury or ARDS (OMEGA) (ARDSNet-Omega-BioLINCC)","short_name":"BL_ARDSNet_Omega_HMB-MDS","commons":"BioData Catalyst","study_url":"","_subjects_count":272,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs003747.v1.p1.c1":{"gen3_discovery":{"authz":"/programs/imaging/projects/img_JHS_HMB-MDS","tags":[],"_unique_id":"phs003747.v1.p1.c1","study_id":"phs003747.v1.p1.c1","study_description":"The Jackson Heart Study (JHS) is a large, community-based, observational study that recruited 5,306 African American adults from three counties (Hinds, Madison and Rankin) in the Jackson, MS area. Participants age 35-84 years at baseline were enrolled from each of 4 recruitment pools: (1) random, 17%, (2) volunteer, 30%, (3) currently enrolled in the Atherosclerosis Risk in Communities (ARIC) Study, 31%, and (4) secondary family members, 22% (family study participants were age≥21 years). Data available include medical history, physical examination, blood/urine analytes, and interview questions on areas such as physical activity, stress, coping and spirituality, racism and discrimination, socioeconomic position, and access to health care. Extensive clinical phenotyping includes anthropometrics, electrocardiography, carotid ultrasound, ankle-brachial blood pressure index, echocardiography, CT chest and abdomen for coronary and aortic calcification, liver fat, subcutaneous and visceral fat measurements, and cardiac MRI. Participants have been contacted annually by telephone to update information, confirm vital status, document interim medical events, hospitalizations and functional status, and obtain sociocultural information. Ongoing cohort surveillance includes abstraction of medical records and death certificates for relevant International Classification of Diseases (ICD) codes and adjudication of nonfatal events and deaths. Study Weblinks: Jackson Heart Study Study Design: Collection Study Type: Cohort Longitudinal Total number of consented subjects: 3883 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Jackson Heart Study - Images","short_name":"img_JHS_HMB-MDS","commons":"BioData Catalyst","study_url":"","_subjects_count":2567,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs003747.v1.p1.c2":{"gen3_discovery":{"authz":"/programs/imaging/projects/img_JHS_HMB-NPU-MDS","tags":[],"_unique_id":"phs003747.v1.p1.c2","study_id":"phs003747.v1.p1.c2","study_description":"The Jackson Heart Study (JHS) is a large, community-based, observational study that recruited 5,306 African American adults from three counties (Hinds, Madison and Rankin) in the Jackson, MS area. Participants age 35-84 years at baseline were enrolled from each of 4 recruitment pools: (1) random, 17%, (2) volunteer, 30%, (3) currently enrolled in the Atherosclerosis Risk in Communities (ARIC) Study, 31%, and (4) secondary family members, 22% (family study participants were age≥21 years). Data available include medical history, physical examination, blood/urine analytes, and interview questions on areas such as physical activity, stress, coping and spirituality, racism and discrimination, socioeconomic position, and access to health care. Extensive clinical phenotyping includes anthropometrics, electrocardiography, carotid ultrasound, ankle-brachial blood pressure index, echocardiography, CT chest and abdomen for coronary and aortic calcification, liver fat, subcutaneous and visceral fat measurements, and cardiac MRI. Participants have been contacted annually by telephone to update information, confirm vital status, document interim medical events, hospitalizations and functional status, and obtain sociocultural information. Ongoing cohort surveillance includes abstraction of medical records and death certificates for relevant International Classification of Diseases (ICD) codes and adjudication of nonfatal events and deaths. Study Weblinks: Jackson Heart Study Study Design: Collection Study Type: Cohort Longitudinal Total number of consented subjects: 3883 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Jackson Heart Study - Images","short_name":"img_JHS_HMB-NPU-MDS","commons":"BioData Catalyst","study_url":"","_subjects_count":711,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs003747.v1.p1.c3":{"gen3_discovery":{"authz":"/programs/imaging/projects/img_JHS_DS-CVD-MDS","tags":[],"_unique_id":"phs003747.v1.p1.c3","study_id":"phs003747.v1.p1.c3","study_description":"The Jackson Heart Study (JHS) is a large, community-based, observational study that recruited 5,306 African American adults from three counties (Hinds, Madison and Rankin) in the Jackson, MS area. Participants age 35-84 years at baseline were enrolled from each of 4 recruitment pools: (1) random, 17%, (2) volunteer, 30%, (3) currently enrolled in the Atherosclerosis Risk in Communities (ARIC) Study, 31%, and (4) secondary family members, 22% (family study participants were age≥21 years). Data available include medical history, physical examination, blood/urine analytes, and interview questions on areas such as physical activity, stress, coping and spirituality, racism and discrimination, socioeconomic position, and access to health care. Extensive clinical phenotyping includes anthropometrics, electrocardiography, carotid ultrasound, ankle-brachial blood pressure index, echocardiography, CT chest and abdomen for coronary and aortic calcification, liver fat, subcutaneous and visceral fat measurements, and cardiac MRI. Participants have been contacted annually by telephone to update information, confirm vital status, document interim medical events, hospitalizations and functional status, and obtain sociocultural information. Ongoing cohort surveillance includes abstraction of medical records and death certificates for relevant International Classification of Diseases (ICD) codes and adjudication of nonfatal events and deaths. Study Weblinks: Jackson Heart Study Study Design: Collection Study Type: Cohort Longitudinal Total number of consented subjects: 3883 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Jackson Heart Study - Images","short_name":"img_JHS_DS-CVD-MDS","commons":"BioData Catalyst","study_url":"","_subjects_count":404,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs003747.v1.p1.c4":{"gen3_discovery":{"authz":"/programs/imaging/projects/img_JHS_DS-CVD-NPU-MDS","tags":[],"_unique_id":"phs003747.v1.p1.c4","study_id":"phs003747.v1.p1.c4","study_description":"The Jackson Heart Study (JHS) is a large, community-based, observational study that recruited 5,306 African American adults from three counties (Hinds, Madison and Rankin) in the Jackson, MS area. Participants age 35-84 years at baseline were enrolled from each of 4 recruitment pools: (1) random, 17%, (2) volunteer, 30%, (3) currently enrolled in the Atherosclerosis Risk in Communities (ARIC) Study, 31%, and (4) secondary family members, 22% (family study participants were age≥21 years). Data available include medical history, physical examination, blood/urine analytes, and interview questions on areas such as physical activity, stress, coping and spirituality, racism and discrimination, socioeconomic position, and access to health care. Extensive clinical phenotyping includes anthropometrics, electrocardiography, carotid ultrasound, ankle-brachial blood pressure index, echocardiography, CT chest and abdomen for coronary and aortic calcification, liver fat, subcutaneous and visceral fat measurements, and cardiac MRI. Participants have been contacted annually by telephone to update information, confirm vital status, document interim medical events, hospitalizations and functional status, and obtain sociocultural information. Ongoing cohort surveillance includes abstraction of medical records and death certificates for relevant International Classification of Diseases (ICD) codes and adjudication of nonfatal events and deaths. Study Weblinks: Jackson Heart Study Study Design: Collection Study Type: Cohort Longitudinal Total number of consented subjects: 3883 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Jackson Heart Study - Images","short_name":"img_JHS_DS-CVD-NPU-MDS","commons":"BioData Catalyst","study_url":"","_subjects_count":201,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs003768.v2.p2.c1":{"gen3_discovery":{"authz":null,"tags":null,"_unique_id":"phs003768.v2.p2.c1","study_id":"phs003768.v2.p2.c1","study_description":null,"full_name":null,"short_name":null,"commons":"BioData Catalyst","study_url":null,"_subjects_count":0,"__manifest":null,"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs003768.v3.p3.c1":{"gen3_discovery":{"authz":"/programs/RECOVER/projects/RC_Autopsy_GRU","tags":[],"_unique_id":"phs003768.v3.p3.c1","study_id":"phs003768.v3.p3.c1","study_description":"No Study Description Available","full_name":"","short_name":"RC_Autopsy_GRU","commons":"BioData Catalyst","study_url":"","_subjects_count":245,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs003769.v1.p1.c1":{"gen3_discovery":{"authz":"/programs/BioLINCC/projects/BL_ARDSNet_LASRS_HMB-MDS","tags":[],"_unique_id":"phs003769.v1.p1.c1","study_id":"phs003769.v1.p1.c1","study_description":"Data Access NOTE: Please refer to the “Authorized Access” section below for information about how access to the data from this accession differs from many other dbGaP accessions. Biospecimens: Access to Biospecimens is through the NHLBI Biologic Specimen and Data Repository Information Coordinating Center (BioLINCC). Biospecimens from ARDSNet-LaSRS include BAL Slides, Bronchial Lavage, and Plasma. Please note that use of biospecimens in genetic research is subject to a tiered consent.Objectives: Since previous reports suggested that corticosteroids may improve survival, this project was developed as a multicenter, randomized controlled trial of corticosteroids in patients with persistent ARDS.Background: Persistent acute respiratory distress syndrome (ARDS) is characterized by excessive fibroproliferation, ongoing inflammation, prolonged mechanical ventilation, and a substantial risk of death.Participants: There were 180 participants.Conclusions: The results do not support the routine use of methylprednisolone for persistent ARDS despite the improvement in cardiopulmonary physiology. In addition, starting methylprednisolone therapy more than two weeks after the onset of ARDS may increase the risk of death. (NEJM April 20, 2006; Vol 354, No. 16, pp 1671-84). Study Weblinks: BioLINCC Repository Study Design: Clinical Trial Study Type: Clinical Trial Total number of consented subjects: 180 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Acute Respiratory Distress Network (ARDSNet) Study 02 Late Steroid Rescue Study (LaSRS) (ARDSNet-LaSRS-BioLINCC)","short_name":"BL_ARDSNet_LASRS_HMB-MDS","commons":"BioData Catalyst","study_url":"","_subjects_count":180,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs003777.v1.p1.c1":{"gen3_discovery":{"authz":"/programs/BioLINCC/projects/BL_ROC_HS_TBI_GRU","tags":[],"_unique_id":"phs003777.v1.p1.c1","study_id":"phs003777.v1.p1.c1","study_description":"Data Access NOTE Please refer to the \"Authorized Access\" section below for information about how access to the data from this accession. Access differs from many other dbGaP accessions.ObjectivesShock: To determine if prehospital administration of 7.5% hypertonic saline with 6% Dextran-70 (HSD) or 7.5% hypertonic saline alone (HS), compared to current standard therapy with normal saline (NS), as an initial resuscitation fluid, affects survival following traumatic injury with hypovolemic shock.TBI: To determine whether out-of-hospital administration of hypertonic fluids improves neurologic outcome following severe traumatic brain injury (TBI).Background Trauma is the leading cause of death among North Americans between the ages of 1 and 44 years. The majority of these deaths result from hypovolemic shock or severe brain injury. Participants in hypovolemic shock develop a state of systemic tissue ischemia then a subsequent reperfusion injury at the time of fluid resuscitation. Conventional resuscitation involves the IV administration of a large volume of isotonic or slightly hypotonic (lactated ringers, LR) solutions beginning in the prehospital setting. Although not conclusive, prior studies have suggested that alternative resuscitation with hypertonic saline (7.5%) solutions may reduce morbidity or mortality in these participants. Furthermore, hypertonic fluids may have specific advantages in the brain-injured participant, as they may aid in the rapid restoration of cerebral perfusion and prevent extravascular fluid sequestration, thereby limiting secondary brain injury. In addition, recent studies have demonstrated that hypertonicity significantly alters the activation of inflammatory cells, an effect that may reduce subsequent organ injury from ischemia-reperfusion and decrease nosocomial infection. The majority of previous clinical trials have focused on the use of HSD. The potential for 7.5% saline alone (HS) to have similar effects has not been well studied. Removal of the dextran component may enhance the anti-inflammatory effects of this solution, which could improve secondary outcomes such as acute respiratory distress syndrome (ARDS), multiple organ failure syndrome (MOFS) and rates of nosocomial infections. Participants Shock: There were 893 participants that were randomized (853 enrolled).TBI: There were 1282 participants enrolled and 6-month outcomes data were available for 1087 (85%).Design Shock: Multicenter, randomized, blinded clinical trials involving 114 emergency medical services agencies in North America within the Resuscitation Outcomes Consortium were conducted from May 2006 to August 2008. Initial resuscitation fluid, 250 mL of either 7.5% saline per 6% dextran 70 (hypertonic saline/dextran, HSD), 7.5% saline (hypertonic saline, HS), or 0.9% saline (normal saline, NS) administered by out-of-hospital providers. Primary outcome was 28-day survival. On the recommendation of the data and safety monitoring board, the study was stopped early (23% of proposed sample size) for futility and potential safety concern.TBI: Multicenter, double-blind, randomized, placebo-controlled clinical trials involving 114 North American emergency medical services agencies within the Resuscitation Outcomes Consortium were conducted between May 2006 and May 2009. A single 250-mL bolus of 7.5% saline/6% dextran 70 (HSD), 7.5% saline (HS), or 0.9% saline (NS) initiated in the out-of-hospital setting. The main outcome measure was a six-month neurologic outcome based on the Extended Glasgow Outcome Scale (GOSE) (dichotomized as >4 or ≤4). The study was terminated by the data and safety monitoring board after randomization of 1331 participants, having met prespecified futility criteria.Conclusions Shock: Among injured participants with hypovolemic shock, initial resuscitation fluid treatment with either HS or HSD, compared with NS, did not result in superior 28-day survival. However, interpretation of these findings is limited by the early stopping of the trial (PMID: 21178763).TBI: Among participants with severe TBI not in hypovolemic shock, initial resuscitation with either HS or HSD, compared with normal saline, did not result in superior 6-month neurologic outcome or survival (PMID: 20924011). Study Weblinks: BioLINCC Repository Study Design: Clinical Trial Study Type: Clinical Trial Total number of consented subjects: 2220 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Resuscitation Outcomes Consortium (ROC) Hypertonic Saline (HS) Trial Shock Study and Traumatic Brain Injury Study (TBI) (ROC-HS/TBI-BioLINCC)","short_name":"BL_ROC_HS_TBI_GRU","commons":"BioData Catalyst","study_url":"","_subjects_count":2220,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs003782.v1.p1.c1":{"gen3_discovery":{"authz":"/programs/BioLINCC/projects/BL_ESCAPE_GRU","tags":[],"_unique_id":"phs003782.v1.p1.c1","study_id":"phs003782.v1.p1.c1","study_description":"Accessing Data Please refer to “Authorized Access” below regarding accessing data through the BioData Catalyst ecosystem. The data from this accession is not available for download through dbGaP. Objectives To test whether pulmonary artery catheter use was safe and could improve clinical outcomes in participants hospitalized with recurrent heart failure. Background Pulmonary artery catheters have been used to guide adjustment of therapy in multiple settings, but recent studies have raised concern that pulmonary artery catheters may lead to increased mortality in hospitalized participants. Participants A total of 433 participants at 26 sites were enrolled, and randomly assigned to receive therapy guided by clinical assessment and the pulmonary artery catheter or clinical assessment alone. Patients with acute decompensation in which the attending heart failure physician considered pulmonary artery catheterization (PAC) was required or likely to be required within the next 24 hours were entered into a PAC registry. A total of 439 patients were added to the registry. Conclusions Therapy to reduce volume overload during hospitalization for heart failure led to marked improvement in signs and symptoms of elevated filling pressures, with or without the pulmonary artery catheter. Addition of the pulmonary artery catheter to careful clinical assessment did not impact overall mortality and hospitalization. Future trials should test noninvasive assessments with specific treatment strategies that could be used to better tailor therapy for both survival time and survival quality as valued by participants. (Binanay, C. et al., JAMA, 2005) Study Weblinks: BioLINCC Study Design: Clinical Trial Study Type: Clinical Trial Total number of consented subjects: 872 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Evaluation Study of Congestive Heart Failure and Pulmonary Artery Catheterization Effectiveness (ESCAPE-BioLINCC)","short_name":"BL_ESCAPE_GRU","commons":"BioData Catalyst","study_url":"","_subjects_count":872,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs003783.v1.p1.c1":{"gen3_discovery":{"authz":"/programs/BioLINCC/projects/BL_RESTORE_GRU","tags":[],"_unique_id":"phs003783.v1.p1.c1","study_id":"phs003783.v1.p1.c1","study_description":"Data Access NOTE Please refer to the \"Authorized Access\" section below for information about how access to the data from this accession differs from many other dbGaP accessions. Objectives The primary aim of the RESTORE clinical trial was to determine whether critically ill children managed with a nurse-implemented, goal-directed sedation protocol would experience fewer days of mechanical ventilation than participants receiving usual care. Background Ensuring the safety and comfort of critically ill infants and children supported by mechanical ventilation is integral to the practice of pediatric critical care. Although sedation therapy benefits young participants who cannot understand the imperative nature of invasive life-sustaining therapies, sedative use is also associated with untoward adverse effects. Specifically, opioids and benzodiazepines commonly used for pediatric sedation may impair bedside neurological assessment, depress spontaneous ventilation, and prolong mechanical ventilation. Over time, drug tolerance develops, which may precipitate iatrogenic withdrawal syndrome when sedation therapy is no longer necessary.Numerous studies in adult critical care support a minimal yet effective approach to sedation management. Sedation goals for mechanically ventilated adults have shifted from an unresponsive state to a calm, easily aroused, readily evaluated participant. Studies in adult participants evaluating targeted sedation, daily interruption and/or titration of sedation, pairing of spontaneous awakening with breathing, and no sedation have reported improved clinical outcomes, including decreased length of mechanical ventilation when compared with usual care. In contrast, few data inform sedation practices in pediatric critical care, and international studies describe significant practice variation. Given unique biobehavioral differences, knowledge generated in adult critical care may not translate to the care of critically ill children. The RESTORE study was conducted to test the effect of a nurse-implemented, goal-directed sedation protocol on clinical outcomes in pediatric participants with acute respiratory failure. Participants There was a total of 2,449 participants (mean age: 4.7 years; range: 2 weeks to 17 years). Design The RESTORE study was a cluster randomized clinical trial conducted in 31 US PICUs. Intervention PICUs (17 sites; 1,225 participants) used a protocol that included targeted sedation, arousal assessments, extubation readiness testing, sedation adjustment every 8 hours, and sedation weaning. Control PICUs (14 sites; 1,224 participants) managed sedation per usual care. The primary outcome variable was duration of mechanical ventilation. Conclusions Among children undergoing mechanical ventilation for acute respiratory failure, the use of a sedation protocol compared with usual care did not reduce the duration of mechanical ventilation. Exploratory analyses of secondary outcomes suggest a complex relationship among wakefulness, pain, and agitation (JAMA 2015; 313(4):379-89). Study Weblinks: BioLINCC Repository Study Design: Clinical Trial Study Type: Clinical Trial Total number of consented subjects: 2449 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Randomized Evaluation of Sedation Titration for Respiratory Failure (RESTORE-BioLINCC)","short_name":"BL_RESTORE_GRU","commons":"BioData Catalyst","study_url":"","_subjects_count":2449,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs003784.v1.p1.c1":{"gen3_discovery":{"authz":"/programs/BioLINCC/projects/BL_ROC_ALPS_GRU","tags":[],"_unique_id":"phs003784.v1.p1.c1","study_id":"phs003784.v1.p1.c1","study_description":"Accessing Data Please refer to “Authorized Access” below regarding accessing data through the BioData Catalyst ecosystem. The data from this accession is not available for download through dbGaP. Objective To compare the effects of amiodarone, lidocaine, and placebo on survival to hospital discharge after out-of-hospital cardiac arrest due to shock-refractory ventricular fibrillation or pulseless ventricular tachycardia. Background Ventricular fibrillation (VF) or pulseless ventricular tachycardia (VT) are common causes of out-of-hospital cardiac arrest, but are considered the most responsive to shock and therefore the most treatable. Nonetheless, most defibrillation attempts do not result in sustained return of spontaneous circulation, and VF or VT may persist or recur after shock. There is also evidence that longer durations of VF or VT are associated with decreases in the likelihood of resuscitation. Amiodarone and lidocaine are commonly used to promote successful defibrillation of shock-refractory VF or VT and prevent recurrences. Previous trials have shown amiodarone to be more effective than placebo or lidocaine for return of spontaneous circulation and survival at hospital admittance. This study sought to further extend the research and examine whether amiodarone would improve survival to hospital discharge and neurologic outcomes, as compared to placebo or lidocaine. Participants 3,026 eligible participants were enrolled, with 974 assigned to amiodarone, 993 assigned to lidocaine, and 1,059 assigned to placebo. An additional 1,627 participants that received a study intervention, but did not meet eligibility criteria, were included in analysis of the intention-to-treat population. Design The study interventions (amiodarone, lidocaine, and saline) were packaged in indistinguishable sealed kits and randomly distributed in to Emergency Medical Services (EMS) providers in a 1:1:1 ratio, stratified by participating site and agency. Each kit contained three syringes, and each syringe held 3 ml of colorless fluid containing 150 mg of amiodarone, 60 mg of lidocaine, or normal saline. Participants with out-of-hospital cardiac arrest were treated in accordance with local EMS protocols, in compliance with American Heart Association (AHA) guidelines. If VF or VT persisted or recurred after one or more shocks, eligible participants received a vasopressor and the masked kit containing amiodarone, lidocaine, or placebo. Approximating current clinical practice, the initial dose consisted of two syringes administered by rapid bolus. If the estimated body weight of the patient was less than 100 lbs., then one syringe was used. If VF or VT persisted, standard resuscitation measures, additional shocks, and an additional syringe of the study drug were administered. At that point the trial interventions were completed and standard interventions for advanced life support were employed. Upon arrival at the hospital, providers were notified of the patient's enrollment in the trial and encouraged to provide usual care in accordance with AHA guidelines, including open-label amiodarone or lidocaine if necessary. Components of hospital care were monitored but not standardized by the trial protocol. Participants, providers, and trial personnel were blinded to the trial drug assignments, with the exception of treating physicians if emergency un-blinding was required for care. Data from pre-hospital patient care records, CPR process measures, and hospital medical records were collected. The primary outcome of the trial was survival to hospital discharge, and the secondary outcome was survival with favorable neurologic status at discharge, defined as a score on the modified Rankin scale of 3 or less. Conclusions Neither amiodarone nor lidocaine resulted in a significantly higher rate of survival to hospital discharge or favorable neurologic outcome, as compared to placebo, among participants with out-of-hospital cardiac arrest due to initial shock-refractory ventricular fibrillation or pulseless ventricular tachycardia. Study Weblinks: BioLINCC Study Design: Clinical Trial Study Type: Clinical Trial Total number of consented subjects: 4653 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Resuscitation Outcomes Consortium (ROC) Amiodarone, Lidocaine or Neither for Out-Of-Hospital Cardiac Arrest Due to Ventricular Fibrillation or Ventricular Tachycardia (ALPS)(ROC-ALPS-BioLINCC)","short_name":"BL_ROC_ALPS_GRU","commons":"BioData Catalyst","study_url":"","_subjects_count":4653,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs003791.v1.p1.c1":{"gen3_discovery":{"authz":"/programs/BioLINCC/projects/BL_PETAL_LOTUS_FRUIT_GRU","tags":[],"_unique_id":"phs003791.v1.p1.c1","study_id":"phs003791.v1.p1.c1","study_description":"Data Access NOTE: Please refer to the “Authorized Access” section below for information about how access to the data from this accession differs from many other dbGaP accessions. Objectives: The two main goals of PETAL-LOTUS FRUIT were to conduct a prospective, observational study within all PETAL Network sites to determine the frequency of and outcomes from acute respiratory failure and the current usual care for tidal volume ventilation in patients with and without acute respiratory distress syndrome (ARDS), and to simulate the design and power of the proposed LOTUS trial. Background: A previous study demonstrated improved survival among patients with ARDS receiving tidal volume (Vt) targeted to 6 ml/kg of predicted body weight (PBW). As a result, low–tidal volume ventilation (LTVV) is now recommended for all patients with ARDS, although penetration of this evidence-based practice has been limited, especially early in mechanical ventilation. LTVV may also benefit patients without ARDS. Consequently, there has been increasing call to apply LTVV for all patients with acute respiratory failure upon initiation of mechanical ventilation. The PETAL Network considered performing a pragmatic stepped-wedge, cluster-randomized, controlled, hybrid implementation trial to examine systematic implementation of a default 6 ml/kg PBW LTVV strategy in patients with acute respiratory failure requiring intubation to improve adherence to LTVV and decrease mortality in acute respiratory failure. Trial planning may be better estimated by simulation than routine, simplistic calculations, but such simulations require detailed data of initial parameters. Participants: 2848 patients from 49 hospitals were enrolled. Enrollment varied by hospital, ranging from 4 to 100 patients, the maximum enrollment allowed per site. Design: PETAL-LOTUS FRUIT was a multicenter, prospective, observational cohort study of patients with acute respiratory failure on mechanical ventilation in the PETAL Network hospitals. For all patients, baseline demographic data, the hospital location, indication for intubation (hypoxemic or hypercapnic respiratory failure or both, altered level of consciousness, or surgery), type of intensive care unit (ICU), and Sequential Organ Failure Assessment score in the first 24 hours after intubation were collected. Baseline ventilator data immediately after intubation, arterial blood gas results and oxygen saturation as measured by pulse oximetry, and presence of ARDS was also collected for all patients. ARDS was defined as a ratio of arterial oxygen tension to fraction of inspired oxygen (FiO2) less than or equal to 300 with a chest radiograph within 24 hours of the qualifying ratio of arterial oxygen tension to FiO2 that had bilateral infiltrates unexplained by mass, collapse, or effusion. For the first 50 patients enrolled at each hospital, daily data on ventilator mode, Vt, and presence of ARDS for the first 3 days after intubation was collected. Vt indexed to PBW was calculated from the set Vt for patients on ventilator mode with volume settings. For patients on pressure ventilation modes, Vt was calculated from the ratio of minute ventilation (in ml/min) to the respiratory rate. Enrolled patients were followed until hospital discharge or 28 days for clinical outcomes including mortality, ventilator-free days, and length of stay. To determine the possible improvement in mortality that could be observed with a reduction in Vt from current usual care in the PETAL-LOTUS FRUIT cohort to 6 ml/kg PBW, mortality was estimated as a function of initial Vt. Five models based on data from three distinct patient populations were used. 500 simulations of a stepped-wedge, cluster-randomized clinical trial using the model with greatest predicted benefit for lowering the Vt to 6 ml/kg PBW in PETAL-LOTUS FRUIT sites were performed. Conclusions: Use of initial tidal volumes less than 8 ml/kg predicted body weight was common at hospitals participating in the PETAL Network. After considering the size and budgetary requirement for a cluster-randomized trial of LTVV versus usual care in acute respiratory failure, the PETAL Network deemed the proposed trial infeasible (PMID: 30407869). Study Weblinks: BioLINCC Repository Study Design: Prospective Longitudinal Cohort Study Type: Observational Total number of consented subjects: 2848 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Prevention and Early Treatment of Acute Lung Injury (PETAL) - Low Tidal Volume Universal Support Feasibility of Recruitment for Interventional Trial (LOTUS FRUIT) (PETAL-LOTUS FRUIT-BioLINCC)","short_name":"BL_PETAL_LOTUS_FRUIT_GRU","commons":"BioData Catalyst","study_url":"","_subjects_count":2848,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs003803.v1.p1.c1":{"gen3_discovery":{"authz":"/programs/BioLINCC/projects/BL_ROC_Cardiac_Epistry_1_2_GRU","tags":[],"_unique_id":"phs003803.v1.p1.c1","study_id":"phs003803.v1.p1.c1","study_description":"Data Access NOTE: Please refer to the “Authorized Access” section below for information about how access to the data from this accession differs from many other dbGaP accessions. Available Data: The ROC Cardiac Epistry versions 1 and 2 include all cardiac arrest cases entered into the ROC database from December 1, 2005 to April 1, 2011. ROC Cardiac Epistry 3 includes cardiac arrest cases captured between 2011 and 2015, and introduced significant changes in how and which data were collected.For ROC traumatic injury Epistry data, please see: ROC-Trauma Epistry Objectives: To build a prospective population-based registry of participants with out-of-hospital cardiac arrest responded to by Emergency Medical Services (EMS). Specific aims: to establish whether the results of Resuscitation Outcomes Consortium (ROC) trials can be generalized to the larger population of participants that experience cardiac arrest;to more fully establish the burden of cardiac arrest; and to examine the relationships between variation in EMS structure and process, regional and periodic factors, and participant outcomes.Background: Cardiac arrest is a common, serious, debilitating and costly public health problem. Although there has been a steady decline in morbidity and mortality from most cardiovascular diseases, high mortality rates for out-of-hospital cardiac arrests continue to pose a challenge for healthcare providers and a significant public health burden. The Resuscitation Outcomes Consortium (ROC) was established in 2004 to conduct clinical research in the areas of cardiopulmonary arrest and life-threatening traumatic injury with the overall goal of improving resuscitation outcomes. Participant and care characteristics can predict favorable outcomes in cardiac arrests, but there is still a wide variation in outcomes that is not well understood. EMS factors such as service level, number of responding providers, use of procedures or drugs in the field, training, quality assurance/feedback, and response time intervals also vary significantly by region. Variations in geographic, socioeconomic and periodic factors may also be associated with differences in outcomes.Prior to ROC Cardiac Epistry, there were no North American population-based registries for out-of-hospital cardiac arrests. Therefore there was a need for standardized data collection of out-of-hospital cardiac arrests in diverse geographic locations in order to identify the independent effects of prognostic or treatment factors accounting for variations in survival. Participants: The registry included 109,326 cardiac arrest events from 264 EMS agencies transporting to 287 acute care hospitals from the following regional centers: Birmingham, Alabama; Dallas, Texas; Iowa City, Iowa; Milwaukee, Wisconsin; Pittsburgh, Pennsylvania; Portland, Oregon; San Diego, California; Seattle/King County, Washington; Ottawa, Ontario; Toronto, Ontario; and Vancouver, British Columbia.Design: ROC Epistry collected standardized data regarding episode-specific factors, participant demographics, clinical information, pre-hospital interventions and disposition, hospital information, and participant outcome for all out-of-hospital cardiac arrests in the ROC regions. Each ROC site had to ensure capture of all eligible cases within the EMS service areas. Out-of-hospital data were extracted from existing databases whenever possible and augmented with targeted review of EMS reports. Hospital data were abstracted directly from the hospital file in most cases. Alternative methods included linkage to death registries and obituaries if the death occurred within 30 days. Sites submitted data using a web-based interface or batch uploads. Participants were not contacted directly. Study Weblinks: BioLINCC Repository Study Design: Prospective Longitudinal Cohort Study Type: Observational Total number of consented subjects: 109326 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Resuscitation Outcomes Consortium (ROC) Cardiac Epidemiologic Registry (Cardiac Epistry) Versions 1 and 2 (ROC-Cardiac Epistry 1 and 2-BioLINCC)","short_name":"BL_ROC_Cardiac_Epistry_1_2_GRU","commons":"BioData Catalyst","study_url":"","_subjects_count":109326,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs003804.v1.p1.c1":{"gen3_discovery":{"authz":"/programs/imaging/projects/img_HFN_INDIE_GRU-IRB","tags":[],"_unique_id":"phs003804.v1.p1.c1","study_id":"phs003804.v1.p1.c1","study_description":"Data Access NOTE: Please refer to the \"Authorized Access\" section below for information about how access to the data from this accession differs from many other dbGaP accessions. Objective: To determine the effect of inhaled, nebulized inorganic nitrite on exercise capacity in patients with heart failure with preserved ejection fraction.Background: Approximately half of patients with heart failure have a preserved ejection fraction (HFpEF). However, there are no proven effective medical treatments for this syndrome. Evidence suggests that impairments in nitric oxide availability have a potentially important role in the pathophysiology of HFpEF.Unlike organic nitrates, inorganic nitrite is converted to nitric oxide in the presence of hypoxia and acidosis, conditions that develop during exercise. Because the cardiac, vascular, and skeletal muscle abnormalities that limit physical capacity and contribute to symptoms in patients with HFpEF characteristically develop during exercise, inorganic nitrite may provide the best way to target nitric oxide delivery precisely at the time of greatest need. The HFN-INDIE trial was initiated to test the hypothesis that compared to placebo, longer-term use of inhaled, nebulized inorganic nitrite would enhance peak exercise capacity in patients with HFpEF. Participants: A total of 105 participants were randomized. 53 were randomized to receive nitrite first and 52 were randomized to receive placebo first.Design: HFN-INDIE was a multicenter, randomized, double-blind, placebo-controlled, crossover study. After enrollment, patients underwent baseline studies to determine eligibility. All patients were required to display objective exercise limitation, evidenced by reduced peak oxygen consumption (V̇o2) on cardiopulmonary exercise testing of less than 75% predicted, with a respiratory exchange ratio indicative of maximal effort (≥1.0). Following qualifying exercise testing, eligible participants received an open-label, single-dose run-in of inhaled, nebulized sodium nitrite (80 mg) to assess tolerability, symptoms, and orthostatic vital signs. Patients developing hypotension (systolic blood pressure <90 mm Hg seated or standing), light-headedness, or any other intolerance were categorized as a run-in failure and were not randomized. Following the baseline studies, eligible patients were randomly assigned to either receive nitrite first or to receive placebo first. Study drug was administered 3 times a day by nebulizer. During each 6-week period, patients were instructed to take no study drug for the first 2 weeks (baseline phase during the first period and washout phase during the second period), followed by 46 mg 3 times daily for 1 week, and then 80 mg 3 times daily for 3 weeks. After the first period, patients returned to the study center to receive the crossover study drug.The prespecified primary end point was peak V̇o2, measured as the highest 30-second average during upright cycle ergometry, during the 4-week period in which patients were receiving inorganic nitrite as compared with placebo. Accelerometry, health-related quality-of-life scores on the self-administered Kansas City Cardiomyopathy Questionnaire (score range, 0-100, with higher scores indicating better quality of life), echocardiographic indicators of cardiac filling pressures measured at trough drug levels (E/e′ ratio, estimated pulmonary artery systolic pressure, and left atrial volume index; lower scores indicate better health for all), ventilatory efficiency (VE/V̇co2, lower indicating better health), exercise time (higher indicating better health), and NT-proBNP levels (lower indicating better health) were also collected.Data Availability: Data available from this study includes transthoracic echocardiogram images from multiple timepoints. There are 199 echocardiographic exams available, totaling over 13,100 individual echocardiogram images. Conclusions: Among patients with HFpEF, administration of inhaled inorganic nitrite for 4 weeks, compared with placebo, did not result in significant improvement in exercise capacity.Reference: Borlaug et al., 2018, PMID: 30398602. Study Weblinks: BioLINCC Study Design: Clinical Trial Study Type: Clinical Trial Controlled Trial Double-Blind Interventional Total number of consented subjects: 100 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Inorganic Nitrite Delivery to Improve Exercise Capacity in Heart Failure with Preserved Ejection Fraction (INDIE-HFpEF): Heart Failure Network (HFN INDIE-Imaging)","short_name":"img_HFN_INDIE_GRU-IRB","commons":"BioData Catalyst","study_url":"","_subjects_count":100,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs003809.v1.p1.c1":{"gen3_discovery":{"authz":"/programs/BioLINCC/projects/BL_ROC-Trauma_Epistry_GRU","tags":[],"_unique_id":"phs003809.v1.p1.c1","study_id":"phs003809.v1.p1.c1","study_description":"Data Access NOTE: Please refer to the \"Authorized Access\" section below for information about how access to the data from this accession differs from many other dbGaP accessions.Available Data: This dataset only includes traumatic injury participants. For ROC cardiac arrest Epistry data please see: ROC-Cardiac Epistry 1 and 2 and ROC-Cardiac Epistry 3.Objectives: To build a prospective population-based registry of participants with out-of-hospital traumatic injury responded to by Emergency Medical Services (EMS). Specific aims included: to establish whether the results of Resuscitation Outcomes Consortium (ROC) trials can be generalized to the larger population of people that experience traumatic injury; to more fully establish the burden of traumatic injury; and to examine the relationships between variation in EMS structure and process, regional and periodic factors, and participant outcomes.Background: Traumatic injury is a major public health problem generating substantial morbidity, mortality, and economic burden on society. The majority of seriously injured persons are initially evaluated and cared for by prehospital providers, however the effect of EMS systems, EMS clinical care, and EMS interventions on trauma patient outcomes is largely unknown. EMS factors such as service level, number of responding providers, use of procedures or drugs in the field, training, quality assurance/feedback, and response time intervals also vary significantly by region.The Resuscitation Outcomes Consortium (ROC) was established in 2004 to conduct clinical research in the areas of cardiopulmonary arrest and life-threatening traumatic injury with the overall goal of improving resuscitation outcomes. Previous trauma registries have generally focused primarily on hospitalized patients with limited prehospital information. Registries may also exclude trauma cases at far ends of the spectrum, such as those who die in the field or in a non-trauma center and/or patients that are treated and released. These limitations do not allow for detailed, outcome-based assessments of EMS system factors necessary to define prehospital resuscitation best practices. Therefore there was a need for standardized data collection of out-of-hospital traumatic injuries matched to hospital-based outcomes in diverse geographic locations in order to identify the independent effects of prognostic or treatment factors accounting for variations in survival. Participants: The registry included 13,830 traumatic events from 264 EMS agencies transporting to 287 acute care hospitals from the following regional centers: Birmingham, Alabama; Dallas, Texas; Iowa City, Iowa; Milwaukee, Wisconsin; Pittsburgh, Pennsylvania; Portland, Oregon; San Diego, California; Seattle/King County, Washington; Ottawa, Ontario; Toronto, Ontario; and Vancouver, British Columbia.Design: ROC Epistry collected standardized data regarding episode-specific factors, participant demographics, clinical information, pre-hospital interventions and disposition, hospital information, and participant outcome for all out-of-hospital traumatic injuries in the ROC regions. Cases were identified through review of emergency response system records including dispatch centers, EMS ground agencies, and air medical services. Out-of-hospital data were extracted from existing databases whenever possible and augmented with targeted review of EMS reports. Hospital data were abstracted directly from the hospital file in most cases. Sites submitted data using a web-based interface or batch uploads (Newgard, et al., 2008, PMID: 18482792). Study Weblinks: BioLINCC Repository Study Design: Prospective Longitudinal Cohort Study Type: Observational Total number of consented subjects: 13730 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Resuscitation Outcomes Consortium (ROC) Trauma Epidemiologic Registry (Trauma Epistry) (ROC-Trauma Epistry-BioLINCC)","short_name":"BL_ROC-Trauma_Epistry_GRU","commons":"BioData Catalyst","study_url":"","_subjects_count":13730,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs003818.v1.p1.c1":{"gen3_discovery":{"authz":"/programs/BioLINCC/projects/BL_ROC_CPR_GRU","tags":[],"_unique_id":"phs003818.v1.p1.c1","study_id":"phs003818.v1.p1.c1","study_description":"Data Access NOTE: Please refer to the \"Authorized Access\" section below for information about how access to the data from this accession differs from many other dbGaP accessions.Objectives: A substudy of the ROC PRIMED trial, the ROC CPR trial sought to investigate whether real-time audio and visual feedback during cardiopulmonary resuscitation (CPR) outside a hospital increases the proportion of participants who achieved prehospital return of spontaneous circulation.Background: Cardiopulmonary resuscitation is an essential link in the chain of survival for treating cardiac arrest. However, performance of CPR is highly variable both outside hospital and in hospital. Interruptions in chest compression, inadequate depth of chest compression, and high rates of ventilation adversely affect blood flow during chest compressions and can hinder resuscitation. Suboptimal CPR, particularly time spent without chest compressions (low chest compression fraction), can reduce survival of cardiac arrest patients.Current technology incorporated into a monitor-defibrillator can assess core components of CPR through the use of an accelerometer and impedance changes across the defibrillation electrodes. This technology can also provide real-time audiovisual feedback so that the rescuer is prompted to perform according to guideline specifications. Use of such feedback increases the likelihood of performing CPR in accordance with guidelines during training and simulation. Participants: There were 1586 participants: 771 treated without feedback and 815 with feedback.Design: CPR feedback was provided through proprietary Q-CPR software operating in the Philips MRx monitor-defibrillator. The feedback feature of the defibrillator includes audible voice prompts and visual messages on the monitor screen that are triggered when measured chest compressions or ventilation deviate from guidelines or are interrupted.The study was conducted in 21 emergency medical service (EMS) agencies at three ROC regions in the U.S. and Canada. Randomized treatment clusters, which ranged from individual emergency medical vehicles to groups of emergency agencies, were assigned to feedback-on or feedback-off treatments. Each cluster remained in its assigned mode for two to seven months, after which it switched to the opposite treatment arm. At the end of those two treatment periods, each cluster was again randomly assigned to feedback-on or feedback-off. This cycle continued for the duration of the study. Each cluster switched treatment arms at least once, and up to four times, during the study. Conclusions: Real-time visual and audible feedback during CPR altered performance to more closely conform with CPR guidelines. Clusters assigned to feedback were associated with increased proportion of time in which chest compressions were provided, increased compression depth, and decreased proportion of compressions with incomplete release. However, frequency of prehospital return of spontaneous circulation did not differ according to feedback status, nor did the presence of a pulse at hospital arrival, survival to discharge, or awake at hospital discharge (Hostler, et al., 2011, PMID: 21296838). Study Weblinks: BioLINCC Repository Study Design: Clinical Trial Study Type: Clinical Trial Total number of consented subjects: 1818 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Resuscitation Outcomes Consortium (ROC) Controlled Study of the Clinical Effectiveness of Automated Real-Time Feedback on CPR Process Conducted at a Subset of ROC Sites (CPR) (ROC-CPR-BioLINCC)","short_name":"BL_ROC_CPR_GRU","commons":"BioData Catalyst","study_url":"","_subjects_count":1818,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs003824.v1.p1.c1":{"gen3_discovery":{"authz":"/programs/imaging/projects/img_WHI_HMB","tags":[],"_unique_id":"phs003824.v1.p1.c1","study_id":"phs003824.v1.p1.c1","study_description":"Objectives: The clinical trial assessed the safety and efficacy of three interventions. Specifically, it evaluated (1) the major health benefits and risks of estrogen plus progestin and estrogen alone, (2) the effects of a low-fat eating pattern on risk of colorectal cancer, and (3) the efficacy of calcium with vitamin D supplementation for preventing hip and other fractures. The objective of the memory study was to determine whether estrogen plus progestin therapy protects global cognitive function, and evaluate the therapy's effect on the incidence of dementia and mild cognitive impairment.The observational study is examining the relationship between lifestyle, socioeconomic, health, and other risk factors with cardiovascular, breast cancer, colorectal cancer and osteoporotic fracture outcomes. Secondary objectives include providing more reliable estimates of the extent to which known risk factors predict disease, more precise estimates of new occurrences of disease, and to provide a future resource for the identification of new or novel risk factors especially factors found in blood. Background: The Women's Health Initiative (WHI) is a long-term national health study that has focused on strategies for preventing the major causes of death, disability, and frailty in postmenopausal women, specifically heart disease, cancer, and osteoporotic fractures. The WHI is primarily composed of an observational study (OS), as well a clinical trial (CT) with three components: Hormone Replacement Therapy (HT), Dietary Modification, (DM) and Calcium/Vitamin D supplementation (CaD).Prior to the WHI, observational studies suggested that postmenopausal hormone therapy was associated with a decreased risk of coronary heart disease (CHD). Potential cardioprotection was based on generally supportive data on lipid levels in intermediate outcome clinical trials, trials in nonhuman primates, and a large body of observational studies suggesting a 40% to 50% reduction in risk among users of either estrogen alone or, less frequently, combined estrogen and progestin. Observational studies primarily examining unopposed estrogen preparations have suggested a 30% to 50% reduction in coronary events, and an 8% to 30% increase in breast cancer with extended use. Other research findings indicated that hormone therapy was also associated with a decreased risk of osteoporosis and increased bone density. The WHI HT trials were designed to test the effects of postmenopausal hormone therapy on risk for coronary heart disease and assess overall risks and benefits in predominantly healthy women. The Women's Health Initiative Memory Program (WHIMS) consists of a suite of studies which include cohorts of women who participated in the WHI HT trials. Postmenopausal women have a greater risk than men of developing Alzheimer's disease, but studies of the effects of estrogen therapy on Alzheimer's disease have been inconsistent. Additionally, observational studies have suggested that postmenopausal hormone treatment may improve cognitive function, but data from randomized clinical trials have been sparse and inconclusive. International comparisons and migration studies have suggested that countries with 50% lower fat intake than the US population had approximately one third the risk of colorectal cancer. Additionally, fairly consistent evidence existed for an effect of dietary fat, vegetables and fruits, and grains on colorectal cancer risk from within-country observational studies, although the protective effect of lower fat intake was no longer clear after adjusting for energy intake. The WHI DM trial was the first randomized trial to directly address the health effects of a low-fat eating pattern in predominantly healthy postmenopausal women from diverse racial/ethnic, geographic, and socioeconomic backgrounds. Osteoporosis is a major cause of injury, loss of independence, and death, and contributes to hip fractures. Observational evidence and data from previous randomized clinical trials suggest that calcium and/or vitamin D supplements may slow bone loss and reduce the risk of falls in postmenopausal and elderly women. However, evidence from trials, observational studies, and meta-analyses of calcium and vitamin D supplementation with respect to hip and other fractures was limited at the time the WHI was initiated. In two prior randomized trials, calcium plus vitamin D supplements did not reduce the risk of nonvertebral fractures among older women. When the WHI CaD trial was designed, guidelines recommended daily intakes of 800 to 1200 mg of calcium with 400 IU of vitamin D for the prevention of osteoporosis, which was not met by many American women. Therefore, the WHI CaD trial was designed to test the primary hypothesis that postmenopausal women randomly assigned to calcium plus vitamin D supplementation would have a lower risk of hip fracture and, secondarily, of all fractures than women assigned to placebo. Subjects: Postmenopausal women ages 50 to 79 were eligible to participate. A woman was considered postmenopausal if she had experienced no vaginal bleeding for 6 months (12 months for women under 55 years of age), had had a hysterectomy, or had ever used postmenopausal hormones. Recruitment was carried out in 40 US clinical centers in 1993-1998. The clinical trial components had additional specific inclusion or exclusion criteria.A total of 68,132 women were randomized into at least one component of the clinical trial. 27,347 women were enrolled in the hormone therapy component with 16,608 in the estrogen plus progestin trial and 10,739 in the unopposed estrogen trial, 48,835 women were enrolled in the diet modification component, and 36,282 women were enrolled in the calcium/vitamin D component. 7,479 women 65 years of age and older at baseline and that participated in the HT trial component were enrolled in the ancillary memory study. Women who were either ineligible or unwilling to participate in the clinical trial component were enrolled in the observational study. For example, many potential participants to the clinical trial component of the study were already undertaking a low fat diet or were using hormone replacement therapy. The effect of the selection process was that women enrolled in the observational study tended to have healthier lifestyles compared to those enrolled in the clinical trial. In total, 93,676 subjects were enrolled in WHI OS, with over 16% being members of a racial/ethnic minority group. The first WHI Extension Study enrolled 115,407 consenting participants from all components of the original WHI study for an additional five years of follow-up, from 2005 to 2010. In 2010, 93,567 women consented to continued follow-up. Design: The clinical trial component of the WHI included three randomized comparisons: hormone therapy, dietary modification, and calcium/vitamin D supplementation. Women could have been randomized into one, two or all three trials.The hormone therapy trial enrolled women to one of two double-blinded trials: estrogen (0.625 mg of conjugated equine estrogens daily) plus progestin (2.5 mg of medroxyprogesterone acetate daily) or estrogen alone. Women with a prior hysterectomy were eligible for the trial of unopposed estrogen. Women with an intact uterus at screening were initially also eligible for unopposed estrogen, but were reassigned to the trial of combined postmenopausal hormones beginning in 1995. Both trials randomized participants 1:1 to either hormone therapy or placebo. A 3-month washout period was required before baseline evaluation of women using postmenopausal hormones at initial screening. Study participants were contacted by telephone 6 weeks after randomization to assess symptoms and reinforce adherence. Follow-up contacts by telephone or clinic visit occurred every 6 months, with clinic visits required annually. The estrogen plus progestin trial was halted in July 2002 after a mean 5.2 years of follow-up because health risks, including increased risk of breast cancer and cardiovascular disease, exceeded benefits. The estrogen alone trial was stopped early in March 2004, because an increased risk of stroke was found with no benefit for coronary heart disease. The primary outcome was coronary heart disease (CHD) (nonfatal myocardial infarction and CHD death), with invasive breast cancer as the primary adverse outcome. The dietary modification trial evaluated the effect of a low-fat, high fruit, vegetable, and grain diet on preventing cardiovascular disease and cancer. Participants were randomly assigned to an intervention or a comparison group in the ratio of 2:3 for cost-efficiency. The intervention was an intensive behavioral modification program, using 18 group sessions in the first year and quarterly sessions thereafter, led by specially trained and certified nutritionists. The program was designed to promote dietary change with the goals of reducing total fat to 20% of energy intake, increasing vegetables and fruits to at least 5 servings daily and grains to at least 6 servings daily. The intervention did not include total energy reduction or weight loss goals. Comparison group participants received a copy of the US Department of Health and Human Services' Dietary Guidelines for Americans and other health-related materials but were not asked to make dietary changes. Dietary intake was monitored using the WHI food frequency questionnaire at 1 year and in a rotating one-third subsample every year thereafter. Women completed a medical update questionnaire every 6 months, and medical records were sought for all women reporting colorectal cancer. The primary outcome was invasive colorectal cancer incidence. Participants in the calcium/vitamin D trial were randomized 1:1 to either supplements or placebo. Active tablets contained 500 mg of elemental calcium (as calcium carbonate) and 200 IU of vitamin D3, to be taken twice daily with meals. The presence and severity of symptoms, safety concerns, and outcomes were ascertained at annual clinic visits and telephone or clinic visits at intervening six-month intervals. Risk factors for fracture were assessed by questionnaire, interview, and clinical examination. The primary outcome was incidence of hip fracture. Participants in the observational study attended a baseline examination and were re-examined three years later. Participants completed annual updates of exposures and clinical outcomes by mail. Final data were collected by mail during the close-out period in April 2004 to March 2005. The major clinical outcomes of interest were coronary heart disease, stroke, breast cancer, colorectal cancer, endometrial cancer, ovarian cancer, osteoporotic fractures, diabetes, and total mortality. Most outcomes were initially ascertained by self-report on an annual questionnaire and documented by hospital and related records. Charts with potential cardiovascular, cancer, and fracture outcomes were sent to the local physician adjudicator for evaluation and classification. Staff at the Clinical Coordinating Center coded and adjudicated all cancers of major interest in the study using standardized SEER guidelines. In 2005, WHI participants were invited to join the Extension Study for an additional five years of follow-up in order to collect long-term outcomes. Participants completed annual data collection forms primarily by mail, similar to the OS follow-up. Women reporting study outcomes were contacted by WHI field center staff to obtain additional details and medical records, which were evaluated by physician adjudicators. In 2010, the woman remaining were invited to join the next Extension Study. In the second extension, women were divided into two groups, one of which would have outcomes documented with medical records (the Medical Records Cohort, MRC), and the other would just be followed by self-report (the Self-Report Cohort, SRC). The MRC consists of women who were in the hormone therapy trials, and all African-American and Hispanic women. In 2012-2013, a subset of the MRC was identified for a potential in-home visit to collect blood and several objective measures of physical functioning. Conclusions: Overall health risks exceeded benefits from use of combined estrogen plus progestin after an average 5.2 year follow-up among healthy postmenopausal US women (Rossouw et al., 2002, PMID:12117397). Among postmenopausal women aged 65 years or older, estrogen plus progestin did not improve cognitive function when compared with placebo (Rapp et al., 2003, PMID: 12771113), increased the risk for probable dementia, and did not prevent mild cognitive impairment (Shumaker, et al., 2003, PMID: 12771112). The use of conjugated equine estrogen increased the risk of stroke, decreased the risk of hip fracture, and did not affect CHD incidence in postmenopausal women with prior hysterectomy after an average of 6.8 years of follow-up (Anderson et al., 2004, PMID: 15082697). Over approximately 8 years of follow-up, a low-fat dietary pattern did not reduce the risk of colorectal cancer (Beresford, et al., PMID: 16467233). Calcium with vitamin D supplementation resulted in a small but significant improvement in hip bone density; however, no significant difference was observed in hip fractures (Jackson, et al., 2006, PMID: 16481635). A recent review summarizes the conclusions from the WHI clinical trials with a focus on clinical practice (Manson, et al., 2024, PMID: 38691368).Description of ECG Imaging Data: Electric cardiograms (ECGs) were given to all clinical trial participants at baseline and in years 3, 6, and 9 of the original WHI study.EKG data consist of 12 lead 10 seconds ECGS sampled at 500Hz via GE ECG machines and process via GE MUSE system. The ECG waveform were directly exported from GE MUSE using MUSE export function in XML format, which include EKG waveform data as well as other ECG characteristics. Waveform data is in base64 encoded format, when it is decoded, it is a binary data that can be used to draw waveform graph. Many programming languages and data tools have built in functions to decode base64 strings. All the other necessary information is included in the LeadData section, total byte size, total sample size etc. (usually 1 sample is 2 bytes). See example below: encoded-data (base64 encoded string) JwAoAC0AKAAiACIAJAAkACQAIwAiACIAHgAcABwAGwAZABgAGAAYABcAEwAQABAAEAAL^/AAsADAAM... decoded-binary-data (1 sample is 2 bytes) 270028002D002800220022002400240024002300220022001E001C001C001B00 1900180018001800170013001000100010000B000B000C000C000D000D000D00 0A000A000A0009000600040004000700070005000500020... These binary values are integers (Y axis data of the graph), hence it is a straightforward process to draw the waveform graph. Acquisition dates have been redacted from this ECG data to comply with WHI policy. All acquisition dates within files and in file names have been set to January 1, 1900 (19000101) to comply with this policy. Study Weblinks: Women's Health Initiative Study Design: Clinical Trial Study Type: Cohort Double-Blind Longitudinal Partial Factorial Randomized Placebo-Controlled Total number of consented subjects: 67979 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Women's Health Initiative Clinical Trial and Observational Study - Imaging","short_name":"img_WHI_HMB","commons":"BioData Catalyst","study_url":"","_subjects_count":59663,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs003824.v1.p1.c2":{"gen3_discovery":{"authz":"/programs/imaging/projects/img_WHI_HMB-NPU","tags":[],"_unique_id":"phs003824.v1.p1.c2","study_id":"phs003824.v1.p1.c2","study_description":"Objectives: The clinical trial assessed the safety and efficacy of three interventions. Specifically, it evaluated (1) the major health benefits and risks of estrogen plus progestin and estrogen alone, (2) the effects of a low-fat eating pattern on risk of colorectal cancer, and (3) the efficacy of calcium with vitamin D supplementation for preventing hip and other fractures. The objective of the memory study was to determine whether estrogen plus progestin therapy protects global cognitive function, and evaluate the therapy's effect on the incidence of dementia and mild cognitive impairment.The observational study is examining the relationship between lifestyle, socioeconomic, health, and other risk factors with cardiovascular, breast cancer, colorectal cancer and osteoporotic fracture outcomes. Secondary objectives include providing more reliable estimates of the extent to which known risk factors predict disease, more precise estimates of new occurrences of disease, and to provide a future resource for the identification of new or novel risk factors especially factors found in blood. Background: The Women's Health Initiative (WHI) is a long-term national health study that has focused on strategies for preventing the major causes of death, disability, and frailty in postmenopausal women, specifically heart disease, cancer, and osteoporotic fractures. The WHI is primarily composed of an observational study (OS), as well a clinical trial (CT) with three components: Hormone Replacement Therapy (HT), Dietary Modification, (DM) and Calcium/Vitamin D supplementation (CaD).Prior to the WHI, observational studies suggested that postmenopausal hormone therapy was associated with a decreased risk of coronary heart disease (CHD). Potential cardioprotection was based on generally supportive data on lipid levels in intermediate outcome clinical trials, trials in nonhuman primates, and a large body of observational studies suggesting a 40% to 50% reduction in risk among users of either estrogen alone or, less frequently, combined estrogen and progestin. Observational studies primarily examining unopposed estrogen preparations have suggested a 30% to 50% reduction in coronary events, and an 8% to 30% increase in breast cancer with extended use. Other research findings indicated that hormone therapy was also associated with a decreased risk of osteoporosis and increased bone density. The WHI HT trials were designed to test the effects of postmenopausal hormone therapy on risk for coronary heart disease and assess overall risks and benefits in predominantly healthy women. The Women's Health Initiative Memory Program (WHIMS) consists of a suite of studies which include cohorts of women who participated in the WHI HT trials. Postmenopausal women have a greater risk than men of developing Alzheimer's disease, but studies of the effects of estrogen therapy on Alzheimer's disease have been inconsistent. Additionally, observational studies have suggested that postmenopausal hormone treatment may improve cognitive function, but data from randomized clinical trials have been sparse and inconclusive. International comparisons and migration studies have suggested that countries with 50% lower fat intake than the US population had approximately one third the risk of colorectal cancer. Additionally, fairly consistent evidence existed for an effect of dietary fat, vegetables and fruits, and grains on colorectal cancer risk from within-country observational studies, although the protective effect of lower fat intake was no longer clear after adjusting for energy intake. The WHI DM trial was the first randomized trial to directly address the health effects of a low-fat eating pattern in predominantly healthy postmenopausal women from diverse racial/ethnic, geographic, and socioeconomic backgrounds. Osteoporosis is a major cause of injury, loss of independence, and death, and contributes to hip fractures. Observational evidence and data from previous randomized clinical trials suggest that calcium and/or vitamin D supplements may slow bone loss and reduce the risk of falls in postmenopausal and elderly women. However, evidence from trials, observational studies, and meta-analyses of calcium and vitamin D supplementation with respect to hip and other fractures was limited at the time the WHI was initiated. In two prior randomized trials, calcium plus vitamin D supplements did not reduce the risk of nonvertebral fractures among older women. When the WHI CaD trial was designed, guidelines recommended daily intakes of 800 to 1200 mg of calcium with 400 IU of vitamin D for the prevention of osteoporosis, which was not met by many American women. Therefore, the WHI CaD trial was designed to test the primary hypothesis that postmenopausal women randomly assigned to calcium plus vitamin D supplementation would have a lower risk of hip fracture and, secondarily, of all fractures than women assigned to placebo. Subjects: Postmenopausal women ages 50 to 79 were eligible to participate. A woman was considered postmenopausal if she had experienced no vaginal bleeding for 6 months (12 months for women under 55 years of age), had had a hysterectomy, or had ever used postmenopausal hormones. Recruitment was carried out in 40 US clinical centers in 1993-1998. The clinical trial components had additional specific inclusion or exclusion criteria.A total of 68,132 women were randomized into at least one component of the clinical trial. 27,347 women were enrolled in the hormone therapy component with 16,608 in the estrogen plus progestin trial and 10,739 in the unopposed estrogen trial, 48,835 women were enrolled in the diet modification component, and 36,282 women were enrolled in the calcium/vitamin D component. 7,479 women 65 years of age and older at baseline and that participated in the HT trial component were enrolled in the ancillary memory study. Women who were either ineligible or unwilling to participate in the clinical trial component were enrolled in the observational study. For example, many potential participants to the clinical trial component of the study were already undertaking a low fat diet or were using hormone replacement therapy. The effect of the selection process was that women enrolled in the observational study tended to have healthier lifestyles compared to those enrolled in the clinical trial. In total, 93,676 subjects were enrolled in WHI OS, with over 16% being members of a racial/ethnic minority group. The first WHI Extension Study enrolled 115,407 consenting participants from all components of the original WHI study for an additional five years of follow-up, from 2005 to 2010. In 2010, 93,567 women consented to continued follow-up. Design: The clinical trial component of the WHI included three randomized comparisons: hormone therapy, dietary modification, and calcium/vitamin D supplementation. Women could have been randomized into one, two or all three trials.The hormone therapy trial enrolled women to one of two double-blinded trials: estrogen (0.625 mg of conjugated equine estrogens daily) plus progestin (2.5 mg of medroxyprogesterone acetate daily) or estrogen alone. Women with a prior hysterectomy were eligible for the trial of unopposed estrogen. Women with an intact uterus at screening were initially also eligible for unopposed estrogen, but were reassigned to the trial of combined postmenopausal hormones beginning in 1995. Both trials randomized participants 1:1 to either hormone therapy or placebo. A 3-month washout period was required before baseline evaluation of women using postmenopausal hormones at initial screening. Study participants were contacted by telephone 6 weeks after randomization to assess symptoms and reinforce adherence. Follow-up contacts by telephone or clinic visit occurred every 6 months, with clinic visits required annually. The estrogen plus progestin trial was halted in July 2002 after a mean 5.2 years of follow-up because health risks, including increased risk of breast cancer and cardiovascular disease, exceeded benefits. The estrogen alone trial was stopped early in March 2004, because an increased risk of stroke was found with no benefit for coronary heart disease. The primary outcome was coronary heart disease (CHD) (nonfatal myocardial infarction and CHD death), with invasive breast cancer as the primary adverse outcome. The dietary modification trial evaluated the effect of a low-fat, high fruit, vegetable, and grain diet on preventing cardiovascular disease and cancer. Participants were randomly assigned to an intervention or a comparison group in the ratio of 2:3 for cost-efficiency. The intervention was an intensive behavioral modification program, using 18 group sessions in the first year and quarterly sessions thereafter, led by specially trained and certified nutritionists. The program was designed to promote dietary change with the goals of reducing total fat to 20% of energy intake, increasing vegetables and fruits to at least 5 servings daily and grains to at least 6 servings daily. The intervention did not include total energy reduction or weight loss goals. Comparison group participants received a copy of the US Department of Health and Human Services' Dietary Guidelines for Americans and other health-related materials but were not asked to make dietary changes. Dietary intake was monitored using the WHI food frequency questionnaire at 1 year and in a rotating one-third subsample every year thereafter. Women completed a medical update questionnaire every 6 months, and medical records were sought for all women reporting colorectal cancer. The primary outcome was invasive colorectal cancer incidence. Participants in the calcium/vitamin D trial were randomized 1:1 to either supplements or placebo. Active tablets contained 500 mg of elemental calcium (as calcium carbonate) and 200 IU of vitamin D3, to be taken twice daily with meals. The presence and severity of symptoms, safety concerns, and outcomes were ascertained at annual clinic visits and telephone or clinic visits at intervening six-month intervals. Risk factors for fracture were assessed by questionnaire, interview, and clinical examination. The primary outcome was incidence of hip fracture. Participants in the observational study attended a baseline examination and were re-examined three years later. Participants completed annual updates of exposures and clinical outcomes by mail. Final data were collected by mail during the close-out period in April 2004 to March 2005. The major clinical outcomes of interest were coronary heart disease, stroke, breast cancer, colorectal cancer, endometrial cancer, ovarian cancer, osteoporotic fractures, diabetes, and total mortality. Most outcomes were initially ascertained by self-report on an annual questionnaire and documented by hospital and related records. Charts with potential cardiovascular, cancer, and fracture outcomes were sent to the local physician adjudicator for evaluation and classification. Staff at the Clinical Coordinating Center coded and adjudicated all cancers of major interest in the study using standardized SEER guidelines. In 2005, WHI participants were invited to join the Extension Study for an additional five years of follow-up in order to collect long-term outcomes. Participants completed annual data collection forms primarily by mail, similar to the OS follow-up. Women reporting study outcomes were contacted by WHI field center staff to obtain additional details and medical records, which were evaluated by physician adjudicators. In 2010, the woman remaining were invited to join the next Extension Study. In the second extension, women were divided into two groups, one of which would have outcomes documented with medical records (the Medical Records Cohort, MRC), and the other would just be followed by self-report (the Self-Report Cohort, SRC). The MRC consists of women who were in the hormone therapy trials, and all African-American and Hispanic women. In 2012-2013, a subset of the MRC was identified for a potential in-home visit to collect blood and several objective measures of physical functioning. Conclusions: Overall health risks exceeded benefits from use of combined estrogen plus progestin after an average 5.2 year follow-up among healthy postmenopausal US women (Rossouw et al., 2002, PMID:12117397). Among postmenopausal women aged 65 years or older, estrogen plus progestin did not improve cognitive function when compared with placebo (Rapp et al., 2003, PMID: 12771113), increased the risk for probable dementia, and did not prevent mild cognitive impairment (Shumaker, et al., 2003, PMID: 12771112). The use of conjugated equine estrogen increased the risk of stroke, decreased the risk of hip fracture, and did not affect CHD incidence in postmenopausal women with prior hysterectomy after an average of 6.8 years of follow-up (Anderson et al., 2004, PMID: 15082697). Over approximately 8 years of follow-up, a low-fat dietary pattern did not reduce the risk of colorectal cancer (Beresford, et al., PMID: 16467233). Calcium with vitamin D supplementation resulted in a small but significant improvement in hip bone density; however, no significant difference was observed in hip fractures (Jackson, et al., 2006, PMID: 16481635). A recent review summarizes the conclusions from the WHI clinical trials with a focus on clinical practice (Manson, et al., 2024, PMID: 38691368).Description of ECG Imaging Data: Electric cardiograms (ECGs) were given to all clinical trial participants at baseline and in years 3, 6, and 9 of the original WHI study.EKG data consist of 12 lead 10 seconds ECGS sampled at 500Hz via GE ECG machines and process via GE MUSE system. The ECG waveform were directly exported from GE MUSE using MUSE export function in XML format, which include EKG waveform data as well as other ECG characteristics. Waveform data is in base64 encoded format, when it is decoded, it is a binary data that can be used to draw waveform graph. Many programming languages and data tools have built in functions to decode base64 strings. All the other necessary information is included in the LeadData section, total byte size, total sample size etc. (usually 1 sample is 2 bytes). See example below: encoded-data (base64 encoded string) JwAoAC0AKAAiACIAJAAkACQAIwAiACIAHgAcABwAGwAZABgAGAAYABcAEwAQABAAEAAL^/AAsADAAM... decoded-binary-data (1 sample is 2 bytes) 270028002D002800220022002400240024002300220022001E001C001C001B00 1900180018001800170013001000100010000B000B000C000C000D000D000D00 0A000A000A0009000600040004000700070005000500020... These binary values are integers (Y axis data of the graph), hence it is a straightforward process to draw the waveform graph. Acquisition dates have been redacted from this ECG data to comply with WHI policy. All acquisition dates within files and in file names have been set to January 1, 1900 (19000101) to comply with this policy. Study Weblinks: Women's Health Initiative Study Design: Clinical Trial Study Type: Cohort Double-Blind Longitudinal Partial Factorial Randomized Placebo-Controlled Total number of consented subjects: 67979 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Women's Health Initiative Clinical Trial and Observational Study - Imaging","short_name":"img_WHI_HMB-NPU","commons":"BioData Catalyst","study_url":"","_subjects_count":8311,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs003825.v2.p2.c1":{"gen3_discovery":{"authz":"/programs/BioLINCC/projects/BL_ROC_PRIMED_GRU","tags":[],"_unique_id":"phs003825.v2.p2.c1","study_id":"phs003825.v2.p2.c1","study_description":"Accessing Data: Please refer to “Authorized Access” below regarding accessing data through the BioData Catalyst ecosystem. The data from this accession is not available for download through dbGaP.Objective: The purpose of this study was to examine two different treatments during a cardiac arrest that occurs outside of the hospital and whether either or both treatments would increase the number of people who lived to hospital discharge with satisfactory functional status. The first treatment involved using a device called the Impedance Threshold Device (ITD). The other treatment involved the amount of CPR given before the emergency medical services (EMS) providers first looked at the heart rhythm to determine if a shock is needed.Background: Out-of-hospital cardiac arrest is a common and lethal problem with a low survival rate, leading to an estimated 330,000 deaths each year in the United States and Canada. The traditional approach to out-of-hospital cardiac arrest has been to emphasize early analysis of cardiac rhythm, with delivery of defibrillatory shocks, if indicated, as quickly as possible. It has been suggested, however, that many participants may benefit from a period of CPR before the first analysis of rhythm.The impedance threshold device (ITD) is designed to enhance venous return and cardiac output during CPR by increasing the degree of negative intrathoracic pressure. Previous studies have suggested that the use of an ITD during CPR may improve survival rates after cardiac arrest. This effect is achieved by preventing the passive inflow of air into the chest during chest recoil between chest compressions without impeding active ventilation. The ITD has been found to improve hemodynamics, the perfusion of vital organs, and neurologically intact survival in studies in animals. The results of small, short-term clinical trials have suggested that the ITD can increase systolic blood pressure during resuscitation and improve short-term survival rates. Participants: In the ITD study, 4,345 participants were assigned to sham ITD and 4,373 to active ITD, while in the early versus later rhythm analysis, 5,290 participants were assigned to early cardiac rhythm analysis, and 4,643 were assigned to later cardiac rhythm analysis. This study qualified for exception from informed consent required for emergency research.Design: Most participants were enrolled simultaneously in both the early analysis versus later analysis component and the active ITD versus sham ITD component of the trial.The use of an active ITD was compared with that of a sham ITD in participants at 10 ROC sites in the United States and Canada. Participants, investigators, study coordinators, and all care providers were unaware of the treatment assignments. EMS personnel were trained in ITD function, proper use of the ITD, and all aspects of protocol implementation, with an emphasis on the optimal performance of CPR according to local guidelines. The first EMS responders to arrive at the scene of the arrest who were equipped with a randomly assigned ITD (active or sham) attached the device between the ventilation bag and face mask or between the bag and an advanced airway. Responders were encouraged to implement use of the device within 5 minutes after their arrival or as soon as clinically possible. Each of the 10 participating ROC centers was also divided into approximately 20 clusters. All episodes of cardiac arrest in a cluster were randomly assigned to one CPR strategy; after a set period of time, ranging from 3 to 12 months, all episodes in that cluster were then assigned to the other strategy. Participants in the early-analysis group were assigned to receive 30 to 60 seconds of chest compressions and ventilations (sufficient time to place defibrillator electrodes) before electrocardiographic (ECG) analysis, and those in the late-analysis group were assigned to receive 3 minutes of chest compressions and ventilations before ECG analysis. The start and stop times for CPR were recorded by the responders, and the information was supplemented by the recording of defibrillator time. Conclusions: All 10 sites halted enrollment in November 2009 when the data and safety monitoring board recommended termination because interim analysis showed that the findings were not likely to change with continuation of the study. Neither use of the ITD nor the amount of CPR given before cardiac rhythm analysis significantly improved survival with satisfactory function (i.e., a score of ≤3 on the modified Rankin scale) among participants with out-of-hospital cardiac arrest receiving standard CPR. There were also no significant differences in the secondary outcomes, including rates of return of spontaneous circulation on arrival at the emergency department, survival to hospital admission, and survival to hospital discharge. Study Weblinks: BioLINCC Repository Study Design: Clinical Trial Study Type: Clinical Trial Total number of consented subjects: 34622 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Resuscitation Outcomes Consortium (ROC) Prehospital Resuscitation Using an Impedance Valve and Early Versus Delayed Analysis (PRIMED) (ROC-PRIMED-BioLINCC)","short_name":"BL_ROC_PRIMED_GRU","commons":"BioData Catalyst","study_url":"","_subjects_count":34622,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs003826.v1.p1.c1":{"gen3_discovery":{"authz":"/programs/BioLINCC/projects/BL_ROC_PROHS_GRU","tags":[],"_unique_id":"phs003826.v1.p1.c1","study_id":"phs003826.v1.p1.c1","study_description":"Accessing Data: Please refer to the \"Authorized Access\" section below regarding accessing data through the BioData Catalyst ecosystem. The data from this accession is not available for download through dbGaP.Objective: To observe if patients with severe traumatic injuries evacuated to level 1 trauma centers on air ambulances who received prehospital red blood cells and/or plasma had decreased in-hospital mortality compared to patients who received only crystalloids.Background: Injury is the leading cause of death in adults and children between the ages of 1 and 44 years. However, approximately 40% of in-hospital deaths among injured patients involve massive truncal hemorrhage that is considered potentially salvageable. Multiple retrospective military and civilian studies have reported that transfusion involving blood component ratios approaching whole blood are associated with significant decreases in 24-hour and 30-day mortality among injured patients. Furthermore, prehospital transfusion (PHT) studies from military and civilian hospitals have shown that prehospital transfusion of plasma and red blood cells (RBCs) is not only feasible, but associated with improved coagulation status on arrival. Prehospital resuscitation practices in the US differ significantly in approach, with most systems using crystalloids while a few offer RBCs or a combination of plasma and RBCs. No large multicenter civilian studies have evaluated the use of prehospital plasma and RBCs in severely injured patients compared to crystalloids.Participants: A total of 25,118 trauma patients were admitted during the 10 month enrollment period to the nine participating centers, of which 2341 arrived by helicopter, and 1058 met the highest risk criteria. Of the high risk sub-set, 585 arrived on helicopters with blood products available and 473 patients arrived via helicopters without blood available. One hundred forty two patients (24%) of those transported on helicopters with blood products available actually received PHT and 916 patients did not.Design: PROHS was a multicenter, prospective pragmatic, observational study of prehospital resuscitation approaches. There were no study guidelines dictating resuscitation practice (i.e., use of blood products or end of resuscitation). Of the 9 participating Level I trauma centers, 5 had helicopter systems with plasma and/or RBCs while the other 4 had helicopter systems that used only crystalloid resuscitation. All patients arriving to the participating center's trauma emergency department via helicopter directly from the scene were screened and had initial data collected. Of that group, all patients who met the highest risk category or received blood during transport were followed by direct observation during the initial resuscitation period and then indirectly through medical chart review until hospital discharge or 30 days after admission (whichever occurred first).The primary outcome was in-hospital mortality at 3 hours, 24 hours, and 30 days. Other outcome measures included length of hospital stay, number of ICU days, number of ventilator days, blood product usage, GOSE score at discharge, number of patients with complications, and number of patients who required hemostatic devices. Conclusions:Because of the unexpected imbalance in injury severity between systems with and without blood products on helicopters, all analyses were inconclusive. With few units transfused to each patient and small outcome differences between groups, large randomized studies will be required to detect significant survival differences in this important population. Study Weblinks: BioLINCC Repository Study Design: Prospective Longitudinal Cohort Study Type: Cohort Observational Prospective Total number of consented subjects: 2341 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Resuscitation Outcomes Consortium (ROC) Prehospital Resuscitation on Helicopter Study (PROHS) (ROC-PROHS-BioLINCC)","short_name":"BL_ROC_PROHS_GRU","commons":"BioData Catalyst","study_url":"","_subjects_count":2341,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs003844.v1.p1.c1":{"gen3_discovery":{"authz":"/programs/BioLINCC/projects/BL_BEST_CLI_GRU","tags":[],"_unique_id":"phs003844.v1.p1.c1","study_id":"phs003844.v1.p1.c1","study_description":"Data Access NOTE Please refer to the “Authorized Access” section below for information about how access to the data from this accession differs from many other dbGaP accessions. Objectives To compare the effectiveness of surgical treatment to the effectiveness of endovascular treatment in adults with chronic limb-threatening ischemia who are eligible for both treatment options. Background Peripheral artery disease (PAD) affects more than 200 million people worldwide. A portion of those individuals develop chronic limb-threatening ischemia (CLTI). CLTI is associated with severe health outcomes. CLTI is defined by ischemic foot pain at rest, ischemic ulcerations, or gangrene. Treatment for CLTI includes revascularization to improve limb perfusion and limit the risk of amputation. However, the choice of surgery or endovascular therapy for revascularization varies greatly. The extent to which this variability affects clinical outcomes in patients with CLTI is unknown. The BEST-CLI trial was initiated to determine whether endovascular revascularization was superior to surgical revascularization in patients with CLTI. Participants A total of 1434 participants with a single segment of great saphenous vein comprised cohort 1. Of these, 718 participants were randomly assigned to the surgical treatment group and 716 participants were randomly assigned to the endovascular therapy group. A total of 396 participants needing an alternative conduit comprised cohort 2. Of these, 197 participants were randomly assigned to the surgical treatment group and 199 participants were randomly assigned to the endovascular therapy group. Design BEST-CLI was an international, randomized, open-label trial. Participants were assigned to one of two cohorts based on the availability of a single segment of great saphenous vein. Participants in both cohorts were randomly assigned to either surgery or endovascular therapy. Follow-up was performed at 30 days after the procedure, 3 months, 6 months, and every 6 months thereafter up to 84 months after randomization. Telephone visits in lieu of clinic visits were planned at 30 months and every 12 months thereafter and at the end of the trial. Participants were followed for major adverse cardiovascular events (myocardial infarction, stroke, or death from any cause), quality of life, level of pain, and performance on the six-minute walk test. The primary outcome was a composite of major adverse limb events or death from any cause. A major adverse limb event was defined as above ankle amputation of the index limb or a major index-limb reintervention (new bypass, interposition graft revision, thrombectomy, or thrombolysis). Conclusions Among patients with CLTI who had an adequate great saphenous vein for surgical revascularization (cohort 1), the incidence of a major adverse limb event or death was significantly lower in the surgical group than in the endovascular group. Among the patients who lacked an adequate saphenous vein conduit (cohort 2), the outcomes in the two groups were similar. Farber A, Menard MT, Conte MS, et al. Surgery or Endovascular Therapy for Chronic Limb-Threatening Ischemia. N Engl J Med. 2022;387(25):2305-2316. PMID 36342173 Study Weblinks: BioLINCC: Best Endovascular vs. Best Surgical Therapy in Patients With Critical Limb Ischemia (BEST-CLI) Study Design: Clinical Trial Study Type: Clinical Trial Total number of consented subjects: 1830 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Best Endovascular vs. Best Surgical Therapy in Patients With Critical Limb Ischemia (BEST CLI-BioLINCC)","short_name":"BL_BEST_CLI_GRU","commons":"BioData Catalyst","study_url":"","_subjects_count":1830,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs003858.v1.p1.c1":{"gen3_discovery":{"authz":"/programs/BioLINCC/projects/BL_PAD_GRU","tags":[],"_unique_id":"phs003858.v1.p1.c1","study_id":"phs003858.v1.p1.c1","study_description":"Data Access NOTE: Please refer to the “Authorized Access” section below for information about how access to the data from this accession differs from many other dbGaP accessions. Objectives The Public Access Defibrillation (PAD) Community Trial sought to evaluate broad implementation of Public Access Defibrillators (PAD) in urban community units. Survival to hospital discharge of participants with out-of-hospital cardiac arrest was the main outcome measure. Survival was compared in community units (e.g., apartment or office buildings, gated communities, sports venues, senior centers, shopping malls) served by non-medical responders trained in CPR and use of automated external defibrillators (AEDs), to units receiving the traditional optimum community standard of care (i.e., rescuers trained to recognize a cardiac emergency, call 911, and initiate CPR). Background Sudden out-of-hospital cardiac arrest (OOH-CA) remains a significant cause of death, in spite of recent declines in overall mortality from cardiovascular disease. Existing methods of emergency resuscitation are inadequate due to time delays inherent in transporting trained responders with defibrillation capabilities to the side of the OOH-CA victim. Existing Emergency Medical Services (EMS) systems typically combine paramedic Emergency Medical Technician (EMT) services with some level of community involvement, such as bystander cardiopulmonary resuscitation (CPR) training. Some communities include automated external defibrillators (AEDs) at isolated sites or in mobile police or fire vehicles. Such an approach typically varies in effectiveness, with an incremental improvement in effectiveness seen in communities that organize and integrate services with the existing EMS system. However, optimal improvement in survival from sudden OOH-CA may require a program that utilizes volunteer non-medical responders (who may not have a traditional duty to respond to an emergency) trained to use AEDs. Participants The PAD trial was a prospective, randomized community based trial. More than 19,000 volunteer responders from 993 community units in 24 North American regions participated. The two study arms had similar unit and volunteer characteristics. Participants with treated out-of-hospital cardiac arrest in the two groups were similar in age (mean: 69.8 years), proportion of men (67 perecnt), rate of cardiac arrest in a public location (70 percent), and rate of witnessed cardiac arrest (72 percent). Conclusions Community units with volunteers trained in CPR and AEDs had significantly more participants surviving to hospital discharge than units with volunteers trained to use CPR only. There were 30 survivors among 128 definite cardiac arrests in the CPR+AED units and 15 survivors among 107 definite cardiac arrests in the CPR only units (p = 0.03). Serious adverse effects were rarely reported. No volunteers received inadvertent shocks, and no participants were shocked unnecessarily. AED maintenance problems were infrequent. A few participating volunteers reported severe stress related to responding to emergency situations. Although residential complexes represented 16% of the units and 29% of the treatable cardiac arrests, only 5% of the survivors were from residential complexes. Such information should be helpful for individual facilities that are considering implementing PAD programs. (NEJM 2004; 351:637-46). Study Weblinks: BioLINCC Repository Study Design: Clinical Trial Study Type: Interventional Total number of consented subjects: 3951 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Public Access Defibrillation Community Trial (PAD)(PAD-BioLINCC)","short_name":"BL_PAD_GRU","commons":"BioData Catalyst","study_url":"","_subjects_count":3951,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs003872.v1.p1.c1":{"gen3_discovery":{"authz":"/programs/BioLINCC/projects/BL_DIG_GRU","tags":[],"_unique_id":"phs003872.v1.p1.c1","study_id":"phs003872.v1.p1.c1","study_description":"Data Access NOTE: Please refer to the “Authorized Access” section below for information about how access to the data from this accession differs from many other dbGaP accessions. Objectives To determine the effect of increasing age on mortality, hospitalizations, and digoxin side effects in patients with heart failure (HF), and to determine whether the effect of digoxin on clinical outcomes varies as a function of age. Background The incidence and prevalence of HF increase with advancing age, but there are limited data on the clinical course and response to specific interventions in elderly patients with HF. Participants A total of 302 centers in the United States and Canada enrolled 7,788 patients between February 1991 and September 1993. Design The Digitalis Investigation Group (DIG) study was a prospective, randomized clinical trial involving 7,788 patients with HF randomized to digoxin or placebo and followed for an average of 37 months. Interactions between age and the following clinical outcomes were examined: total mortality, all-cause hospitalizations, HF hospitalizations, the composite of HF death or HF hospitalizations, hospitalization for suspected digoxin toxicity and withdrawal from therapy because of side effects. Conclusions Increasing age is associated with progressively worse clinical outcomes in patients with HF. However, the beneficial effects of digoxin in reducing all-cause admissions, HF admissions, and HF death or hospitalization are independent of age. Thus, digoxin remains a useful agent to the adjunctive treatment of HF due to impaired left ventricular systolic function in patients of all ages. Study Weblinks: BioLINCC Repository Study Design: Clinical Trial Study Type: Clinical Trial Interventional Total number of consented subjects: 7788 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Digitalis Investigation Group (DIG-BioLINCC)","short_name":"BL_DIG_GRU","commons":"BioData Catalyst","study_url":"","_subjects_count":7788,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs003878.v1.p1.c1":{"gen3_discovery":{"authz":"/programs/BioLINCC/projects/BL_PETAL_ROSE_HMB-MDS","tags":[],"_unique_id":"phs003878.v1.p1.c1","study_id":"phs003878.v1.p1.c1","study_description":"Data Access NOTE: Please refer to the \"Authorized Access\" section below regarding accessing data through the BioData Catalyst ecosystem. The data from this accession is not available for download through dbGaP. Available Data: The data available for request now include Long Term Outcome data.Biospecimens: Access to Biospecimens is through the NHLBI Biologic Specimen and Data Repository Information Coordinating Center (BioLINCC). Biospecimens from PETAL ROSE include Plasma, DNA, Whole Blood, and Urine. Please note that use of biospecimens in genetic research is subject to a tiered consent.Objectives: To determine the efficacy and safety of early neuromuscular blockade with concomitant heavy sedation as compared with a strategy of usual care with lighter sedation targets in patients with moderate-to-severe ARDS.Background: It has been well established that the approaches used for the application of mechanical ventilation in patients with acute respiratory distress syndrome (ARDS) can affect survival and outcomes after discharge from the intensive care unit (ICU). A large, multicenter trial conducted a decade before this study reported that the early administration of a 48-hour infusion of neuromuscular blockade in patients with moderate-to-severe ARDS (defined by a ratio of the partial pressure of arterial oxygen [Pao2] to the fraction of inspired oxygen [Fio2] of <150 mm Hg with a positive end-expiratory pressure [PEEP] of ≥5 cm of water) resulted in lower mortality than a strategy of deep sedation without routine neuromuscular blockade. Despite these encouraging results, early neuromuscular blockade has not been widely adopted. Potential concerns include the lack of research comparing neuromuscular blockade and deep sedation with current practice (which promotes lighter sedation targets) as well as limited data on the effect of neuromuscular blockade on neuromuscular function and other long-term outcomes. Therefore, the PETAL-ROSE study was initiated to determine the efficacy and safety of early neuromuscular blockade with concomitant heavy sedation as compared with a strategy of usual care with lighter sedation targets.Participants: There were 1006 participants.Design: PETAL-ROSE was a multicenter, unblinded, randomized trial of patients with moderate-to-severe ARDS. Participants were randomly assigned in a 1:1 ratio to receive 48 hours of continuous neuromuscular blockade with concomitant deep sedation (intervention group) or to receive usual care without routine neuromuscular blockade and with lighter sedation targets (control group).Patients in the intervention group who were not under deep sedation at baseline were deeply sedated within 4 hours after randomization. Subsequently, patients in this group received an intravenous bolus of 15 mg of cisatracurium, followed by a continuous infusion of 37.5 mg per hour for 48 hours. After the 48-hour trial intervention period, decisions regarding further use of neuromuscular blockade, including the choice of agent, were left to the discretion of the treating clinician. Neuromuscular blockade could be stopped early if the patient met the criteria for freedom from mechanical ventilation (Fio2 ≤0.40 and PEEP ≤8 cm of water) for at least 12 hours. All patients were treated with a strategy of low tidal volume ventilation within 2 hours after randomization and a high PEEP strategy for up to 5 days after randomization. Assessors who were unaware of the group assignment interviewed surviving patients or their proxies at 3, 6, and 12 months after randomization. The primary end point was in-hospital death from any cause at 90 days (in-hospital was defined as the time in the trial hospital plus transfer to another hospital, including the time in long-term acute care facilities). Conclusions: After the second interim analysis, the decision to stop the trial for futility was made independently by the data and safety monitoring board.In critically ill patients identified shortly after the diagnosis of moderate-to-severe ARDS, the addition of early continuous neuromuscular blockade with concomitant deep sedation did not result in lower mortality than a usual-care approach to mechanical ventilation that included lighter sedation targets. Study Weblinks: Prevention and Early Treatment of Acute Lung Injury Network – Reevaluation of Systemic Early Neuromuscular Blockade (PETAL Study Design: Clinical Trial Study Type: Clinical Trial Total number of consented subjects: 1006 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Prevention and Early Treatment of Acute Lung Injury Network - Reevaluation of Systemic Early Neuromuscular Blockade (PETAL ROSE-BioLINCC)","short_name":"BL_PETAL_ROSE_HMB-MDS","commons":"BioData Catalyst","study_url":"","_subjects_count":1006,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs003879.v1.p1.c1":{"gen3_discovery":{"authz":"/programs/BioLINCC/projects/BL_PETAL_VIOLET_HMB-MDS","tags":[],"_unique_id":"phs003879.v1.p1.c1","study_id":"phs003879.v1.p1.c1","study_description":"Data Access NOTE: Please refer to the \"Authorized Access\" section below regarding accessing data through the BioData Catalyst ecosystem. The data from this accession is not available for download through dbGaP. Biospecimens: Access to Biospecimens is through the NHLBI Biologic Specimen and Data Repository Information Coordinating Center (BioLINCC). Biospecimens from PETAL VIOLET include Plasma and Whole Blood. Please note that use of biospecimens in genetic research is subject to a tiered consent. Specimens may not be used to produce commercial products.Objectives: To evaluate the effect of short-term vitamin D supplementation on mortality among critically ill patients with a vitamin D deficiency.Background: Observational data indicate that vitamin D deficiency is common among critically ill patients and constitutes a potentially modifiable risk factor associated with longer lengths of stay in the hospital and intensive care unit (ICU), lung and other organ injury, prolonged mechanical ventilation, and death. In a previous phase 2 trial, vitamin D supplementation administered to vitamin D-deficient, critically ill patients was associated with lower observed mortality than placebo at 28 days and at 6 months. Because of the need for a larger, phase 3 trial, the PETAL-VIOLET study was initiated to determine if early administration of high-dose vitamin D3 would reduce all-cause mortality among critically ill patients with a vitamin D deficiency.Participants: 1360 patients underwent randomization, 690 were assigned to the vitamin D group and 668 were assigned to the placebo group. Of the 1078 patients confirmed to have a vitamin D deficiency by liquid chromatography-tandem mass spectrometry (LC-MS-MS), 538 had been assigned to the vitamin D group and 540 had been assigned to the placebo group.Design: PETAL-VIOLET was a multicenter, double-blind, placebo-controlled, phase 3 trial. Patients were enrolled within 12 hours after the clinician's decision to admit the patient to the ICU from the emergency department, hospital ward, operating room, or outside facility. Patients were tested for vitamin D deficiency, with a threshold of plasma 25-hydroxyvitamin D level of less than 20 ng per milliliter. Patients were randomly assigned in a 1:1 ratio, stratified according to site, to receive either a single enteral (administered orally or through a nasogastric or orogastric tube) dose of 540,000 IU of vitamin D3 or matched placebo, in liquid form, administered within 2 hours after randomization.Conclusions: After the first interim analysis, the data and safety monitoring board recommended that the trial be stopped for futility.A single 540,000 IU enteral dose of vitamin D3 administered early during critical illness rapidly corrected vitamin D deficiency but did not provide an advantage over placebo with respect to mortality or other clinically important end points. Study Weblinks: BioLINCC PETAL VIOLET study page Study Design: Clinical Trial Study Type: Clinical Trial Total number of consented subjects: 1358 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Prevention and Early Treatment of Acute Lung Injury Network - Vitamin D to Improve Outcomes by Leveraging Early Treatment (PETAL VIOLET-BioLINCC)","short_name":"BL_PETAL_VIOLET_HMB-MDS","commons":"BioData Catalyst","study_url":"","_subjects_count":1358,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs003885.v1.p1.c1":{"gen3_discovery":{"authz":"/programs/BioLINCC/projects/BL_REACT_GRU","tags":[],"_unique_id":"phs003885.v1.p1.c1","study_id":"phs003885.v1.p1.c1","study_description":"Data Access NOTE: Please refer to the “Authorized Access” section below for information about how access to the data from this accession differs from many other dbGaP accessions. Objectives: This multicenter controlled community study developed and evaluated the impact of a community educational intervention program on participant delay time from onset of symptoms of an acute myocardial infarction (AMI) to arrival at a hospital emergency department.Background: Although early reperfusion or thrombolytic therapy can reduce morbidity and mortality following an AMI, delayed access to medical care in participants is relatively common. Mean delay times from symptom onset to hospital arrival range from more than 4 hours to 24 hours, and the largest component of prolonged delay is participant recognition and action.Participants: A total of 20 communities from 5 field centers in the U.S. were pair-matched (10 pairs) according to geographic proximity and demographic characteristics. After initiation of a 4 month baseline surveillance period, one community in each pair was randomly selected to receive the intervention. The baseline surveillance period was followed by an 18 month community intervention and surveillance period. The community surveillance captured a total of 59,944 adults aged 30 years or older presenting to hospital emergency departments with chest pain, of whom 20,364 met study criteria for suspected acute coronary heart disease (CHD) at admission and discharged with a CHD diagnosis.Conclusions: Delay times were decreased in the intervention and reference communities. The results showed that the multicomponent community intervention program did not differentially reduce delay time from onset of AMI symptoms to arrival at a hospital, but did significantly increase the use of Emergency Medical Services by these participants in the intervention communities. (PMID:10872014). Study Weblinks: BioLINCC Repository Study Design: Clinical Trial Study Type: Clinical Trial Interventional Total number of consented subjects: 92404 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Rapid Early Action for Coronary Treatment (REACT-BioLINCC)","short_name":"BL_REACT_GRU","commons":"BioData Catalyst","study_url":"","_subjects_count":92404,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs003899.v1.p1.c1":{"gen3_discovery":{"authz":"/programs/BioLINCC/projects/TOLSURF_GRU","tags":[],"_unique_id":"phs003899.v1.p1.c1","study_id":"phs003899.v1.p1.c1","study_description":"Data Access NOTE: Please refer to the “Authorized Access” section below for information about how access to the data from this accession differs from many other dbGaP accessions.Objectives: To assess whether late surfactant treatment in extremely low gestational age newborn (ELGAN, ≤28 week gestation) infants requiring ventilation at 7-14 days safely improves survival without bronchopulmonary dysplasia.Background: Bronchopulmonary dysplasia (BPD) is the most common form of chronic lung disease in children with an estimated 15,000 new cases annually in the United States. BPD affects infants born prematurely, is a major contributor to the cost of prematurity each year, and is associated with long-term pulmonary disability, neurodevelopmental abnormalities and death.Increases in the survival of ELGAN infants have resulted in another form of BPD, which is characterized by impaired alveolar and microvascular development with excess tone and reactivity of airway smooth muscle. Despite treatments to enhance lung maturation, premature infants often need prolonged intubation and mechanical ventilation and/or oxygen support. When mechanical ventilation is required longer than 7 days, BPD results in 70% of surviving ELGAN infants. Most of these infants experience clinical episodes of increased requirement for ventilatory support that are associated with dysfunctional surfactant, which is primarily due to low surfactant protein B (SP-B). In pilot studies of late surfactant treatment in premature infants, there was short-term improvement in SP-B content. These prior studies provided the rationale for a larger clinical trial for later doses of surfactant treatment to prevent episodes of respiratory decompensation and BPD. Participants: 511 infants were eligible for randomization of the 2693 infants screened. Of the 511 infants eligible for randomization, there were 252 infants allocated to the treatment arm and 259 infants allocated to the placebo arm.Design: The study was designed to assess the effect of late doses of surfactant on survival without BPD at 36 weeks post menstrual age (PMA) in ELGAN infants who required intubation and mechanical ventilation between 7 and 14 days of age and were receiving Inhaled nitric oxide (iNO). Infants were stratified within clinical centers and gestational age groups and randomized to treatment with calfactant, a natural surfactant extracted from bovine lung lavage fluid, or a sham procedure.All infants received iNO according to the protocol used in the Nitric Oxide Chronic Lung Disease (NOCLD) trial. A masked syringe containing either a standard dose of calfactant for the treatment group, or air for the placebo group, was administered to the infant behind a screen by staff not involved in providing the infant's clinical care. Monitor and ventilator alarms were turned off during dosing to avoid unblinding of clinical staff. To accommodate research staff availability and infant instability, the dosing interval was not strictly set but could be repeated every 24 – 72 hours up to 5 doses if the infant still required intubation. Dosing could be discontinued by physician request or parental withdrawal from the study. Due to parental preference, the first infant in a multiple birth was randomized according to the randomization schedule and subsequent infants were assigned to the same treatment group. Follow-up to assess pulmonary and neurologic development continued until 2 years of age, with treatment group blinding maintained. The primary outcome was survival without BPD at 36 weeks PMA. Secondary outcomes included BPD at 40 weeks PMA, pulmonary outcome at 12–24 months of age, and neurodevelopmental outcome at 2 years of age. Conclusions: There were no significant differences observed between the treatment group and the control group for survival without BPD at 36 weeks or 40 weeks. Study Weblinks: BioLINCC Repository Study Design: Clinical Trial Study Type: Clinical Trial Total number of consented subjects: 511 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Trial of Late Surfactant for Prevention of Bronchopulmonary Dysplasia: A Study in Ventilated Preterm Infants Receiving Inhaled Nitric Oxide (TOLSURF-BioLINCC)","short_name":"TOLSURF_GRU","commons":"BioData Catalyst","study_url":"","_subjects_count":511,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs003900.v1.p1.c1":{"gen3_discovery":{"authz":"/programs/BioLINCC/projects/PETAL_ASTER_HMB-MDS","tags":[],"_unique_id":"phs003900.v1.p1.c1","study_id":"phs003900.v1.p1.c1","study_description":"Data Access NOTE: Please refer to the “Authorized Access” section below for information about how access to the data from this accession differs from many other dbGaP accessions. Access to Biospecimens is through the NHLBI Biologic Specimen and Data Repository Information Coordinating Center (BioLINCC). Biospecimens from PETAL ASTER include plasma, urine and whole blood. Please note that use of biospecimens in genetic research is subject to a tiered consent. Objectives: To determine whether acetaminophen increases days alive and free of organ dysfunction in sepsis participants compared with placebo.Background: Acetaminophen (paracetamol) has many effects that can be beneficial in sepsis treatment, including analgesia, antipyresis, cyclooxygenase-2 inhibition, as well as a potent and specific hemoprotein reduction that can block hemoglobin-induced oxidation of lipids and other substrates. The majority of sepsis participants experience elevated circulating cell-free hemoglobin levels, which is associated with development of organ dysfunction including acute respiratory distress syndrome (ARDS) and death.Acetaminophen has been found in observational studies to be associated with improved survival in critically ill sepsis participants with elevated plasma cell-free hemoglobin, and small clinical trials have had positive sepsis participant outcomes such as reduced plasma biomarkers of lipid peroxidation and improved kidney function. However, a large, randomized trial of acetaminophen administration for treatment of fever in participants with suspected infection did not show a mortality benefit. The NHLBI PETAL Network initiated ASTER as a larger phase trial to examine the utility of plasma cell-free hemoglobin level as a biomarker for future sepsis trials and whether acetaminophen would increase the number of days alive and free of organ support for participants with sepsis and respiratory or circulatory organ dysfunction. Participants: A total of 447 participants were enrolled and randomized, 227 to the acetaminophen arm and 220 to the placebo arm. Data from 40 participants who were randomized to the Vitamin C arm, which was stopped early (see Design section below), is also included.Design: ASTER was a phase 2b multicenter, randomized, double-blind trial. The study originally had a 3-arm platform trial in which participants were randomized 1:1:1 to treatment with intravenous acetaminophen, vitamin C, or a common placebo. The vitamin C arm of the trial was stopped after enrolling 79 participants due to external clinical trial data for vitamin C.Participants randomized to the acetaminophen arm received acetaminophen at the dose of 1 g in 100 mL diluent (or 15 mg/kg if actual body weight was <50 kg) every 6 hours intravenously for 5 days for a total of 20 doses. Participants randomized to placebo received an identical appearing intravenous infusion of 100 mL of 5% dextrose in water every 6 hours for 5 days. In both arms, the study drug was discontinued prior to 120 hours, if one of the following occurred, (1) discharge from the study hospital, (2) discharge from the ICU, (3) withdrawal from the study, or (4) death. Serum aspartate aminotransferase (AST) and alanine aminotransferase (ALT) were monitored on study day 0, and days 2 through 5 . New measured values of AST or ALT greater than or equal to 10 times the upper limit of normal on any measurement prompted permanent discontinuation of the study drug. The primary efficacy variable was days alive and free of any organ support (dialysis, assisted ventilation, and vasopressors) out to day 28. Conclusions: Intravenous acetaminophen was considered to be safe but did not significantly improve days alive and free of organ support in critically ill sepsis participants. There was no significant interaction between cell-free hemoglobin levels and acetaminophen. Study Weblinks: BioLINCC Repository Study Design: Clinical Trial Study Type: Double-Blind Randomized Total number of consented subjects: 487 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Prevention and Early Treatment of Acute Lung Injury (PETAL) Acetaminophen in Sepsis: Targeted Therapy to Enhance Recovery (ASTER) (PETAL ASTER-BioLINCC)","short_name":"PETAL_ASTER_HMB-MDS","commons":"BioData Catalyst","study_url":"","_subjects_count":487,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs003901.v1.p1.c1":{"gen3_discovery":{"authz":"/programs/BioLINCC/projects/BL_ROC_CCC_GRU","tags":[],"_unique_id":"phs003901.v1.p1.c1","study_id":"phs003901.v1.p1.c1","study_description":"Data Access NOTE: Please refer to the “Authorized Access” section below for information about how access to the data from this accession differs from many other dbGaP accessions.Objectives: To compare the rate of survival to hospital discharge after continuous chest compressions versus standard American Heart Association recommended cardiopulmonary resuscitation with interrupted chest compressions in patients with out-of-hospital cardiac arrest.Background: Standard cardiopulmonary resuscitation (CPR) consists of manual chest compressions to maintain blood flow and positive-pressure ventilation to maintain oxygenation until spontaneous circulation is restored. Chest compressions during standard CPR are interrupted frequently by ventilations. These interruptions reduce blood flow and potentially reduce the effectiveness of CPR. In animals with cardiac arrest, the interruption of chest compressions has been associated with decreased survival. Observational studies involving humans with out-of-hospital cardiac arrest of presumed cardiac cause have suggested that continuous compressions are associated with higher rates of survival than interrupted compressions.Participants: Of 35,904 patients with out-of-hospital cardiac arrest who were screened, 26,148 were eligible for participation in the trial and were enrolled in the trial during either the run-in phase or the active-enrollment phase. The active-enrollment phase included 23,711 patients, of whom 12,653 were assigned to the intervention group and 11,058 to the control group.Design: There were 114 participating EMS agencies across the eight participating Resuscitation Outcomes Consortium (ROC) sites, which were grouped into 47 clusters. Clusters of agencies were randomly assigned, in a 1:1 ratio, to perform continuous chest compressions or interrupted chest compressions during all the out-of-hospital cardiac arrests to which they responded. Each cluster was required to begin enrolling patients in a run-in phase to demonstrate adherence to the protocol before entering the active-enrollment phase of the trial. Twice per year, each cluster was crossed over to the other resuscitation strategy.Patients assigned to the group that received continuous chest compressions (intervention group) were to receive continuous chest compressions at a rate of 100 compressions per minute, with asynchronous positive-pressure ventilations delivered at a rate of 10 ventilations per minute. Patients assigned to the group that received interrupted chest compressions (control group) were to receive compressions that were interrupted for ventilations at a ratio of 30 compressions to two ventilations; ventilations were to be given with positive pressure during a pause in compressions of less than 5 seconds in duration. The primary outcome was the rate of survival to hospital discharge. Secondary outcomes included neurologic function at discharge, which was measured with the use of the modified Rankin scale, and adverse events. Conclusions: During the active-enrollment phase, 1129 of 12,613 patients in the continuous chest compression group and 1072 of 11,035 patients in the interrupted chest compressions group survived to hospital discharge.In patients with out-of-hospital cardiac arrest, continuous chest compressions during CPR performed by EMS providers did not result in significantly higher rates of survival or favorable neurologic function than did interrupted chest compressions. Study Weblinks: BioLINCC: Resuscitation Outcomes Consortium (ROC) Trial Of Continuous Compressions Versus Standard CPR In Patients With Out-Of-H Study Design: Clinical Trial Study Type: Clinical Trial Total number of consented subjects: 26148 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Resuscitation Outcomes Consortium Trial of Continuous Compressions Versus Standard CPR in Patients With out-of-Hospital Cardiac Arrest (ROC CCC-BioLINCC)","short_name":"BL_ROC_CCC_GRU","commons":"BioData Catalyst","study_url":"","_subjects_count":26148,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs003902.v1.p1.c1":{"gen3_discovery":{"authz":"/programs/BioLINCC/projects/BL_ROC_PART_GRU","tags":[],"_unique_id":"phs003902.v1.p1.c1","study_id":"phs003902.v1.p1.c1","study_description":"Data Access NOTE: Please refer to the “Authorized Access” section below for information about how access to the data from this accession differs from many other dbGaP accessions.Objectives: To determine the effect of an initial airway management strategy using laryngeal tube (LT) insertion, compared with endotracheal intubation (ETI), on survival among adults with out-of-hospital cardiac arrest (OHCA).Background: Out-of-hospital cardiopulmonary arrest (OHCA) affects more than 350,000 adults in the United States each year, with only a low percentage of patients surviving to hospital discharge. Emergency medical services (EMS) paramedics commonly perform ETI or insertion of supraglottic airways (SGAs), such as the LT, on patients with OHCA to facilitate oxygenation and protect the lungs from aspiration of vomitus. Because SGA insertion is rapid, simple, and requires less training compared to ETI, many EMS agencies have incorporated this as the primary method of ventilation during OHCA resuscitation. However, the optimal method for OHCA advanced airway management is unknown.Participants: A total of 3004 patients were included; 1505 assigned to initial LT and 1499 assigned to initial ETI.Design: PART was a multicenter cluster-crossover randomized trial. The trial included 27 EMS agencies associated with US sites of the Resuscitation Outcomes Consortium (ROC). The EMS agencies were grouped into 13 randomization clusters. Each cluster selected a crossover interval of 3 or 5 months. Within each cluster, treatment assignments for consecutive intervals were computer-randomized in blocks of 2 to ensure balanced exposure to both airway groups. Crossovers between study groups could occur more than once. Treatment assignments were initial LT insertion or initial ETI. Neuromuscular blocking agents or video laryngoscopy was permitted for initial intubation efforts. The trial did not limit the number of initial LT insertion or ETI attempts. If the initial insertion efforts were unsuccessful, EMS personnel performed rescue airway management using any available airway technique. EMS personnel followed local protocols for confirmation of airway placement and management of OHCA, including field termination of resuscitation efforts. Patients receiving bag-valve mask (BVM) ventilation only were retained in their assigned treatment group per intention-to-treat principles. The trial did not prescribe clinical care at the receiving hospitals, including use of EMS airway, targeted temperature management, percutaneous coronary intervention, or the timing of withdrawal of life-sustaining therapy.The primary outcome was 72-hour survival. Secondary outcomes included return of spontaneous circulation, survival to hospital discharge, and favorable neurological status at hospital discharge (Modified Rankin Scale score ≤3). Conclusions: Among adults with OHCA, a strategy of initial LT insertion was associated with significantly greater 72-hour survival compared with a strategy of initial ETI. These findings suggest that LT insertion may be considered as an initial airway management strategy in patients with OHCA, but limitations of the pragmatic design, practice setting, and ETI performance characteristics suggest that further research is warranted. Study Weblinks: BioLINCC: Resuscitation Outcomes Consortium (ROC) Pragmatic Trial of Airway Management in Out-of-Hospital Cardiac Arrest (PART) Study Design: Clinical Trial Study Type: Clinical Trial Total number of consented subjects: 3004 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Resuscitation Outcomes Consortium Pragmatic Trial of Airway Management in out-of-Hospital Cardiac Arrest (ROC PART-BioLINCC)","short_name":"BL_ROC_PART_GRU","commons":"BioData Catalyst","study_url":"","_subjects_count":3004,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs003907.v1.p1.c1":{"gen3_discovery":{"authz":"/programs/BioLINCC/projects/BL_HPP_GRU","tags":[],"_unique_id":"phs003907.v1.p1.c1","study_id":"phs003907.v1.p1.c1","study_description":"Data Access NOTE: Please refer to the “Authorized Access” section below for information about how access to the data from this accession differs from many other dbGaP accessions. Access to Biospecimens is through the NHLBI Biologic Specimen and Data Repository Information Coordinating Center (BioLINCC). Biospecimens from HHP include DNA, plasma, serum, and whole blood. Please note that use of biospecimens in genetic research is subject to a tiered consent. Objectives: The initial objectives of the Honolulu Heart Program were to: 1) estimate morbidity and mortality from coronary heart disease and stroke among Japanese men in Honolulu; 2) compare morbidity and mortality from coronary heart disease and stroke among Japanese men in Japan, Honolulu, and San Francisco; 3) investigate relationships among risk factors, coronary heart disease, and stroke in Japanese men in Honolulu; 4) compare distributions of risk factors among men in Japan, Honolulu, and San Francisco, and relate similarities and differences in risk factors to the occurrence of disease in these areas and in other populations, including Framingham and Puerto Rico; 5) conduct an autopsy study, and to relate pathological findings to morbidity and mortality data; and 6) investigate relationships between risk factors and pathological evidence of atherosclerosis and its complications.Background: The Honolulu Heart Program was initiated in 1965 by the NHLBI as a prospective study of environmental and biological causes of cardiovascular disease among Japanese Americans living in Hawaii. This population was known to have low incidence of coronary heart disease and higher incidence of stroke. The study provided opportunities to investigate relationships among disease frequencies, pathologic findings, and disease predictors in the cohort and to compare the findings in this population with those in other populations, especially cohorts of Japanese men resident in Japan or the U.S.Participants: There were 8006 participants.Design: The study began in 1965 with the first examination of a cohort of 8,006 Japanese-American men residing on the island of Oahu, Hawaii who were born during the period 1900-1919. The first examination was completed in 1968 and was followed by the initiation of a second examination that same year. Three subsequent sub-examinations (Lipoprotein Exams I, II and III) were conducted between 1970 and 1982 to collect lipid measurements on a subset of those who participated in Exam II. The fourth examination of surviving members of the original cohort was conducted during 1991-93 and collected data on 3,741 men. Morbidity and mortality follow-up continues through grant and contract-supported efforts, and the current HHP dataset includes events through 1998. Study Weblinks: BioLINCC Repository Study Design: Prospective Longitudinal Cohort Study Type: Observational Total number of consented subjects: 8006 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Honolulu Heart Program (HHP-BioLINCC)","short_name":"BL_HPP_GRU","commons":"BioData Catalyst","study_url":"","_subjects_count":8006,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs003913.v1.p1.c1":{"gen3_discovery":{"authz":"/programs/BioLINCC/projects/BL_LTRC_DS-LD-MDS","tags":[],"_unique_id":"phs003913.v1.p1.c1","study_id":"phs003913.v1.p1.c1","study_description":"Data Access NOTE: Please refer to the \"Authorized Access\" section below for information about how access to the data from this accession differs from many other dbGaP accessions. Biospecimens: Access to Biospecimens is through the NHLBI Biologic Specimen and Data Repository Information Coordinating Center (BioLINCC). Biospecimens from LTRC include DNA, Plasma, Serum, Tissue - FFPE Cassettes, Tissue – RNALater Frozen, and Tissue - Snap Frozen. Please note that use of biospecimens in genetic research is subject to a tiered consent. Objectives: The LTRC was a biobank resource established by the NHLBI to collect and distribute lung tissue, blood samples, clinical data, and radiographic studies from participants with chronic obstructive pulmonary disease (COPD), idiopathic pulmonary fibrosis (IPF), other related idiopathic interstitial pneumonias (IIP) and interstitial pneumonias associated with connective tissue diseases who undergo medically-indicated lung resection. All tissue and blood specimens and clinical data were banked centrally and stored for distribution to external investigators who have approved study proposals to investigate the pathogenesis or management of lung diseases. The ultimate goal of this program was to enable research that illuminates the pathobiology of lung diseases and leads to novel interventional treatments for these conditions. Background: Chronic lung diseases are a main cause of death and disability in the United States. COPD affects over 14 million individuals in the United States and represents the third leading cause of mortality. Cigarette smoking is a major risk factor. However, only one of six individuals who smoke develops COPD. This could imply either an individual susceptibility or an additional immunologic or infectious injury to lung cells. Current treatments offer symptomatic relief, but do not prevent disease progression. Better understanding of disease pathogenesis, including the potential roles of lung parenchymal cell apoptosis, immunologic injury, and inflammation may lead to therapies that improve survival and quality of life. Interstitial pneumonias, including IPF and those associated with connective tissue disease, are less common than COPD, but for many of these diseases there are poor outcomes. For example, IPF has a 50% survival rate 2-3 years following diagnosis, and currently no treatment exists which prolongs survival. The prevalence of IPF is approximately 28 cases per 100,000. The underlying histology of IPF is usual interstitial pneumonia (UIP), which can also occur in connective tissue diseases. The incidences of other interstitial pneumonias such as non-specific interstitial pneumonia (NSIP) or acute interstitial pneumonia (AIP) are less frequent but also occur as an expression of interstitial lung disease in the connective tissue diseases. Moreover, there is significant crossover of these three interstitial pneumonias so that cases of IPF/UIP may also reveal fibrotic NSIP and be complicated by episodes of AIP. This implies common injuries but dissimilar histological responses. All of these processes are characterized by epithelial injury, uncontrolled fibroproliferation and the deposition of collagen, irrespective of the histology. It is clear that a better understanding of the genesis of the interstitial pneumonias is required before effective interventions can be developed. Participants: A total of 4,486 participants were enrolled, and lung tissue was obtained from 3,333 of these participants.Design: Written informed consent of each participant was required before any LTRC procedure was performed. Phenotypic data were then obtained that included recording of relevant medical information, a limited exposure history, radiological evaluation, and pulmonary physiological and lung function testing. Questionnaires were administered to determine the extent of symptoms, associated medical illnesses, smoking, environmental and occupational exposures, and quality of life. Laboratory testing included pulmonary function testing, a six-minute walk test, and chest x-ray CT. Blood specimens were collected both for defining the clinical phenotype of donors and to obtain serum, plasma, and DNA for later investigative purposes. At the time of surgery, lung tissues were collected and processed for long-term storage. The LTRC collected only the 'non-tumorous' portions of lung tissue from surgical procedures performed for primary or metastatic lung tumors and received those specimens only after the local pathologist had procured all tissue required for clinical care. Samples of appropriate size were cut and placed in formalin, RNAlater, glutaraldehyde, or liquid nitrogen within 30 minutes of excision (approximately 5% of cases exceeded this target time). Blood and tissue specimens were subsequently shipped to a central Tissue Repository for further processing and long-term storage. A Radiology Center provided quality control and quality assessment of CT data. A Data Coordinating Center managed study operations and maintained a repository of study data. Conclusions: LTRC established a biospecimen collection that is unique in its size, diseases included, standardization of methods, and extent of phenotypic data, serving as a valuable resource to facilitate research on the pathobiology of lung diseases. Study Weblinks: BioLINCC Repository Study Design: Cross-Sectional Study Type: Observational Total number of consented subjects: 4486 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Lung Tissue Research Consortium (LTRC-BioLINCC)","short_name":"BL_LTRC_DS-LD-MDS","commons":"BioData Catalyst","study_url":"","_subjects_count":4486,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs003926.v1.p1.c1":{"gen3_discovery":{"authz":"/programs/Individual_Study/projects/PRIME_AIR_HMB-MDS","tags":[],"_unique_id":"phs003926.v1.p1.c1","study_id":"phs003926.v1.p1.c1","study_description":"Data Access NOTE: Please refer to the \"Authorized Access\" section below for information about how access to the data from this accession differs from many other dbGaP accessions.The PRIME-AIR study (\"Positive end-expiratory pressure, Recruitment, Incentive spirometry, Muscle relaxant optimization, preoperative Education, postoperative early Ambulation, Individualized, and Reinforced\") was a prospective multi-center randomized controlled pragmatic trial, with a blinded assessor, to compare post-operative pulmonary complications (PPCs) in patients with an individualized anesthetic-centered intervention (including individualized mechanical ventilation positive end-expiratory pressure (PEEP) management to maximize respiratory system compliance and minimize driving pressures, a neuromuscular agent and subsequent reversal, and post-operative lung expansion and early mobilization) versus usual care. Study Weblinks: The PRIME-AIR Study Study Design: Clinical Trial Study Type: Clinical Trial Total number of consented subjects: 735 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"The PRIME-AIR Study: Positive End-Expiratory Pressure, Recruitment, Incentive Spirometry, Muscle Relaxant Optimization, Preoperative Education, Postoperative Early Ambulation, Individualized, and Reinforced","short_name":"PRIME_AIR_HMB-MDS","commons":"BioData Catalyst","study_url":"","_subjects_count":735,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs003929.v1.p1.c1":{"gen3_discovery":{"authz":"/programs/Individual_Study/projects/PETAL_ROSE_ARDS_RNASeq_HMB","tags":[],"_unique_id":"phs003929.v1.p1.c1","study_id":"phs003929.v1.p1.c1","study_description":"This study of the ROSE trial data explored two distinct molecular subtypes of ARDS (Acute Respiratory Distress Syndrome) to better understand the disease's complexity and potential for personalized treatment. Previous studies had identified different inflammatory profiles in ARDS patients, with this research addressing three key questions: Can these molecular subtypes be consistently identified in a more severe group of ARDS patients? Do these subtypes respond differently to neuromuscular blockade treatment? What specific biological processes differentiate these inflammatory profiles? Advanced transcriptomic and protein analyses examined blood samples from ARDS patients. Analysis of these data revealed two main molecular phenotypes: Hypoinflammatory phenotype (60.4% of patients) Hyperinflammatory phenotype (39.6% of patients) Key findings demonstrated that the hyperinflammatory subtype was associated with:Significantly higher mortality rates relative to hypoinflammatory (61.6% vs. 30.3%)Significantly higher mortality rates relative to hypoinflammatory (61.6% vs. 30.3%)Distinct gene expression patterns related to immune responseUnique changes in genes associated with tissue remodeling and cellular processes Notably, the neuromuscular blockade treatment showed no difference in effects across these subtypes. Complex relationships emerged between gene expression and protein levels, with some genes closely matching their protein counterparts and others displaying more variable connections. The study concludes that these molecular phenotypes possess distinct clinical, protein, and genetic characteristics, suggesting potential for more precise, personalized approaches to ARDS treatment in the future. Study Design: Case-Control Study Type: RNA Sequencing Total number of consented subjects: 128 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Re-Evaluation of Systemic Early Neuromuscular Blockade","short_name":"PETAL_ROSE_ARDS_RNASeq_HMB","commons":"BioData Catalyst","study_url":"","_subjects_count":128,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs003930.v1.p1.c1":{"gen3_discovery":{"authz":"/programs/BioLINCC/projects/BL_PRHHP_GRU","tags":[],"_unique_id":"phs003930.v1.p1.c1","study_id":"phs003930.v1.p1.c1","study_description":"Data Access NOTE: Please refer to the “Authorized Access” section below for information about how access to the data from this accession differs from many other dbGaP accessions. Objectives: To investigate morbidity and mortality from Coronary Heart Disease (CHD) in Puerto Rican rural and urban men. The objectives of the study were: (1) to identify factors related to the development of CHD, (2) compare the etiology of disease in rural versus urban men, and (3) determine the prevalence and incidence of CHD and other cardiovascular diseases in Puerto Rican males.Background: As Puerto Rico became more industrialized in the 1940s and 1950s, mortality rates for CHD increased. Since many factors related to CHD can be relatively homogenous within a population, two contrasting subgroups were selected for study in Puerto Rico: a rural population of men from a mountainous community and an urban population selected from San Juan. The NHLBI initiated the Puerto Rico Heart Health Program in May, 1965 as a prospective study of lifestyle, environmental and biological factors in the progression of cardiovascular disease in Puerto Rican men.Participants: A total of 9,824 (2,976 rural, 6,848 urban) men, age 45 to 64 were examined at the baseline exam.Design: The examination consisted of standardized questionnaires to determine education, occupation, smoking habits, and physical activity. Trained interviewers conducted a nutritional survey through a 24 hour diet recall. Subjects were also examined to determine prevalent cardiovascular, cerebrovascular and peripheral vascular abnormalities. The examination included vital capacity, a 12-lead ECG, and laboratory tests for hematocrit, glucose, serum cholesterol, serum glycercides and lipoprotein electrophoresis. A medical history was also obtained. Three additional exams, approximately three years apart, were conducted and morbidity and mortality follow-up concluded in 1980. Study Weblinks: BioLINCC Respository Study Design: Prospective Longitudinal Cohort Study Type: Cohort Observational Prospective Total number of consented subjects: 9824 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Puerto Rico Heart Health Program (PRHHP-BioLINCC)","short_name":"BL_PRHHP_GRU","commons":"BioData Catalyst","study_url":"","_subjects_count":9824,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs003933.v1.p1.c1":{"gen3_discovery":{"authz":"/programs/BioLINCC/projects/BL_LOTT_GRU","tags":[],"_unique_id":"phs003933.v1.p1.c1","study_id":"phs003933.v1.p1.c1","study_description":"Data Access NOTE: Please refer to the “Authorized Access” section below for information about how access to the data from this accession differs from many other dbGaP accessions. Objectives: To evaluate the efficacy of long-term treatment with supplemental oxygen in people with stable chronic obstructive pulmonary disease (COPD) and resting or exercise-induced moderate desaturation. Background: COPD is the fourth leading cause of death in the United States, with more than twelve million people currently diagnosed with the disease. In 2011, Medicare reimbursements for oxygen-related costs for people with COPD exceeded two billion dollars. The quality of life of a person with COPD decreases as the disease progresses, making treating and managing COPD in the moderate stages important. The benefits of oxygen supplementation were studied in the 1970s, but these benefits were specific to people with COPD who have severe resting hypoxemia. The LOTT trial was designed to address the effectiveness of supplemental oxygen therapy in treating people with COPD who have moderately low blood oxygen levels at rest or who have normal blood oxygen levels at rest, but have low or very low blood oxygen levels during exercise. Participants: There were a total of 1759 people screened for eligibility for the LOTT trial. Of the 1759 screened, 738 people with COPD were selected for randomization with 368 randomly assigned to the supplemental-oxygen group and 370 to the no-supplemental-oxygen group. Of the 738 people with COPD who underwent randomization, 133 (18%) had resting desaturation only, 319 (43%) had exercise-induced desaturation only, and 286 (39%) had both types of desaturation. Furthermore, in the supplemental-oxygen group, 220 people were prescribed 24-hour oxygen and 148 were prescribed oxygen during exercise and sleep only. Design: The LOTT trial was originally designed to test whether the use of supplemental oxygen would result in a longer time to death for people with COPD and moderate resting desaturation. After seven months, the trial design was judged to be infeasible; therefore, the trial was redesigned to include people with exercise-induced desaturation with a primary composite outcome of death or first hospitalization for any cause, whichever occurs first. Other outcomes measured included: death, health care utilization, COPD exacerbation, quality of life measurements, anxiety, depression, and measures of functional status. Potential participants were screened using questionnaires, a breathing test, a brief physical exam, a blood draw, and measurements of resting and walking blood oxygen levels. Based on those results, eligible participants returned for a second screening visit for further evaluations. At the end of the second visit, eligible participants were assigned randomly to supplemental oxygen therapy or no oxygen therapy. Participants assigned to supplemental oxygen therapy received stationary and/or portable oxygen systems. Participants were required to return for a one hour visit to determine how much oxygen to use while walking and to learn how to use the equipment. Participants who had low blood oxygen levels during rest were instructed to use supplemental oxygen 24 hours per day. Participants with normal resting blood oxygen levels, but low or very low blood oxygen levels during exercise were instructed to use it during physical activity and sleep. Throughout the treatment period, participants were asked to keep records of the number of oxygen tanks emptied or pounds of oxygen delivered, meter readings, and changes in equipment. Study officials contacted participants weekly for the first month, monthly for the next five months, and then every two months until the Year 1 study visit. Participants assigned to receive no oxygen treatment were contacted one week after assignment for a check-up. All participants returned for study visits once a year for up to seven years. At each of these visits, participants completed some of the same tests and questionnaires from the screening visit. Participants underwent a blood draw during the one year study visit. Participants in both treatment groups received two phone calls each year to check on status and use of oxygen. In addition, participants in both groups were asked to complete a quality of life questionnaire by mail at four months and sixteen months. Medicare claims were collected for the duration of each participant's enrollment in the study. Conclusions: In participants with stable COPD and resting or exercise-induced moderate desaturation, the prescription of long-term supplemental oxygen did not result in a longer time to death or first hospitalization than no long-term supplemental oxygen, nor did it provide sustained benefit with regard to any of the other measured outcomes. Long-Term Oxygen Treatment Trial Research Group, Albert RK, Au DH, Blackford AL, Casaburi R, Cooper JA Jr, Criner GJ, Diaz P, Fuhlbrigge AL, Gay SE, Kanner RE, MacIntyre N, Martinez FJ, Panos RJ, Piantadosi S, Sciurba F, Shade D, Stibolt T, Stoller JK, Wise R, Yusen RD, Tonascia J, Sternberg AL, Bailey W. A Randomized Trial of Long-Term Oxygen for COPD with Moderate Desaturation. N Engl J Med. 2016 Oct 27;375(17):1617-1627. Study Weblinks: BioLINCC Repository Study Design: Clinical Trial Study Type: Clinical Trial Total number of consented subjects: 1759 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Long-Term Oxygen Treatment Trial (LOTT-BioLINCC)","short_name":"BL_LOTT_GRU","commons":"BioData Catalyst","study_url":"","_subjects_count":1759,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs003941.v1.p1.c1":{"gen3_discovery":{"authz":"/programs/COVID19/projects/ACTIV6_GRU","tags":[],"_unique_id":"phs003941.v1.p1.c1","study_id":"phs003941.v1.p1.c1","study_description":"This study is a platform protocol designed to be flexible so that it is suitable for a wide range of settings within healthcare systems and in community settings where it can be integrated into routine COVID-19 testing programs and subsequent treatment plans. This platform protocol will enroll participants in an outpatient setting with a confirmed polymerase chain reaction (PCR) or antigen test for SARS-CoV-2. Each appendix will describe a repurposed medication (study drug) to meet the protocol objectives. When only one study drug/appendix is under study, allocation between study drug and placebo will be 1:1. If multiple study drugs/appendices are under study, participants will also be randomized among the study drugs for which eligibility is confirmed. Since the route of administration of each study drug may differ, the placebos may also differ. To achieve blinding and an equitable randomization probability, a two-step randomization process will be used.In the first step, the participant will be randomized m:1 active study drug to placebo, where m is the number of active study drugs for which the participant is eligible. Then, participants will be randomized among the m study drugs for which they are eligible. Participants will carry their ‘study drug' versus ‘placebo' randomization with them into the study drug appendix. In this way, a participant allocated to placebo who is randomized to study drug A will be given the placebo that matches study drug A. This achieves equal probability of exposure to a placebo or an active study drug, and equitable distribution among all study arms for which a participant is eligible. Sites will be informed to which study drug appendix the participant is randomized, but not whether they are allocated to the study drug arm or placebo arm within that appendix. For analysis, concurrent placebo participants who were eligible for the study drug appendix will be pooled. This will result in approximately a 1:1 allocation ratio for any study drug to placebo. If a study drug appendix is stopped for efficacy and becomes standard of care, the active study drug arm may serve as a concurrent placebo for other study drugs.Participants will receive complete supply of repurposed medication (study drug) or placebo with length of treatment and amount of study drug/placebo depending on the study drug appendix and arm to which they are randomized.This study is designed so that it can be done completely remotely. However, screening and enrollment may occur in person at sites and unplanned study visits may occur in person or remotely, as deemed appropriate by an investigator for safety purposes. Participants will be on-study for up to 180 days, during which they will complete various questionnaires. Study Weblinks: ACTIV-6 Study Design: Clinical Trial Study Type: Placebo-Controlled Total number of consented subjects: 10488 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"ACTIV-6: COVID-19 Outpatient Randomized Trial to Evaluate Efficacy of Repurposed Medications","short_name":"ACTIV6_GRU","commons":"BioData Catalyst","study_url":"","_subjects_count":10488,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs003946.v1.p3.c1":{"gen3_discovery":{"authz":"/programs/imaging/projects/img_ARIC_HMB-IRB-NPU-MDS","tags":[],"_unique_id":"phs003946.v1.p3.c1","study_id":"phs003946.v1.p3.c1","study_description":"The Atherosclerosis Risk in Communities (ARIC) Study, sponsored by the National Heart, Lung and Blood Institute (NHLBI), is a prospective epidemiologic study conducted in four U.S. communities. The four communities are Forsyth County, NC; Jackson, MS; the northwest suburbs of Minneapolis, MN; and Washington County, MD. ARIC is designed to investigate the etiology and natural history of atherosclerosis, the etiology of clinical atherosclerotic diseases, and variation in cardiovascular risk factors, medical care and disease by race, gender, location, and date.ARIC includes two parts: the Cohort Component and the Community Surveillance Component. The Cohort Component began in 1987, and each ARIC field center randomly selected and recruited a cohort sample of approximately 4,000 individuals aged 45-64 from a defined population in their community. A total of 15,792 participants received an extensive examination, including medical, social, and demographic data. These participants were examined with the baseline visit occurring in 1987-89, the second visit in 1990-92, the third visit in 1993-95, the fourth visit in 1996-98, the fifth visit in 2011-13, the sixth visit 2016-17, the seventh visit 2018-19 and the eighth visit 2020. Follow-up occurs yearly by telephone to maintain contact with participants and to assess health status of the cohort.In the Community Surveillance Component, these four communities were investigated to determine the community-wide occurrence of hospitalized myocardial infarction and coronary heart disease deaths in men and women aged 35-84 years. Hospitalized stroke is investigated in cohort participants only. Starting in 2006, the study conducted community surveillance of inpatient (ages 55 years and older) and outpatient heart failure (ages 65 years and older) for heart failure events beginning in 2005. Community Surveillance for non-cohorts ended in event year 2014.ARIC is currently funded through 2028.The ARIC Cohort is utilized in the following dbGaP sub-studies. To view genotypes, other molecular data, and derived variables collected in these sub-studies, please click on the following sub-studies below or in the \"Sub-studies\" section of this top-level study page phs000280 ARIC Cohort.phs000557 ARIC_CARe phs000090 GENEVA_ARIC phs000223 PAGE_CALiCo_ARIC phs000398 GO-ESP: HeartGo_ARIC phs000668 CHARGE_ARIC phs000860 MICORTEX phs001536 CCDG_ARIC phs003388 ARIC SomaScan Study Weblinks: ARIC Atherosclerosis Risk in Communities Study Study Design: Prospective Longitudinal Cohort Study Type: Cohort Longitudinal Total number of consented subjects: 15636 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Atherosclerosis Risk in Communities - Imaging","short_name":"img_ARIC_HMB-IRB-NPU-MDS","commons":"BioData Catalyst","study_url":"","_subjects_count":15129,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs003948.v1.p1.c1":{"gen3_discovery":{"authz":"/programs/Individual_Study/projects/PATH_HHT_DS-HHT-IRB-PUB-COL","tags":[],"_unique_id":"phs003948.v1.p1.c1","study_id":"phs003948.v1.p1.c1","study_description":"Data Access NOTE: Please refer to the \"Authorized Access\" section below for information about how access to the data from this accession differs from many other dbGaP accessions.Objectives: To determine efficacy (reduction in severity of epistaxis), tolerability, and improvement in quality of life of pomalidomide compared to placebo after 24 weeks of treatment.Background: This study addresses the efficacy of pomalidomide in the treatment of epistaxis in patients with Hereditary Hemorrhagic Telangiectasia (HHT) who have anemia and/or require blood transfusion or iron infusion for treatment of bleeding-induced anemia and iron deficiency. HHT (also known as Osler-Weber-Rendu disease) is an inherited bleeding disorder. Over 95% of patients develop recurrent epistaxis, which may be severe and result in chronic anemia, need for iron infusions and blood transfusions, substantial psychiatric comorbidity (including depression and post-traumatic stress disorder) and reduction in health-related quality of life (HRQoL). HHT is clinically diagnosed using the Curacao criteria, which consists of 1) spontaneous and recurrent epistaxis, 2) telangiectasias at characteristic sites, 3) visceral arteriovenous malformations (AVMs) or telangiectasias, and 4) a first degree relative with HHT (inheritance is usually autosomal dominant). Patients with three criteria are considered to have definite HHT, and those with 2 criteria probable HHT. HHT affects approximately 1 in 3,800 individuals. Significant manifestations of HHT often do not appear until the third or fourth decades, sometimes later.Participants: 144 patients from 11 clinical centers were enrolled.Design: This is a multi-center, double blind, randomized placebo-controlled trial that investigated the efficacy and safety of pomalidomide in patients with HHT and chronic epistaxis leading to iron-deficiency anemia or requiring intravenous iron infusions or blood transfusion.Screening evaluation included the Epistaxis Severity Score (ESS) with three-month recall, which reflected the patient's history of epistaxis and bleeding over the prior three months, as well as detailed review of iron infusion and red cell transfusion over the preceding six months. Eligible patients were provided a diary to record the duration of each epistaxis event that occurred during the 4 weeks prior to the baseline visit, and then returned for the baseline randomization visit, at which time patients underwent genetic testing, if this had not been previously performed, and completed an ESS with 4-week recall and quality of life assessments. Patients were randomized 2:1, stratified by study site, to either pomalidomide 4 mg/day or matching placebo during each of six 28 day cycles (24 weeks). Patients were seen every four weeks during treatment, and at a 4-week post-treatment follow-up visit to measure the ESS (with 4-week recall), laboratory assessments including iron stores and need for iron infusion, CBC, and metabolic profile. Patients were assessed for adverse events (AE) throughout the study. Treatment dosage could be reduced, or temporarily or permanently discontinued following AE-specific guidelines related to fatigue, cytopenias or other toxicities.Quality of life assessments were completed at baseline, and the 12- and 24-week visits, and the 4-week post-treatment follow-up visit using validated NIH instruments of 1) Neuro-QOL satisfaction with social roles and activities, 2) PROMIS emotional distress – depression, and 3) PROMIS fatigue, and the HHT-specific quality of life instrument developed specifically for this study. The effect of pomalidomide on duration of epistaxis was assessed via diary between weeks 8-12, 20-24 and the 4-week post-treatment period.Conclusions: Among patients with HHT, pomalidomide treatment resulted in a significant, clinically relevant reduction in epistaxis severity. No unexpected safety signals were identified (Al-Samkari et al., 2024; PMID: 39292928) Study Design: Clinical Trial Study Type: Double-Blind Interventional Placebo-Controlled Randomized Controlled Clinical Trial Total number of consented subjects: 144 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Pomalidomide for the Treatment of Bleeding in HHT (PATH-HHT)","short_name":"PATH_HHT_DS-HHT-IRB-PUB-COL","commons":"BioData Catalyst","study_url":"","_subjects_count":144,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs003954.v1.p1.c1":{"gen3_discovery":{"authz":"/programs/BioLINCC/projects/BL_PF_ILD_GRU","tags":[],"_unique_id":"phs003954.v1.p1.c1","study_id":"phs003954.v1.p1.c1","study_description":"Data Access NOTE: Please refer to the “Authorized Access” section below for information about how access to the data from this accession differs from many other dbGaP accessions. Objectives: To identify novel plasma biomarkers of progressive fibrosing interstitial lung disease and develop a proteomic signature to predict this phenotype. Background: Progressive fibrosing interstitial lung disease (ILD) is a devastating condition characterized by parenchymal scar formation, leading to deteriorating lung function and early death. Whereas almost all patients with idiopathic pulmonary fibrosis (IPF) progress, a variable proportion of patients with other common ILDs, including connective tissue disease associated ILD, chronic hypersensitivity pneumonitis, and unclassifiable ILD, develop progressive fibrosing ILD. There are criteria that effectively identify those experiencing ILD progression. However, the criteria do not allow patients who are at risk to be identified before progression occurs. Several blood-based biomarkers have been linked to differential progression in patients with IPF and other fibrosing ILDs. Inflammatory signaling also appears to have a prominent role in fibrotic-predominant ILDs. As such, cytokines, interleukins, and other immune mediators might serve as useful biomarkers of progressive fibrosing ILD. The PF-ILD Proteomics study was a targeted investigation of inflammation-related proteins to identify and validate novel biomarkers of progressive fibrosing ILD in patients with fibrotic connective tissue disease-associated ILD, chronic hypersensitivity pneumonitis, and unclassifiable ILD. Participants: There were 589 participants. The discovery cohort comprised 385 participants and the validation cohort comprised 204 participants. Design: PF-ILD Proteomics was a multicenter cohort analysis study. Peripheral blood was collected from consenting patients and plasma was isolated according to center-specific protocols. Relative plasma concentrations for 368 biomarkers were determined with use of a semi-quantitative, targeted proteomic platform. Patients from UC Davis and UCSF comprised the discovery cohort and those from UTSW comprised the validation cohort. Participants who were alive with less than 10% relative decline in forced vital capacity (FVC) at 12 months-after blood draw were considered to have non-progressive ILD. Participants who died of any cause, underwent lung transplant, or experienced 10% or greater relative FVC decline within 12 months of blood draw were deemed to have progressive fibrosing ILD. Conclusions: 17 plasma biomarkers of progressive fibrosing interstitial lung disease were identified and showed consistent associations across ILD subtypes. Study Weblinks: BioLINCC Repository Study Design: Prospective Longitudinal Cohort Study Type: Observational Total number of consented subjects: 589 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Proteomic Biomarkers of Progressive Fibrosing Interstitial Lung Disease: a Multicentre Cohort Analysis (PF-ILD Proteomics-BioLINCC)","short_name":"BL_PF_ILD_GRU","commons":"BioData Catalyst","study_url":"","_subjects_count":589,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs003963.v1.p1.c1":{"gen3_discovery":{"authz":"/programs/imaging/projects/img_HCSC-SOL_HMB-NPU","tags":[],"_unique_id":"phs003963.v1.p1.c1","study_id":"phs003963.v1.p1.c1","study_description":"The Hispanic Community Health Study/Study of Latinos (HCHS/SOL) is a multi-center epidemiologic study in Hispanic/Latino populations to determine the role of acculturation in the prevalence and development of disease, and to identify risk factors playing a protective or harmful role in Hispanics/Latinos. The study is sponsored by the National Heart, Lung, and Blood Institute (NHLBI) and six other institutes, centers, and offices of the National Institutes of Health (NIH). The goals of the HCHS/SOL include studying the prevalence and development of disease in Hispanics/Latinos, including the role of acculturation, and identifying disease risk factors that play protective or harmful roles in Hispanics/Latinos. A total of 16,415 persons of Cuban, Dominican, Mexican, Puerto Rican, Central American, and South American backgrounds were recruited through four Field Centers affiliated with San Diego State University, Northwestern University in Chicago, Albert Einstein College of Medicine in the Bronx area of New York, and the University of Miami. Seven additional academic centers serve as scientific and logistical support centers. Study participants aged 18-74 years took part in an extensive clinic exam and assessments to ascertain socio-demographic, cultural, environmental and biomedical characteristics. Annual follow-up interviews are conducted to determine a range of health outcomes. Study Weblinks: Hispanic Community Health Study/Study of Latinos (HCHS/SOL): project description Study Design: Prospective Longitudinal Cohort Study Type: Cohort Total number of consented subjects: 13175 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Imaging: Hispanic Community Health Study/Study of Latinos (HCHS/SOL)","short_name":"img_HCSC-SOL_HMB-NPU","commons":"BioData Catalyst","study_url":"","_subjects_count":3787,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs003963.v1.p1.c2":{"gen3_discovery":{"authz":"/programs/imaging/projects/img_HCSC-SOL_HMB","tags":[],"_unique_id":"phs003963.v1.p1.c2","study_id":"phs003963.v1.p1.c2","study_description":"The Hispanic Community Health Study/Study of Latinos (HCHS/SOL) is a multi-center epidemiologic study in Hispanic/Latino populations to determine the role of acculturation in the prevalence and development of disease, and to identify risk factors playing a protective or harmful role in Hispanics/Latinos. The study is sponsored by the National Heart, Lung, and Blood Institute (NHLBI) and six other institutes, centers, and offices of the National Institutes of Health (NIH). The goals of the HCHS/SOL include studying the prevalence and development of disease in Hispanics/Latinos, including the role of acculturation, and identifying disease risk factors that play protective or harmful roles in Hispanics/Latinos. A total of 16,415 persons of Cuban, Dominican, Mexican, Puerto Rican, Central American, and South American backgrounds were recruited through four Field Centers affiliated with San Diego State University, Northwestern University in Chicago, Albert Einstein College of Medicine in the Bronx area of New York, and the University of Miami. Seven additional academic centers serve as scientific and logistical support centers. Study participants aged 18-74 years took part in an extensive clinic exam and assessments to ascertain socio-demographic, cultural, environmental and biomedical characteristics. Annual follow-up interviews are conducted to determine a range of health outcomes. Study Weblinks: Hispanic Community Health Study/Study of Latinos (HCHS/SOL): project description Study Design: Prospective Longitudinal Cohort Study Type: Cohort Total number of consented subjects: 13175 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Imaging: Hispanic Community Health Study/Study of Latinos (HCHS/SOL)","short_name":"img_HCSC-SOL_HMB","commons":"BioData Catalyst","study_url":"","_subjects_count":9388,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs003968.v1.p1.c1":{"gen3_discovery":{"authz":"/programs/BioLINCC/projects/BL_WRAP_IPF_GRU","tags":[],"_unique_id":"phs003968.v1.p1.c1","study_id":"phs003968.v1.p1.c1","study_description":"Data Access NOTE: Please refer to the \"Authorized Access\" section below for information about how access to the data from this accession differs from many other dbGaP accessions. Objectives: To determine if the reduction of abnormal gastro-esophageal reflux (GER) with laparoscopic anti-reflux surgery will slow the progression of idiopathic pulmonary fibrosis (IPF) as measured by forced vital capacity (FVC).Background: Idiopathic pulmonary fibrosis (IPF) is a chronic progressive lung disease of unknown cause and increasing prevalence in the United States. Aside from lung transplantation, which approximately only 1% of participants will receive, there is no FDA-approved therapy. Abnormal acid gastro-esophageal reflux (GER) has been well described in participants with IPF and is thought to play a role in the progression of the disease. The several retrospective cohort studies that have assessed the association of anti-acid therapies for GER with clinical outcomes in IPF have had inconsistent results.Participants: A total of 58 participants were enrolled.Design: The WRAP-IPF trial was a multicenter, unblinded randomized clinical trial with participants randomized to either laparoscopic anti-reflux surgery or no surgery. Participants in the no-surgery group had the option of receiving laparoscopic anti-reflux surgery from 24 weeks after randomization if their clinician deemed it medically necessary. Medications for acid GER were allowed in both groups if the clinician felt it was necessary.Participants were followed up from time of randomization to 52 weeks. All participants had study visits at baseline, 12, 24, 36, and 48 weeks, during which spirometry, 6-min walk testing, and participant-related outcome assessments were done. Participants in the surgery group had clinical visits for preoperative evaluation, laparoscopic anti-reflux surgery, and postoperative management as clinically indicated. Surgery participants additionally underwent repeat 24-hour pH testing at 24 weeks to assess the efficacy of the surgery. All participants were contacted by telephone for safety assessments at weeks 4, 8, 16, 20, 28, 32, 40, 44, and 52. All participants completed an exploratory questionnaire on reflux symptoms at baseline and 48 weeks. The primary endpoint was change in FVC from randomization (baseline) to 48 weeks. Secondary endpoints included acute exacerbation, non-elective hospitalization (both all-cause and respiratory-related), death, change in cough severity, change in dyspnea severity, change in health-related quality of life, change in 6-min walk distance, and time to selected event-driven composite endpoints of disease progression. Conclusions: In participants with IPF and abnormal acid GER, laparoscopic anti-reflux surgery is safe and well tolerated but did not significantly slow the rate of FVC decline. Further research is needed, particularly with a larger study in order to achieve sufficient statistical power, regarding the possible benefits of anti-reflux surgery in this population.Raghu G, Pellegrini CA, Yow E, et al. Laparoscopic anti-reflux surgery for the treatment of idiopathic pulmonary fibrosis (WRAP-IPF): a multicentre, randomised, controlled phase 2 trial. Reference: Raghu, et al., 2018; PMID: 30100404. Study Weblinks: BioLINCC Repository Study Design: Clinical Trial Study Type: Randomized Controlled Clinical Trial Total number of consented subjects: 58 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Weighing Risks and Benefits of Laparoscopic Anti-Reflux Surgery in Patients With Idiopathic Pulmonary Fibrosis (WRAP-IPF-BioLINCC)","short_name":"BL_WRAP_IPF_GRU","commons":"BioData Catalyst","study_url":"","_subjects_count":58,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs003995.v1.p1.c1":{"gen3_discovery":{"authz":"/programs/BioLINCC/projects/BL_LRC_PS_GRU","tags":[],"_unique_id":"phs003995.v1.p1.c1","study_id":"phs003995.v1.p1.c1","study_description":"Data Access NOTE: Please refer to the “Authorized Access” section below for information about how access to the data from this accession differs from many other dbGaP accessions. Objectives: The LRC Program began in 1971 under the sponsorship of the National Heart, Lung, and Blood Institute, National Institutes of Health. Part of this program was the Lipid Research Clinics Prevalence Study, a standardized series of cross-sectional surveys of various North American populations designed to determine the prevalence of dyslipidemias and to describe the distributions of lipids and lipoproteins in major ethnic and social groups. In addition to contributing to the aggregate analysis, each independent population-based study was designed with capabilities for separate analyses of lipid and lipoprotein distributions. The participating populations were not selected to be a probability sample representative of the North American population per se, but by virtue of their size and economic and geographical diversity, they provide a useful cross-sectional group. The Family Study was the third phase of the Lipids Research Clinics North American Population Studies. The Family Study was designed to obtain knowledge of the distribution of lipids and lipoproteins among family members and of the association of familial and genetic attributes to dyslipoproteinemias. Background: An association between serum cholesterol and coronary heart disease is well established. A system was developed for classifying hyperlipoproteinemias into six types of patterns, as a basis for characterizing lipoprotein disorders. The Lipid Research Clinics was thus created to improve the detection of and clinical management of hyperlipoproteinemias. The three primary objectives were: 1) to acquire data on the prevalence of different types of hyperlipoproteinemia in various age and ethnic groups, with special emphasis on the nature and frequency of genetic forms; 2) to collect reliable data on the prevalence and incidence of atherosclerosis in different types of hyperlipoproteinemia; and 3) to conduct an intervention trial to determine if lowering plasma lipid levels would reduce the risk of CHD. Participants: There were 60,495 participants. Conclusions: Data from this study confirm findings from earlier studies in developed countries, showing age-related differences in plasma lipid levels. However, for overall distributions, the LRC data showed slightly lower cholesterol and markedly higher trigylceride values than those previously reported for North America. Some variation in plasma lipid values was evident among the clinic populations. The large number of participants within most subgroups permitted a variety of analytic and comparative studies. For example, data from the large pediatric population revealed a drop in plasma cholesterol levels in adolescent males and females. Males aged 20-50 years had higher cholesterol levels than females in the same age group, and higher trigylceride levels between ages 20-70 years. Numbers were also significient for meaningful comparisons between lipid distributions of females who were taking sex hormones and those who were not; in females taking sex hormones, cholesterol and triglyceride levels were higher for subjects younger than 45 years, but slightly lower after age 45, than lipid levels in females not taking hormones (Circulation 1979; 60(2):427-439). Study Weblinks: BioLINCC Repository Study Design: Cross-Sectional Study Type: Cross-Sectional Observational Total number of consented subjects: 60495 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Lipid Research Clinics - Prevalence Study (LRC-PS-BioLINCC)","short_name":"BL_LRC_PS_GRU","commons":"BioData Catalyst","study_url":"","_subjects_count":60489,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs004002.v1.p1.c1":{"gen3_discovery":{"authz":"/programs/imaging/projects/img_dMRI_VGC_GRU","tags":[],"_unique_id":"phs004002.v1.p1.c1","study_id":"phs004002.v1.p1.c1","study_description":"Objectives We are sharing a database of dynamic magnetic resonance imaging (dMRI) scans of normal children, which can serve as a reference standard to quantify regional respiratory abnormalities in young patients with various respiratory conditions and facilitate treatment planning and response assessment. The database can also be useful to advance future AI-based research on image-based object segmentation and analysis. Background In pediatric patients with respiratory abnormalities, it is important to understand the alterations in regional dynamics of the lungs and other thoracoabdominal components, which in turn requires a quantitative understanding of what is considered as normal in healthy children. Currently, such a normative database of regional respiratory structure and function in healthy children does not exist. Participants 200 normal children (ages 6-18 years) participated in our research study related to this dataset. DesignThe shared open-source normative database is from our ongoing virtual growing child (VGC) project, which includes 4D dMRI images representing one breathing cycle for each normal child and also segmentations of 10 objects at end expiration (EE) and end inspiration (EI) phases of the respiratory cycle in the 4D image. The lung volumes at EE and EI as well as the excursion volumes of chest wall and diaphragm from EE to EI, left and right sides separately, are also reported. The database has thus 4,000 3D segmentations from 200 normal children in total. The database is unique and provides dMRI images, object segmentations, and quantitative regional respiratory measurement parameters of volumes for normal children. All dMRI scans are acquired from normal children during free-breathing. The dMRI acquisition protocol was as follows: 3T MRI scanner (Verio, Siemens, Erlangen, Germany), true-FISP bright-blood sequence, TR=3.82 ms, TE=1.91 ms, voxel size ~1×1×6 mm3, 320×320 matrix, bandwidth 258 Hz, and flip angle 76o. With recent advances, for each sagittal location across the thorax and abdomen, we acquired 40 2D slices over several tidal breathing cycles at ~480 ms/slice. On average, 35 sagittal locations are imaged, yielding a total of ~1400 2D MRI slices, with a resulting total scan time of 11-13 minutes for any particular study participant.The collected dMRI scan data then went through the procedure of 4D image construction, image processing, object segmentation, and volumetric measurements from segmentations. 4D image construction: For the acquired dMRI scans, we utilized an automated 4D image construction approach to form one 4D image over one breathing cycle (consisting of typically 5-8 respiratory phases) from each acquired dMRI scan to represent the whole dynamic thoraco-abdominal body region. The algorithm selects 175-280 slices (35 sagittal locations × 5-8 respiratory phases) from the 1400 acquired slices in an optimal manner using an optical flux method. Image processing: Intensity standardization is performed on every time point/3D volume of the 4D image so that image values have the same tissue-specific meaning across all subjects. Object segmentation: For each subject, there are 10 objects segmented at both EE and EI time points in this database. They include the thoracoabdominal skin outer boundary, left and right lungs, liver, spleen, left and right kidneys, diaphragm, and left and right hemi-diaphragms. All dMRI scans utilize large field of view images, which include the full thorax and abdomen to the inferior aspect of the kidneys in the sagittal plane. We used a pretrained U-Net based deep learning network to first segment all objects, and then all auto-segmentation results were visually checked and manually refined as needed, under the supervision of a radiologist with over 25 years of expertise in MRI and thoracoabdominal radiology. Manual segmentations have been performed for all objects in all datasets. Volumetric measurements based on object segmentations for lung volumes (left and right separately) at EE and EI, as well as for chest wall and diaphragm excursion volumes (left and right separately) are reported. ConclusionsThe provided database is unique and provides dMRI images, object segmentations, and quantitative regional respiratory measurement parameters of volumes for normal children. The database has 4,000 3D segmentations from 200 normal children, which to our knowledge is the largest and only such dMRI dataset to date. All images and object segmentations are saved in DICOM. All DICOM files (176,574 in total) have been anonymized, and PHI has been removed. The database can be used as a reference standard to quantify regional respiratory abnormalities in young patients with various respiratory conditions and facilitate treatment planning and response assessment. The large amount of object segmentations can potentially benefit AI-based research on image-based object segmentation and analysis. Study Design: Collection Study Type: Control Set Total number of consented subjects: 200 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Virtual Growing Child 5-Dimensional Functional Models for Treating Respiratory Anomalies (dMRI-VGC)","short_name":"img_dMRI_VGC_GRU","commons":"BioData Catalyst","study_url":"","_subjects_count":200,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs004010.v1.p1.c1":{"gen3_discovery":{"authz":"/programs/BioLINCC/projects/BL_IPPB_GRU","tags":[],"_unique_id":"phs004010.v1.p1.c1","study_id":"phs004010.v1.p1.c1","study_description":"Data Access NOTE: Please refer to the “Authorized Access” section below for information about how access to the data from this accession differs from many other dbGaP accessions. Objectives: To evaluate the efficacy of long-term intermittent positive pressure breathing (IPPB) treatment when used as an adjunct to the overall care of ambulatory outpatients with chronic obstructive pulmonary disease. The evaluation compared the use of IPPB with use of a powered nebulizer.Participants: A total of 3218 participants were enrolled.Design: Multicenter randomized controlled clinical trial. Conclusions: Compliance with treatment, lung function, and quality of life were evaluated at regular intervals during follow-up, and records were kept of hospitalizations and vital status. Treatment compliance was less than optimal; only half of the participants used their devices for the prescribed amount of time or 10 minutes at least three times a day. Although this was disappointing, it was probably the best compliance that could be attained. There was no statistically significant difference between the treatment groups in mortality, rate and duration of hospitalizations, or change in lung function or life quality with time, overall or for clinically relevant subgroups. The trial group saw no advantage of IPPB over compressor nebulizer therapy and concluded that, if an advantage existed, it must be marginal. Study Weblinks: BioLINCC Repository Study Design: Clinical Trial Study Type: Randomized Controlled Clinical Trial Total number of consented subjects: 3218 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Clinical Study of Intermittent Positive Pressure Breathing (IPPB-BioLINCC)","short_name":"BL_IPPB_GRU","commons":"BioData Catalyst","study_url":"","_subjects_count":3218,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs004011.v1.p1.c1":{"gen3_discovery":{"authz":"/programs/Individual_Study/projects/INVESTED_GRU","tags":[],"_unique_id":"phs004011.v1.p1.c1","study_id":"phs004011.v1.p1.c1","study_description":"INVESTED was planned as a large, adequately powered, multicenter trial to assess the cardiopulmonary benefit of high- compared with standard-dose influenza vaccine in a high-risk cardiovascular population. In contrast to more complex interventions in patients with cardiac disease, the major potential benefits of this intervention are a) the ease of administration, b) low cost, c) 100% vaccination adherence and d) well established and extremely low risk. This trial, if positive, has the potential to substantially impact a major population attributable CV risk, change practice, and inform health policy by boosting utilization of influenza vaccination. Study Weblinks: INVESTED Trial Study Design: Clinical Trial Study Type: Controlled Trial Interventional Total number of consented subjects: 5260 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"INfluenza Vaccine to Effectively Stop Cardio Thoracic Events and Decompensated Heart Failure (INVESTED)","short_name":"INVESTED_GRU","commons":"BioData Catalyst","study_url":"","_subjects_count":5260,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs004013.v1.p1.c1":{"gen3_discovery":{"authz":"/programs/BioLINCC/projects/BL_LHS_GRU","tags":[],"_unique_id":"phs004013.v1.p1.c1","study_id":"phs004013.v1.p1.c1","study_description":"Data Access NOTE: Please refer to the “Authorized Access” section below for information about how access to the data from this accession differs from many other dbGaP accessions. Objectives: To determine the effects of Special Care, compared to Usual Care, on rate of decline in pulmonary function in a group of cigarette smokers identified as having mild abnormalities in pulmonary function. In addition, the study sought to determine if participants with chronic obstructive pulmonary disease, who were assigned to inhaled corticosteroids had a lower rate of decline in lung function and lower incidence of respiratory morbidity compared to participants assigned to placebo. Also, the study sought to determine the long-term effects of smoking cessation and continued smoking, on cardiopulmonary morbidity, mortality, and the rate of decline in the one second forced expiratory volume in men and women with early chronic obstructive lung disease who have been followed prospectively for 12 to 15 years.Participants: A total of 5887 participants were enrolled.Conclusions: Participants in the two smoking intervention groups showed significantly smaller declines in Forced Expiratory Volume 1 (FEV1) than did those in the control group. Most of this difference occurred during the first year following entry into the study and was attributable to smoking cessation, with those who achieved sustained smoking cessation experiencing the largest benefit. The small noncumulative benefit associated with use of the active bronchodilator vanished after the bronchodilator was discontinued at the end of the study. The authors concluded that an aggressive smoking intervention program significantly reduced the age-related decline in FEV1 in middle-aged smokers with mild airways obstruction. Use of an inhaled anticholinergic bronchodilator resulted in a relatively small improvement in FEV1 that appeared to be reversed after the drug was discontinued. Use of the bronchodilator did not influence the long-term decline of FEV1. Additionally, the study showed that lung function decline in the participants treated with the inhaled corticosteroid was statistically no different from that in the placebo group. Corticosteroid use did, however, result in 25 percent fewer respiratory symptoms and nearly 50 percent fewer outpatient visits for respiratory problems. However, after three years, bone density in the hip and back was lower in the corticosteroid group. Study Weblinks: BioLINCC Repository Study Design: Clinical Trial Study Type: Interventional Total number of consented subjects: 5887 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Lung Health Study (LHS-BioLINCC)","short_name":"BL_LHS_GRU","commons":"BioData Catalyst","study_url":"","_subjects_count":5887,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs004019.v1.p1.c1":{"gen3_discovery":{"authz":"/programs/DIR/projects/Stressors_and_Health_Study_HMB-PUB-COL","tags":[],"_unique_id":"phs004019.v1.p1.c1","study_id":"phs004019.v1.p1.c1","study_description":"ObjectivesThe objectives of the Stressors and Health Study were to: (1) examine the prevalence of stressors and health outcomes and (2) assess differences in the associations between multi-level stressors and health outcomes, and (3) explore the protective and adaptive factors in the associations between multi-level stressors and health outcomes. Background Stressors have been posited to explain disparities in health. However, no surveys to our knowledge have simultaneously collected multiple stressors at various levels and the coping strategies used to deal with these stressors. Measuring these factors can provide a better understanding of the stressors experienced by specific groups and the impact that these experiences have on their health and health practices. In addition, exploring the various resilience and coping strategies employed to deal with stressors can help design appropriate interventions to reduce health disparities. Participants Participants included 1000 White, 1000 Black or African American, 1000 Latino or Hispanic, 1000 Asian, 500 American Indian or Alaska Native, 500 Native Hawaiian or Pacific Islander, and 500 mixed or multi-race adults (≥18 years) across the United States. Design The Stressors and Health Study is a cross-sectional online survey of adults across the US. A sampling frame (target population) of US residents based on the American Community Survey (ACS) was constructed using a rigorous two-step sampling matching approach to establish national representation. Study Design: Cross-Sectional Study Type: Cross-Sectional Total number of consented subjects: 5500 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Stressors and Health Study","short_name":"Stressors_and_Health_Study_HMB-PUB-COL","commons":"BioData Catalyst","study_url":"","_subjects_count":5500,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs004020.v1.p1.c1":{"gen3_discovery":{"authz":"/programs/BioLINCC/projects/BL_PIOPED_GRU","tags":[],"_unique_id":"phs004020.v1.p1.c1","study_id":"phs004020.v1.p1.c1","study_description":"Data Access NOTE: Please refer to the “Authorized Access” section below for information about how access to the data from this accession differs from many other dbGaP accessions. Objectives: To determine the sensitivities and specificities of ventillation/perfusion (V/Q) lung scans for acute pulmonary embolism (PE).Participants: A total of 1487 participants were enrolled.Conclusions: Almost all participants with pulmonary embolism had abnormal scans of high, intermediate, or low probability, but so did most without pulmonary embolism. Only in a minority of participants did the clinical assessment combined with the V/Q scan interpretation improve the overall chance of reaching a correct diagnosis of acute PE. Although a high probability scan usually indicated the presence of PE, only a small number of participants with PE had a high probability scan. Reference: PIOPED Investigators, 1990, PMID: 2332918. Study Weblinks: BioLINCC Repository Study Design: Clinical Trial Study Type: Interventional Total number of consented subjects: 1487 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Prospective Investigation of Pulmonary Embolism Diagnosis (PIOPED-BioLINCC)","short_name":"BL_PIOPED_GRU","commons":"BioData Catalyst","study_url":"","_subjects_count":1487,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs004021.v1.p1.c1":{"gen3_discovery":{"authz":"/programs/BioLINCC/projects/BL_ALLHAT_GRU","tags":[],"_unique_id":"phs004021.v1.p1.c1","study_id":"phs004021.v1.p1.c1","study_description":"Data Access NOTE: Please refer to the “Authorized Access” section below for information about how access to the data from this accession differs from many other dbGaP accessions. ObjectivesHypertension Study: To determine whether treatment with a calcium channel blocker or an angiotensin-converting enzyme inhibitor lowers the incidence of coronary heart disease (CHD) or other cardiovascular disease (CVD) events vs treatment with a diuretic.Lipid Study: To determine whether pravastatin compared with usual care reduces all-cause mortality in older, moderately hypercholesterolemic, hypertensive participants with at least an additional CHD risk factor. BackgroundHypertension Study: Antihypertensive therapy is well established to reduce hypertension-related morbidity and mortality, but the optimal first-step therapy is unknown.Lipid Study: Studies have demonstrated that statins administered to individuals with risk factors for coronary heart disease (CHD) reduce CHD events. However, many of these studies were too small to assess all-cause mortality or outcomes in important subgroups.ParticipantsHypertension Study: A total of 33,357 participants. Lipid Study: A total of 10,355 participants. Baseline mean total cholesterol was 224 mg/dL; LDL-C, 146 mg/dL; high-density lipoprotein cholesterol, 48 mg/dL; and triglycerides, 152 mg/dL. Mean age was 66 years; 49% were women, 38% black and 23% Hispanic, 14% had a history of CHD, and 35% had type 2 diabetes. DesignHypertension Study: A randomized, double-blind, active-controlled clinical trial conducted from February 1994 through March 2002. Participants were randomly assigned to receive chlorthalidone, 12.5 to 25 mg/d (n = 15,255); amlodipine, 2.5 to 10 mg/d (n = 9048); or lisinopril, 10 to 40 mg/d (n = 9054) for planned follow-up of approximately 4 to 8 years. The primary outcome was combined fatal CHD or nonfatal myocardial infarction, analyzed by intent-to-treat. Secondary outcomes were all-cause mortality, stroke, combined CHD (primary outcome, coronary revascularization, or angina with hospitalization), and combined CVD (combined CHD, stroke, treated angina without hospitalization, heart failure (HF), and peripheral arterial disease).Lipid Study: Multicenter (513 primarily community-based North American clinical centers), randomized, non-blinded trial conducted from 1994 through March 2002 in a subset of participants from the Antihypertensive and Lipid-Lowering Treatment to Prevent Heart Attack Trial (ALLHAT). The interventions in the trial were pravastatin, 40 mg/d, vs usual care. The primary outcome was all-cause mortality, with follow-up for up to 8 years. Secondary outcomes included non-fatal myocardial infarction or fatal CHD (CHD events) combined, cause-specific mortality, and cancer.ConclusionsHypertension Study: Thiazide-type diuretics are superior in preventing one or more major forms of CVD and are less expensive. They should be preferred for first-step antihypertensive therapy.Lipid Study: Pravastatin did not reduce either all-cause mortality or CHD significantly when compared with usual care in older participants with well-controlled hypertension and moderately elevated LDL-C. The results may be due to the modest differential in total cholesterol (9.6%) and LDL-C (16.7%) between pravastatin and usual care compared with prior statin trials supporting cardiovascular disease prevention. Study Weblinks: ALLHAT - BioLINCC Study Design: Clinical Trial Study Type: Interventional Total number of consented subjects: 42418 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Antihypertensive and Lipid-Lowering Treatment to Prevent Heart Attack Trial (ALLHAT-BioLINCC)","short_name":"BL_ALLHAT_GRU","commons":"BioData Catalyst","study_url":"","_subjects_count":42418,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs004022.v1.p1.c1":{"gen3_discovery":{"authz":"/programs/BioLINCC/projects/BL_BEST_COPD_GRU","tags":[],"_unique_id":"phs004022.v1.p1.c1","study_id":"phs004022.v1.p1.c1","study_description":"Data Access NOTE: Please refer to the “Authorized Access” section below for information about how access to the data from this accession differs from many other dbGaP accessions. Objectives: To establish a safe and tolerable dose of sulforaphane that effects in vivo antioxidants via Nrf2 for development as a potential novel treatment for participants with Chronic Obstructive Pulmonary Disease (COPD).Background: Chronic Obstructive Pulmonary Disease (COPD), caused primarily by smoking, is the third leading cause of death in the United States and world-wide. Surprisingly, there are few treatments available to address the pathobiology of COPD other than cessation of smoking. The development and progression of COPD are associated with increased inflammatory response(s) and increased oxidative stress in the lung. Thus, one approach to the development of novel therapies is the stimulation of endogenous antioxidant defense mechanisms.Nuclear factor erythroid-2-related factor 2 (NFE2L2/Nrf2) is a transcription factor activated by oxidative stress. Nrf2 activity promotes anti-oxidant enzymes, and anti-oxidant enzymes play key roles in cellular defenses. Sulforaphane, a derivative of broccoli and other cruciferous vegetables, has been shown to stimulate Nrf2 activity in both in vivo and in vitro experiments. For example, activation of Nrf2 protected mice from developing emphysema after chronic smoke exposure and decreased oxidative stress. Similarly, activation of Nrf2 in human COPD lung cells resulted in decreased oxidative stress. Therefore, this study was designed to assess whether daily ingestion of sulforaphane by COPD participants for four weeks increased Nrf2 activity in alveolar macrophages and bronchial epithelial cells. Participants: There were a total of 89 participants randomized to one of three treatment arms. Of these, 31 participants were randomized to the placebo arm, and 29 participants were randomized to the each of the sulforaphane arms. One participant withdrew from the placebo arm, therefore, a total of 88 participants completed the study.Design: Participants were assigned to receive sulforaphane at 25 micromoles (4.4mg), sulforaphane at 150 micromoles (26.6 mg), or placebo (microcellulose) once daily by mouth. Computer-generated treatment assignments were blinded to participants, clinical staff, and study staff. Doses were back-filled with methylcellulose and presented in similar capsules to compensate for appearance and weight differences in sulforaphane and placebo treatments arms.There were a total of five study visits over the six-week study period. Prior to randomization, participants were assessed for eligibility, which included baseline data collection. Participants provided medical histories, underwent a physical examination, pre-and-post bronchodilator spirometry, lung volume measurements, carbon monoxide diffusing capacity (DLCO), and pulse oximetry over the six-week study period. Follow up data and biospecimens were collected at the final visit, which was targeted for four weeks after randomization. Two fiberoptic bronchoscopies were performed under sedation to collect endobronchial brushings and bronchoalveolar lavage used to isolate alveolar macrophages and bronchial epithelial cells. The first bronchoscopy was performed on the day of randomization, and the second bronchoscopy was performed the day after the final visit. In addition, nasal brushings were obtained prior to bronchoscopy to isolate nasal epithelial cells. The primary outcomes were changes in Nrf2 target gene expression at four weeks in alveolar macrophages and bronchial epithelial cells. The target genes for the primary outcome were NQ01, H01, AKR1C1, and AKR1C3. Secondary outcomes included the evaluation of: expression of other genes in the Nrf2/Keap1 pathway (e.g. Nrf2/NFE2L2, KEAP1, and SLPI), markers of oxidative stress (e.g., isoprostane and thiobarbituric acid reactive substances) in plasma and expired breath condensate, and cytokine profiles in bronchoalveolar lavage fluid. Conclusions: Sulforaphane administered at four weeks doses of 25umoles and 150umoles to participants with COPD did not significantly increase Nrf2 target gene expression in alveolar macrophages or bronchial epithelial cells. In addition, changes in oxidative stress markers and the expression of other genes in the Nrf2/Keap1 pathway were not statistically significant between the treatment groups.Wise RA, Holbrook JT, Criner G, et al. Lack of Effect of Oral Sulforaphane Administration on Nrf2 Expression in COPD: A Randomized, Double-Blind, Placebo Controlled Trial. Vij N, ed. PLoS ONE. 2016; 11(11):e0163716. doi:10.1371/journal.pone.0163716 (PMID: 27832073; PMID: 28350841). Study Weblinks: BioLINCC Repository Study Design: Clinical Trial Study Type: Double-Blind Placebo-Controlled Randomized Total number of consented subjects: 89 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Broccoli Sprouts Extracts Trial (BEST-COPD-BioLINCC)","short_name":"BL_BEST_COPD_GRU","commons":"BioData Catalyst","study_url":"","_subjects_count":89,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs004023.v1.p2.c1":{"gen3_discovery":{"authz":"/programs/imaging/projects/img_COPDGene_HMB","tags":[],"_unique_id":"phs004023.v1.p1.c1","study_id":"phs004023.v1.p1.c1","study_description":"This study contains CT imaging files, obtained at each of the on-site visits. Chronic obstructive pulmonary disease (COPD) is the fourth leading cause of death in the United States and the only leading cause of death that is steadily increasing in frequency. This project established a racially diverse cohort that is sufficiently large and appropriately designed for genome-wide association analysis of COPD. A total of 10,720 subjects were recruited, including control smokers and nonsmokers, definite COPD cases (GOLD Stage 2 to 4), and subjects not included in either group (GOLD 1 and PRISm). This cohort is being used for cross-sectional analysis, and long-term longitudinal follow-up visits after five years and after ten years are also being performed. The primary focus of the study is to identify the genetic risk factors that determine susceptibility for COPD and COPD-related phenotypes. Detailed phenotyping of both cases and controls, including chest CT scan assessment of emphysema and airway disease, will allow identification of genetic determinants for the heterogeneous components of the COPD syndrome. The hypotheses to be studied are: 1) Precise phenotypic characterization of COPD subjects using computed tomography, as well as clinical and physiological measures, will provide data that will enable the broad COPD syndrome to be decomposed into clinically significant subtypes. 2) Genome-wide association studies will identify genetic determinants for COPD susceptibility that will provide insight into clinically relevant COPD subtypes. 3) Distinct genetic determinants influence the development of emphysema and airway disease. Roughly 9,500 of the participants have one or more CT imaging files. Some subjects may not have CT scans for a few reasons, including: CT image failed QC due to incorrect protocol, too much motion, portion of lung not in field of view, inadequate inspiration, imaging files incomplete/damaged, and early recruited controls had option to decline CT scan. Not all subjects completed on-site visits/CT scans in all phases of the study.CT files are DICOM; users will need DICOM-reading software. Study Weblinks: COPDGene Study Design: Case-Control Study Type: Case-Control Total number of consented subjects: 10404 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Genetic Epidemiology of COPD (COPDGene) Imaging Data","short_name":"img_COPDGene_HMB","commons":"BioData Catalyst","study_url":"","_subjects_count":10122,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs004023.v1.p2.c2":{"gen3_discovery":{"authz":"/programs/imaging/projects/img_COPDGene_DS-CS","tags":[],"_unique_id":"phs004023.v1.p1.c2","study_id":"phs004023.v1.p1.c2","study_description":"This study contains CT imaging files, obtained at each of the on-site visits. Chronic obstructive pulmonary disease (COPD) is the fourth leading cause of death in the United States and the only leading cause of death that is steadily increasing in frequency. This project established a racially diverse cohort that is sufficiently large and appropriately designed for genome-wide association analysis of COPD. A total of 10,720 subjects were recruited, including control smokers and nonsmokers, definite COPD cases (GOLD Stage 2 to 4), and subjects not included in either group (GOLD 1 and PRISm). This cohort is being used for cross-sectional analysis, and long-term longitudinal follow-up visits after five years and after ten years are also being performed. The primary focus of the study is to identify the genetic risk factors that determine susceptibility for COPD and COPD-related phenotypes. Detailed phenotyping of both cases and controls, including chest CT scan assessment of emphysema and airway disease, will allow identification of genetic determinants for the heterogeneous components of the COPD syndrome. The hypotheses to be studied are: 1) Precise phenotypic characterization of COPD subjects using computed tomography, as well as clinical and physiological measures, will provide data that will enable the broad COPD syndrome to be decomposed into clinically significant subtypes. 2) Genome-wide association studies will identify genetic determinants for COPD susceptibility that will provide insight into clinically relevant COPD subtypes. 3) Distinct genetic determinants influence the development of emphysema and airway disease. Roughly 9,500 of the participants have one or more CT imaging files. Some subjects may not have CT scans for a few reasons, including: CT image failed QC due to incorrect protocol, too much motion, portion of lung not in field of view, inadequate inspiration, imaging files incomplete/damaged, and early recruited controls had option to decline CT scan. Not all subjects completed on-site visits/CT scans in all phases of the study.CT files are DICOM; users will need DICOM-reading software. Study Weblinks: COPDGene Study Design: Case-Control Study Type: Case-Control Total number of consented subjects: 10404 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Genetic Epidemiology of COPD (COPDGene) Imaging Data","short_name":"img_COPDGene_DS-CS","commons":"BioData Catalyst","study_url":"","_subjects_count":282,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs004032.v1.p1.c1":{"gen3_discovery":{"authz":"/programs/BioLINCC/projects/BL_HIFI_GRU","tags":[],"_unique_id":"phs004032.v1.p1.c1","study_id":"phs004032.v1.p1.c1","study_description":"Data Access NOTE: Please refer to the “Authorized Access” section below for information about how access to the data from this accession differs from many other dbGaP accessions. Objectives: To evaluate the hypothesis that high frequency oscillatory ventilation in preterm infants would reduce the incidence of mortality and pulmonary complications compared to conventional mechanical ventilation.Background: With the introduction of mechanical ventilation in preterm infants, mortality and morbidity significantly improved but remained high. The improvement in survival that accompanied the use of mechanical ventilation also brought about an increase in the incidence of pulmonary complications. The principal complication occurs in the form of bronchopulmonary dysplasia. Barotrauma and oxygen toxicity are considered to be in the pathogenesis for this disorder. Considerable interest in high frequency ventilation for preterm infants was generated when animal studies indicated high frequency ventilation to be effective in promoting gas exchange without apparent adverse effects. High Frequency Ventilation (HFV) delivers small tidal volumes at high frequencies of 4 to 15 Hz, and animal studies had indicated that HFV was associated with effective gas exchange, less barotrauma, and lower mean airway pressure. However, the efficacy and safety of HFV in preterm infants had not been studied. The HIFI Planning Phase was initiated in August 1984, and recruitment and intervention began in February, 1986. Follow-up studies continued thru September, 1988.Participants: A total of 673 infants were enrolled.Conclusions: Bronchopulmonary dysplasia incidence was similar in the two groups as was mortality and the need for ventilatory support during the first 28 days. There was a significantly greater rate of pneumoperitoneum of pulmonary origin in the high frequency group as was a greater incidence rate of intracranial hemorrhage. (HIFI Study Group, 1989, PMID: 2643039) Study Weblinks: BioLINCC Repository Study Design: Clinical Trial Study Type: Interventional Total number of consented subjects: 2272 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"High Frequency Ventilation in Premature Infants (HIFI-BioLINCC)","short_name":"BL_HIFI_GRU","commons":"BioData Catalyst","study_url":"","_subjects_count":2272,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs004051.v1.p1.c1":{"gen3_discovery":{"authz":"/programs/Individual_Study/projects/VDKA_DS-ASTHMA","tags":[],"_unique_id":"phs004051.v1.p1.c1","study_id":"phs004051.v1.p1.c1","study_description":"The Vitamin D Kids Asthma Study (VDKA) was a 48-week multicenter randomized, double-blinded, placebo-controlled trial of vitamin D3 for severe asthma exacerbations in children 6-16 years old, recruited from February 28, 2016 to September 20, 2019. An ancillary study for nasal sampling was conducted at the Pittsburgh site. Prior to randomization, participants completed questionnaires and underwent collection of nasal samples for gene expression studies. VDKA was approved by the IRBs of all participating institutions, and the ancillary study was approved by the IRB of the University of Pittsburgh. Written parental consent was obtained for participating children, from whom written assent was also obtained. Study Design: Clinical Trial Study Type: Clinical Trial Total number of consented subjects: 66 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Vitamin-D-Kids Asthma","short_name":"VDKA_DS-ASTHMA","commons":"BioData Catalyst","study_url":"","_subjects_count":66,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs004052.v1.p1.c1":{"gen3_discovery":{"authz":"/programs/Individual_Study/projects/STAR_DS-ASTHMA","tags":[],"_unique_id":"phs004052.v1.p1.c1","study_id":"phs004052.v1.p1.c1","study_description":"The Stress and Treatment Response in Puerto Rican and African American Children with Asthma Study (STAR) was a 6-week study of response to inhaled corticosteroids (ICS) in youth aged 8-20 years recruited at the University of Puerto Rico Medical Center and UPMC Children's Hospital of Pittsburgh from June 5, 2018 to May 16, 2022. At a baseline visit, participants completed questionnaires and underwent collection of nasal specimens. After nasal sampling, participants were treated with daily medium-dose inhaled Mometasone for 6 weeks, with adherence measured using a dose-counter. Spirometry and fractional exhaled nitric oxide (FeNO) measurements were conducted at baseline and after 6 weeks of ICS. STAR was approved by the institutional review boards (IRBs) of the University of Puerto Rico and the University of Pittsburgh. Written parental consent and assent were obtained from participants < 18 years old, and written consent was obtained from participants ≥ 18 years old. Study Design: Case Set Study Type: Case Set RNA Sequencing Total number of consented subjects: 156 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Stress and Treatment Response in Puerto Rican and African American Children with Asthma (STAR)","short_name":"STAR_DS-ASTHMA","commons":"BioData Catalyst","study_url":"","_subjects_count":156,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs004055.v1.p1.c1":{"gen3_discovery":{"authz":"/programs/BioLINCC/projects/BL_CONCERT_HF_GRU","tags":[],"_unique_id":"phs004055.v1.p1.c1","study_id":"phs004055.v1.p1.c1","study_description":"Data Access Note: Please refer to the “Authorized Access” section below for information about how access to the data from this accession differs from many other dbGaP accessions. ObjectivesTo assess the feasibility, safety, and efficacy of autologous mesenchymal stromal cells (MSCs) and c-kit positive cardiac cells (CPCs), alone or in combination, in participants with ischemic heart failure.Background The prognosis of heart failure (HF) caused by chronic ischemic cardiomyopathy (coronary artery disease and prior myocardial infarction), hereby referred to as “ischemic HF”, remains poor. Many studies have explored the use of various types of stem or progenitor cells in participants with chronic ischemic HF, with encouraging results. Several clinical trials have suggested that MSCs and CPCs are both safe and beneficial in participants with ischemic HF. At the time of this study, no information was available on the efficacy of MSCs and CPCs in humans, however, both cell types have been shown to attenuate left ventricle (LV) dysfunction in animal models. Preclinical models indicate that combining MSCs and CPCs increases the therapeutic effects, but this had not yet been tested in humans. The CONCERT-HF study was initiated to assess whether autologous MSCs and CPCs, alone or in combination, can be manufactured and delivered to participants with ischemic HF; are well-tolerated; and improve LV function, quality of life, and functional capacity, and/or reduce scar size. Participants A total of 125 participants were randomized with 33 participants randomized to the MSCs and CPCs group, 29 participants to the MSCs alone group, 31 participants to the CPCs alone group, and 32 participants to the placebo group. Design The CONCERT-HF study was a multi-center Phase II, double-blind, randomized, placebo-controlled trial designed to evaluate the feasibility, safety, and efficacy of MSCs alone, CPCs alone, and their combination compared with placebo as well as each other in patients with ischemic HF. In Stage 1 (open label, lead-in study) participants were randomized 1:1 to either a standard-of-care control group (i.e., they did not undergo harvest, mapping, or injection procedures) or combination therapy (MSCs + CPCs, as described for Stage 2) to complete safety assessments. Once approval was granted for Stage 2, participants were randomized (1:1:1:1) to one of four treatments: placebo, autologous MSCs (target dose, 150 × 106 cells), autologous CPCs (target dose, 5 × 106 cells), or a combination of autologous MSCs and CPCs. At the harvest visit, right ventricular endocardial biopsy (EMB) was performed in participants randomized to receive CPCs alone or a combination of MSCs and CPCs. Participants randomized to receive MSCs alone or placebo had a sham procedure (right heart catheterization without EMB). All participants underwent a bone marrow aspiration and approximately 14 weeks later had transendocardial, electromechanically-guided injections of study product. Visits occurred at 1 day, 1 week, and 1, 3, 6, and 12 months after study product injection. A telephone contact took place at 24 months to assess the participant's current medications, as well as morbidity and mortality. Study endpoints included measures of safety, feasibility, and efficacy. Safety outcomes included all adverse events grade 2 and higher, including major adverse cardiac events (MACE) related to HF (death, hospitalization for worsening HF, and HF exacerbation not requiring hospitalization). Efficacy endpoints included quality of life, MRI measures of LV function and structure, functional capacity, and N-terminal pro-brain natriuretic peptide (NT-proBNP) levels. Conclusions In patients with ischemic HF, autologous MSCs and CPCs, alone or in combination, are safe and feasible; CPCs were associated with a reduction in the incidence of MACE related to HF compared to placebo; MSCs, either alone or in combination with CPCs, were associated with improved quality of life; these seemingly beneficial effects of CPCs and MSCs on clinical outcome were not associated with changes in LV function or structure; and combination therapy with MSCs and CPCs was associated with the best clinical outcomes with respect to both MACE related to HF and quality of life. Study Weblinks: BioLINCC Repository Study Design: Clinical Trial Study Type: Placebo-Controlled Randomized Total number of consented subjects: 125 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Cardiovascular Cell Therapy Research Network (CCTRN): A Phase II, RCT of Mesenchymal Stem Cells & Cardiac Stem Cells in Subjects With Ischemic HF (CONCERT HF-BioLINCC)","short_name":"BL_CONCERT_HF_GRU","commons":"BioData Catalyst","study_url":"","_subjects_count":125,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs004067.v1.p1.c1":{"gen3_discovery":{"authz":"/programs/BioLINCC/projects/BL_EPIC_GRU","tags":[],"_unique_id":"phs004067.v1.p1.c1","study_id":"phs004067.v1.p1.c1","study_description":"Data Access NOTE: Please refer to the “Authorized Access” section below for information about how access to the data from this accession differs from many other dbGaP accessions. Objectives: To investigate the efficacy and safety of 4 antipseudomonal treatments in children with cystic fibrosis (CF) with recently acquired Pseudomonas aeruginosa (PA) infection.Background: CF is an inherited disease that causes mucus to build up in the lungs and digestive tract, which can cause lung infections and digestive problems. It is the most common type of chronic lung disease in children and young adults and may result in early death. There is no cure for this disease. The primary cause of death in individuals with CF is progressive obstructive pulmonary disease associated with chronic Pseudomonas aeruginosa (PA) infection. PA infection can occur early in life and can become highly resistant to antibiotics. Once an individual has been diagnosed with chronic PA infection, it is almost impossible to manage effectively. The need exists for an effective treatment to control and eliminate PA infection. Past research has shown that if PA infection is treated early, there is a greater likelihood that it may be eliminated completely.Participants: There were 304 participants.Design: Participants were randomized to 1 of 4 antibiotic regimens for 18 months (six 12-week quarters) between December 2004 and June 2009. Participants randomized to cycled therapy received tobramycin inhalation solution (300 mg twice a day) for 28 days, with oral ciprofloxacin (15-20 mg/kg twice a day) or oral placebo for 14 days every quarter, while participants randomized to culture-based therapy received the same treatments only during quarters with positive P aeruginosa cultures. The primary end points were time to pulmonary exacerbation requiring intravenous antibiotics and proportion of PA - positive cultures.Conclusions: No difference in the rate of exacerbation or prevalence of PA positivity was detected between cycled and culture-based therapies. Adding ciprofloxacin produced no benefits (Arch Pediatr Adolesc Med 2011; 165(9):847-856). Study Weblinks: BioLINCC Repository Study Design: Clinical Trial Study Type: Interventional Total number of consented subjects: 304 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Effectiveness and Safety of Intermittent Antimicrobial Therapy for the Treatment of New Onset Pseudomonas Aeruginosa Airway Infection in Young Patients With Cystic Fibrosis (EPIC-BioLINCC)","short_name":"BL_EPIC_GRU","commons":"BioData Catalyst","study_url":"","_subjects_count":304,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs004070.v1.p1.c1":{"gen3_discovery":{"authz":"/programs/BioLINCC/projects/BL_ACE_IPF_GRU","tags":[],"_unique_id":"phs004070.v1.p1.c1","study_id":"phs004070.v1.p1.c1","study_description":"Data Access NOTE: Please refer to the \"Authorized Access\" section below for information about how access to the data from this accession differs from many other dbGaP accessions. Objectives: The ACE-IPF trial tested the hypothesis that treatment with warfarin at recognized therapeutic doses would reduce rates of mortality, hospitalization, and declines in Forced Vital Capacity (FVC) in subjects with Idiopathic pulmonary fibrosis (IPF).Background: IPF is a chronic, progressive lung disease of unknown cause characterized by the histopathologic pattern of usual interstitial pneumonia. The median survival of patients with IPF after the onset of symptoms is 2 to 5 years. Prior animal and human studies in pulmonary fibrosis provide a compelling rationale to examine anticoagulation as a therapeutic approach in IPF. Large epidemiologic studies link IPF with thrombosis-related clinical events, such as an increased risk of acute coronary syndrome and deep vein thrombosis. The suspected causal relationship may extend beyond simple coagulation cascade-induced thrombus formation, as procoagulant enzymes may directly stimulate fibrosis via cell surface receptor - mediated responses.Participants: Patients aged 35 to 80 years with progressive IPF were potentially eligible. Progressive IPF was defined as a history of (1) worsening of dyspnea, or (2) physiologic deterioration defined as an absolute decline of either FVC greater than or equal to 10% or DlCO greater than or equal to 15%, a reduction in arterial oxygen saturation of greater than or equal to 5%, or progression of radiographic findings. Between December 14, 2009 and April 1, 2011, 145 subjects were enrolled: 72 in the warfarin group and 73 in the placebo group. The mean age for the population was 67 years. 27% of the subjects were women and 92% were white.Participants were excluded if they met any of the following criteria: current indication for, or treatment with, warfarin, prasugrel, or clopidogrel combined with aspirin; the presence of an increased risk of bleeding; a recent cerebral vascular accident or gastrointestinal bleeding; any current signs or symptoms of severe, progressive, or uncontrolled comorbid illness; and their presence on the active list for lung transplantation. Design: ACE-IPF was a double-blind, randomized, placebo-controlled trial of warfarin targeting an international normalized ratio (INR) of 2.0 to 3.0 in patients with IPF. Subjects were randomized in a 1:1 ratio to warfarin or matching placebo for a planned treatment period of 48 weeks. Study subjects were provided two strengths of warfarin tablets (1 mg and 2.5 mg) or matching placebos. Subjects measured their INR with encrypted meters at least weekly. Participants were seen at screening, baseline, and at 16, 32, and 48 weeks after enrollment. Home monitoring was validated by plasma INR measurement at the week 1 and 16 visits.The primary outcome was a composite endpoint based on the time to all-cause mortality; nonelective, nonbleeding hospitalization; or a decrease in the absolute FVC greater than or equal to 10% from baseline value. Secondary outcome measures included rates of mortality, hospitalization, respiratory-related hospitalization, acute exacerbation, bleeding, cardiovascular events, and changes over time in FVC, 6-minute walk test distance, DlCO, plasma fibrin D-dimer levels, and quality of life (QOL).Conclusions: The study did not show a benefit for warfarin in the treatment of patients with progressive IPF and was terminated due to excess mortality in the warfarin treatment group. Treatment with warfarin was associated with an increased risk of mortality in an IPF population who lacked other indications for anticoagulation.Reported causes of death indicated 11 of the 14 were respiratory-related in the warfarin group versus three of the three in the placebo group. There were also three cardiovascular deaths in the warfarin group versus none in the placebo group. No deaths were attributed to bleeding. The warfarin group also demonstrated an increased rate of combined all-cause hospitalization and all-cause mortality. (Am J Respir Crit Care Med. 2012 Jul 1;186(1):88-95.) Study Weblinks: IPFNet-ACE-IPF-BioLINCC Study Design: Clinical Trial Study Type: Interventional Total number of consented subjects: 145 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Idiopathic Pulmonary Fibrosis Network AntiCoagulant Effectiveness in Idiopathic Pulmonary Fibrosis (IPFNet-ACE-IPF-BioLINCC)","short_name":"BL_ACE_IPF_GRU","commons":"BioData Catalyst","study_url":"","_subjects_count":145,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs004071.v1.p1.c1":{"gen3_discovery":{"authz":"/programs/BioLINCC/projects/BL_Panther_IPF_GRU","tags":[],"_unique_id":"phs004071.v1.p1.c1","study_id":"phs004071.v1.p1.c1","study_description":"Data Access NOTE: Please refer to the \"Authorized Access\" section below for information about how access to the data from this accession differs from many other dbGaP accessions.Objectives: The initial objective of the PANTHER-IPF study was to evaluate the effectiveness of a drug combination of prednisone, azathioprine, and N-acetylcysteine in the treatment of mild-to-moderate idiopathic pulmonary fibrosis (IPF) compared to N-acetylcysteine alone or placebo. After interim analysis presented safety concerns regarding the three drug regimen, the protocol was modified to evaluate only N-acetylcysteine effectiveness. Background: IPF is a chronic, progressive lung disease of unknown cause that is characterized by the histopathological or radiologic patterns of usual interstitial pneumonia in a typical clinical setting. The median survival of participants with idiopathic pulmonary fibrosis after diagnosis is 2 to 5 years. To date, no pharmacologic therapies have been shown to improve survival. Acetylcysteine has been suggested as a beneficial treatment for idiopathic pulmonary fibrosis, although data from placebo-controlled studies are lacking.Design: Patients with mild-to-moderate impairment in pulmonary function were randomly assigned to receive a three-drug regimen (prednisone, azathioprine, and acetylcysteine), acetylcysteine alone (plus matched placebos for prednisone and azathioprine), or matched placebos for each of the active therapies. After the planned midpoint interim analysis, the data and safety monitoring board recommended discontinuation of the three-drug regimen because of an excess in the number of deaths, hospitalizations, and serious adverse events among patients in the combination-therapy group, as compared with the placebo group. After NHLBI accepted this recommendation on October 14, 2011, the three-drug regimen was discontinued and patients were recruited for only the acetylcysteine group and the placebo group. Patients were seen at the clinical centers for screening, at baseline, and at 4, 15, 30, 45, and 60 weeks. The primary outcome measure was change in FVC over 60 weeks.Conclusions: As compared with placebo, acetylcysteine offered no significant benefit with respect to the preservation of FVC in patients with idiopathic pulmonary fibrosis with mild-to-moderate impairment in lung function. In addition, there were no significant differences between the acetylcysteine group and the placebo group in the rates of death or acute exacerbation. Study Weblinks: IPFNet-Panther-IPF-BioLINCC Study Design: Clinical Trial Study Type: Clinical Trial Total number of consented subjects: 264 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Idiopathic Pulmonary Fibrosis Network (IPFnet) Prednisone, Azathioprine, and N-Acetylcysteine: A Study That Evaluates Response in Idiopathic Pulmonary Fibrosis (IPFNet-Panther-IPF-BioLINCC)","short_name":"BL_Panther_IPF_GRU","commons":"BioData Catalyst","study_url":"","_subjects_count":264,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs004077.v1.p1.c1":{"gen3_discovery":{"authz":"/programs/BioLINCC/projects/BL_NETT_GRU","tags":[],"_unique_id":"phs004077.v1.p1.c1","study_id":"phs004077.v1.p1.c1","study_description":"Data Access NOTE: Please refer to the “Authorized Access” section below for information about how access to the data from this accession differs from many other dbGaP accessions. Available Data: The current release of the NETT study dataset includes follow-up data through May of 2013.Objectives: To compare lung-volume-reduction surgery with medical therapy for severe emphysema, and to identify participant selection criteria for lung volume reduction surgery.Background: Lung-volume-reduction surgery has been proposed as a palliative treatment for severe emphysema. Effects on mortality, the magnitude and durability of benefits, and criteria for the selection of participants have not been established.Participants: A total of 1,218 participants with severe emphysema underwent pulmonary rehabilitation and were randomly assigned at 17 centers to undergo lung-volume-reduction surgery (bilateral stapled wedge resection) or to receive continued medical treatment. Participants were randomized after a 6-10 week pulmonary rehabilitation period and participants with a forced expiratory volume in one second (FEV1) that was 20 percent or less of predicted and a homogeneous distribution of emphysema or carbon monoxide diffusing capacity 20 percent or less of predicted were not eligible for randomization due to poor post-surgery prognosis for death or functional improvement.Conclusions: Overall, lung-volume-reduction surgery increases the chance of improved exercise capacity but does not confer a survival advantage over medical therapy. It does yield a survival advantage for participants with both predominantly upper-lobe emphysema and low base-line exercise capacity. Participants previously reported to be at high risk and those with non-upper-lobe emphysema and high base-line exercise capacity are poor candidates for lung-volume-reduction surgery, because of increased mortality and negligible functional gain. (NEJM 2003;348:2059-2073). Study Weblinks: BioLINCC Repository Study Design: Clinical Trial Study Type: Interventional Total number of consented subjects: 3775 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"National Emphysema Treatment Trial (NETT-BioLINCC)","short_name":"BL_NETT_GRU","commons":"BioData Catalyst","study_url":"","_subjects_count":3775,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs004080.v1.p1.c1":{"gen3_discovery":{"authz":"/programs/BioLINCC/projects/BL_PETAL_CLOVERS_HMB-MDS","tags":[],"_unique_id":"phs004080.v1.p1.c1","study_id":"phs004080.v1.p1.c1","study_description":"Data Access NOTE: Please refer to the \"Authorized Access\" section below for information about how access to the data from this accession differs from many other dbGaP accessions. Access to Biospecimens is through the NHLBI Biologic Specimen and Data Repository Information Coordinating Center (BioLINCC). Biospecimens from PETAL CLOVERS include plasma, and whole blood. Please note that use of biospecimens in genetic research is subject to a tiered consent. Available Data: The data available for request now include Long Term Outcome data.Objectives: To compare the effects of a restrictive fluid strategy (with early use of vasopressors) to a liberal fluid strategy in participants with sepsis-induced hypotension.Background: Intravenous fluid resuscitation is a common therapy used in the initial treatment of participants with septic shock and sepsis-induced hypotension. The goal of initial fluid therapy is to increase depleted or functionally reduced intravascular volume that occurs in sepsis due to a vasodilated vascular network. However, intravenous fluid resuscitation can create dilutional coagulopathy, fluid overload, and pathogenic edema in the lungs and other organs. Vasopressor agents are also commonly used to treat hypoperfusion by inducing constriction of arterioles and venules and increasing cardiac contractility. Vasopressor therapy also comes with risks that include vasoconstriction resulting in tissue ischemia, increased cardiac workload, and arrhythmias. Clinicians have used these strategies, typically in combination, to provide supportive care for participants with sepsis-induced hypoperfusion. However, at the time of the CLOVERS study, there was limited data to guide specific use of these therapies, including fluid volumes, in the early care of participants with sepsis-induced hypotension. The CLOVERS study hypothesized that a restrictive fluid strategy used during the first 24-hours of resuscitation for sepsis-induced hypotension would lead to lower mortality before discharge home by day 90 than a liberal fluid strategy.Participants: A total of 1,563 participants, from 60 medical centers, of the planned 2,230 participants were enrolled, with 782 assigned to the restrictive fluid group and 781 to the liberal fluid group. Enrollment in the trial was ended after the second interim analysis due to a lack of significant difference observed between the two 24-hour strategies.Design: This study was a multi-center, prospective, phase 3 randomized non-blinded interventional trial of fluid treatment strategies in the first 24 hours for participants with sepsis-induced hypotension. Participants were randomly assigned in a 1:1 ratio to either a restrictive fluid strategy (with early vasopressor use) or a liberal fluid strategy. In each group, the assigned protocol was followed for a period of 24 hours. The restrictive fluid protocol prioritized vasopressors as the primary treatment for sepsis-induced hypotension, with 'rescue fluids' being permitted for prespecified indications that suggested severe intravascular volume depletion. The liberal fluid protocol consisted of a recommended initial 2000-ml intravenous infusion of isotonic crystalloid, followed by fluid boluses administered on the basis of clinical triggers (e.g., tachycardia) with 'rescue vasopressors' permitted for prespecified indications. A protocol amendment implemented in October, 2019, allowed for limiting the initial infusion to 1,000 ml if the participant's blood pressure and heart rate had stabilized and the clinical assessment was that the participant was unlikely to benefit from additional intravenous fluid administration. The clinical team could override the protocol-specified care instructions at any time if it was judged to be in the best interest of the participant.The primary outcome was death from any cause before discharge home by day 90. Secondary outcomes included 28-day measures of the number of days free from ventilator use, days free from renal-replacement therapy, days free from vasopressor use, days out of the ICU, and days out of the hospital. Conclusions: Among participants with sepsis-induced hypotension, the restrictive fluid strategy that was used in this trial did not result in significantly lower (or higher) mortality, or other measures of recovery such as length of hospital stay, before discharge home by day 90 than the liberal fluid strategy. Study Weblinks: BioLINCC Repository Study Design: Clinical Trial Study Type: Interventional Phase III Prospective Randomized Total number of consented subjects: 1563 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Prevention and Early Treatment of Acute Lung Injury (PETAL) Crystalloid Liberal or Vasopressors Early Resuscitation in Sepsis (CLOVERS) (PETAL CLOVERS-BioLINCC)","short_name":"BL_PETAL_CLOVERS_HMB-MDS","commons":"BioData Catalyst","study_url":"","_subjects_count":1563,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs004085.v1.p1.c1":{"gen3_discovery":{"authz":"/programs/BioLINCC/projects/BL_STEP_IPF_GRU","tags":[],"_unique_id":"phs004085.v1.p1.c1","study_id":"phs004085.v1.p1.c1","study_description":"Data Access NOTE: Please refer to the \"Authorized Access\" section below for information about how access to the data from this accession differs from many other dbGaP accessions. Objectives: The STEP-IPF study sought to evaluate whether treatment with sildenafil would improve walk distance, dyspnea, and quality of life in participants with advanced idiopathic pulmonary fibrosis (IPF).Background: IPF is a chronic, progressive lung disease of unknown cause that is characterized by the histopathologic pattern of usual interstitial pneumonia. Progression to end-stage respiratory insufficiency and death within 5 years after the onset of symptoms is characteristic. To date, no pharmacologic therapies have definitively been shown to improve survival or quality of life in participants with this disease.Participants with severe IPF have abnormalities of the pulmonary vasculature leading to decreased levels of resting and exercise-induced production of nitric oxide. Since nitric oxide is a potent pulmonary vasodilator, reduced levels are associated with pulmonary vasoconstriction and impaired gas exchange. Sildenafil (Revatio, Pfizer) is a phosphodiesterase-5 inhibitor that stabilizes the second messenger of nitric oxide, cyclic guanosine monophosphate, which leads to pulmonary vasodilatation. Such vasodilatation could improve ventilation–perfusion matching and thus gas exchange in with IPF.Design: STEP-IPF was a double-blind, randomized, placebo-controlled trial of oral sildenafil (20 mg three times daily). Participants meeting eligibility criteria were randomly assigned in a 1:1 ratio to receive sildenafil or matched placebo with the use of a permuted-block design, with stratification according to clinical center. The primary outcome was the presence or absence of an improvement of at least 20% in the 6-minute walk distance at 12 weeks, as compared with baseline. Key secondary outcomes included changes in the 6-minute walk distance, degree of dyspnea, and quality of life.Screening procedures included the taking of a detailed history, a physical examination, spirometry, echocardiography, CT imaging, and measurements of lung volume on plethysmography, carbon monoxide diffusion capacity, and arterial blood gases. Eligible participants returned for an enrollment visit within 6 weeks after screening. All participants received an initial dose of a study drug at this visit and were monitored for 60 minutes for adverse effects. Follow-up visits were scheduled at 1, 6, and 12 weeks. After completion of the 12-week visit, all participants were started on treatment with open-label sildenafil. Visits were scheduled at 13, 18, and 24 weeks; at 28 weeks, serious adverse events and vital status were documented. Testing of the 6-minute walk distance was performed with the use of a standardized protocol at the time of screening and enrollment and at study visits at 6, 12, 18, and 24 weeks. Participants with pulse oxygen saturation below 88% received supplemental oxygen. Conclusions: This study did not show a benefit for sildenafil for the primary outcome. The presence of some positive secondary outcomes creates clinical equipoise for further research. There were small but significant differences in arterial oxygenation, carbon monoxide diffusion capacity, degree of dyspnea, and quality of life favoring the sildenafil group. Study Weblinks: Idiopathic Pulmonary Fibrosis Network (IPFnet) Sildenafil Trial of Exercise Performance in Idiopathic Pulmonary Fibrosis (STEP I Study Design: Clinical Trial Study Type: Clinical Trial Interventional Total number of consented subjects: 180 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Idiopathic Pulmonary Fibrosis Network (IPFNet) Sildenafil Trial of Exercise Performance in Idiopathic Pulmonary Fibrosis (IPFNet-STEP-IPF-BioLINCC)","short_name":"BL_STEP_IPF_GRU","commons":"BioData Catalyst","study_url":"","_subjects_count":180,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs004117.v1.p1.c1":{"gen3_discovery":{"authz":"/programs/BioLINCC/projects/BL_PROP_GRU","tags":[],"_unique_id":"phs004117.v1.p1.c1","study_id":"phs004117.v1.p1.c1","study_description":"Data Access NOTE: Please refer to the \"Authorized Access\" section below for information about how access to the data from this accession differs from many other dbGaP accessions. Objectives: The Prematurity and Respiratory Outcomes Program (PROP) was performed to identify suitable predictors of respiratory outcomes that may serve as surrogate endpoints in future trials of prevention and therapy of respiratory diseases in preterm infants.Background: Acute and chronic respiratory morbidities are common in premature births, and can pose significant risk to the infant's health, particularly during the first two years of life. One such condition is bronchopulmonary dysplasia (BPD) where infants require oxygen therapy due to abnormal repair and impaired lung development after acute lung injury. BPD poses a high mortality risk, even in infants that survive the initial hospitalization. Regardless of BPD diagnosis, preterm infants frequently return for medical care due to symptoms of post-prematurity respiratory disease (PRD), which includes intermittent or chronic wheezing, cough without cold, poor growth, apnea and cyanosis, and lower respiratory tract infections. Impaired lung function can persist into adulthood, contributing to chronic respiratory diseases including asthma and emphysema.However, at the time of the PROP study, there were no objective measures to predict which preterm infants would have persistent respiratory problems after discharge from the hospital. Furthermore, improved survival rates of premature infants and the high prevalence of lasting respiratory morbidities highlight the need for more comprehensive strategies to address both short-term and long-term respiratory complications. Thus, the Prematurity and Respiratory Outcomes Program (PROP) was formed to investigate multiple research hypotheses on the molecular mechanisms that contribute to respiratory disease risk of premature neonates over the first year of life. Specifically, PROP investigators hypothesized that in survivors of extreme prematurity to 36 weeks postmenstrual age (PMA), specific biologic, physiologic and clinical data obtained during the initial hospitalization will predict respiratory morbidity between discharge and 1 year corrected age. Participants: A total of 835 infants were enrolled.Design: PROP was a collaboratively developed multicenter prospective cohort study of very preterm infants from birth through the time of discharge from the NICU and up to one year corrected age.Clinical data included maternal and infant demographics, co-morbidities, and daily infant respiratory, nutritional, and medication data until discharge. These were prospectively collected from birth using medical record review and family interviews. After discharge, phone interviews were conducted with the infant's main caregiver at 3, 6, 9 and 12 months corrected age to assess domains of respiratory morbidity. At 6 and 12 months corrected age, a survey of environmental respiratory irritant exposures and an assessment for gastroesophageal reflux disease were also completed. A standardized physical exam was performed at 36-40 weeks PMA and again at one year corrected age. The exam focused on anthropometrics, vital signs, and respiratory system signs. At 34-41 weeks PMA and within one week of anticipated discharge based on physiologic stability, a set of non-invasive respiratory assessments were performed to assess physiologic biomarkers in infants that were not mechanically ventilated or receiving non-invasive positive pressure ventilation. Respiratory inductance plethysmography (RIP) was performed before and after inhaled albuterol to assess potential airway reactivity. During the RIP study, continuous pulse oximetry was performed during quiet sleep in order to analyze oxygen desaturations and apneas. Standardized oxygen requirement challenge tests were performed at about 36 weeks PMA, and at about 40 weeks PMA if the infant was still hospitalized and was not eligible for, or failed, the previous challenge. Failure was defined as SpO2 < 90% for 5 continuous minutes, SpO2 < 80% for 15 seconds, or apnea for >20 seconds at any point in the testing. Infants breathing ambient air or that passed the 36 week challenge test underwent a hypoxia challenge consisting of a 15-minute trial of FiO2 of 0.15. Failure was defined as SpO2 < 85% for 60 consecutive seconds, SpO2 < 80% for 15 seconds, bradycardia, or persistent apnea. Infant pulmonary function testing (iPFT) was also performed on a subset of infants at one year corrected age to evaluate lung growth and respiratory dysfunction. The primary outcome was respiratory morbidity, as measured by the presence or absence of substantial post-prematurity respiratory disease (PRD) up to one year corrected age. PRD was classified as a positive response in at least one of four morbidity domains during at least two separate parental interviews. The domains were respiratory medications, hospitalizations for cardiopulmonary cause, respiratory symptoms, and home technology dependence (oxygen, ventilator, or CPAP/BiPAP). Mortality from a respiratory cause was also incorporated. Study Weblinks: BioLINCC Repository Study Design: Clinical Trial Study Type: Cohort Observational Prospective Total number of consented subjects: 835 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Prematurity and Respiratory Outcomes Program (PROP) Core Database Protocol (PROP-BioLINCC)","short_name":"BL_PROP_GRU","commons":"BioData Catalyst","study_url":"","_subjects_count":835,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs004130.v1.p1.c1":{"gen3_discovery":{"authz":"/programs/BioLINCC/projects/BL_FIRE_CORAL_HMB-MDS","tags":[],"_unique_id":"phs004130.v1.p1.c1","study_id":"phs004130.v1.p1.c1","study_description":"Data Access NOTE: Please refer to the “Authorized Access” section below for information about how access to the data from this accession differs from many other dbGaP accessions.Biospecimens: Access to Biospecimens is through the NHLBI Biologic Specimen and Data Repository Information Coordinating Center (BioLINCC). Biospecimens from PETAL FIRE CORAL include plasma and whole blood. Please note that use of biospecimens in genetic research is subject to a tiered consent and biospecimens may not be used to produce commercial products.Objectives: To examine the recovery from COVID-19 disease following acute hospitalization with an emphasis on functional, imaging, and respiratory evaluation, and assess the feasibility of conducting a larger study to evaluate variables associated with differential recovery.Background: The BLUE CORAL study, dbGaP phs003419, was intended to address the knowledge gaps and provide critical data to help guide clinical care, public health, and scientific efforts regarding SARS-CoV-2 (COVID-19) recovery. The understanding and treatment of long-term sequelae of COVID-19, referred to variously as post-acute sequelae of COVID-19 (PASC), post-acute COVID, long COVID, or long-haul COVID, is fundamental to patient recovery. These long-term consequences are common and increasingly recognized, although heterogeneous in manifestation, and can result in a failure to return to baseline level of health. At the time of the FIRE CORAL study, there were limited studies that collected objective assessments following hospital discharge for a wide spectrum of patients surviving COVID-19.Participants: FIRE CORAL enrolled adult participants as a subset of those enrolled in the BLUE CORAL study with a recent COVID-19 hospitalization and that completed the 1- or 3-month post-hospital telephone long-term outcomes assessment. The target enrollment for this pilot study cohort was 80 participants.Design: FIRE CORAL was a multicenter prospective cohort study of participants recovering from COVID-19 disease with in-person follow-up, as an extension of the BLUE CORAL study. The study consisted of a battery of assessments objectively measuring pulmonary function, abnormalities on lung imaging, and functional status. Participants were to attend and perform initial in-person testing at 3 to 9 months after hospital discharge. Participants with abnormal findings on pulmonary function testing or chest imaging during their initial assessment or those with persistent respiratory symptoms were eligible to repeat study procedures 3 months later with a subsequent visit at 12 months. All participants were invited to return for in-person follow up at 12 months after hospital discharge. Assessments included high-resolution chest CT scan without contrast, spirometry, lung volume assessment, diffusing capacity measured by single breath measurement, Six Minute Walk Test, Short Physical Performance Battery, St. George's Respiratory Questionnaire, and Functional Assessment of Chronic Illness Therapy-Fatigue scale. Demographic and hospitalization data are available as part of the BLUE CORAL study.The primary aim of the FIRE CORAL study was to examine the feasibility of conducting rigorous in-person follow-up testing of participants discharged from the hospital following COVID-19 illness to assist with planning for a larger study to evaluate variables associated with differential recovery. The secondary aim was to describe the pulmonary, imaging, and functional recovery following COVID-19 hospitalization in a diverse population of patients. Study Weblinks: Prevention and Early Treatment of Acute Lung Injury (PETAL Network) Study Design: Prospective Longitudinal Cohort Study Type: Clinical Cohort Cohort Total number of consented subjects: 99 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Prevention and Early Treatment of Acute Lung Injury (PETAL) Network - Functional, Imaging, and Respiratory Evaluation in CORAL (PETAL FIRE CORAL-BioLINCC)","short_name":"BL_FIRE_CORAL_HMB-MDS","commons":"BioData Catalyst","study_url":"","_subjects_count":99,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs004165.v1.p1.c1":{"gen3_discovery":{"authz":"/programs/BioLINCC/projects/BL_ARDSNet_FACTT_HMB-MDS","tags":[],"_unique_id":"phs004165.v1.p1.c1","study_id":"phs004165.v1.p1.c1","study_description":"Data Access NOTE: Please refer to the “Authorized Access” section below for information about how access to the data from this accession differs from many other dbGaP accessions.Biospecimens: Access to Biospecimens is through the NHLBI Biologic Specimen and Data Repository Information Coordinating Center (BioLINCC). Biospecimens from ARDSNet-FACTT include plasma, DNA, and serum. Please note that use of biospecimens in genetic research is subject to a tiered consent. Objectives: This study evaluated the benefits and risks of Pulmonary Artery Catheters (PACs) in patients with established acute lung injury in a trial comparing hemodynamic management guided by a PAC with hemodynamic management guided by a central venous catheter (CVC) using an explicit management protocol.Background: Optimal fluid management in patients with acute lung injury is unknown. Diuresis or fluid restriction may improve lung function but could jeopardize extrapulmonary organ perfusion.Participants: This randomized study compared a conservative and a liberal strategy of fluid management using explicit protocols applied for seven days in 1000 patients with acute lung injury. The primary end point was death at 60 days. Secondary end points included the number of ventilator-free days and organ-failure-free days and measures of lung physiology. Design: Participants were randomly assigned to a strategy involving either conservative or liberal use of fluids with concealed allocation in permuted blocks of eight with the use of an automated system. Participants were simultaneously and randomly assigned to receive either a pulmonary-artery catheter or a central venous catheter in a two-by-two factorial design.Conclusions: There was no significant difference in the primary outcome of 60-day mortality; however, the conservative strategy of fluid management was associated with improved lung function and shortened the duration of mechanical ventilation and intensive care without increasing non-pulmonary organ failures. These results support the use of a conservative strategy of fluid management in patients with acute lung injury. (NEJM June 15, 2006; Vol 354, No. 24, pp 2564-75; NEJM May 25, 2006; Vol 354, No. 21, pp 2213-24) Study Weblinks: ARDSNet FACTT-BioLINCC Study Design: Clinical Trial Study Type: Clinical Trial Total number of consented subjects: 1000 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Acute Respiratory Distress Syndrome Clinical Network: Fluid and Catheter Treatment Trial (ARDSNet FACTT-BioLINCC)","short_name":"BL_ARDSNet_FACTT_HMB-MDS","commons":"BioData Catalyst","study_url":"","_subjects_count":1000,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs004168.v1.p1.c1":{"gen3_discovery":{"authz":"/programs/BioLINCC/projects/BL_ARDSNet_EDEN_HMB-MDS","tags":[],"_unique_id":"phs004168.v1.p1.c1","study_id":"phs004168.v1.p1.c1","study_description":"Data Access NOTE: Please refer to the “Authorized Access” section below for information about how access to the data from this accession differs from many other dbGaP accessions. Biospecimens: Access to Biospecimens is through the NHLBI Biologic Specimen and Data Repository Information Coordinating Center (BioLINCC). Biospecimens from ARDSNet-EDEN include bronchial lavage, plasma, DNA, and urine. Please note that use of biospecimens in genetic and non-genetic research is subject to a tiered consent. Objectives: To determine if initial lower-volume trophic enteral feeding would increase ventilator-free days (VFDs) and decrease gastrointestinal intolerances compared with initial full enteral feeding. Background: Mechanically ventilated patients cannot eat normally and if not fed for long periods become malnourished. Because malnutrition is associated with poor outcomes in critically ill patients, artificial nutrition is often provided, especially in those with acute lung injury (ALI) and with expected longer duration of mechanical ventilation. When feasible, enteral nutrition targeting full caloric needs has been advocated over parenteral nutrition. However, feeding intolerance and common care practices often serve as practical barriers to reaching recommended goals. Although confounded by indication and severity of illness, several observational studies have shown improved clinical outcomes, including fewer infections, shorter duration of mechanical ventilation, and lower mortality for patients receiving a higher percentage of calculated caloric needs. Nonetheless, the best timing, formulation, and amount of enteral nutrition remain unknown. Participants: A total of 1,000 participants were enrolled. Design: Participants were randomized, stratified by site and presence of shock at enrollment, to receive either trophic or full enteral feeding for the first 6 days of mechanical ventilation. The initial 272 patients were also simultaneously randomized to a separate trial (the OMEGA study) comparing a nutritional supplement containing omega-3 fatty acids and antioxidants with an isocaloric, isovolemic control in a 2 × 2 factorial design.The designated feeding strategy was initiated within 6 hours of randomization and continued until death, extubation, or day 6. The care of mechanically ventilated patients still receiving enteral feedings after day 6 was managed according to the full feeding strategy in both groups. In extubated patients who then required reintubation, enteral nutrition was restarted and managed according to the study protocol.In the full-feeding group, enteral nutrition was initiated at 25 mL/h and advanced to goal rates as quickly as possible. Gastric residual volumes were checked every 6 hours while enteral feeding was increased. Patients randomized to the initial trophic-feeding group had enteral nutrition initiated at 10 mL/h (10-20 kcal/h) for the first 272 patients who also received the omega-3 or control supplement (240 mL volume per day). After the data and safety monitoring board stopped the OMEGA portion of the factorial design, the initial trophic feeding rate was changed to 20 kcal/h to approximate the calories that had been delivered in the OMEGA study. Gastric Residual Volumes (GRVs) were checked every 12 hours during trophic feeding. In patients randomized to trophic feeding, enteral nutrition was advanced to full-energy feeding rates following the same protocol used for the full-feeding group if they were still receiving mechanical ventilation at 144 hours. Conclusions: There was no difference between groups with regard to the primary end point, VFDs to day 28. There also were no differences in 60-day mortality, organ failure−free days, ICU-free days, or the incidence of infection between groups. Similarly, there were no differences between groups in VFDs or survival when analyzed by body mass index category or when subsets of patients with shock or more severe lung injury (acute respiratory distress syndrome) were examined.JAMA. 2012 Feb 22;307(8):795-803 Study Weblinks: ARDSNet EDEN-BioLINCC Study Design: Clinical Trial Study Type: Clinical Trial Total number of consented subjects: 1000 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Acute Respiratory Distress Network Early Versus Delayed Enteral Feeding to Treat People with Acute Lung Injury or Acute Respiratory Distress Syndrome (ARDSNet EDEN-BioLINCC)","short_name":"BL_ARDSNet_EDEN_HMB-MDS","commons":"BioData Catalyst","study_url":"","_subjects_count":1000,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs004171.v1.p1.c1":{"gen3_discovery":{"authz":"/programs/BioLINCC/projects/BL_HFN_LIFE_GRU","tags":[],"_unique_id":"phs004171.v1.p1.c1","study_id":"phs004171.v1.p1.c1","study_description":"Data Access NOTE: Please refer to the \"Authorized Access\" section below for information about how access to the data from this accession differs from many other dbGaP accessions.Objectives: To compare treatment with sacubitril/valsartan versus valsartan alone in patients with advanced heart failure with a reduced ejection fraction and recent New York Heart Association class IV symptoms.Background: Treatment with evidence-based medical therapies improves survival, reduces heart failure hospitalizations, and improves quality of life in patients with chronic heart failure with a reduced ejection fraction. However, evidence supporting the use of medical therapies among patients with advanced heart failure is limited. Patients with New York Heart Association (NYHA) class IV heart failure are not often enrolled in clinical trials.A previous trial reported that, compared with the angiotensin-converting enzyme inhibitor enalapril, sacubitril/valsartan, an angiotensin receptor-neprilysin inhibitor, reduced the relative risk of cardiovascular mortality and heart failure hospitalizations by 20% in ambulatory patients with heart failure with a reduced ejection fraction. Although patients with NYHA class IV heart failure were eligible to enroll, this population was underrepresented. The HFN-LIFE trial was initiated to provide additional information about the tolerability, safety, and potential efficacy of sacubitril/valsartan in patients with advanced heart failure.Participants: Of the eligible patients that enrolled, a total of 335 patients tolerated the run-in phase and were randomized to a treatment group. 167 patients were randomly assigned to receive sacubitril/valsartan and 168 patients were randomly assigned to receive valsartan alone.Design: The HFN-LIFE trial was a prospective, multicenter, randomized, double-blind phase 4 clinical trial. Trial enrollment was suspended early, due to the high risk for adverse outcomes associated with COVID-19 infection.Eligible patients were enrolled and began an unblinded run-in period of 3 to 7 days with sacubitril/valsartan, 24/26 mg (50-mg fixed dose), administered orally twice daily. Participants tolerating the run-in phase were randomized in a 1:1 fashion to receive sacubitril/valsartan (target dose, 200 mg twice daily) or valsartan (target dose, 160 mg twice daily). The initial doses were selected based on guidelines with dose adjustments being made every 2 weeks.The primary efficacy outcome was the area under the curve of NT-proBNP levels at 2, 4, 8, 12, and 24 weeks compared with the level of NT-proBNP at randomization. The secondary efficacy end point was the number of days the patient was alive, out of the hospital, and free from any of the following outcomes: listing for cardiac transplant, cardiac transplant, implantation of a left ventricular assist device, receipt of continuous inotropic therapy for 7 or more days, or hospitalization for heart failure on 2 or more occasions other than the index admission.Conclusions: In patients with chronic advanced heart failure with a reduced ejection fraction, there was no statistically significant difference between sacubitril/valsartan and valsartan alone with respect to reducing NT-proBNP levels. Study Weblinks: HFN LIFE-BioLINCC Study Design: Clinical Trial Study Type: Clinical Trial Total number of consented subjects: 365 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Heart Failure Network: Entresto(TM) in Advanced Heart Failure (HFN-LIFE-BioLINCC)","short_name":"BL_HFN_LIFE_GRU","commons":"BioData Catalyst","study_url":"","_subjects_count":365,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs004173.v1.p1.c1":{"gen3_discovery":{"authz":"/programs/BioLINCC/projects/BL_BHS_HMB-MDS","tags":[],"_unique_id":"phs004173.v1.p1.c1","study_id":"phs004173.v1.p1.c1","study_description":"Objectives: To investigate the early natural history of cardiovascular disease in a cohort of children and young adults in a biracial, semirural community.Background: The Bogalusa Heart Study has been a long-term epidemiologic study. The investigators have identified and followed black and white participants for nearly 40 years, and have described the incidence and prevalence of biologic and behavioral cardiovascular disease risk factors from childhood through adulthood. Their participation has enabled the study to not only document differences between males and females, but also between blacks and whites. The results from the Bogalusa Heart Study have clearly documented that the genesis of atherosclerosis has its basis in childhood, and that prevention can and must begin at the early ages.The Bogalusa Heart Study had been funded over the years by the Specialized Centers of Research (SCOR) Program. The SCOR program was initiated by NHLBI in 1970 to expedite the development and application of new knowledge essential for improved diagnosis, treatment, and prevention of arteriosclerosis, hypertension, pulmonary disease, and thrombosis. In 1984 a Demonstration and Education Component was added to the parent SCOR of the Bogalusa Heart Study in order to translate the experience gained in epidemiological studies into an intervention study designed to retard the development of cardiovascular risk factors in children. Beginning in 1997, the study was supported by the cooperative agreement mechanism. Participants: The Bogalusa dataset includes 11,796 participants that attended at least one of seven cross-sectional pediatric exams and/or the 1995-96 adult examination. Subjects ranged in age from 3 to 20 years at the pediatric exams and 20-37 at the time of the adult exam. Approximately 6,000 have more than one examination constituting a dynamic cohort. Design: The initial survey in 1973-1974 was restricted to children ages 2 1/2 to 14. A physical examination was conducted and information was collected on anthropometric data, hemoglobin, blood pressure, serum lipids, and health history. Over 3,500 children participated. The second cross-sectional survey of 1976-1977 and subsequent surveys expanded the eligible population to include all children ages 5-17 years. The second survey of over 4,000 children also included information on salt intake, smoking, health beliefs, and attitudes, and for girls ages 8-17, menstrual history and oral contraceptive use. The third survey of over 3,500 participants in 1978-1979 also collected anthropometric measurements on skinfold thickness and two measurements of heart rate. The fourth survey of over 3,300 participants in 1981-1982 added data on alcohol use, Type A behavior, peer networks and dieting habits.The Bogalusa Heart Study continued to use a cross-sectional and longitudinal design with the general cross-sectional survey of approximately 3,700 Bogalusa children ages five to seventeen in 1988-1989 in the sixth screen and additional longitudinal studies to recall children in defined subgroups for more intensive evaluation. Half of the 12,000 participants screened since 1973 had been studied three or more times. The Post High School Study examined young adults ages 21 through 30 who previously were examined as children ages five through fourteen in the first Bogalusa Heart Study screening in 1973-1974. The population included approximately 4,603 young adults originally screened and any other children or adolescents examined for the first time in any subsequent surveys. The cardiovascular phenotypes include obesity, blood pressure, lipids, lipoproteins, apoproteins, homocysteine, glucose-insulin, fibrinogen, plasminogen activator inhibitor-1 and von Willebrand Factor. Environmental risk factors consist of sociodemographic characteristics, tobacco and alcohol use, oral contraception, physical activity, cognitive and physical function, and quality of sleep and diet. Subclinical morbidity includes echo-Doppler measurements of cardiac-carotid structure and function. Study Weblinks: Bogalusa Heart Study (BHS-BioLINCC) Study Design: Prospective Longitudinal Cohort Study Type: Cross-Sectional Longitudinal Cohort Total number of consented subjects: 11816 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Bogalusa Heart Study (BHS-BioLINCC)","short_name":"BL_BHS_HMB-MDS","commons":"BioData Catalyst","study_url":"","_subjects_count":11816,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs004174.v1.p1.c1":{"gen3_discovery":{"authz":"/programs/BioLINCC/projects/BL_WHI_LILAC_GRU","tags":[],"_unique_id":"phs004174.v1.p1.c1","study_id":"phs004174.v1.p1.c1","study_description":"No Study Description Available","full_name":"","short_name":"BL_WHI_LILAC_GRU","commons":"BioData Catalyst","study_url":"","_subjects_count":79556,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs004183.v1.p1.c1":{"gen3_discovery":{"authz":"/programs/BioLINCC/projects/PIMI_GRU","tags":[],"_unique_id":"phs004183.v1.p1.c1","study_id":"phs004183.v1.p1.c1","study_description":"Data Access NOTE: Please refer to the \"Authorized Access\" section below for information about how access to the data from this accession differs from many other dbGaP accessions. Objectives: To investigate psychophysiological factors related to both symptomatic and asymptomatic cardiac ischemia.Background: An important hypothesis has been generated from current research in this area: manifestations and expressions of cardiac ischemia are influenced by specified psychophysiological mechanisms.Participants: The study population consisted of 196 participants recruited from four clinical units, all of which were clinical units for the Asymptomatic Cardiac Ischemia Pilot (ACIP). Participants eligible for PIMI were identified throughout the screening process established for the enrollment of participants in ACIP.Design: The primary goal of PIMI was to test the hypothesis, \"Manifestations and expressions of cardiac ischemia are influenced by specific psychophysiological mechanisms.\" The specific relationships investigated were:Patients who are susceptible to mental stress ischemia (indexed by new left ventricular wall motion abnormalities) would display more ischemia during daily activities and would have ambulatory ischemia at lower heart rate and activity level thresholds than patients who are not susceptible. Cardiovascular and catecholamine reactivity to mental stress would be a predictive of severity of mental stress ischemia and of ambulatory ischemia. Β-edorphin responses to mental stress and to exercise would be predictive of asymptomatic ischemia. Patients with systematic ischemia and those with asymptomatic ischemia would show differences in each of the following at rest and after response to stresses (exercise and/or mental tests). Mental stress would produce different hormonal and perceptual responses than exercise. Asymptomatic ischemia would be associated with a lesser severity of ischemia than symptomatic ischemia. The location of the ischemic myocardium would be inferior in a higher proportion of patients with asymptomatic ischemia than of patients with symptomatic ischemia. The latency internal that would be the onset of ST segment depression and the onset of ischemic pain would be related to somatic sensory perception, autonomic nervous system reflux control of the heart, Β-endorphin responses, and psychosocial characteristics. Study Weblinks: BioLINCC Repository Study Design: Prospective Longitudinal Cohort Study Type: Cohort Observational Total number of consented subjects: 196 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Psychophysiological Investigation of Myocardial Ischemia (PIMI-BioLINCC)","short_name":"PIMI_GRU","commons":"BioData Catalyst","study_url":"","_subjects_count":196,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs004187.v1.p1.c1":{"gen3_discovery":{"authz":"/programs/BioLINCC/projects/BL_AADR_GRU","tags":[],"_unique_id":"phs004187.v1.p1.c1","study_id":"phs004187.v1.p1.c1","study_description":"Data Access NOTE: Please refer to the “Authorized Access” section below for information about how access to the data from this accession differs from many other dbGaP accessions. Objectives: To characterize the clinical and laboratory course of patients with severe alpha 1-antitrypsin deficiency whether or not the patient is undergoing long-term augmentation therapy.Background: A hereditary disorder, patients with low serum levels of alpha-1-antitrypsin are at an increased risk for the early onset of emphysema. The only approved treatment for alpha-1-antitrypsin deficiency is augmentation therapy using a purified preparation of human alpha-1-antitryspin. Sample sizes for a randomized controlled clinical trial of augmentation therapy were determined to be infeasible; therefore, a multi-center registry was initiated in 1988 to explore the natural history of the disease and the relative efficacy of augmentation therapy in patients with a severe deficiency of alpha-1-antitrypsin.Participants: Eligible participants included individuals 18 years of age or greater for whom the Central Laboratory confirmed that the serum alpha 1-antitrypsin level is < 11 micromolar, or a ZZ genotype confirmed by DNA gene-probe analysis. Individuals with alpha 1-antitrypsin deficiency were accepted into the Registry independent of status of augmentation therapy. However, if the individual was receiving therapy, the serum alpha 1-antitrypsin phenotype and level in the absence of therapy were confirmed by the Central Laboratory. A total of 1,129 participants were enrolled from 37 clinical centers between March 1989 and October 1992. Follow-up continued through April 1996.Conclusions: Participants receiving augmentation therapy had decreased mortality risk during follow-up. FEV1 decline among all participants did not differ by augmentation therapy; however, among participants with FEV1 35-49% predicted, FEV1 decline was significantly slower for participants on augmentation therapy than for those not receiving therapy. (Am J Respir Crit Care Med, 1998; 158:49-59) Study Weblinks: BioLINCC Repository Study Design: Clinical Trial Study Type: Cohort Observational Total number of consented subjects: 1129 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Alpha1-Antitrypsin Deficiency Registry (AADR-BioLINCC)","short_name":"BL_AADR_GRU","commons":"BioData Catalyst","study_url":"","_subjects_count":1129,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs004203.v1.p1.c1":{"gen3_discovery":{"authz":"/programs/BioLINCC/projects/SCDIC_GRU","tags":[],"_unique_id":"phs004203.v1.p1.c1","study_id":"phs004203.v1.p1.c1","study_description":"Data Access NOTE: Please refer to the \"Authorized Access\" section below for information about how access to the data from this accession differs from many other dbGaP accessions.Objectives: To understand the barriers to care and other factors related to reduced healthcare utilization after the transition from pediatric to adult SCD care which may contribute to increased morbidity and mortality.Background: Fifty years ago, it was rare for individuals with SCD to live beyond childhood. Advances in care delivery and treatment have more than doubled the life expectancy of individuals with sickle cell disease (SCD) since 1972. Beginning in the 1970s, measures such as newborn screening, prophylactic administration of penicillin, and immunization against bacterial infections decreased complications and morbidity, increasing the length and quality of life of children with SCD. Blood transfusions are currently the only proven way to prevent some of the major complications of SCD, especially recurrent stroke. They are also used frequently to help manage some of the acute complications of SCD. More recently, the use of hydroxyurea (HU) as a therapeutic agent to increase fetal hemoglobin has been shown to further reduce the debilitating symptoms of and improve survival in SCD. L-glutamine and crizanlizumab are additional treatments to reduce pain crises and voxelotor is approved to lower the risk of anemia and improve blood flow. In the absence of a widely accessible cure, treatment for SCD is usually aimed at avoiding crises, relieving symptoms, and preventing complications. Many of the advances in treatment have not translated into an increase in longevity or quality of life for adolescents and adults because of disparities in access to routine primary health care.Individuals with SCD experience a markedly increased mortality beginning in the second decade of life. The third and later decades of life are frequently associated with severe chronic pain progressive organ damage and frequent hospitalizations. The provision of evidence-based and expert opinion-based care in SCD is complicated by the difficulties that many patients experience in obtaining access to the health care system and in receiving long-term care from knowledgeable providers. A registry of 2,400 people with SCD was established to provide a rich resource to study the natural history of SCD and to understand barriers to care during the transition from pediatric to adult care. Participants: 2,438 participants with a confirmed diagnosis of SCD were enrolled into the registry over an 18-month period. At the time of enrollment, all participants were 15-45 years of age, English speaking, and without a bone marrow transplant.Design: The SCDIC Registry is a longitudinal observational cohort study. At enrollment, data collection included a medical record abstraction of clinical history, the most recent lab results, and a participant survey which included several patient reported outcomes from PROMIS, ASCQ-Me and NeuroQoL. Similar surveys were administered at annual follow-up. Four to five years after enrollment, a second record abstraction was completed with all clinical events that occurred since enrollment and another set of recent labs. There were many research questions proposed to be answered with the study data thus there was no primary outcome.Conclusions: As noted previously, there were no primary outcomes determined at the start of the study. Research questions included examination of co-morbidities, healthcare utilization, and patient reported outcomes. Key findings from the Registry include:Executive dysfunction, learning difficulties, and poor comprehension significantly associated with poor activities of daily living skills. Executive dysfunction also associated with HU non-adherence. Continuing HU after conception increased odds of miscarriage or stillbirth compared to women who were not using HU. Continuing HU after conception increased odds of low birth weight in infants. Compared to adolescents, young adults had significantly more severe pain, organ dysfunction, mental health disorders, sleep problems, and barriers to medical care. Young adults were significantly less likely to see a sickle cell specialist in the past 2 years. Females had higher pain frequency and severity, more pain episodes, anxiety, depression, hospitalizations, and higher fetal hemoglobin levels. Males had more respiratory, musculoskeletal, genitourinary, and cardiovascular complications, more skin ulcers, and more use of HU. Among 128 subjects that died during the study period, iron overload, pulmonary hypertension, and depression, were significant predictors of the risk of death in multivariate analyses. Study Weblinks: SCDIC Registry BioLINCC Study Design: Case Set Study Type: Observational Total number of consented subjects: 2445 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Sickle Cell Disease Implementation Consortium Registry (SCDIC Registry-BioLINCC)","short_name":"SCDIC_GRU","commons":"BioData Catalyst","study_url":"","_subjects_count":2445,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs004254.v1.p1.c1":{"gen3_discovery":{"authz":"/programs/imaging/projects/img_HFN_NEAT_GRU","tags":[],"_unique_id":"phs004254.v1.p1.c1","study_id":"phs004254.v1.p1.c1","study_description":"Data Access NOTE: Please refer to the “Authorized Access” section below for information about how access to the data from this accession differs from many other dbGaP accessions.Objectives: To determine the effect of isosorbide mononitrate on daily activity in patients with heart failure and preserved ejection fraction.Background: Nitrates are commonly prescribed for symptom relief in patients with heart failure. Early studies in patients with heart failure with a reduced ejection fraction concluded that long-acting nitrates improves activity tolerance; however, approximately half of heart failure patients have preserved ejection fraction. The effects of nitrates in patients with heart failure and a preserved ejection fraction have not been extensively studied and the overall effect of nitrates on activity tolerance in such patients is uncertain.Subjects: There were a total of 110 patients enrolled with 51 patients assigned to receive isosorbide mono-nitrate first and placebo second, and 59 patients assigned to receive placebo first and isosorbide mononitrate second.Design: Enrolled subjects underwent baseline assessments, including echocardiography, quality-of-life scores, 6-minute walk test distance, and NT-proBNP levels. Subjects were also supplied with two kinetic activity monitors containing high-sensitivity triaxis accelerometers, to be worn 24 hours per day. The accelerometer measurements were expressed as arbitrary accelerometer units and stored every 15 minutes equaling 96 data points per day. The 15-minute cumulative accelerometer units were totaled over a 24-hour period to provide daily accelerometer units.Subjects were assigned to one of two treatment groups: 6 weeks of placebo first with crossover to 6 weeks of isosorbide mononitrate, or 6 weeks of isosorbide mononitrate first with crossover to 6 weeks of placebo. The study drugs were prepared as 30-mg tablets of isosorbide mononitrate and matching placebo. During each 6-week period, patients were instructed to take no study drug for the first 2 weeks followed by one tablet (30 mg daily) for 1 week, two tablets (60 mg once daily) for 1 week, and four tablets (120 mg once daily) until the next study visit, for a treatment duration of at least 2 weeks and up to 4 weeks. After each 6-week period, patients returned to the study center to repeat end-point assessments. The primary outcome for the study was the comparison of average daily accelerometer units during the period in which patients were receiving the 120-mg dose of isosorbide mononitrate compared to the period in which patients received the placebo. Other secondary end points included the 6-minute walk distance and the post-walk Borg dyspnea score, scores on the Kansas City Cardiomyopathy Questionnaire and the Minnesota Living with Heart Failure Questionnaire, and NT-proBNP levels. In addition, subjects completed a questionnaire indicating in which period (first, second, no preference) they felt better. Conclusions: Patients were active for fewer hours of the day during the 120-mg phase of receipt of isosorbide mononitrate as compared with placebo. Furthermore, during all study-drug regimens combined (30 mg to 120 mg), patients were less active during receipt of isosorbide mononitrate as compared with placebo. There was no significant effect of isosorbide mononitrate on secondary outcomes. Study Weblinks: BioLINCC: Heart Failure Network (HFN) Nitrate's Effect on Activity Tolerance in Heart Failure with Preserved Ejection Fraction Study Design: Clinical Trial Study Type: Clinical Trial Total number of consented subjects: 110 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Heart Failure Network - Imaging from Nitrate's Effect on Activity Tolerance in Heart Failure with Preserved Ejection Fraction (HFN NEAT-Imaging)","short_name":"img_HFN_NEAT_GRU","commons":"BioData Catalyst","study_url":"","_subjects_count":110,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs004275.v1.p1.c1":{"gen3_discovery":{"authz":"/programs/BioLINCC/projects/BL_PPH_Registry_GRU","tags":[],"_unique_id":"phs004275.v1.p1.c1","study_id":"phs004275.v1.p1.c1","study_description":"Data Access NOTE: Please refer to the \"Authorized Access\" section below for information about how access to the data from this accession differs from many other dbGaP accessions. Objectives Establish a patient registry to evaluate the natural history, etiology, pathogenesis and treatment of primary pulmonary hypertension. Specific aims included the characterization of the demographic, medical history, family history, physical and laboratory findings of patients at time of diagnosis, and to characterize the survival duration of patients by traits evaluated at diagnosis and by medical interventions. Background There are several known causes of pulmonary hypertension: chronic obstructive pulmonary disease, congenital heart disease, mitral stenosis, left ventricular dysfunction and recurrent pulmonary emboli. Primary Pulmonary Hypertension is a disorder of unknown etiology which is diagnosed only after the known causes of pulmonary hypertension have been eliminated. Prior to the PPH registry, little was known regarding the epidemiology, etiology, natural history or ultimate survival among patients with PPH. In 1973, the WHO met to review the current state of knowledge on PPH and proposed the establishment of a multicenter collaborative study. The NHLBI PPH registry enrolled patients in the registry from 1981 to 1985. Participants Participants were enrolled into the registry from 32 medical centers throughout the US. Pulmonary hypertension was defined as a mean pulmonary arterial pressure of >25 mmHg at rest or 30 mmHg with exercise at catheterization. The diagnosis of primary pulmonary hypertension was only accepted after the following secondary causes of pulmonary hypertension had been excluded: pulmonary hypertension within the first year of life, congenital abnormalities of the heart, lungs, or diaphragm, pulmonary thromboembolic disease, diagnosis of sickle cell anemia, history of intravenous drug abuse, obstructive lung disease, interstitial lung disease, arterial hypoxemia, collagen vascular disease, parasitic disease affecting the lungs, pulmonary artery or valve stenosis, or pulmonary venous hypertension. Baseline and follow-up data collected on participants include demographic characteristics, chest radiograph, pulmonary function tests, lung perfusion scan or pulmonary angiogram, intracardiac left-to-right shunt, pulmonary hemodynamics, as well as a history, physical findings and other laboratory measurements. Participants were followed for approximately 5 years. Conclusions There were 1.7 females for each male in the registry, and females tended to present with more severe symptoms. The mean time from onset of symptoms to diagnosis was 2 years. Right ventricular hypertrophy was found in 87% of participants and right atrial pressure was elevated in 72% of participants. The estimated median survival was 2.8 years with single year survival rates of: 1 year, 68%; 3 years, 48%; and 5 years, 34%. (Ann Intern Med, 1987; 107:216-23, Ann Intern Med, 1991; 115:343-49). Study Weblinks: BioLINCC Repository Study Design: Clinical Trial Study Type: Observational Total number of consented subjects: 317 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Patient Registry for Primary Pulmonary Hypertension (PPH Registry-BioLINCC)","short_name":"BL_PPH_Registry_GRU","commons":"BioData Catalyst","study_url":"","_subjects_count":317,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs004276.v1.p1.c1":{"gen3_discovery":{"authz":"/programs/BioLINCC/projects/BL_ACCESS_HMB-MDS","tags":[],"_unique_id":"phs004276.v1.p1.c1","study_id":"phs004276.v1.p1.c1","study_description":"Data Access NOTE: Please refer to the \"Authorized Access\" section below for information about how access to the data from this accession differs from many other dbGaP accessions. Access to Biospecimens is through the NHLBI Biologic Specimen and Data Repository Information Coordinating Center (BioLINCC). Biospecimens from (ACCESS) include Bronchial Lavage, DNA, Peripheral Blood Mononuclear Cells, and Plasma. Please note that use of biospecimens in genetic research is subject to a tiered consent. Objectives: To determine the etiology of sarcoidosis by establishing a case control, multi-center study. In addition to etiology, this study also sought to examine socioeconomic variables and the clinical course of patients with sarcoidosis, including quality of life.Background: Sarcoidosis is a chronic granulomatous disorder of unknown cause that is characterized by activation of T-lymphocytes and macrophages. For many years, sarcoidosis was presumed to be an atypical manifestation of tuberculosis because of the similarity between the inflammatory responses of the two diseases. However, as culture techniques became more widely employed to diagnose tuberculosis and it became less common, it became clear that sarcoidosis was not simply a variation of tuberculosis. Data on the etiology of sarcoidosis have come from diverse sources: in clinical investigations, alveolitis has been found to precede granulomatous inflammation; in case control studies, familial aggregation has been identified; and in case reports, recurrence of granulomatous inflammation has been observed after lung transplantation. The cause may not prove to be a single, known exposure. Interactions of exposures with genetic dispositions could have important implications for our understanding of immune responses as well as the pathogenesis of sarcoidosis.Participants: 736 participants with sarcoidosis enrolled within 6 months of diagnosis from 10 clinical centers in the U.S. Using the ACCESS sarcoidosis assessment system, organ involvement was determined for the whole group and for subgroups differentiated by sex, race, and age (<40 or 40 and older). Cases were matched with a control, and there was a two-year follow-up on cases. The ACCESS group proposed an instrument fo defining organ involvement in sarcoidosis. Biological specimens included DNA, plasma, and bronchoalveolar lavage samples were obtained. The data set includes 718 cases, 686 controls, and two-year follow-up data on 241 cases.Conclusions: The initial presentation of sarcoidosis is related to sex, race and age, and it tends to remain stable over two years in the majority of patients. The etiology is probably multifactoral with both genetic and environmental factors contributing.Specimen Details: The PBMC for this study are pelleted and suspended in guanidinium-based solution and are nonviable. Study Weblinks: BioLINCC Repository Study Design: Clinical Trial Study Type: Cohort Observational Total number of consented subjects: 1404 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"A Case Controlled Etiologic Study of Sarcoidosis (ACCESS-BioLINCC)","short_name":"BL_ACCESS_HMB-MDS","commons":"BioData Catalyst","study_url":"","_subjects_count":1404,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs004310.v1.p1.c1":{"gen3_discovery":{"authz":"/programs/BioLINCC/projects/BL_WISE_GRU","tags":[],"_unique_id":"phs004310.v1.p1.c1","study_id":"phs004310.v1.p1.c1","study_description":"Data Access NOTE: Please refer to the \"Authorized Access\" section below for information about how access to the data from this accession differs from many other dbGaP accessions. Objectives: This is a National Heart, Lung and Blood Institute sponsored, four-center study designed to: 1) optimize symptom evaluation and diagnostic testing for ischemic heart disease; 2) explore mechanisms for symptoms and myocardial ischemia in the absence of epicardial coronary artery stenoses, and 3) evaluate the influence of reproductive hormones on symptoms and diagnostic test response.Background: Women tend to have a higher prevalence of chest pain than men, yet a lower prevalence of epicardial coronary stenoses, and diagnostic tests such as exercise-induced ECG changes tend to have a higher false-positive rate in women than in men. Thus, accurate diagnosis of ischemic heart disease in women is a major challenge to physicians. In addition, prognosis in women with abnormal diagnostic tests is largely unknown and the role reproductive hormones play in this diagnostic uncertainty is unexplored. Moreover, the significance and pathophysiology of ischemia in the absence of significant epicardial coronary stenoses is unknown.Participants: In Phase I (1996-1997), a pilot phase, 256 women were studied. During Phase II (1997-1999) angiographic and baseline data were collected on an additional 680 women to bring total enrollment to 936. Baseline data was also collected on a reference population of 70 women.Conclusions: Among women without CAD, abnormal Magnetic Resonance Spectroscopy (MRS) consistent with myocardial ischemia predicted cardiovascular outcome, notably higher rates of anginal hospitalization, repeat catherization, and greater treatment costs. Study Weblinks: BioLINCC Repository Study Design: Clinical Trial Study Type: Observational Total number of consented subjects: 1024 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Women's Ischemia Syndrome Evaluation (WISE-BioLINCC)","short_name":"BL_WISE_GRU","commons":"BioData Catalyst","study_url":"","_subjects_count":1024,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs004313.v1.p1.c1":{"gen3_discovery":{"authz":"/programs/BioLINCC/projects/BL_LEEP_HMB-NPU","tags":[],"_unique_id":"phs004313.v1.p1.c1","study_id":"phs004313.v1.p1.c1","study_description":"Data Access NOTE: Please refer to the “Authorized Access” section below for information about how access to the data from this accession differs from many other dbGaP accessions. Objectives To evaluate the efficacy of losartan, an angiotensin receptor blocker, to reduce emphysema progression in patients with COPD and mild to moderate emphysema. Background Chronic obstructive pulmonary disease (COPD) is a heterogeneous disease comprising chronic bronchitis and emphysema. COPD is a major cause of morbidity and mortality. Smoking cessation slows the progression of the disease, and bronchodilators can provide sustained improvement in lung function, but there are no pharmacologic agents that clearly modify emphysema progression. Angiotensin receptor blockers (ARBs) have been suggested as potential drugs to slow the progression of COPD. A few trials have shown that patients treated with ARBs had slower progression of radiographic emphysema. The LEEP study was initiated to test the hypothesis that the ARB losartan would reduce the progression of emphysema in patients with COPD with mild to moderate emphysema.ParticipantsA total of 220 participants were enrolled. 108 participants were randomized to receive losartan, and 112 participants were randomized to receive the placebo.Design LEEP was a randomized, placebo-controlled multicenter trial. Participants were randomly assigned (1:1) to receive losartan or placebo. The dose was 50 mg losartan or placebo given as one capsule daily for 2 weeks, and, if well tolerated and the systolic blood pressure was >90 mm Hg, it was increased to two capsules. Participants and site investigators were masked to treatment assignment. Participant responses to the St George's Respiratory Questionnaire, the modified Medical Research Council dyspnea scale, the COPD Assessment Test, and the Physical Function–Short Form 20a were collected. The number and severity of COPD exacerbations were recorded. COPD exacerbations were defined as two or more new or worse symptoms for ≥3 days and classified by treatment as mild (neither antibiotics nor oral steroids), moderate (an antibiotic or oral steroid), or severe (hospitalization). The primary outcome measure was the change in quantitative whole-lung emphysema score after 48 weeks measured by the percentage of lung voxels less than -950 Hounsfield units (PCT950) on full inspiratory HRCT. Conclusions Losartan does not prevent progression of emphysema in patients with COPD who have mild to moderate pulmonary emphysema. Study Weblinks: LEEP-BioLINCC Study Design: Clinical Trial Study Type: Clinical Trial Total number of consented subjects: 220 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Losartan Effects on Emphysema Progression (LEEP-BioLINCC)","short_name":"BL_LEEP_HMB-NPU","commons":"BioData Catalyst","study_url":"","_subjects_count":220,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"phs004314.v1.p1.c1":{"gen3_discovery":{"authz":"/programs/BioLINCC/projects/BL_CleanUP_IPF_GRU","tags":[],"_unique_id":"phs004314.v1.p1.c1","study_id":"phs004314.v1.p1.c1","study_description":"Data Access NOTE: Please refer to the “Authorized Access” section below for information about how access to the data from this accession differs from many other dbGaP accessions. Objectives To investigate whether the addition of antimicrobial treatments improves outcomes compared to usual care alone among patients with idiopathic pulmonary fibrosis. Background Idiopathic pulmonary fibrosis (IPF) is a chronic progressive lung disease. Lung dysbiosis, characterized by increased bacterial load and/or loss of diversity, has been reported in patients with IPF and may contribute to hospitalization and death. Clinical trials investigating other chronic disorders suggest that antimicrobial therapy favorably alters the lung microbial community. The CleanUP IPF study was initiated to determine if an antimicrobial treatment reduces respiratory hospitalization or death among patients with IPF. Participants A total of 513 participants were enrolled. 254 participants were randomized to receive antimicrobials, of those 128 were randomized to receive co-trimoxazole and 126 were randomized to receive doxycycline. 259 participants were randomized to receive usual care alone. Design CleanUP IPF was a randomized, unblinded, multicenter study. Patients were randomized to receive antimicrobials in addition to usual care or usual care alone. Antimicrobials included co-trimoxazole (trimethoprim 160 mg/sulfamethoxazole 800 mg twice daily plus folic acid 5 mg daily) or doxycycline (100 mg once daily if body weight < 50 kg or 100 mg twice daily if ≥ 50 kg). Follow-up schedules varied depending on the assigned treatment group. Data collected included diffusion capacity of lungs for carbon monoxide (DLCO), forced vital capacity (FVC), and occurrence of severe adverse events. Several questionnaires were administered to assess quality of life, including the impacts of shortness of breath, fatigue, and chronic cough on participants. The primary end point was time to first nonelective respiratory hospitalization or all-cause mortality. The study was terminated early due to futility. Conclusions Among adults with idiopathic pulmonary fibrosis, the addition of co-trimoxazole or doxycycline to usual care, compared with usual care alone, did not significantly improve time to nonelective respiratory hospitalization or death. Martinez FJ, Yow E, Flaherty KR, et al. Effect of Antimicrobial Therapy on Respiratory Hospitalization or Death in Adults With Idiopathic Pulmonary Fibrosis: The CleanUP-IPF Randomized Clinical Trial. JAMA. 2021;325(18):1841-1851. doi:10.1001/jama.2021.4956 Study Weblinks: CleanUP IPF BioLINCC Study Design: Clinical Trial Study Type: Clinical Trial Total number of consented subjects: 513 Subject Sample Telemetry Report (SSTR) NOTE: This text was scraped from https://www.ncbi.nlm.nih.gov/ on 2026-01-09 and may not include exact formatting or images.","full_name":"Study of Clinical Efficacy of Antimicrobial Therapy Strategy Using Pragmatic Design in Idiopathic Pulmonary Fibrosis (CleanUP IPF-BioLINCC)","short_name":"BL_CleanUP_IPF_GRU","commons":"BioData Catalyst","study_url":"","_subjects_count":513,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"TOPMed_Common_Exchange_Area-Freeze_1":{"gen3_discovery":{"authz":"/programs/TOPMed_Common_Exchange_Area/projects/Freeze_1","tags":[],"_unique_id":"TOPMed_Common_Exchange_Area-Freeze_1_PROXY_Study","study_id":"TOPMed_Common_Exchange_Area-Freeze_1_PROXY_Study","study_description":"","full_name":"","short_name":"","commons":"BioData Catalyst","study_url":"https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=..","_subjects_count":1,"__manifest":[],"commons_url":"gen3.biodatacatalyst.nhlbi.nih.gov","commons_name":"BioData Catalyst"}}},{"TOPMed_Common_Exchange_Area-Freeze_10a":{"gen3_discovery":{"authz":"/programs/TOPMed_Common_Exchange_Area/projects/Freeze_10a","tags":[],"_unique_id":"TOPMed_Common_Exchange_Area-Freeze_10a_PROXY_Study","study_id":"TOPMed_Common_Exchange_Area-Freeze_10a_PROXY_Study","study_description":"","full_name":"","short_name":"","commons":"BioData 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subjects in the community of Framingham,\nMassachusetts. The Framingham Heart Study was a landmark study in epidemiology in that it\nwas the first prospective study of cardiovascular disease and identified the concept of risk\nfactors and their joint effects. The study began in 1948 and 5,209 subjects were initially enrolled\nin the study. Participants have been examined biennially since the inception of the study and all\nsubjects are continuously followed through regular surveillance for cardiovascular outcomes.\nClinic examination data has included cardiovascular disease risk factors and markers of\ndisease such as blood pressure, blood chemistry, lung function, smoking history, health\nbehaviors, ECG tracings, Echocardiography, and medication use. Through regular surveillance\nof area hospitals, participant contact, and death certificates, the Framingham Heart Study\nreviews and adjudicates events for the occurrence of Angina Pectoris, Myocardial Infarction,\nHeart Failure, and Cerebrovascular disease.\nThe enclosed dataset is a subset of the data collected as part of the Framingham study and\nincludes laboratory, clinic, questionnaire, and adjudicated event data on 4,434 participants.\nParticipant clinic data was collected during three examination periods, approximately 6 years\napart, from roughly 1956 to 1968. Each participant was followed for a total of 24 years for the\noutcome of the following events: Angina Pectoris, Myocardial Infarction, Atherothrombotic\nInfarction or Cerebral Hemorrhage (Stroke) or death. (NOTE: Although the enclosed dataset\ncontains Framingham data 'as collected' by Framingham investigators, specific methods\nwere employed to ensure an anonymous dataset that protects patient confidentiality;\ntherefore, this dataset is inappropriate for publication purposes. All persons teaching\nwith this dataset are encouraged to ensure all users are aware that this dataset is\ninappropriate for publication purposes.)","full_name":"","short_name":"","commons":"BioData 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Images should be interpreted and aligned with the date-shifted field visit_start_datetime to correlate severity with the imaging data.","full_name":"Stony Brook University COVID-19 Positive Cases (COVID-19-NY-SBU)","short_name":"COVID-19-NY-SBU","commons":"Medical Imaging and Data Resource Center (MIDRC)","study_url":"https://doi.org/10.7937/TCIA.BBAG-2923","_subjects_count":1384,"__manifest":[{"object_id":"dg.MD1R/abb6a36b-f5ec-4e20-9189-48da9f126382"}],"commons_url":"data.midrc.org","commons_name":"MIDRC"}}},{"TCIA-RICORD-1a":{"gen3_discovery":{"authz":"/programs/TCIA/projects/RICORD","tags":[{"name":"COVID-19","category":"disease_type"},{"name":"Chest","category":"primary_site"}],"_unique_id":"TCIA-RICORD-1a","study_id":"TCIA-RICORD-1a","study_description":"MIDRC-RICORD dataset 1a consists of 120 thoracic computed tomography (CT) scans from four international sites annotated with detailed segmentation and diagnostic labels.","full_name":"Medical Imaging Data Resource Center (MIDRC) - RSNA International COVID-19 Open Radiology Database (RICORD) Release 1a - Chest CT Covid+ (MIDRC-RICORD-1a)","short_name":"MIDRC-RICORD Release 1a","commons":"Medical Imaging and Data Resource Center (MIDRC)","study_url":"https://doi.org/10.7937/VTW4-X588","_subjects_count":110,"__manifest":[{"object_id":"dg.MD1R/b6fa25d8-2075-4d0b-b9de-55371ae11113"}],"commons_url":"data.midrc.org","commons_name":"MIDRC"}}},{"TCIA-RICORD-1b":{"gen3_discovery":{"authz":"/programs/TCIA/projects/RICORD","tags":[{"name":"COVID-19","category":"disease_type"},{"name":"Chest","category":"primary_site"}],"_unique_id":"TCIA-RICORD-1b","study_id":"TCIA-RICORD-1b","study_description":"The RSNA International COVID-19 Open Annotated Radiology Database (RICORD) release 1b consists of 120 thoracic computed tomography (CT) scans of COVID negative patients from four international sites.","full_name":"Medical Imaging Data Resource Center (MIDRC) - RSNA International COVID-19 Open Radiology Database (RICORD) Release 1b - Chest CT Covid- (MIDRC-RICORD-1b)","short_name":"RICORD-1b","commons":"Medical Imaging and Data Resource Center (MIDRC)","study_url":"https://doi.org/10.7937/31V8-4A40","_subjects_count":117,"__manifest":[{"object_id":"dg.MD1R/51e1f939-14b7-44e9-9140-8eea3b6457e7"}],"commons_url":"data.midrc.org","commons_name":"MIDRC"}}},{"TCIA-RICORD-1c":{"gen3_discovery":{"authz":"/programs/TCIA/projects/RICORD","tags":[{"name":"COVID-19","category":"disease_type"},{"name":"Chest","category":"primary_site"}],"_unique_id":"TCIA-RICORD-1c","study_id":"TCIA-RICORD-1c","study_description":"The RSNA International COVID-19 Open Annotated Radiology Database (RICORD) consists of 998 chest x-rays from 361 patients at four international sites annotated with diagnostic labels. Patient Selection: Patients at least 18 years in age receiving positive diagnosis for COVID-19.","full_name":"Medical Imaging Data Resource Center (MIDRC) - RSNA International COVID-19 Open Radiology Database (RICORD) Release 1c - Chest x-ray Covid+ (MIDRC-RICORD-1c)","short_name":"RICORD-1c","commons":"Medical Imaging and Data Resource Center (MIDRC)","study_url":"https://doi.org/10.7937/91ah-v663","_subjects_count":361,"__manifest":[{"object_id":"dg.MD1R/5cc5ac99-b3b0-4f23-be50-2ec5e51c69d3"}],"commons_url":"data.midrc.org","commons_name":"MIDRC"}}}],"JCOIN":[{"1U2CDA050098-01_a":{"gen3_discovery":{"authz":"/programs/JCOIN/projects/SURVEYS","tags":[{"name":"InCommon","category":"RequiredIDP"}],"_unique_id":"1U2CDA050098-01_a","study_id":"1U2CDA050098-01_a","study_description":"Abstract: Tracking changes in stigma associated with OUD is important,for as stigma intensifies over time it might make it more difficult to find positive treatment effects in JCOIN. 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The data will allow us to assess the public opinion on issues related to OUD, stigma, and the justice system and monitor trends over time.","full_name":"Amerispeak Opioid Stigma Surveys","short_name":"Amerispeak Brief Stigma Survey (JCOIN 026)","commons":"JCOIN","study_url":null,"data_availability":"available","_subjects_count":1000,"__manifest":[{"md5sum":"f9abf52cb64fc5b1a786d688e2ae88fa","file_name":"jcoin-protocol1-surveys-v2.0.zip","file_size":2118265,"object_id":"dg.6VTS/327c76a1-0912-43e3-b64c-f67b849fa996"}],"commons_url":"jcoin.datacommons.io","commons_name":"JCOIN"}}},{"1U2CDA050098-01_b":{"gen3_discovery":{"authz":"/programs/JCOIN/projects/OEPS","tags":[{"name":"Community","category":"Study Setting"},{"name":"Opioid Use","category":"Substance Use"},{"name":"Practice","category":"Other"},{"name":"Quality","category":"Other"},{"name":"Racial and Ethnic Populations","category":"Subject Characteristics"},{"name":"Justice-involved Populations","category":"Subject Characteristics"}],"_unique_id":"1U2CDA050098-01_b","study_id":"1U2CDA050098-01_b","study_description":"The Opioid Environment Policy Scan (OEPS) is a free, open-source data warehouse centered on the multi-dimensional risk environment impacting opioid use and health outcomes, particularly for justice communities, across the United States. \nThe OEPS consolidates cleaned and processed data spanning Medications for Opioid Use Disorder (MOUD) Access, Health, Built Environment, Economic, and other contextual data at the Census tract, zip code, county, and state levels. Its data supports JCOIN research into the communities and conditions impacting and impacted by opioid use and identifying strategies or policies to reduce harm in communities nationwide.","full_name":"Methodology and Advanced Analytics Resource Center","short_name":"Opioid Environment Policy Scan (OEPS) ","commons":"JCOIN","study_url":null,"data_availability":"available","_subjects_count":0,"__manifest":[{"md5sum":"5db998ad11f417758724c0cff0c32f21","file_name":"oeps-v2-export-20240603_no_foreign_keys.zip","file_size":235053934,"object_id":"dg.6VTS/e3165ea2-293b-4599-a895-728b5b1213cb"}],"commons_url":"jcoin.datacommons.io","commons_name":"JCOIN"}}},{"NIDA_PDAPS_1a":{"gen3_discovery":{"authz":"/programs/NIDA/projects/PDAPS","tags":[{"name":"Opioid Use","category":"Substance Use"}],"_unique_id":"NIDA_PDAPS_1a","study_id":"NIDA_PDAPS_1a","study_description":"PDAPS is funded by the National Institute on Drug Abuse to track key state laws related to prescription drug abuse. PDAPS has broken down its datasets into the following major topics: Expanded Access to Naloxone, Good Samaritan 911 Immunity, Medical Marijuana, Opioid Related Controls, Prescription Drug Monitoring Program, and Related Topics. It is intended to be used as a source of rigorous legal data for researchers and provide detailed policy information for the public.","full_name":"Prescription Drug Abuse Policy System (NIDA)","short_name":"Prescription Drug Abuse Policy System (NIDA)","commons":"JCOIN","study_url":null,"data_availability":"","_subjects_count":0,"__manifest":[],"commons_url":"jcoin.datacommons.io","commons_name":"JCOIN"}}}],"CRDC Genomic Data Commons":[{"HCMI-CMDC":{"gen3_discovery":{"commons":"CRDC Genomic Data Commons","short_name":"HCMI-CMDC","full_name":"NCI Cancer Model Development for the Human Cancer Model Initiative","disease_type":["Transitional Cell Papillomas and Carcinomas","Nevi and Melanomas","Mature T- and NK-Cell Lymphomas","Squamous Cell Neoplasms","Osseous and Chondromatous Neoplasms","Neuroepitheliomatous Neoplasms","Myomatous Neoplasms","Epithelial Neoplasms, NOS","Malignant Lymphomas, NOS or Diffuse","Soft Tissue Tumors and Sarcomas, NOS","Complex Epithelial Neoplasms","Cystic, 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'Adenomas and Adenocarcinomas', 'Gliomas', 'Synovial-like Neoplasms', 'Complex Mixed and Stromal Neoplasms', 'Lymphoid Leukemias'] in ['Ovary', 'Hematopoietic and reticuloendothelial systems', 'Nasal cavity and middle ear', 'Other and ill-defined sites', 'Skin', 'Other and unspecified parts of biliary tract', 'Breast', 'Small intestine', 'Liver and intrahepatic bile ducts', 'Corpus uteri', 'Gallbladder', 'Stomach', 'Brain', 'Eye and adnexa', 'Bladder', 'Thyroid gland', 'Connective, subcutaneous and other soft tissues', 'Kidney', 'Other and unspecified parts of tongue', 'Larynx', 'Bones, joints and articular cartilage of other and unspecified sites', 'Adrenal gland', 'Colon', 'Other and unspecified parts of mouth', 'Rectum', 'Unknown', 'Lymph nodes', 'Uterus, NOS', 'Rectosigmoid junction', 'Bronchus and lung', 'Pancreas', 'Esophagus']","commons_name":"CRDC Genomic Data Commons"}}},{"CPTAC-3":{"gen3_discovery":{"commons":"CRDC Genomic Data 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['Small intestine', 'Cervix uteri', 'Colon', 'Parotid gland', 'Ovary', 'Breast', 'Unknown', 'Skin', 'Liver and intrahepatic bile ducts', 'Renal pelvis', 'Prostate gland', 'Other and unspecified female genital organs', 'Rectosigmoid junction', 'Bladder', 'Rectum', 'Other and unspecified parts of biliary tract', 'Gallbladder']","commons_name":"CRDC Genomic Data Commons"}}},{"CMI-ASC":{"gen3_discovery":{"commons":"CRDC Genomic Data Commons","short_name":"CMI-ASC","full_name":"Count Me In (CMI): The Angiosarcoma (ASC) Project","disease_type":["Soft Tissue Tumors and Sarcomas, NOS"],"primary_site":["Heart, mediastinum, and pleura","Bronchus and lung","Breast","Skin","Lymph nodes","Other and ill-defined digestive organs","Other and ill-defined sites","Bladder","Other and ill-defined sites within respiratory system and intrathoracic organs"],"_unique_id":"CMI-ASC","tags":[{"name":"Soft Tissue Tumors and Sarcomas, NOS","category":"disease_type"},{"name":"Heart, mediastinum, and 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Please see the DICOM converted Slide Microscopy images for the TCGA-PRAD collection page to learn more about the histopathology images and to obtain any supporting metadata for this collection.","image_types":"ANN, SEG, SEG, CT, MR, PT, SM","_subjects_count":500,"doi":"10.5281/ZENODO.16966285 10.7937/K9/TCIA.2016.YXOGLM4Y 10.5281/ZENODO.12689935 10.5281/ZENODO.11099004","species":"Human","disease_type":"Prostate Cancer","data_type":"Clinical, Genomics, Histopathology","primary_site":"Prostate","tags":[{"name":"Prostate Cancer","category":"disease_type"},{"name":"Clinical, Genomics, Histopathology","category":"data_type"},{"name":"Prostate","category":"primary_site"}],"commons_name":"CRDC Cancer Imaging Data Commons"}}},{"tcga_blca":{"gen3_discovery":{"commons":"CRDC Cancer Imaging Data Commons","_unique_id":"tcga_blca","study_title":"tcga_blca","accession_number":"tcga_blca","short_name":"TCGA_BLCA","full_name":"TCGA_BLCA","dbgap_accession_number":"TCGA_BLCA","study_description":" The Cancer Genome Atlas-Bladder Endothelial Carcinoma (TCGA-BLCA) data collection is part of a larger effort to enhance the TCGA http://cancergenome.nih.gov/ data set with characterized radiological images. 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Please see the DICOM converted Slide Microscopy images for the TCGA-BLCA collection page to learn more about the histopathology images and to obtain any supporting metadata for this collection.","image_types":"SM, ANN, SEG, SEG, CR, CT, DX, MR, PT","_subjects_count":412,"doi":"10.7937/K9/TCIA.2016.8LNG8XDR 10.5281/ZENODO.11099004 10.5281/ZENODO.12690045 10.5281/ZENODO.16966285","species":"Human","disease_type":"Bladder Endothelial Carcinoma","data_type":"Clinical, Genomics, Histopathology","primary_site":"Bladder","tags":[{"name":"Bladder Endothelial Carcinoma","category":"disease_type"},{"name":"Clinical, Genomics, Histopathology","category":"data_type"},{"name":"Bladder","category":"primary_site"}],"commons_name":"CRDC Cancer Imaging Data Commons"}}},{"tcga_ucec":{"gen3_discovery":{"commons":"CRDC Cancer Imaging Data Commons","_unique_id":"tcga_ucec","study_title":"tcga_ucec","accession_number":"tcga_ucec","short_name":"TCGA_UCEC","full_name":"TCGA_UCEC","dbgap_accession_number":"TCGA_UCEC","study_description":" The Cancer Genome Atlas-Uterine Corpus Endometrial Carcinoma (TCGA-UCEC) data collection is part of a larger effort to enhance the TCGA http://cancergenome.nih.gov/ data set with characterized radiological images. 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Please see the DICOM converted Slide Microscopy images for the TCGA-UCEC collection page to learn more about the histopathology images and to obtain any supporting metadata for this collection.","image_types":"CR, CT, MR, PT, SEG, SM, ANN, SEG","_subjects_count":560,"doi":"10.5281/ZENODO.16966285 10.5281/ZENODO.11099004 10.5281/ZENODO.12689968 10.7937/K9/TCIA.2016.GKJ0ZWAC","species":"Human","disease_type":"Uterine Corpus Endometrial Carcinoma","data_type":"Clinical, Genomics, Histopathology","primary_site":"Uterus","tags":[{"name":"Uterine Corpus Endometrial Carcinoma","category":"disease_type"},{"name":"Clinical, Genomics, Histopathology","category":"data_type"},{"name":"Uterus","category":"primary_site"}],"commons_name":"CRDC Cancer Imaging Data Commons"}}},{"tcga_hnsc":{"gen3_discovery":{"commons":"CRDC Cancer Imaging Data Commons","_unique_id":"tcga_hnsc","study_title":"tcga_hnsc","accession_number":"tcga_hnsc","short_name":"TCGA_HNSC","full_name":"TCGA_HNSC","dbgap_accession_number":"TCGA_HNSC","study_description":"The Cancer Imaging Program (CIP) is working directly with primary investigators from institutes participating in TCGA to obtain and load images relating to the genomic, clinical, and pathological data being stored within the TCGA Data Portal. Currently this large PET/CT multi-sequence image collection of head and neck squamous cell carcinoma (HNSC) patients can be matched by each unique case identifier with the extensive gene and expression data of the same case from The Cancer Genome Atlas Data Portal to research the link between clinical phenome and tissue genome.Please see the TCGA-HNSC page to learn more about the radiology images and to obtain any supporting metadata for this collection. Please see the DICOM converted Slide Microscopy images for the TCGA-HNSC collection page to learn more about the histopathology images and to obtain any supporting metadata for this collection.","image_types":"SEG, SM","_subjects_count":523,"doi":"10.5281/ZENODO.12690033 10.5281/ZENODO.16966285","species":"Human","disease_type":"Head and Neck Squamous Cell Carcinoma","data_type":"Clinical, Genomics, Histopathology","primary_site":"Head-Neck","tags":[{"name":"Head and Neck Squamous Cell Carcinoma","category":"disease_type"},{"name":"Clinical, Genomics, Histopathology","category":"data_type"},{"name":"Head-Neck","category":"primary_site"}],"commons_name":"CRDC Cancer Imaging Data Commons"}}},{"tcga_lusc":{"gen3_discovery":{"commons":"CRDC Cancer Imaging Data Commons","_unique_id":"tcga_lusc","study_title":"tcga_lusc","accession_number":"tcga_lusc","short_name":"TCGA_LUSC","full_name":"TCGA_LUSC","dbgap_accession_number":"TCGA_LUSC","study_description":" The Cancer Genome Atlas-Lung Squamous Cell Carcinoma (TCGA-LUSC) data collection is part of a larger effort to enhance the TCGA http://cancergenome.nih.gov/ data set with characterized radiological images. 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Please see the DICOM converted Slide Microscopy images for the TCGA-THCA collection page to learn more about the histopathology images and to obtain any supporting metadata for this collection.","image_types":"CT, PT, SM","_subjects_count":507,"doi":"10.7937/K9/TCIA.2016.9ZFRVF1B 10.5281/ZENODO.12689958","species":"Human","disease_type":"Thyroid Cancer","data_type":"Clinical, Genomics, Histopathology","primary_site":"Thyroid","tags":[{"name":"Thyroid Cancer","category":"disease_type"},{"name":"Clinical, Genomics, Histopathology","category":"data_type"},{"name":"Thyroid","category":"primary_site"}],"commons_name":"CRDC Cancer Imaging Data Commons"}}},{"tcga_sarc":{"gen3_discovery":{"commons":"CRDC Cancer Imaging Data Commons","_unique_id":"tcga_sarc","study_title":"tcga_sarc","accession_number":"tcga_sarc","short_name":"TCGA_SARC","full_name":"TCGA_SARC","dbgap_accession_number":"TCGA_SARC","study_description":" The Cancer Genome Atlas-Sarcoma Cancer (TCGA-SARC) data collection is part of a larger effort to enhance the TCGA http://cancergenome.nih.gov/ data set with characterized radiological images. 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Please see the DICOM converted Slide Microscopy images for the TCGA-SARC collection page to learn more about the histopathology images and to obtain any supporting metadata for this collection.","image_types":"SM, SEG, CT, MR","_subjects_count":261,"doi":"10.7937/K9/TCIA.2016.CX6YLSUX 10.5281/ZENODO.12689917 10.5281/ZENODO.16966285","species":"Human","disease_type":"Sarcomas","data_type":"Clinical, Genomics, Histopathology","primary_site":"Chest-Abdomen-Pelvis, Leg, TSpine","tags":[{"name":"Sarcomas","category":"disease_type"},{"name":"Clinical, Genomics, Histopathology","category":"data_type"},{"name":"Chest-Abdomen-Pelvis, Leg, TSpine","category":"primary_site"}],"commons_name":"CRDC Cancer Imaging Data Commons"}}},{"tcga_esca":{"gen3_discovery":{"commons":"CRDC Cancer Imaging Data Commons","_unique_id":"tcga_esca","study_title":"tcga_esca","accession_number":"tcga_esca","short_name":"TCGA_ESCA","full_name":"TCGA_ESCA","dbgap_accession_number":"TCGA_ESCA","study_description":" The Cancer Genome Atlas-Esophageal Carcinoma (TCGA-ESCA) data collection is part of a larger effort to enhance the TCGA data set with characterized radiological images. 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Please see the DICOM converted Slide Microscopy images for the TCGA-ESCA collection page to learn more about the histopathology images and to obtain any supporting metadata for this collection.","image_types":"SEG, SM, CT","_subjects_count":185,"doi":"10.5281/ZENODO.16966285 10.7937/K9/TCIA.2016.VPTNRGFY 10.5281/ZENODO.12690012","species":"Human","disease_type":"Esophageal Carcinoma","data_type":"Clinical, Genomics, Histopathology","primary_site":"Esophagus","tags":[{"name":"Esophageal Carcinoma","category":"disease_type"},{"name":"Clinical, Genomics, Histopathology","category":"data_type"},{"name":"Esophagus","category":"primary_site"}],"commons_name":"CRDC Cancer Imaging Data Commons"}}},{"tcga_cesc":{"gen3_discovery":{"commons":"CRDC Cancer Imaging Data Commons","_unique_id":"tcga_cesc","study_title":"tcga_cesc","accession_number":"tcga_cesc","short_name":"TCGA_CESC","full_name":"TCGA_CESC","dbgap_accession_number":"TCGA_CESC","study_description":" The Cancer Genome Atlas-Cervical Squamous Cell Carcinoma and Endocervical Adenocarcinoma (TCGA-CESC) data collection is part of a larger effort to enhance the TCGA http://cancergenome.nih.gov/ data set with characterized radiological images. 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Please see the DICOM converted Slide Microscopy images for the TCGA-CESC collection page to learn more about the histopathology images and to obtain any supporting metadata for this collection.","image_types":"SEG, MR, ANN, SEG, SM","_subjects_count":307,"doi":"10.5281/ZENODO.12689956 10.7937/K9/TCIA.2016.SQ4M8YP4 10.5281/ZENODO.16966285 10.5281/ZENODO.11099004","species":"Human","disease_type":"Cervical Squamous Cell Carcinoma, Endocervical Adenocarcinoma","data_type":"Clinical, Genomics, Histopathology","primary_site":"Cervix","tags":[{"name":"Cervical Squamous Cell Carcinoma, Endocervical Adenocarcinoma","category":"disease_type"},{"name":"Clinical, Genomics, Histopathology","category":"data_type"},{"name":"Cervix","category":"primary_site"}],"commons_name":"CRDC Cancer Imaging Data Commons"}}},{"tcga_stad":{"gen3_discovery":{"commons":"CRDC Cancer Imaging Data Commons","_unique_id":"tcga_stad","study_title":"tcga_stad","accession_number":"tcga_stad","short_name":"TCGA_STAD","full_name":"TCGA_STAD","dbgap_accession_number":"TCGA_STAD","study_description":" The Cancer Genome Atlas-Stomach Adenoarcinoma (TCGA-STAD) data collection is part of a larger effort to enhance the TCGA http://cancergenome.nih.gov/ data set with characterized radiological images. The Cancer Imaging Program (CIP) with the cooperation of several of the TCGA tissue-contributing institutions are working to archive a large portion of the radiological images of the genetically-analyzed STAD cases. Please see the TCGA-STAD page to learn more about the radiology images and to obtain any supporting metadata for this collection. Please see the DICOM converted Slide Microscopy images for the TCGA-STAD collection page to learn more about the histopathology images and to obtain any supporting metadata for this collection.","image_types":"CT, SM, SEG, ANN, SEG","_subjects_count":443,"doi":"10.5281/ZENODO.16966285 10.5281/ZENODO.12690037 10.5281/ZENODO.11099004 10.7937/K9/TCIA.2016.GDHL9KIM","species":"Human","disease_type":"Stomach Adenocarcinoma","data_type":"Clinical, Genomics, Histopathology","primary_site":"Stomach","tags":[{"name":"Stomach Adenocarcinoma","category":"disease_type"},{"name":"Clinical, Genomics, Histopathology","category":"data_type"},{"name":"Stomach","category":"primary_site"}],"commons_name":"CRDC Cancer Imaging Data Commons"}}},{"tcga_coad":{"gen3_discovery":{"commons":"CRDC Cancer Imaging Data Commons","_unique_id":"tcga_coad","study_title":"tcga_coad","accession_number":"tcga_coad","short_name":"TCGA_COAD","full_name":"TCGA_COAD","dbgap_accession_number":"TCGA_COAD","study_description":" The Cancer Genome Atlas-Colon Adenocarcinoma (TCGA-COAD) data collection is part of a larger effort to enhance the TCGA http://cancergenome.nih.gov/ data set with characterized radiological images. The Cancer Imaging Program (CIP), with the cooperation of several of the TCGA tissue-contributing institutions, has archived a large portion of the radiological images of the COAD cases. Please see the TCGA-COAD page to learn more about the radiology images and to obtain any supporting metadata for this collection. Please see the DICOM converted Slide Microscopy images for the TCGA-COAD collection page to learn more about the histopathology images and to obtain any supporting metadata for this collection.","image_types":"CT, OT, ANN, SEG, SEG, SM","_subjects_count":464,"doi":"10.5281/ZENODO.11099004 10.7937/K9/TCIA.2016.HJJHBOXZ 10.5281/ZENODO.16966285 10.5281/ZENODO.12689970","species":"Human","disease_type":"Colon adenocarcinoma","data_type":"Clinical, Genomics, Histopathology","primary_site":"Colon","tags":[{"name":"Colon adenocarcinoma","category":"disease_type"},{"name":"Clinical, Genomics, Histopathology","category":"data_type"},{"name":"Colon","category":"primary_site"}],"commons_name":"CRDC Cancer Imaging Data Commons"}}},{"tcga_kich":{"gen3_discovery":{"commons":"CRDC Cancer Imaging Data Commons","_unique_id":"tcga_kich","study_title":"tcga_kich","accession_number":"tcga_kich","short_name":"TCGA_KICH","full_name":"TCGA_KICH","dbgap_accession_number":"TCGA_KICH","study_description":" The Cancer Genome Atlas-Kidney Chromophobe (TCGA-KICH) data collection is part of a larger effort to enhance the The Cancer Genome Atlas (TCGA) https://cancergenome.nih.gov/ data set with characterized radiological images. The Cancer Imaging Program (CIP) with the cooperation of several of the TCGA tissue-contributing institutions has archived a large portion of the radiological images of the genetically-analyzed KICH cases. Please see the TCGA-KICH page to learn more about the radiology images and to obtain any supporting metadata for this collection. Please see the DICOM converted Slide Microscopy images for the TCGA-KICH collection page to learn more about the histopathology images and to obtain any supporting metadata for this collection.","image_types":"SM, SEG, CT, MR","_subjects_count":113,"doi":"10.5281/ZENODO.8345959 10.5281/ZENODO.12690004 10.7937/K9/TCIA.2016.YU3RBCZN","species":"Human","disease_type":"Kidney Chromophobe","data_type":"Clinical, Genomics, Histopathology","primary_site":"Kidney","tags":[{"name":"Kidney Chromophobe","category":"disease_type"},{"name":"Clinical, Genomics, Histopathology","category":"data_type"},{"name":"Kidney","category":"primary_site"}],"commons_name":"CRDC Cancer Imaging Data Commons"}}},{"tcga_read":{"gen3_discovery":{"commons":"CRDC Cancer Imaging Data Commons","_unique_id":"tcga_read","study_title":"tcga_read","accession_number":"tcga_read","short_name":"TCGA_READ","full_name":"TCGA_READ","dbgap_accession_number":"TCGA_READ","study_description":" The Cancer Genome Atlas-Rectum Adenocarcinoma (TCGA-READ) data collection is part of a larger effort to enhance the TCGA http://cancergenome.nih.gov/ data set with characterized radiological images. The Cancer Imaging Program (CIP), with the cooperation of several TCGA tissue-contributing institutions, has archived a large portion of the radiological images of the genetically-analyzed READ cases. Please see the TCGA-READ wiki page to learn more about the radiology images and to obtain any supporting metadata for this collection. Please see the DICOM converted Slide Microscopy images for the TCGA-READ collection page to learn more about the histopathology images and to obtain any supporting metadata for this collection.","image_types":"CT, MR, ANN, SEG, SM, SEG","_subjects_count":171,"doi":"10.7937/K9/TCIA.2016.F7PPNPNU 10.5281/ZENODO.12689998 10.5281/ZENODO.11099004 10.5281/ZENODO.16966285","species":"Human","disease_type":"Rectal Adenocarcinoma","data_type":"Clinical, Genomics, Histopathology","primary_site":"Rectum","tags":[{"name":"Rectal Adenocarcinoma","category":"disease_type"},{"name":"Clinical, Genomics, Histopathology","category":"data_type"},{"name":"Rectum","category":"primary_site"}],"commons_name":"CRDC Cancer Imaging Data Commons"}}},{"ispy1":{"gen3_discovery":{"commons":"CRDC Cancer Imaging Data Commons","_unique_id":"ispy1","study_title":"ispy1","accession_number":"ispy1","short_name":"ISPY1","full_name":"ISPY1","dbgap_accession_number":"ISPY1","study_description":"ISPY1/ACRIN 6657 was designed as a prospective study to test MRI for ability to predict response to treatment and risk-of-recurrence in patients with stage 2 or 3 breast cancer receiving neoadjuvant chemotherapy (NACT). ACRIN 6657 was conducted as a companion study to CALGB 150007, a correlative science study evaluating tissue-based biomarkers in the setting of neoadjuvant treatment of breast cancer. Collectively, CALGB 150007 and ACRIN 6657 formed the basis of the multicenter Investigation of Serial Studies to Predict Your Therapeutic Response with Imaging and moLecular Analysis (I-SPY TRIAL) breast cancer trial, a study of imaging and tissue-based biomarkers for predicting pathologic complete response (pCR) and recurrence-free survival (RFS).The collection consists of 847 MR studies from 222 subjects.Please see the ISPY1 page to learn more about the images and to obtain any supporting metadata for this collection.","image_types":"SR, MR, SEG","_subjects_count":222,"doi":"10.7937/TCIA.2019.WGLLSSG1 10.7937/K9/TCIA.2016.HDHPGJLK","species":"Human","disease_type":"Breast Cancer","data_type":"Clinical, Image Analyses","primary_site":"Breast","tags":[{"name":"Breast Cancer","category":"disease_type"},{"name":"Clinical, Image Analyses","category":"data_type"},{"name":"Breast","category":"primary_site"}],"commons_name":"CRDC Cancer Imaging Data Commons"}}},{"lidc_idri":{"gen3_discovery":{"commons":"CRDC Cancer Imaging Data Commons","_unique_id":"lidc_idri","study_title":"lidc_idri","accession_number":"lidc_idri","short_name":"LIDC_IDRI","full_name":"LIDC_IDRI","dbgap_accession_number":"LIDC_IDRI","study_description":"The Lung Image Database Consortium (LIDC-IDRI) image collection consists of diagnostic and lung cancer screening thoracic CT scans with marked-up annotated lesions. It is a web-accessible international resource for development, training, and evaluation of computer-assisted diagnostic (CAD) methods for lung cancer detection and diagnosis. For more information about the LIDC-IDRI images please visit the LIDC-IDRI page.  For comprehensive information about utilizing the associated metadata please see the Research Project page for the Lung Image Database Consortium .","image_types":"SEG, SR, CR, CT, DX, SEG","_subjects_count":1010,"doi":"10.7937/K9/TCIA.2015.LO9QL9SX 10.7937/K9/TCIA.2015.1BUVFJR7 10.7937/TCIA.2018.H7UMFURQ","species":"Human","disease_type":"Lung Cancer, Non-Cancer, Metastatic disease","data_type":"Clinical, Image Analyses, Software/Source Code","primary_site":"Chest","tags":[{"name":"Lung Cancer, Non-Cancer, Metastatic disease","category":"disease_type"},{"name":"Clinical, Image Analyses, Software/Source Code","category":"data_type"},{"name":"Chest","category":"primary_site"}],"commons_name":"CRDC Cancer Imaging Data Commons"}}},{"tcga_luad":{"gen3_discovery":{"commons":"CRDC Cancer Imaging Data Commons","_unique_id":"tcga_luad","study_title":"tcga_luad","accession_number":"tcga_luad","short_name":"TCGA_LUAD","full_name":"TCGA_LUAD","dbgap_accession_number":"TCGA_LUAD","study_description":"The Cancer Imaging Program (CIP) is working directly with primary investigators from institutes participating in TCGA to obtain and load images relating to the genomic, clinical, and pathological data being stored within the TCGA Data Portal Currently this large CT multi-sequence image collection of lung adenocarcinoma (LUAD) patients can be matched by each unique case identifier with the extensive gene and expression data of the same case from The Cancer Genome Atlas Data Portal to research the link between clinical phenome and tissue genome.Please see the TCGA-LUAD page to learn more about the radiology images and to obtain any supporting metadata for this collection. Please see the DICOM converted Slide Microscopy images for the TCGA-LUAD collection page to learn more about the histopathology images and to obtain any supporting metadata for this collection.","image_types":"SEG, SM, ANN, SEG, CT, NM, PT","_subjects_count":560,"doi":"10.5281/ZENODO.8345959 10.7937/K9/TCIA.2016.JGNIHEP5 10.5281/ZENODO.16966285 10.5281/ZENODO.11099004 10.5281/ZENODO.12689915","species":"Human","disease_type":"Lung Adenocarcinoma","data_type":"Clinical, Genomics, Histopathology, Image Analyses","primary_site":"Chest","tags":[{"name":"Lung Adenocarcinoma","category":"disease_type"},{"name":"Clinical, Genomics, Histopathology, Image Analyses","category":"data_type"},{"name":"Chest","category":"primary_site"}],"commons_name":"CRDC Cancer Imaging Data Commons"}}},{"tcga_lihc":{"gen3_discovery":{"commons":"CRDC Cancer Imaging Data Commons","_unique_id":"tcga_lihc","study_title":"tcga_lihc","accession_number":"tcga_lihc","short_name":"TCGA_LIHC","full_name":"TCGA_LIHC","dbgap_accession_number":"TCGA_LIHC","study_description":"The Cancer Imaging Program (CIP) is working directly with primary investigators from institutes participating in TCGA to obtain and load images relating to the genomic, clinical, and pathological data being stored within the TCGA Data Portal. Currently this CT and MR multi-sequence image collection of liver hepatocellular carcinoma (LIHC) patients can be matched by each unique case identifier with the extensive gene and expression data of the same case from The Cancer Genome Atlas Data Portal to research the link between clinical phenome and tissue genome.Please see the TCGA-LIHC page to learn more about the radiology images and to obtain any supporting metadata for this collection. Please see the DICOM converted Slide Microscopy images for the TCGA-LIHC collection page to learn more about the histopathology images and to obtain any supporting metadata for this collection.","image_types":"CT, MR, PT, SEG, SM","_subjects_count":377,"doi":"10.7937/K9/TCIA.2016.IMMQW8UQ 10.5281/ZENODO.12690002 10.5281/ZENODO.16966285 10.5281/ZENODO.8345959","species":"Human","disease_type":"Liver Hepatocellular Carcinoma","data_type":"Clinical, Genomics, Histopathology, Image Analyses","primary_site":"Liver","tags":[{"name":"Liver Hepatocellular Carcinoma","category":"disease_type"},{"name":"Clinical, Genomics, Histopathology, Image Analyses","category":"data_type"},{"name":"Liver","category":"primary_site"}],"commons_name":"CRDC Cancer Imaging Data Commons"}}},{"tcga_brca":{"gen3_discovery":{"commons":"CRDC Cancer Imaging Data Commons","_unique_id":"tcga_brca","study_title":"tcga_brca","accession_number":"tcga_brca","short_name":"TCGA_BRCA","full_name":"TCGA_BRCA","dbgap_accession_number":"TCGA_BRCA","study_description":"The Cancer Imaging Program (CIP) is working directly with primary investigators from institutes participating in TCGA to obtain and load images relating to the genomic, clinical, and pathological data being stored within the TCGA Data Portal. Currently this MR multi-sequence image collection of breast invasive carcinoma patients can be matched by each unique case identifier with the extensive gene and expression data of the same case from The Cancer Genome Atlas Data Portal to research the link between clinical phenome and tissue genome. Please see the TCGA-BRCA page to learn more about the radiology images and to obtain any supporting metadata for this collection. Please see the DICOM converted Slide Microscopy images for the TCGA-BRCA collection page to learn more about the histopathology images and to obtain any supporting metadata for this collection.","image_types":"SM, ANN, SEG, SR, MG, MR, SEG","_subjects_count":1098,"doi":"10.5281/ZENODO.16966285 10.7937/K9/TCIA.2016.AB2NAZRP 10.5281/ZENODO.11099004 10.5281/ZENODO.12689962 10.7937/TCIA.2019.WGLLSSG1","species":"Human","disease_type":"Breast Cancer","data_type":"Clinical, Genomics, Image Analyses, Histopathology","primary_site":"Breast","tags":[{"name":"Breast Cancer","category":"disease_type"},{"name":"Clinical, Genomics, Image Analyses, Histopathology","category":"data_type"},{"name":"Breast","category":"primary_site"}],"commons_name":"CRDC Cancer Imaging Data Commons"}}},{"tcga_ov":{"gen3_discovery":{"commons":"CRDC Cancer Imaging Data Commons","_unique_id":"tcga_ov","study_title":"tcga_ov","accession_number":"tcga_ov","short_name":"TCGA_OV","full_name":"TCGA_OV","dbgap_accession_number":"TCGA_OV","study_description":" The Cancer Genome Atlas-Ovarian Cancer (TCGA-OV) data collection is part of a larger effort to enhance the TCGA http://cancergenome.nih.gov/ data set with characterized radiological images. The Cancer Imaging Program (CIP) with the cooperation of several of the TCGA tissue-contributing institutions are working to archive a large portion of the radiological images of the genetically-analyzed OV cases. Please see the TCGA-OV page to learn more about the radiology images and to obtain any supporting metadata for this collection. Please see the DICOM converted Slide Microscopy images for the TCGA-OV collection page to learn more about the histopathology images and to obtain any supporting metadata for this collection.","image_types":"SM, CT, MR, OT, SEG","_subjects_count":591,"doi":"10.7937/K9/TCIA.2016.NDO1MDFQ 10.5281/ZENODO.16966285 10.5281/ZENODO.12689954","species":"Human","disease_type":"Ovarian Serous Cystadenocarcinoma","data_type":"Clinical, Genomics, Image Analyses, Histopathology","primary_site":"Ovary","tags":[{"name":"Ovarian Serous Cystadenocarcinoma","category":"disease_type"},{"name":"Clinical, Genomics, Image Analyses, Histopathology","category":"data_type"},{"name":"Ovary","category":"primary_site"}],"commons_name":"CRDC Cancer Imaging Data Commons"}}},{"tcga_kirc":{"gen3_discovery":{"commons":"CRDC Cancer Imaging Data Commons","_unique_id":"tcga_kirc","study_title":"tcga_kirc","accession_number":"tcga_kirc","short_name":"TCGA_KIRC","full_name":"TCGA_KIRC","dbgap_accession_number":"TCGA_KIRC","study_description":"The Cancer Imaging Program (CIP) is working directly with primary investigators from institutes participating in TCGA to obtain and load images relating to the genomic, clinical, and pathological data being stored within the TCGA Data Portal. Currently this large CT and MR multi-sequence image collection of kidney renal clear cell carcinoma (KIRC) patients can be matched by each unique case identifier with the extensive gene and expression data of the same case from The Cancer Genome Atlas Data Portal to research the link between clinical phenome and tissue genome.Please see the TCGA -KIRC page to learn more about the radiology images and to obtain any supporting metadata for this collection. Please see the DICOM converted Slide Microscopy images for the TCGA-KIRC collection page to learn more about the histopathology images and to obtain any supporting metadata for this collection.","image_types":"SEG, SM, CR, CT, MR","_subjects_count":537,"doi":"10.5281/ZENODO.16966285 10.5281/ZENODO.8345959 10.5281/ZENODO.12689952 10.7937/K9/TCIA.2016.V6PBVTDR","species":"Human","disease_type":"Kidney Renal Clear Cell Carcinoma","data_type":"Clinical, Genomics, Image Analyses, Histopathology","primary_site":"Kidney","tags":[{"name":"Kidney Renal Clear Cell Carcinoma","category":"disease_type"},{"name":"Clinical, Genomics, Image Analyses, Histopathology","category":"data_type"},{"name":"Kidney","category":"primary_site"}],"commons_name":"CRDC Cancer Imaging Data Commons"}}},{"tcga_lgg":{"gen3_discovery":{"commons":"CRDC Cancer Imaging Data Commons","_unique_id":"tcga_lgg","study_title":"tcga_lgg","accession_number":"tcga_lgg","short_name":"TCGA_LGG","full_name":"TCGA_LGG","dbgap_accession_number":"TCGA_LGG","study_description":" Note: This collection has special restrictions on its usage. See Data Usage Policies and Restrictions .The Cancer Imaging Program (CIP) is working directly with primary investigators from institutes participating in TCGA to obtain and load images relating to the genomic, clinical, and pathological data being stored within the TCGA Data Portal. Currently this large MR multi-sequence image collection of low grade glioma patients can be matched by each unique case identifier with the extensive gene and expression data of the same case from The Cancer Genome Atlas Data Portal to research the link between clinical phenome and tissue genome.Please see the TCGA-LGG page to learn more about the radiology images and to obtain any supporting metadata for this collection. Please see the DICOM converted Slide Microscopy images for the TCGA-LGG collection page to learn more about the histopathology images and to obtain any supporting metadata for this collection.","image_types":"SM","_subjects_count":516,"doi":"10.5281/ZENODO.12689948","species":"Human","disease_type":"Low Grade GLioma","data_type":"Clinical, Genomics, Histopathology, Image Analyses","primary_site":"Brain","tags":[{"name":"Low Grade GLioma","category":"disease_type"},{"name":"Clinical, Genomics, Histopathology, Image Analyses","category":"data_type"},{"name":"Brain","category":"primary_site"}],"commons_name":"CRDC Cancer Imaging Data Commons"}}},{"tcga_gbm":{"gen3_discovery":{"commons":"CRDC Cancer Imaging Data Commons","_unique_id":"tcga_gbm","study_title":"tcga_gbm","accession_number":"tcga_gbm","short_name":"TCGA_GBM","full_name":"TCGA_GBM","dbgap_accession_number":"TCGA_GBM","study_description":"The Cancer Imaging Program (CIP) is working directly with primary investigators from institutes participating in TCGA to obtain and load images relating to the genomic, clinical, and pathological data being stored within the TCGA Data Portal Currently this large MR multi-sequence image collection of glioblastoma patients can be matched by each unique case identifier with the extensive gene and expression data of the same case from The Cancer Genome Atlas Data Portal to research the link between clinical phenome and tissue genome. Please see the TCGA-GBM page to learn more about the radiology images and to obtain any supporting metadata for this collection. Please see the DICOM converted Slide Microscopy images for the TCGA-GBM collection page to learn more about the histopathology images and to obtain any supporting metadata for this collection.","image_types":"OT, ANN, SEG, SM","_subjects_count":607,"doi":"10.5281/ZENODO.11099004 10.5281/ZENODO.17470190 10.5281/ZENODO.12690010","species":"Human","disease_type":"Glioblastoma Multiforme","data_type":"Clinical, Genomics, Image Analyses, Histopathology","primary_site":"Brain","tags":[{"name":"Glioblastoma Multiforme","category":"disease_type"},{"name":"Clinical, Genomics, Image Analyses, Histopathology","category":"data_type"},{"name":"Brain","category":"primary_site"}],"commons_name":"CRDC Cancer Imaging Data Commons"}}},{"nsclc_radiomics":{"gen3_discovery":{"commons":"CRDC Cancer Imaging Data Commons","_unique_id":"nsclc_radiomics","study_title":"nsclc_radiomics","accession_number":"nsclc_radiomics","short_name":"NSCLC_RADIOMICS","full_name":"NSCLC_RADIOMICS","dbgap_accession_number":"NSCLC_RADIOMICS","study_description":"This collection contains images from 422 non-small cell lung cancer (NSCLC) patients. For these patients pretreatment CT scans and clinical outcome data are available. This dataset refers to the Lung1 dataset of the study published in Nature CommunicationsPlease see the NSCLC-Radiomics page to learn more about the images and to obtain any supporting metadata for this collection.","image_types":"SEG, SR, CT, RTSTRUCT, SEG","_subjects_count":422,"doi":"10.5281/ZENODO.7473970 10.7937/K9/TCIA.2015.PF0M9REI","species":"Human","disease_type":"Lung Cancer","data_type":"Clinical, Image Analyses","primary_site":"Lung","tags":[{"name":"Lung Cancer","category":"disease_type"},{"name":"Clinical, Image Analyses","category":"data_type"},{"name":"Lung","category":"primary_site"}],"commons_name":"CRDC Cancer Imaging Data Commons"}}},{"mouse_astrocytoma":{"gen3_discovery":{"commons":"CRDC Cancer Imaging Data Commons","_unique_id":"mouse_astrocytoma","study_title":"mouse_astrocytoma","accession_number":"mouse_astrocytoma","short_name":"MOUSE_ASTROCYTOMA","full_name":"MOUSE_ASTROCYTOMA","dbgap_accession_number":"MOUSE_ASTROCYTOMA","study_description":"This collection consists of magnetic resonance images (MRI) of genetically engineered mouse models (GEMMs) of high grade astrocytoma, including glioblastoma multiforme (GBM).The MRI data contained herein includes anatomic T2 weighted images and dynamic contrast enhanced MRI.Please see the Mouse-Astrocytoma page to learn more about the images and to obtain any supporting metadata for this collection.","image_types":"MR","_subjects_count":48,"doi":"10.7937/K9TCIA.2017.SGW7CAQW","species":"Mouse","disease_type":"Glioblastoma Multiforme","data_type":"","primary_site":"Head","tags":[{"name":"Glioblastoma Multiforme","category":"disease_type"},{"name":"","category":"data_type"},{"name":"Head","category":"primary_site"}],"commons_name":"CRDC Cancer Imaging Data Commons"}}},{"anti_pd_1_lung":{"gen3_discovery":{"commons":"CRDC Cancer Imaging Data Commons","_unique_id":"anti_pd_1_lung","study_title":"anti_pd_1_lung","accession_number":"anti_pd_1_lung","short_name":"ANTI_PD_1_LUNG","full_name":"ANTI_PD_1_LUNG","dbgap_accession_number":"ANTI_PD_1_LUNG","study_description":"This collection includes 46 lung cases treated with anti-PD1 immunotherapy in 2016, each with pre-treatment imaging (CT,PT,SC) and most with 1 imaging follow-up timepoint.Please see the Anti-PD-1_Lung wiki page to learn more about the images and to obtain any supporting metadata for this collection.","image_types":"SEG, CT, PT, SC","_subjects_count":46,"doi":"10.5281/ZENODO.8345959 10.7937/TCIA.2019.ZJJWB9IP","species":"Human","disease_type":"Lung Cancer","data_type":"","primary_site":"Lung","tags":[{"name":"Lung Cancer","category":"disease_type"},{"name":"","category":"data_type"},{"name":"Lung","category":"primary_site"}],"commons_name":"CRDC Cancer Imaging Data Commons"}}},{"rider_lung_pet_ct":{"gen3_discovery":{"commons":"CRDC Cancer Imaging Data Commons","_unique_id":"rider_lung_pet_ct","study_title":"rider_lung_pet_ct","accession_number":"rider_lung_pet_ct","short_name":"RIDER_LUNG_PET_CT","full_name":"RIDER_LUNG_PET_CT","dbgap_accession_number":"RIDER_LUNG_PET_CT","study_description":"RIDER Lung PET-CT is a subsection of the broader Reference Image Database to Evaluate Therapy Response (RIDER) collection. RIDER is a targeted data collection for the purpose of generating an initial consensus on how to harmonize data collection and analysis for quantitative imaging methods as applied to measure the response to drug or radiation therapy. The long term goal is to provide a resource to permit harmonized methods for data collection and analysis across different commercial imaging platforms, as required to support multi-site clinical trials, using imaging as a biomarker for therapy response.More information about the RIDER Lung PET-CT sub-collection can be found in the corresponding section of the RIDER wiki page.","image_types":"SEG, CT, PT","_subjects_count":243,"doi":"10.7937/K9/TCIA.2015.OFIP7TVM 10.5281/ZENODO.8345959","species":"Human","disease_type":"Lung Cancer","data_type":"","primary_site":"Lung","tags":[{"name":"Lung Cancer","category":"disease_type"},{"name":"","category":"data_type"},{"name":"Lung","category":"primary_site"}],"commons_name":"CRDC Cancer Imaging Data Commons"}}},{"victre":{"gen3_discovery":{"commons":"CRDC Cancer Imaging Data Commons","_unique_id":"victre","study_title":"victre","accession_number":"victre","short_name":"VICTRE","full_name":"VICTRE","dbgap_accession_number":"VICTRE","study_description":"The VICTRE Trial: Open-Source, In-Silico Clinical Trial For Evaluating Digital Breast TomosynthesisA total of 2986 subjects, with breast sizes and radiographic densities representative of a screening population and compressed thicknesses from 3.5 to 6 cm, were simulated and imaged on in-silico versions of DM and DBT systems using fast Monte Carlo x-ray transport. Images were interpreted by a computational reader detecting the presence of lesions. The in-silico trial (VICTRE) was designed to replicate a comparative trial from a previous regulatory submission. The endpoint was the difference in area under the receiver-operating-characteristic curve between modalities (delta-AUC) for lesion detection.See the VICTRE Collection wiki page to learn more about the images and to obtain any supporting metadata for this collection.","image_types":"MG","_subjects_count":2994,"doi":"10.7937/TCIA.2019.HO23NXAW","species":"Human","disease_type":"Breast Cancer","data_type":"Software/Source Code","primary_site":"Breast","tags":[{"name":"Breast Cancer","category":"disease_type"},{"name":"Software/Source Code","category":"data_type"},{"name":"Breast","category":"primary_site"}],"commons_name":"CRDC Cancer Imaging Data Commons"}}},{"rider_breast_mri":{"gen3_discovery":{"commons":"CRDC Cancer Imaging Data Commons","_unique_id":"rider_breast_mri","study_title":"rider_breast_mri","accession_number":"rider_breast_mri","short_name":"RIDER_BREAST_MRI","full_name":"RIDER_BREAST_MRI","dbgap_accession_number":"RIDER_BREAST_MRI","study_description":"RIDER Breast MRI is a subsection of the broader Reference Image Database to Evaluate Therapy Response (RIDER) collection. RIDER is a targeted data collection for the purpose of generating an initial consensus on how to harmonize data collection and analysis for quantitative imaging methods as applied to measure the response to drug or radiation therapy. The long term goal is to provide a resource to permit harmonized methods for data collection and analysis across different commercial imaging platforms, as required to support multi-site clinical trials, using imaging as a biomarker for therapy response.More information about the RIDER Breast MRI sub-collection page can be found in the corresponding section of the RIDER wiki page.","image_types":"MR","_subjects_count":5,"doi":"10.7937/K9/TCIA.2015.H1SXNUXL","species":"Human","disease_type":"Breast Cancer","data_type":"","primary_site":"Breast","tags":[{"name":"Breast Cancer","category":"disease_type"},{"name":"","category":"data_type"},{"name":"Breast","category":"primary_site"}],"commons_name":"CRDC Cancer Imaging Data Commons"}}},{"c4kc_kits":{"gen3_discovery":{"commons":"CRDC Cancer Imaging Data Commons","_unique_id":"c4kc_kits","study_title":"c4kc_kits","accession_number":"c4kc_kits","short_name":"C4KC_KITS","full_name":"C4KC_KITS","dbgap_accession_number":"C4KC_KITS","study_description":"Data from the training set of the 2019 Kidney and Kidney Tumor Segmentation Challenge (C4KC-KiTS)This collection contains subjects from the training set of the 2019 Kidney and Kidney Tumor Segmentation Challenge (KiTS19). The challenge aimed to accelerate progress in automatic 3D semantic segmentation by releasing a dataset of CT scans for 210 patients with manual semantic segmentations of the kidneys and tumors in the corticomedullary phase.The imaging was collected during routine care of patients who were treated by either partial or radical nephrectomy at the University of Minnesota Medical Center. Many of the CT scans were acquired at referring institutions and are therefore heterogeneous in terms of scanner manufacturers and acquisition protocols. Semantic segmentations were performed by students under the supervision of an experienced urologic cancer surgeon.Please see the C4KC-KiTS wiki page to learn more about the images and to obtain any supporting metadata for this collection.","image_types":"CT, SEG","_subjects_count":210,"doi":"10.7937/TCIA.2019.IX49E8NX","species":"Human","disease_type":"Kidney Cancer","data_type":"","primary_site":"Kidney","tags":[{"name":"Kidney Cancer","category":"disease_type"},{"name":"","category":"data_type"},{"name":"Kidney","category":"primary_site"}],"commons_name":"CRDC Cancer Imaging Data Commons"}}},{"mouse_mammary":{"gen3_discovery":{"commons":"CRDC Cancer Imaging Data Commons","_unique_id":"mouse_mammary","study_title":"mouse_mammary","accession_number":"mouse_mammary","short_name":"MOUSE_MAMMARY","full_name":"MOUSE_MAMMARY","dbgap_accession_number":"MOUSE_MAMMARY","study_description":"This collection consists of Magnetic Resonance Imaging (MRI) of mouse breast cancer in 32 mice. Please see the Mouse-Mammary wiki page to learn more about the images and to obtain any supporting metadata for this collection.","image_types":"MR","_subjects_count":32,"doi":"10.7937/K9/TCIA.2015.9P42KSE6","species":"Mouse","disease_type":"Breast Cancer","data_type":"","primary_site":"Abdomen","tags":[{"name":"Breast Cancer","category":"disease_type"},{"name":"","category":"data_type"},{"name":"Abdomen","category":"primary_site"}],"commons_name":"CRDC Cancer Imaging Data Commons"}}},{"dro_toolkit":{"gen3_discovery":{"commons":"CRDC Cancer Imaging Data Commons","_unique_id":"dro_toolkit","study_title":"dro_toolkit","accession_number":"dro_toolkit","short_name":"DRO_TOOLKIT","full_name":"DRO_TOOLKIT","dbgap_accession_number":"DRO_TOOLKIT","study_description":"DRO Toolkit: This is a sample collection of synthetic 3D Digital Reference Objects (DROs) intended for standardization of quantitative imaging feature extraction pipelines. We have developed a software toolkit for the creation of DROs with customizable size, shape, intensity, texture, and margin sharpness values. Using user-supplied input parameters, these objects are defined mathematically as continuous functions, discretized, and then saved as DICOM objects. This collection includes objects with a range of values for the various feature categories and many combinations of these categories.Please see the DRO Toolkit page to learn more about the images and to obtain the supporting metadata for this collection.","image_types":"CT, SEG","_subjects_count":32,"doi":"10.7937/T062-8262","species":"Human","disease_type":"Phantom","data_type":"Software/Source Code","primary_site":"Phantom","tags":[{"name":"Phantom","category":"disease_type"},{"name":"Software/Source Code","category":"data_type"},{"name":"Phantom","category":"primary_site"}],"commons_name":"CRDC Cancer Imaging Data Commons"}}},{"cc_radiomics_phantom_2":{"gen3_discovery":{"commons":"CRDC Cancer Imaging Data Commons","_unique_id":"cc_radiomics_phantom_2","study_title":"cc_radiomics_phantom_2","accession_number":"cc_radiomics_phantom_2","short_name":"CC_RADIOMICS_PHANTOM_2","full_name":"CC_RADIOMICS_PHANTOM_2","dbgap_accession_number":"CC_RADIOMICS_PHANTOM_2","study_description":"Credence Cartridge Radiomics Phantom CT Scans with Controlled Scanning Approach (CC-Radiomics-Phantom-2)This collection consists of 251 CT scans of the Credence Cartridge Radiomic (CCR) phantom. This texture phantom was developed to investigate the feature robustness in the emerging field of radiomics. This phantom dataset was acquired on 4-8 CT scanners using a set of imaging parameters (e.g., reconstruction Field of View, Slice thickness, reconstruction kernels, mAs, and Pitch). A controlled scanning approach was employed to assess the variability in radiomic features due to each imaging parameter. This dataset will be useful to radiomic research community to identify a subset of robust radiomic features and for establishing the ground truths for future clinical investigations.Using this dataset, the numerical values of radiomic features can be cross-validated by other research groups using their own feature extraction tools.Please see the CC-Radiomics-Phantom-2 wiki page to learn more about the images and to obtain any supporting metadata for this collection.","image_types":"CT","_subjects_count":251,"doi":"10.7937/TCIA.2019.4L24TZ5G","species":"Human","disease_type":"Phantom","data_type":"","primary_site":"Phantom","tags":[{"name":"Phantom","category":"disease_type"},{"name":"","category":"data_type"},{"name":"Phantom","category":"primary_site"}],"commons_name":"CRDC Cancer Imaging Data Commons"}}},{"qin_pet_phantom":{"gen3_discovery":{"commons":"CRDC Cancer Imaging Data Commons","_unique_id":"qin_pet_phantom","study_title":"qin_pet_phantom","accession_number":"qin_pet_phantom","short_name":"QIN_PET_PHANTOM","full_name":"QIN_PET_PHANTOM","dbgap_accession_number":"QIN_PET_PHANTOM","study_description":"This collection consists of positron emission tomography (PET) phantom scans originally utilized by the Quantitative Imaging Network (QIN) PET Segmentation Challenge to assess the variability of segmentations and subsequently derived quantitative analysis results on phantom PET scans with known ground truth.Please see the QIN PET Phantom page to learn more about the images and to obtain any supporting metadata for this collection. ","image_types":"PT","_subjects_count":2,"doi":"10.7937/K9/TCIA.2015.ZPUKHCKB","species":"Human","disease_type":"Phantom","data_type":"","primary_site":"Phantom","tags":[{"name":"Phantom","category":"disease_type"},{"name":"","category":"data_type"},{"name":"Phantom","category":"primary_site"}],"commons_name":"CRDC Cancer Imaging Data Commons"}}},{"qiba_ct_1c":{"gen3_discovery":{"commons":"CRDC Cancer Imaging Data Commons","_unique_id":"qiba_ct_1c","study_title":"qiba_ct_1c","accession_number":"qiba_ct_1c","short_name":"QIBA_CT_1C","full_name":"QIBA_CT_1C","dbgap_accession_number":"QIBA_CT_1C","study_description":"Phantom data provided by the RSNA Quantitative Imaging Biomarkers Alliance,,s 1C group.  Please see the QIBA wiki page through RSNA, and TCIA,,s QIBA CT-1C page,  to learn more about the images and to obtain any supporting metadata for this collection.","image_types":"CT, PR, SEG, SR","_subjects_count":1,"doi":"10.7937/K9/TCIA.2016.YXGR4BLU","species":"Human","disease_type":"Phantom","data_type":"","primary_site":"Phantom","tags":[{"name":"Phantom","category":"disease_type"},{"name":"","category":"data_type"},{"name":"Phantom","category":"primary_site"}],"commons_name":"CRDC Cancer Imaging Data Commons"}}},{"rider_phantom_mri":{"gen3_discovery":{"commons":"CRDC Cancer Imaging Data Commons","_unique_id":"rider_phantom_mri","study_title":"rider_phantom_mri","accession_number":"rider_phantom_mri","short_name":"RIDER_PHANTOM_MRI","full_name":"RIDER_PHANTOM_MRI","dbgap_accession_number":"RIDER_PHANTOM_MRI","study_description":" RIDER Phantom MRI is a subsection of the broader Reference Image Database to Evaluate Therapy Response (RIDER) collection.RIDER is a targeted data collection for the purpose of generating an initial consensus on how to harmonize data collection and analysis for quantitative imaging methods as applied to measure the response to drug or radiation therapy. The long term goal is to provide a resource to permit harmonized methods for data collection and analysis across different commercial imaging platforms, as required to support multi-site clinical trials, using imaging as a biomarker for therapy response. More information about the RIDER Phantom MRI sub-collection page can be found in the corresponding section of the RIDER wiki page. ","image_types":"MR","_subjects_count":10,"doi":"10.7937/K9/TCIA.2015.MI4QDDHU","species":"Human","disease_type":"Phantom","data_type":"","primary_site":"Phantom","tags":[{"name":"Phantom","category":"disease_type"},{"name":"","category":"data_type"},{"name":"Phantom","category":"primary_site"}],"commons_name":"CRDC Cancer Imaging Data Commons"}}},{"pseudo_phi_dicom_data":{"gen3_discovery":{"commons":"CRDC Cancer Imaging Data Commons","_unique_id":"pseudo_phi_dicom_data","study_title":"pseudo_phi_dicom_data","accession_number":"pseudo_phi_dicom_data","short_name":"PSEUDO_PHI_DICOM_DATA","full_name":"PSEUDO_PHI_DICOM_DATA","dbgap_accession_number":"PSEUDO_PHI_DICOM_DATA","study_description":"The process of image de-identification is time consuming, requires significant human resources, and is prone to human error. Automated image de-identification algorithms have been developed but the research community requires some method of evaluation before such tools can be widely accepted. This evaluation requires a robust dataset that can be used as part of an evaluation process for de-identification algorithms. We developed a DICOM dataset that can be used to evaluate the performance of de-identification algorithms. Please see the Medical Imaging De-Identification Initiative (MIDI) wiki page to learn more about the images and to obtain any supporting metadata for this collection.","image_types":"CR, CT, DX, MG, MR, PT","_subjects_count":42,"doi":"10.7937/S17Z-R072","species":"Human","disease_type":"Various","data_type":"","primary_site":"Various","tags":[{"name":"Various","category":"disease_type"},{"name":"","category":"data_type"},{"name":"Various","category":"primary_site"}],"commons_name":"CRDC Cancer Imaging Data Commons"}}},{"naf_prostate":{"gen3_discovery":{"commons":"CRDC Cancer Imaging Data Commons","_unique_id":"naf_prostate","study_title":"naf_prostate","accession_number":"naf_prostate","short_name":"NAF_PROSTATE","full_name":"NAF_PROSTATE","dbgap_accession_number":"NAF_PROSTATE","study_description":"This is a collection of F-18 NaF positron emission tomography/computed tomography (PET/CT) images in patients with prostate cancer, with suspected or known bone involvement.Please see the NaF PROSTATE page to learn more about the images and to obtain any supporting metadata for this collection.","image_types":"CT, PT","_subjects_count":9,"doi":"10.7937/K9/TCIA.2015.ISOQTHKO","species":"Human","disease_type":"Prostate Cancer","data_type":"","primary_site":"Prostate","tags":[{"name":"Prostate Cancer","category":"disease_type"},{"name":"","category":"data_type"},{"name":"Prostate","category":"primary_site"}],"commons_name":"CRDC Cancer Imaging Data Commons"}}},{"prostate_mri":{"gen3_discovery":{"commons":"CRDC Cancer Imaging Data Commons","_unique_id":"prostate_mri","study_title":"prostate_mri","accession_number":"prostate_mri","short_name":"PROSTATE_MRI","full_name":"PROSTATE_MRI","dbgap_accession_number":"PROSTATE_MRI","study_description":"This is a collection of MRIs of the prostate obtained with an endorectal coil and phased array surface coil at 3T (Philips Achieva). Each patient had biopsy confirmation of cancer and then underwent robotic assisted radical prostatectomy. A mold was generated from each MRI and the prostatectomy specimen was first placed in the mold and then cut in the same plane as the MRI. The data was generated at the National Cancer Institute, Bethesda, Maryland, USA between 2008-2010.Please see the Prostate-MRI page to learn more about the images and to obtain any supporting metadata for this collection.","image_types":"MR","_subjects_count":26,"doi":"10.7937/K9/TCIA.2016.6046GUDV","species":"Human","disease_type":"Prostate Cancer","data_type":"","primary_site":"Prostate","tags":[{"name":"Prostate Cancer","category":"disease_type"},{"name":"","category":"data_type"},{"name":"Prostate","category":"primary_site"}],"commons_name":"CRDC Cancer Imaging Data Commons"}}},{"phantom_fda":{"gen3_discovery":{"commons":"CRDC Cancer Imaging Data Commons","_unique_id":"phantom_fda","study_title":"phantom_fda","accession_number":"phantom_fda","short_name":"PHANTOM_FDA","full_name":"PHANTOM_FDA","dbgap_accession_number":"PHANTOM_FDA","study_description":"A series of CT sets scanned at differing slice thicknesses and exposure parameters of a chest simulating phantom containing lung nodules. It was constructed by an NCI-FDA joint effort to provide data for nodule-detecting CAD processes.Please see the Phantom FDA page to learn more about the images and to obtain any supporting metadata for this collection.","image_types":"CT","_subjects_count":7,"doi":"10.7937/K9/TCIA.2015.ORBJKMUX","species":"Human","disease_type":"Phantom","data_type":"","primary_site":"Lung Phantom","tags":[{"name":"Phantom","category":"disease_type"},{"name":"","category":"data_type"},{"name":"Lung Phantom","category":"primary_site"}],"commons_name":"CRDC Cancer Imaging Data Commons"}}},{"midrc_ricord_1b":{"gen3_discovery":{"commons":"CRDC Cancer Imaging Data Commons","_unique_id":"midrc_ricord_1b","study_title":"midrc_ricord_1b","accession_number":"midrc_ricord_1b","short_name":"MIDRC_RICORD_1B","full_name":"MIDRC_RICORD_1B","dbgap_accession_number":"MIDRC_RICORD_1B","study_description":"The first multi-institutional, multi-national expert annotated COVID-19 imaging dataset made freely available to the machine learning community as a research and educational resource for COVID-19 chest imaging. The Radiological Society of North America (RSNA) assembled the RSNA International COVID-19 Open Radiology Database (RICORD) collection of COVID-related imaging datasets and expert annotations to support research and education. RICORD data will be incorporated in the Medical Imaging and Data Resource Center (MIDRC) , a multi-institutional research data repository funded by the National Institute of Biomedical Imaging and Bioengineering of the National Institutes of Health.Please see the MIDRC-RICORD-1b wiki page to learn more about the images and to obtain any supporting metadata for this collection.","image_types":"CT","_subjects_count":117,"doi":"10.7937/31V8-4A40","species":"Human","disease_type":"COVID-19 (non-cancer)","data_type":"Clinical","primary_site":"Lung","tags":[{"name":"COVID-19 (non-cancer)","category":"disease_type"},{"name":"Clinical","category":"data_type"},{"name":"Lung","category":"primary_site"}],"commons_name":"CRDC Cancer Imaging Data Commons"}}},{"midrc_ricord_1c":{"gen3_discovery":{"commons":"CRDC Cancer Imaging Data Commons","_unique_id":"midrc_ricord_1c","study_title":"midrc_ricord_1c","accession_number":"midrc_ricord_1c","short_name":"MIDRC_RICORD_1C","full_name":"MIDRC_RICORD_1C","dbgap_accession_number":"MIDRC_RICORD_1C","study_description":"The first multi-institutional, multi-national expert annotated COVID-19 imaging dataset made freely available to the machine learning community as a research and educational resource for COVID-19 chest imaging. The Radiological Society of North America (RSNA) assembled the RSNA International COVID-19 Open Radiology Database (RICORD) collection of COVID-related imaging datasets and expert annotations to support research and education. RICORD data will be incorporated in the Medical Imaging and Data Resource Center (MIDRC) , a multi-institutional research data repository funded by the National Institute of Biomedical Imaging and Bioengineering of the National Institutes of Health. The collection contains 998 Chest x-ray examinations.Please see the MIDRC-RICORD-1c wiki page to learn more about the images and to obtain any supporting metadata for this collection.","image_types":"CR, DX","_subjects_count":361,"doi":"10.7937/91AH-V663","species":"Human","disease_type":"COVID-19 (non-cancer)","data_type":"Clinical","primary_site":"Lung","tags":[{"name":"COVID-19 (non-cancer)","category":"disease_type"},{"name":"Clinical","category":"data_type"},{"name":"Lung","category":"primary_site"}],"commons_name":"CRDC Cancer Imaging Data Commons"}}},{"midrc_ricord_1a":{"gen3_discovery":{"commons":"CRDC Cancer Imaging Data Commons","_unique_id":"midrc_ricord_1a","study_title":"midrc_ricord_1a","accession_number":"midrc_ricord_1a","short_name":"MIDRC_RICORD_1A","full_name":"MIDRC_RICORD_1A","dbgap_accession_number":"MIDRC_RICORD_1A","study_description":"The Radiological Society of North America (RSNA) set out to create the RSNA International COVID-19 Open Radiology Database (RICORD) collection of COVID-related imaging datasets and expert annotations to support research and education. RICORD data will be incorporated in the Medical Imaging and Data Resource Center (MIDRC) , a multi-institutional research data repository funded by the National Institute of Biomedical Imaging and Bioengineering of the National Institutes of Health.Please see the MIDRC-RICORD-1a WIKI page to learn more about the images and to obtain any supporting metadata for this collection.","image_types":"CT","_subjects_count":110,"doi":"10.7937/VTW4-X588","species":"Human","disease_type":"COVID-19 (non-cancer)","data_type":"Clinical, Software/Source Code","primary_site":"Lung","tags":[{"name":"COVID-19 (non-cancer)","category":"disease_type"},{"name":"Clinical, Software/Source Code","category":"data_type"},{"name":"Lung","category":"primary_site"}],"commons_name":"CRDC Cancer Imaging Data Commons"}}},{"nsclc_radiomics_interobserver1":{"gen3_discovery":{"commons":"CRDC Cancer Imaging Data Commons","_unique_id":"nsclc_radiomics_interobserver1","study_title":"nsclc_radiomics_interobserver1","accession_number":"nsclc_radiomics_interobserver1","short_name":"NSCLC_RADIOMICS_INTEROBSERVER1","full_name":"NSCLC_RADIOMICS_INTEROBSERVER1","dbgap_accession_number":"NSCLC_RADIOMICS_INTEROBSERVER1","study_description":"NSCLC-Radiomics-Interobserver1 contains clinical data and computed tomography (CT) from 22 non-small cell lung cancer (NSCLC) radiotherapy patients. This dataset refers to the "Multiple delineation" dataset of the study published in Nature Communications (https://doi.org/10.1038/ncomms5006 ). In short, the publication used a radiomics approach to computed tomography data of 1,019 patients with lung or head-and-neck cancer.Please see the NSCLC-Radiomics-Interobserver1 page to learn more about the images and to obtain any supporting metadata for this collection.","image_types":"CT, RTSTRUCT, SEG","_subjects_count":22,"doi":"10.7937/TCIA.2019.CWVLPD26","species":"Human","disease_type":"Non-small Cell Lung Cancer","data_type":"Clinical","primary_site":"Lung","tags":[{"name":"Non-small Cell Lung Cancer","category":"disease_type"},{"name":"Clinical","category":"data_type"},{"name":"Lung","category":"primary_site"}],"commons_name":"CRDC Cancer Imaging Data Commons"}}},{"acrin_nsclc_fdg_pet":{"gen3_discovery":{"commons":"CRDC Cancer Imaging Data Commons","_unique_id":"acrin_nsclc_fdg_pet","study_title":"acrin_nsclc_fdg_pet","accession_number":"acrin_nsclc_fdg_pet","short_name":"ACRIN_NSCLC_FDG_PET","full_name":"ACRIN_NSCLC_FDG_PET","dbgap_accession_number":"ACRIN_NSCLC_FDG_PET","study_description":" Thirty-seven institutions accrued 250 patients to the study ACRIN 6668. Eligible patients were >18 years with AJCC-criteria clinical stage IIB/III non-small cell lung carcinoma who were being planned for definitive concurrent chemoradiotherapy (inoperable disease). 173 had evaluable post-treatment PET, representing the analysis cohort for the primary end point. Please see the ACRIN-NSCLC-FDG-PET wiki page to learn more about the images and to obtain any supporting metadata for this collection.","image_types":"CR, CT, DX, MR, NM, PT, SC, SEG","_subjects_count":242,"doi":"10.7937/TCIA.2019.30ILQFCL 10.5281/ZENODO.8345959","species":"Human","disease_type":"Non-small Cell Lung Cancer","data_type":"Clinical","primary_site":"Lung","tags":[{"name":"Non-small Cell Lung Cancer","category":"disease_type"},{"name":"Clinical","category":"data_type"},{"name":"Lung","category":"primary_site"}],"commons_name":"CRDC Cancer Imaging Data Commons"}}},{"cptac_cm":{"gen3_discovery":{"commons":"CRDC Cancer Imaging Data Commons","_unique_id":"cptac_cm","study_title":"cptac_cm","accession_number":"cptac_cm","short_name":"CPTAC_CM","full_name":"CPTAC_CM","dbgap_accession_number":"CPTAC_CM","study_description":" This collection contains subjects from the National Cancer Institute’s Clinical Proteomic Tumor Analysis Consortium Cutaneous Melanoma (CPTAC-CM) cohort. CPTAC is a national effort to accelerate the understanding of the molecular basis of cancer through the application of large-scale proteome and genome analysis, or proteogenomics. Radiology and pathology images from CPTAC Phase 3 patients are being collected and made publicly available by The Cancer Imaging Archive to enable researchers to investigate cancer phenotypes which may correlate to corresponding proteomic, genomic and clinical data. Please see the CPTAC-CM wiki page to learn more about the radiology images and to obtain any supporting metadata for this collection.Please see the DICOM converted Slide Microscopy images for the CPTAC-CM collection page to learn more about the histopathology images and to obtain any supporting metadata for this collection.","image_types":"SM, CT, MR, PT","_subjects_count":95,"doi":"10.7937/K9/TCIA.2018.ODU24GZE 10.5281/ZENODO.12666775","species":"Human","disease_type":"Cutaneous Melanoma","data_type":"Clinical","primary_site":"Skin","tags":[{"name":"Cutaneous Melanoma","category":"disease_type"},{"name":"Clinical","category":"data_type"},{"name":"Skin","category":"primary_site"}],"commons_name":"CRDC Cancer Imaging Data Commons"}}},{"pdmr_997537_175_t":{"gen3_discovery":{"commons":"CRDC Cancer Imaging Data Commons","_unique_id":"pdmr_997537_175_t","study_title":"pdmr_997537_175_t","accession_number":"pdmr_997537_175_t","short_name":"PDMR_997537_175_T","full_name":"PDMR_997537_175_T","dbgap_accession_number":"PDMR_997537_175_T","study_description":" We identified and characterized a patient derived xenograft model with metastatic potential, adenocarcinoma colon xenograft 997537-175-T. In this study we performed a detailed imaging characterization of this model, which develops spontaneous lung metastases. Please see the PDMR-997537-175-T wiki page to learn more about the images and to obtain any supporting metadata for this collection. ","image_types":"MR, SR","_subjects_count":24,"doi":"10.7937/TCIA.2020.BRY9-4N29","species":"Mouse","disease_type":"Colon adenocarcinoma","data_type":"Clinical","primary_site":"Colon","tags":[{"name":"Colon adenocarcinoma","category":"disease_type"},{"name":"Clinical","category":"data_type"},{"name":"Colon","category":"primary_site"}],"commons_name":"CRDC Cancer Imaging Data Commons"}}},{"breast_cancer_screening_dbt":{"gen3_discovery":{"commons":"CRDC Cancer Imaging Data Commons","_unique_id":"breast_cancer_screening_dbt","study_title":"breast_cancer_screening_dbt","accession_number":"breast_cancer_screening_dbt","short_name":"BREAST_CANCER_SCREENING_DBT","full_name":"BREAST_CANCER_SCREENING_DBT","dbgap_accession_number":"BREAST_CANCER_SCREENING_DBT","study_description":"Breast cancer is among the most common cancers and a common cause of death among women. Here, we share a curated dataset of digital breast tomosynthesis images that includes normal, actionable, biopsy-proven benign, and biopsy-proven cancer cases. The dataset contains four components: (1) DICOM images, (2) a spreadsheet indicating which group each case belongs to, and (3) annotation boxes. Please see the Breast-Cancer-Screening-DBT to learn more about the images and to obtain any supporting metadata for this collection.","image_types":"MG","_subjects_count":5060,"doi":"10.7937/E4WT-CD02","species":"Human","disease_type":"Breast Cancer, Non-Cancer","data_type":"Clinical, Software/Source Code","primary_site":"Breast","tags":[{"name":"Breast Cancer, Non-Cancer","category":"disease_type"},{"name":"Clinical, Software/Source Code","category":"data_type"},{"name":"Breast","category":"primary_site"}],"commons_name":"CRDC Cancer Imaging Data Commons"}}},{"acrin_flt_breast":{"gen3_discovery":{"commons":"CRDC Cancer Imaging Data Commons","_unique_id":"acrin_flt_breast","study_title":"acrin_flt_breast","accession_number":"acrin_flt_breast","short_name":"ACRIN_FLT_BREAST","full_name":"ACRIN_FLT_BREAST","dbgap_accession_number":"ACRIN_FLT_BREAST","study_description":"ACRIN 6688, a [18F]-fluorothymidine (FLT) imaging study using positron emission tomography (PET), was designed to evaluate the relationship between [18F] FLT uptake parameters and pathologic complete response to neoadjuvant therapy of the primary tumor in patients with locally advanced breast cancer.Participant Eligibility and Enrollment: Criteria for inclusion were patients with pathologically confirmed breast cancer and determined to be a candidate for primary systemic (neoadjuvant) therapy and for whom surgical resection of residual primary tumor following completion of neoadjuvant therapy is planned.Please see the ACRIN-FLT-Breast wiki page to learn more about the images and to obtain any supporting metadata for this collection.","image_types":"CT, OT, PT","_subjects_count":83,"doi":"10.7937/K9/TCIA.2017.OL20ZMXG","species":"Human","disease_type":"Breast Cancer","data_type":"Clinical","primary_site":"Breast","tags":[{"name":"Breast Cancer","category":"disease_type"},{"name":"Clinical","category":"data_type"},{"name":"Breast","category":"primary_site"}],"commons_name":"CRDC Cancer Imaging Data Commons"}}},{"qin_breast":{"gen3_discovery":{"commons":"CRDC Cancer Imaging Data Commons","_unique_id":"qin_breast","study_title":"qin_breast","accession_number":"qin_breast","short_name":"QIN_BREAST","full_name":"QIN_BREAST","dbgap_accession_number":"QIN_BREAST","study_description":" This collection contains longitudinal PET/CT and quantitative MR images collected for the purpose of studying treatment assessment in breast cancer in the neoadjuvant setting. Images were acquired at three time points: prior to the start of treatment (t1), after the first cycle of treatment (t2), and either after the second cycle of treatment or at the completion of all treatments (prior to surgery) (t3). The PET/CT images were acquired with a support device built in-house to allow the patient to be in the prone position to facilitate registration with the MRI data. The value of this collection is to provide clinical imaging data for the development and evaluation of quantitative imaging methods for treatment assessment early in the course of therapy for breast cancer. An extension of this dataset is available via the QIN-BREAST-02 collection. Please see the QIN-Breast wiki page to learn more about the images and to obtain any supporting metadata for this collection. ","image_types":"SEG, CT, MR, PT","_subjects_count":68,"doi":"10.7937/K9/TCIA.2016.21JUEBH0 10.5281/ZENODO.8345959","species":"Human","disease_type":"Breast Cancer","data_type":"Clinical","primary_site":"Breast","tags":[{"name":"Breast Cancer","category":"disease_type"},{"name":"Clinical","category":"data_type"},{"name":"Breast","category":"primary_site"}],"commons_name":"CRDC Cancer Imaging Data Commons"}}},{"pdmr_833975_119_r":{"gen3_discovery":{"commons":"CRDC Cancer Imaging Data Commons","_unique_id":"pdmr_833975_119_r","study_title":"pdmr_833975_119_r","accession_number":"pdmr_833975_119_r","short_name":"PDMR_833975_119_R","full_name":"PDMR_833975_119_R","dbgap_accession_number":"PDMR_833975_119_R","study_description":"PDMR-833975-119-R is a dataset of detailed MRI, PET/CT (FDG and FLT) in patient-derived xenograft in mouse model of pancreatic adenocarcinoma from the National Cancer Institute Patient-Derived Models Repository (https://pdmr.cancer.gov/) with baseline and bi-weekly monitoring imaging. Please see the PDMR-833975-119-R wiki page to learn more about the images and to obtain any supporting metadata for this collection.","image_types":"MR, SR","_subjects_count":20,"doi":"10.7937/TCIA.0ECK-C338","species":"Mouse","disease_type":"Pancreatic Ductal Adenocarcinoma","data_type":"Clinical","primary_site":"Abdomen","tags":[{"name":"Pancreatic Ductal Adenocarcinoma","category":"disease_type"},{"name":"Clinical","category":"data_type"},{"name":"Abdomen","category":"primary_site"}],"commons_name":"CRDC Cancer Imaging Data Commons"}}},{"pdmr_292921_168_r":{"gen3_discovery":{"commons":"CRDC Cancer Imaging Data Commons","_unique_id":"pdmr_292921_168_r","study_title":"pdmr_292921_168_r","accession_number":"pdmr_292921_168_r","short_name":"PDMR_292921_168_R","full_name":"PDMR_292921_168_R","dbgap_accession_number":"PDMR_292921_168_R","study_description":"We identified and characterized a patient derived xenograft model with metastatic potential, adenocarcinoma pancreas xenograft 292921-168-R. In this study we performed a detailed imaging characterization of this model, which develops spontaneous lung metastases. Please see the Imaging characterization of a metastatic patient derived model of adenocarcinoma pancreas: PDMR-292921-168-R wiki page to learn more about the images and to obtain any supporting metadata for this collection. ","image_types":"MR, SR","_subjects_count":20,"doi":"10.7937/TCIA.2020.PCAK-8Z10","species":"Mouse","disease_type":"Pancreatic Adenocarcinoma","data_type":"Clinical","primary_site":"Abdomen","tags":[{"name":"Pancreatic Adenocarcinoma","category":"disease_type"},{"name":"Clinical","category":"data_type"},{"name":"Abdomen","category":"primary_site"}],"commons_name":"CRDC Cancer Imaging Data Commons"}}},{"pdmr_425362_245_t":{"gen3_discovery":{"commons":"CRDC Cancer Imaging Data Commons","_unique_id":"pdmr_425362_245_t","study_title":"pdmr_425362_245_t","accession_number":"pdmr_425362_245_t","short_name":"PDMR_425362_245_T","full_name":"PDMR_425362_245_T","dbgap_accession_number":"PDMR_425362_245_T","study_description":"We identified and characterized a patient derived xenograft model with metastatic potential, melanoma xenograft 425362-245-T. In this study we performed a detailed imaging characterization of this model, which develops spontaneous lung metastases.Please see the PDMR-425362-245-T wiki page to learn more about the images and to obtain any supporting metadata for this collection.","image_types":"MR, SR","_subjects_count":20,"doi":"10.7937/TCIA.2020.7YRS-7J97","species":"Mouse","disease_type":"Melanoma","data_type":"Clinical","primary_site":"Abdomen","tags":[{"name":"Melanoma","category":"disease_type"},{"name":"Clinical","category":"data_type"},{"name":"Abdomen","category":"primary_site"}],"commons_name":"CRDC Cancer Imaging Data Commons"}}},{"pdmr_bl0293_f563":{"gen3_discovery":{"commons":"CRDC Cancer Imaging Data Commons","_unique_id":"pdmr_bl0293_f563","study_title":"pdmr_bl0293_f563","accession_number":"pdmr_bl0293_f563","short_name":"PDMR_BL0293_F563","full_name":"PDMR_BL0293_F563","dbgap_accession_number":"PDMR_BL0293_F563","study_description":"We identified and characterized a patient-derived xenograft model with metastatic potential, bladder xenograft BL0293-F563. In this study we performed a detailed imaging characterization of this model, which develops spontaneous liver and bone metastases.Please see the PDMR-BL0293-F563 wiki page to learn more about the images and to obtain any supporting metadata for this collection.","image_types":"MR","_subjects_count":19,"doi":"10.7937/TCIA.2019.B6U7WMQW","species":"Mouse","disease_type":"Bladder Cancer","data_type":"Clinical","primary_site":"Bladder","tags":[{"name":"Bladder Cancer","category":"disease_type"},{"name":"Clinical","category":"data_type"},{"name":"Bladder","category":"primary_site"}],"commons_name":"CRDC Cancer Imaging Data Commons"}}},{"cptac_pda":{"gen3_discovery":{"commons":"CRDC Cancer Imaging Data Commons","_unique_id":"cptac_pda","study_title":"cptac_pda","accession_number":"cptac_pda","short_name":"CPTAC_PDA","full_name":"CPTAC_PDA","dbgap_accession_number":"CPTAC_PDA","study_description":" This collection contains subjects from the National Cancer Institute’s Clinical Proteomic Tumor Analysis Consortium Pancreatic Ductal Adenocarcinoma (CPTAC-PDA) cohort. CPTAC is a national effort to accelerate the understanding of the molecular basis of cancer through the application of large-scale proteome and genome analysis, or proteogenomics. Radiology and pathology images from CPTAC Phase 3 patients are being collected and made publicly available by The Cancer Imaging Archive to enable researchers to investigate cancer phenotypes which may correlate to corresponding proteomic, genomic and clinical data. Please see the CPTAC-PDA wiki page to learn more about the radiology images and to obtain any supporting metadata for this collection.Please see the DICOM converted Slide Microscopy images for the CPTAC-PDA collection page to learn more about the histopathology images and to obtain any supporting metadata for this collection.","image_types":"CT, MR, PT, US, SM, RTSTRUCT","_subjects_count":195,"doi":"10.7937/K9/TCIA.2018.SC20FO18 10.7937/BW9V-BX61 10.5281/ZENODO.12666859","species":"Human","disease_type":"Ductal Adenocarcinoma","data_type":"Clinical, Genomics, Proteomics","primary_site":"Pancreas","tags":[{"name":"Ductal Adenocarcinoma","category":"disease_type"},{"name":"Clinical, Genomics, Proteomics","category":"data_type"},{"name":"Pancreas","category":"primary_site"}],"commons_name":"CRDC Cancer Imaging Data Commons"}}},{"cptac_sar":{"gen3_discovery":{"commons":"CRDC Cancer Imaging Data Commons","_unique_id":"cptac_sar","study_title":"cptac_sar","accession_number":"cptac_sar","short_name":"CPTAC_SAR","full_name":"CPTAC_SAR","dbgap_accession_number":"CPTAC_SAR","study_description":" This collection contains subjects from the National Cancer Institute’s Clinical Proteomic Tumor Analysis Consortium Sarcomas (CPTAC-SAR) cohort. CPTAC is a national effort to accelerate the understanding of the molecular basis of cancer through the application of large-scale proteome and genome analysis, or proteogenomics. Radiology and pathology images from CPTAC Phase 3 patients are being collected and made publicly available by The Cancer Imaging Archive to enable researchers to investigate cancer phenotypes which may correlate to corresponding proteomic, genomic and clinical data. Please see the CPTAC-SAR wiki page to learn more about the radiology images and to obtain any supporting metadata for this collection.Please see the DICOM converted Slide Microscopy images for the CPTAC-SAR collection page to learn more about the histopathology images and to obtain any supporting metadata for this collection.","image_types":"CT, MR, PT, SM","_subjects_count":88,"doi":"10.7937/TCIA.2019.9BT23R95 10.5281/ZENODO.12666862","species":"Human","disease_type":"Sarcomas","data_type":"Clinical","primary_site":"Abdomen, Arm, Bladder, Chest, Head-Neck, Kidney, Leg, Retroperitoneum, Stomach, Uterus","tags":[{"name":"Sarcomas","category":"disease_type"},{"name":"Clinical","category":"data_type"},{"name":"Abdomen, Arm, Bladder, Chest, Head-Neck, Kidney, Leg, Retroperitoneum, Stomach, Uterus","category":"primary_site"}],"commons_name":"CRDC Cancer Imaging Data Commons"}}},{"icdc_glioma":{"gen3_discovery":{"commons":"CRDC Cancer Imaging Data Commons","_unique_id":"icdc_glioma","study_title":"icdc_glioma","accession_number":"icdc_glioma","short_name":"ICDC_GLIOMA","full_name":"ICDC_GLIOMA","dbgap_accession_number":"ICDC_GLIOMA","study_description":"ICDC-Glioma  contains treatment-naïve naturally-occurring canine glioma participants from the Integrated Canine Data Commons. Brain radiology (57/81 participant animals) and H&E-stained biopsy or necropsy pathology (76/81 participants) are classified by veterinary and physician neuropathologists. Please see the wiki ICDC-Glioma  to learn more about the radiology images and to obtain any supporting metadata for this collection. Please see the wiki DICOM converted Slide Microscopy images for the ICDC-Glioma collection  to learn more about the histopathology images and to obtain any supporting metadata for this collection. ","image_types":"MR, SM","_subjects_count":80,"doi":"10.5281/ZENODO.12690000 10.7937/TCIA.SVQT-Q016","species":"Canine","disease_type":"Glioma","data_type":"Genomics","primary_site":"Head","tags":[{"name":"Glioma","category":"disease_type"},{"name":"Genomics","category":"data_type"},{"name":"Head","category":"primary_site"}],"commons_name":"CRDC Cancer Imaging Data Commons"}}},{"lung_pet_ct_dx":{"gen3_discovery":{"commons":"CRDC Cancer Imaging Data Commons","_unique_id":"lung_pet_ct_dx","study_title":"lung_pet_ct_dx","accession_number":"lung_pet_ct_dx","short_name":"LUNG_PET_CT_DX","full_name":"LUNG_PET_CT_DX","dbgap_accession_number":"LUNG_PET_CT_DX","study_description":"This dataset consists of CT and PET-CT DICOM images of lung cancer subjects with XML Annotation files that indicate tumor location with bounding boxes. The images were retrospectively acquired from patients with suspicion of lung cancer, and who underwent standard-of-care lung biopsy and PET/CT. Subjects were grouped according to a tissue histopathological diagnosis. Patients with Names/IDs containing the letter ,,A,, were diagnosed with Adenocarcinoma, ,,B,, with Small Cell Carcinoma, ,,C,, with Large Cell Carcinoma, and ,,G,, with Squamous Cell Carcinoma.Please see the LUNG-PET-CT-Dx wiki page to learn more about the images and to obtain any supporting metadata for this collection.","image_types":"CT, PT, SR, SEG","_subjects_count":355,"doi":"10.5281/ZENODO.8345959 10.5281/ZENODO.16989819 10.7937/TCIA.2020.NNC2-0461","species":"Human","disease_type":"Lung Cancer","data_type":"Image Analyses, Software/Source Code","primary_site":"Lung","tags":[{"name":"Lung Cancer","category":"disease_type"},{"name":"Image Analyses, Software/Source Code","category":"data_type"},{"name":"Lung","category":"primary_site"}],"commons_name":"CRDC Cancer Imaging Data Commons"}}},{"lung_fused_ct_pathology":{"gen3_discovery":{"commons":"CRDC Cancer Imaging Data Commons","_unique_id":"lung_fused_ct_pathology","study_title":"lung_fused_ct_pathology","accession_number":"lung_fused_ct_pathology","short_name":"LUNG_FUSED_CT_PATHOLOGY","full_name":"LUNG_FUSED_CT_PATHOLOGY","dbgap_accession_number":"LUNG_FUSED_CT_PATHOLOGY","study_description":"This is the first attempt of mapping the extent of Invasive Adenocarcinoma onto in vivo lung CT. The mappings constitute ground truth of disease and may be used to further investigate the imaging signatures of Invasive Adenocarcinoma in ground glass pulmonary nodules. Please see the Lung-Fused-CT-Pathology Collection page to learn more about the images and to obtain any supporting metadata for this collection.","image_types":"CT, FUSION, SEG","_subjects_count":6,"doi":"10.7937/K9/TCIA.2018.SMT36LPN","species":"Human","disease_type":"Lung Cancer","data_type":"Image Analyses, Software/Source Code","primary_site":"Lung","tags":[{"name":"Lung Cancer","category":"disease_type"},{"name":"Image Analyses, Software/Source Code","category":"data_type"},{"name":"Lung","category":"primary_site"}],"commons_name":"CRDC Cancer Imaging Data Commons"}}},{"lctsc":{"gen3_discovery":{"commons":"CRDC Cancer Imaging Data Commons","_unique_id":"lctsc","study_title":"lctsc","accession_number":"lctsc","short_name":"LCTSC","full_name":"LCTSC","dbgap_accession_number":"LCTSC","study_description":"This Lung CT and Radiation therapy data set was provided in association with an autocontouring challenge competition and related conference session conducted at the AAPM 2017 Annual Meeting Please see the LCTSC wiki page to learn more about the images and to obtain any supporting metadata for this collection. ","image_types":"CT, RTSTRUCT","_subjects_count":60,"doi":"10.7937/K9/TCIA.2017.3R3FVZ08","species":"Human","disease_type":"Lung Cancer","data_type":"Image Analyses","primary_site":"Lung","tags":[{"name":"Lung Cancer","category":"disease_type"},{"name":"Image Analyses","category":"data_type"},{"name":"Lung","category":"primary_site"}],"commons_name":"CRDC Cancer Imaging Data Commons"}}},{"qin_lung_ct":{"gen3_discovery":{"commons":"CRDC Cancer Imaging Data Commons","_unique_id":"qin_lung_ct","study_title":"qin_lung_ct","accession_number":"qin_lung_ct","short_name":"QIN_LUNG_CT","full_name":"QIN_LUNG_CT","dbgap_accession_number":"QIN_LUNG_CT","study_description":"The Computed tomography (CT) Image data was obtained on patients diagnosed with Non-Small Cell Lung Cancer (NSCLC) with mixed stage & histology from the H. Lee Moffitt Cancer Center and Research Institute. Scans were obtained from patients who underwent surgical resection and had corresponding pre-surgery diagnostic CTs. Please see the QIN LUNG CT page to learn more about the images and to obtain any supporting metadata for this collection.","image_types":"SEG, CT","_subjects_count":47,"doi":"10.5281/ZENODO.8345959 10.7937/K9/TCIA.2015.NPGZYZBZ 10.7937/K9/TCIA.2015.1BUVFJR7","species":"Human","disease_type":"Non-small Cell Lung Cancer","data_type":"","primary_site":"Lung","tags":[{"name":"Non-small Cell Lung Cancer","category":"disease_type"},{"name":"","category":"data_type"},{"name":"Lung","category":"primary_site"}],"commons_name":"CRDC Cancer Imaging Data Commons"}}},{"4d_lung":{"gen3_discovery":{"commons":"CRDC Cancer Imaging Data Commons","_unique_id":"4d_lung","study_title":"4d_lung","accession_number":"4d_lung","short_name":"4D_LUNG","full_name":"4D_LUNG","dbgap_accession_number":"4D_LUNG","study_description":" This data collection consists of images acquired during chemoradiotherapy of 20 locally-advanced, non-small cell lung cancer patients. The images include four-dimensional (4D) fan beam (4D-FBCT) and 4D cone beam CT (4D-CBCT). All patients underwent concurrent radiochemotherapy to a total dose of 64.8-70 Gy using daily 1.8 or 2 Gy fractions. A single Radiation Oncologist delineated targets and organs at risk in all 4D-FBCT and a limited number of 4D-CBCT images. All patients underwent concurrent radiochemotherapy to a total dose of 64.8-70 Gy using daily 1.8 or 2 Gy fractions. Please see the 4D-Lung page to learn more about the images and to obtain any supporting metadata for this collection.","image_types":"CT, RTSTRUCT","_subjects_count":20,"doi":"10.7937/K9/TCIA.2016.ELN8YGLE","species":"Human","disease_type":"Non-small Cell Lung Cancer","data_type":"Image Analyses","primary_site":"Lung","tags":[{"name":"Non-small Cell Lung Cancer","category":"disease_type"},{"name":"Image Analyses","category":"data_type"},{"name":"Lung","category":"primary_site"}],"commons_name":"CRDC Cancer Imaging Data Commons"}}},{"rider_lung_ct":{"gen3_discovery":{"commons":"CRDC Cancer Imaging Data Commons","_unique_id":"rider_lung_ct","study_title":"rider_lung_ct","accession_number":"rider_lung_ct","short_name":"RIDER_LUNG_CT","full_name":"RIDER_LUNG_CT","dbgap_accession_number":"RIDER_LUNG_CT","study_description":"RIDER Lung CT is a subsection of the broader Reference Image Database to Evaluate Therapy Response (RIDER) collection. RIDER is a targeted data collection for the purpose of generating an initial consensus on how to harmonize data collection and analysis for quantitative imaging methods as applied to measure the response to drug or radiation therapy. The long term goal is to provide a resource to permit harmonized methods for data collection and analysis across different commercial imaging platforms, as required to support multi-site clinical trials, using imaging as a biomarker for therapy response.More information about the RIDER Lung CT sub-collection page can be found in the corresponding section of the RIDER page.","image_types":"PR, SEG, SR, RTSTRUCT, SEG, CT, SEG, SEG","_subjects_count":32,"doi":"10.7937/K9/TCIA.2015.1BUVFJR7 10.7937/TCIA.2020.1C3H-VP70 10.7937/K9/TCIA.2015.U1X8A5NR 10.7937/TCIA.2020.JIT9GRK8","species":"Human","disease_type":"Lung Cancer","data_type":"Image Analyses","primary_site":"Chest","tags":[{"name":"Lung Cancer","category":"disease_type"},{"name":"Image Analyses","category":"data_type"},{"name":"Chest","category":"primary_site"}],"commons_name":"CRDC Cancer Imaging Data Commons"}}},{"ct_colonography":{"gen3_discovery":{"commons":"CRDC Cancer Imaging Data Commons","_unique_id":"ct_colonography","study_title":"ct_colonography","accession_number":"ct_colonography","short_name":"CT_COLONOGRAPHY","full_name":"CT_COLONOGRAPHY","dbgap_accession_number":"CT_COLONOGRAPHY","study_description":"The CT Colonography collection consists of a limited portion of The National CT Colonography Trial (ACRIN PROTOCOL 6664 ). The collection is offered to enlarge the broader research community''s ability to develop CAD algorithms for polyp detection. Please see the CT COLONOGRAPHY wiki page to learn more about the images and to obtain any supporting metadata for this collection.","image_types":"CT","_subjects_count":825,"doi":"10.7937/K9/TCIA.2015.NWTESAY1","species":"Human","disease_type":"Colon Cancer","data_type":"Image Analyses","primary_site":"Colon","tags":[{"name":"Colon Cancer","category":"disease_type"},{"name":"Image Analyses","category":"data_type"},{"name":"Colon","category":"primary_site"}],"commons_name":"CRDC Cancer Imaging Data Commons"}}},{"cbis_ddsm":{"gen3_discovery":{"commons":"CRDC Cancer Imaging Data Commons","_unique_id":"cbis_ddsm","study_title":"cbis_ddsm","accession_number":"cbis_ddsm","short_name":"CBIS_DDSM","full_name":"CBIS_DDSM","dbgap_accession_number":"CBIS_DDSM","study_description":"This CBIS-DDSM (Curated Breast Imaging Subset of DDSM) is an updated and standardized version of the Digital Database for Screening Mammography (DDSM) . The DDSM is a database of 2,620 scanned film mammography studies. It contains normal, benign, and malignant cases with verified pathology information.Please see the CBIS-DDSM page to learn more about the images and to obtain any supporting metadata for this collection.","image_types":"MG","_subjects_count":6671,"doi":"10.7937/K9/TCIA.2016.7O02S9CY","species":"Human","disease_type":"Breast Cancer, Non-Cancer","data_type":"Image Analyses","primary_site":"Breast","tags":[{"name":"Breast Cancer, Non-Cancer","category":"disease_type"},{"name":"Image Analyses","category":"data_type"},{"name":"Breast","category":"primary_site"}],"commons_name":"CRDC Cancer Imaging Data Commons"}}},{"rider_phantom_pet_ct":{"gen3_discovery":{"commons":"CRDC Cancer Imaging Data Commons","_unique_id":"rider_phantom_pet_ct","study_title":"rider_phantom_pet_ct","accession_number":"rider_phantom_pet_ct","short_name":"RIDER_PHANTOM_PET_CT","full_name":"RIDER_PHANTOM_PET_CT","dbgap_accession_number":"RIDER_PHANTOM_PET_CT","study_description":"RIDER Phantom PET-CT is a subsection of the broader Reference Image Database to Evaluate Therapy Response (RIDER) collection. RIDER is a targeted data collection for the purpose of generating an initial consensus on how to harmonize data collection and analysis for quantitative imaging methods as applied to measure the response to drug or radiation therapy. The long term goal is to provide a resource to permit harmonized methods for data collection and analysis across different commercial imaging platforms, as required to support multi-site clinical trials, using imaging as a biomarker for therapy response.More information about the RIDER Phantom PET-CT sub-collection page can be found in the corresponding section of the RIDER page.","image_types":"CT, PT","_subjects_count":20,"doi":"10.7937/K9/TCIA.2015.8WG2KN4W","species":"Human","disease_type":"Phantom","data_type":"Image Analyses","primary_site":"Phantom","tags":[{"name":"Phantom","category":"disease_type"},{"name":"Image Analyses","category":"data_type"},{"name":"Phantom","category":"primary_site"}],"commons_name":"CRDC Cancer Imaging Data Commons"}}},{"pancreas_ct":{"gen3_discovery":{"commons":"CRDC Cancer Imaging Data Commons","_unique_id":"pancreas_ct","study_title":"pancreas_ct","accession_number":"pancreas_ct","short_name":"PANCREAS_CT","full_name":"PANCREAS_CT","dbgap_accession_number":"PANCREAS_CT","study_description":"The National Institutes of Health Clinical Center performed 82 abdominal contrast enhanced 3D CT scans (~70 seconds after intravenous contrast injection in portal-venous) from 53 male and 27 female subjects. Seventeen of the subjects are healthy kidney donors scanned prior to nephrectomy. The remaining 65 patients were selected by a radiologist from patients who neither had major abdominal pathologies nor pancreatic cancer lesions. A medical student manually performed slice-by-slice segmentations of the pancreas as ground-truth and these were verified/modified by an experienced radiologist.Please see the Pancreas-CT wiki page to learn more about the images and to obtain any supporting metadata for this collection.","image_types":"CT, SEG","_subjects_count":80,"doi":"10.7937/K9/TCIA.2016.TNB1KQBU 10.5281/ZENODO.12130275","species":"Human","disease_type":"Healthy Controls (non-cancer)","data_type":"Image Analyses","primary_site":"Pancreas","tags":[{"name":"Healthy Controls (non-cancer)","category":"disease_type"},{"name":"Image Analyses","category":"data_type"},{"name":"Pancreas","category":"primary_site"}],"commons_name":"CRDC Cancer Imaging Data Commons"}}},{"qin_prostate_repeatability":{"gen3_discovery":{"commons":"CRDC Cancer Imaging Data Commons","_unique_id":"qin_prostate_repeatability","study_title":"qin_prostate_repeatability","accession_number":"qin_prostate_repeatability","short_name":"QIN_PROSTATE_REPEATABILITY","full_name":"QIN_PROSTATE_REPEATABILITY","dbgap_accession_number":"QIN_PROSTATE_REPEATABILITY","study_description":"This is a dataset with multiparametric prostate MRI applied in a test-retest setting, allowing to evaluate repeatability of the MRI-based measurements in the prostate. There is very limited data about the repeatability in mpMRI of the prostate, while such information is critical for establishing technical characteristics of mpMRI as imaging biomarker of prostate cancer.Please see the QIN-PROSTATE-Repeatability wiki page to learn more about the images and to obtain any supporting metadata for this collection.","image_types":"MR, SEG, SR","_subjects_count":15,"doi":"10.7937/K9/TCIA.2018.MR1CKGND","species":"Human","disease_type":"Prostate Cancer","data_type":"Image Analyses","primary_site":"Prostate","tags":[{"name":"Prostate Cancer","category":"disease_type"},{"name":"Image Analyses","category":"data_type"},{"name":"Prostate","category":"primary_site"}],"commons_name":"CRDC Cancer Imaging Data Commons"}}},{"prostate_mri_us_biopsy":{"gen3_discovery":{"commons":"CRDC Cancer Imaging Data Commons","_unique_id":"prostate_mri_us_biopsy","study_title":"prostate_mri_us_biopsy","accession_number":"prostate_mri_us_biopsy","short_name":"PROSTATE_MRI_US_BIOPSY","full_name":"PROSTATE_MRI_US_BIOPSY","dbgap_accession_number":"PROSTATE_MRI_US_BIOPSY","study_description":"This dataset was derived from tracked biopsy sessions using the Artemis biopsy system, many of which included image fusion with MRI targets. Patients received a 3D transrectal ultrasound scan, after which nonrigid registration (e.g. “fusion”) was performed between real-time ultrasound and preoperative MRI, enabling biopsy cores to be sampled from MR regions of interest. Most cases also included sampling of systematic biopsy cores using a 12-core digital template. The Artemis system tracked targeted and systematic core locations using encoder kinematics of a mechanical arm, and recorded locations relative to the Ultrasound scan. MRI biopsy coordinates were also recorded for most cases. Please see the Prostate-MRI-US-Biopsy page to learn more about the images and to obtain any supporting metadata for this collection.","image_types":"MR, US, M3D, SEG, SEG","_subjects_count":1151,"doi":"10.5281/ZENODO.8345959 10.7937/TCIA.2020.A61IOC1A 10.5281/ZENODO.10069910","species":"Human","disease_type":"Prostate Cancer","data_type":"Image Analyses","primary_site":"Prostate","tags":[{"name":"Prostate Cancer","category":"disease_type"},{"name":"Image Analyses","category":"data_type"},{"name":"Prostate","category":"primary_site"}],"commons_name":"CRDC Cancer Imaging Data Commons"}}},{"prostatex":{"gen3_discovery":{"commons":"CRDC Cancer Imaging Data Commons","_unique_id":"prostatex","study_title":"prostatex","accession_number":"prostatex","short_name":"PROSTATEX","full_name":"PROSTATEX","dbgap_accession_number":"PROSTATEX","study_description":"SPIE, along with the support of the American Association of Physicists in Medicine (AAPM) and the National Cancer Institute (NCI), will conduct a “Grand Challenge” on quantitative image analysis methods for the diagnostic classification of clinically significant prostate lesions. As part of the 2017 SPIE Medical Imaging Symposium, the PROSTATEx Challenge will provide a unique opportunity for participants to compare their algorithms with those of others from academia, industry, and government in a structured, direct way using the same data sets. For more details, go to https://www.spie.org/search?&term=PROSTATEx . rel=\"nofollow\">http://spiechallenges.cloudapp.net/. Release date of training set cases with truth:  November 21, 2016 Release date of test set cases without truth:  December 12, 2016 Submission date for participants’ test set classification output:  January 15, 2017 Challenge results released to participants:  January 20, 2017 SPIE Medical Imaging Symposium:  February 13-16, 2017Please see the PROSTATEx page to learn more about the images and to obtain any supporting metadata for this collection.","image_types":"SR, SEG, MR","_subjects_count":346,"doi":"10.7937/TCIA.NBB4-4655 10.7937/TCIA.2019.DEG7ZG1U 10.5281/ZENODO.15643312 10.7937/K9TCIA.2017.MURS5CL 10.5281/ZENODO.8345959","species":"Human","disease_type":"Prostate Cancer, Non-Cancer","data_type":"Image Analyses","primary_site":"Prostate","tags":[{"name":"Prostate Cancer, Non-Cancer","category":"disease_type"},{"name":"Image Analyses","category":"data_type"},{"name":"Prostate","category":"primary_site"}],"commons_name":"CRDC Cancer Imaging Data Commons"}}},{"prostate_fused_mri_pathology":{"gen3_discovery":{"commons":"CRDC Cancer Imaging Data Commons","_unique_id":"prostate_fused_mri_pathology","study_title":"prostate_fused_mri_pathology","accession_number":"prostate_fused_mri_pathology","short_name":"PROSTATE_FUSED_MRI_PATHOLOGY","full_name":"PROSTATE_FUSED_MRI_PATHOLOGY","dbgap_accession_number":"PROSTATE_FUSED_MRI_PATHOLOGY","study_description":"This collection comprises a total of 28 3 Tesla T1-weighted, T2-weighted, Diffusion weighted and Dynamic Contrast Enhanced prostate MRI along with accompanying digitized histopathology (H&Estained) images of corresponding radical prostatectomy specimens.Fused MATLAB objects are also provided combining both the MR and Pathology Images.Please see the Prostate Fused-MRI-Pathology wiki page to learn more about the images and to obtain any supporting metadata for this collection.","image_types":"MR","_subjects_count":28,"doi":"10.7937/K9/TCIA.2016.TLPMR1AM","species":"Human","disease_type":"Prostate Cancer","data_type":"Image Analyses","primary_site":"Prostate","tags":[{"name":"Prostate Cancer","category":"disease_type"},{"name":"Image Analyses","category":"data_type"},{"name":"Prostate","category":"primary_site"}],"commons_name":"CRDC Cancer Imaging Data Commons"}}},{"prostate_3t":{"gen3_discovery":{"commons":"CRDC Cancer Imaging Data Commons","_unique_id":"prostate_3t","study_title":"prostate_3t","accession_number":"prostate_3t","short_name":"PROSTATE_3T","full_name":"PROSTATE_3T","dbgap_accession_number":"PROSTATE_3T","study_description":"Prostate transversal T2 -weighted MRIs acquired on a 3.0T Siemens TrioTim using only a pelvic phased array coil. Images were acquired for prostate cancer detection. Please see the Prostate-3T page to learn more about the images and to obtain any supporting metadata for this collection.","image_types":"MR","_subjects_count":64,"doi":"10.7937/K9/TCIA.2015.QJTV5IL5","species":"Human","disease_type":"Prostate Cancer","data_type":"Image Analyses","primary_site":"Prostate","tags":[{"name":"Prostate Cancer","category":"disease_type"},{"name":"Image Analyses","category":"data_type"},{"name":"Prostate","category":"primary_site"}],"commons_name":"CRDC Cancer Imaging Data Commons"}}},{"cc_radiomics_phantom":{"gen3_discovery":{"commons":"CRDC Cancer Imaging Data Commons","_unique_id":"cc_radiomics_phantom","study_title":"cc_radiomics_phantom","accession_number":"cc_radiomics_phantom","short_name":"CC_RADIOMICS_PHANTOM","full_name":"CC_RADIOMICS_PHANTOM","dbgap_accession_number":"CC_RADIOMICS_PHANTOM","study_description":"This collection consists of 17 CT scans of the Credence Cartridge Radiomics (CCR) phantom, which was designed for use in studies of texture feature robustness. The scans were acquired at four medical centers using each center’s chest protocol and were taken using GE (7 scans), Philips (5 scans), Siemens (2 scans), and Toshiba (3 scans) scanners. The CCR phantom has 10 cartridges, each with a unique texturePlease see the CC-Radiomics-Phantom wiki page to learn more about the images and to obtain any supporting metadata for this collection.","image_types":"CT, RTSTRUCT","_subjects_count":17,"doi":"10.7937/K9/TCIA.2017.ZUZRML5B","species":"Human","disease_type":"Phantom","data_type":"Image Analyses","primary_site":"Lung Phantom","tags":[{"name":"Phantom","category":"disease_type"},{"name":"Image Analyses","category":"data_type"},{"name":"Lung Phantom","category":"primary_site"}],"commons_name":"CRDC Cancer Imaging Data Commons"}}},{"lung_phantom":{"gen3_discovery":{"commons":"CRDC Cancer Imaging Data Commons","_unique_id":"lung_phantom","study_title":"lung_phantom","accession_number":"lung_phantom","short_name":"LUNG_PHANTOM","full_name":"LUNG_PHANTOM","dbgap_accession_number":"LUNG_PHANTOM","study_description":"The FDA anthropomorphic thorax phantom with 12 phantom lesions of different sizes (10 and 20 mm in effective diameter), shapes (spherical, elliptical, lobulated, and spiculated), and densities (−630,−10, and +100 HU) was scanned at Columbia University Medical Center on a 64-detector row scanner (LightSpeed VCT, GE Healthcare, Milwaukee, WI). The CT scanning parameters were 120 kVp, 100 mAs, 64x0.625 collimation, and pitch of 1.375. The images were reconstructed with the lung kernel using 1.25 mm slice thickness.Please see the Lung Phantom wiki page to learn more about the images and to obtain any supporting metadata for this collection.","image_types":"CT, SEG","_subjects_count":1,"doi":"10.7937/K9/TCIA.2015.1BUVFJR7 10.7937/K9/TCIA.2015.08A1IXOO","species":"Human","disease_type":"Phantom","data_type":"Image Analyses","primary_site":"Lung Phantom","tags":[{"name":"Phantom","category":"disease_type"},{"name":"Image Analyses","category":"data_type"},{"name":"Lung Phantom","category":"primary_site"}],"commons_name":"CRDC Cancer Imaging Data Commons"}}},{"ct_lymph_nodes":{"gen3_discovery":{"commons":"CRDC Cancer Imaging Data Commons","_unique_id":"ct_lymph_nodes","study_title":"ct_lymph_nodes","accession_number":"ct_lymph_nodes","short_name":"CT_LYMPH_NODES","full_name":"CT_LYMPH_NODES","dbgap_accession_number":"CT_LYMPH_NODES","study_description":"This collection consists of Computed Tomography (CT) images of the mediastinum and abdomen in which lymph node positions are marked by radiologists at the National Institutes of Health, Clinical Center. Radiologists at the Imaging Biomarkers and Computer-Aided Diagnosis Laboratory labeled a total of 388 mediastinal lymph nodes in CT images of 90 patients and a total of 595 abdominal lymph nodes in 86 patients.Please see the CT Lymph Nodes wiki page to learn more about the images and to obtain supporting data from this collection.","image_types":"CT, SEG","_subjects_count":176,"doi":"10.7937/K9/TCIA.2015.AQIIDCNM","species":"Human","disease_type":"Lymphadenopathy (non-cancer)","data_type":"Image Analyses, Organ segmentations","primary_site":"Abdomen, Mediastinum","tags":[{"name":"Lymphadenopathy (non-cancer)","category":"disease_type"},{"name":"Image Analyses, Organ segmentations","category":"data_type"},{"name":"Abdomen, Mediastinum","category":"primary_site"}],"commons_name":"CRDC Cancer Imaging Data Commons"}}},{"cc_radiomics_phantom_3":{"gen3_discovery":{"commons":"CRDC Cancer Imaging Data Commons","_unique_id":"cc_radiomics_phantom_3","study_title":"cc_radiomics_phantom_3","accession_number":"cc_radiomics_phantom_3","short_name":"CC_RADIOMICS_PHANTOM_3","full_name":"CC_RADIOMICS_PHANTOM_3","dbgap_accession_number":"CC_RADIOMICS_PHANTOM_3","study_description":"CT Phantom Scans for Head, Chest, and Controlled Protocols on 100 Scanners (CC-Radiomics-Phantom-3)This data collection contains one physical phantom, imaged across three protocols, on 100 scanners. CT scans were acquired on 100 scanners at 35 clinics: 51 GE scanners, 20 Philips scanners, 11 Toshiba scanners, and 1 Philips and Neusoft Medical System scanner. The commonly used chest and head protocols of the local clinic were acquired without changing the protocol parameters. Additionally, a controlled protocol was acquired that was designed to minimize radiomics feature differences between manufacturers. Please see the CC-Radiomics-Phantom-3 wiki page to learn more about the images and to obtain any supporting metadata for this collection.","image_types":"CT, RTSTRUCT","_subjects_count":95,"doi":"10.7937/TCIA.2019.J71I4FAH","species":"Phantom","disease_type":"Phantom","data_type":"Image Analyses","primary_site":"Head, Chest, Phantom","tags":[{"name":"Phantom","category":"disease_type"},{"name":"Image Analyses","category":"data_type"},{"name":"Head, Chest, Phantom","category":"primary_site"}],"commons_name":"CRDC Cancer Imaging Data Commons"}}},{"pelvic_reference_data":{"gen3_discovery":{"commons":"CRDC Cancer Imaging Data Commons","_unique_id":"pelvic_reference_data","study_title":"pelvic_reference_data","accession_number":"pelvic_reference_data","short_name":"PELVIC_REFERENCE_DATA","full_name":"PELVIC_REFERENCE_DATA","dbgap_accession_number":"PELVIC_REFERENCE_DATA","study_description":"This collection links expertly selected landmark points on clinical image pairs to provide a basis for rigid registration validation. Using combinatorial rigid registration optimization (CORRO) we provide a statistically characterized reference data set for image registration of the pelvis by estimating the optimal ground truth. Landmark points for each CT/CBCT image pair for 58 pelvic cases were identified. The mean and the standard deviation of the registration were used as the final registration for each image pair.Please see the Pelvic-Reference-Data wiki page to learn more about the images and to obtain any supporting metadata for this collection. ","image_types":"CT","_subjects_count":58,"doi":"10.7937/TCIA.2019.WOSKQ5OO","species":"Human","disease_type":"Prostate Cancer, Anal Cancer","data_type":"Image Analyses","primary_site":"Pelvis, Prostate, Anus","tags":[{"name":"Prostate Cancer, Anal Cancer","category":"disease_type"},{"name":"Image Analyses","category":"data_type"},{"name":"Pelvis, Prostate, Anus","category":"primary_site"}],"commons_name":"CRDC Cancer Imaging Data Commons"}}},{"vestibular_schwannoma_seg":{"gen3_discovery":{"commons":"CRDC Cancer Imaging Data Commons","_unique_id":"vestibular_schwannoma_seg","study_title":"vestibular_schwannoma_seg","accession_number":"vestibular_schwannoma_seg","short_name":"VESTIBULAR_SCHWANNOMA_SEG","full_name":"VESTIBULAR_SCHWANNOMA_SEG","dbgap_accession_number":"VESTIBULAR_SCHWANNOMA_SEG","study_description":"This collection contains a labelled dataset of MRI images collected on 242 consecutive patients with vestibular schwannoma (VS) undergoing Gamma Knife stereotactic radiosurgery (GK SRS). The structural images included contrast-enhanced T1-weighted (ceT1) images and high-resolution T2-weighted (hrT2) images. Each imaging dataset is accompanied by the patient’s radiation therapy (RT) dataset including the RTDose, RTStructures and RTPlan.Please see the Vestibular-Schwannoma-SEG wiki page to learn more about the images and to obtain any supporting metadata for this collection.","image_types":"MR, RTDOSE, RTPLAN, RTSTRUCT","_subjects_count":242,"doi":"10.7937/TCIA.9YTJ-5Q73","species":"Human","disease_type":"Vestibular Schwannoma (non-cancer)","data_type":"Image Analyses, Software/Source Code","primary_site":"Brain","tags":[{"name":"Vestibular Schwannoma (non-cancer)","category":"disease_type"},{"name":"Image Analyses, Software/Source Code","category":"data_type"},{"name":"Brain","category":"primary_site"}],"commons_name":"CRDC Cancer Imaging Data Commons"}}},{"covid_19_ar":{"gen3_discovery":{"commons":"CRDC Cancer Imaging Data Commons","_unique_id":"covid_19_ar","study_title":"covid_19_ar","accession_number":"covid_19_ar","short_name":"COVID_19_AR","full_name":"COVID_19_AR","dbgap_accession_number":"COVID_19_AR","study_description":"Radiology imaging is playing an increasingly vital role in the diagnosis of COVID-19 patients and determining therapeutic options, patient care management and new research directions. We have published a collection of radiographic and CT imaging studies for patients who tested positive for COVID-19. Each patient is described by a limited set of clinical data correlates that includes demographics, comorbidities, selected lab data and key radiology findings. These data are cross-linked to SARS-COV-2 cDNA sequence data extracted from clinical isolates from the same population, uploaded to the Genbank repository. Please see the COVID-19-AR page to learn more about the images and to obtain any supporting metadata for this collection.","image_types":"CR, CT, DX","_subjects_count":105,"doi":"10.7937/TCIA.2020.PY71-5978","species":"Human","disease_type":"COVID-19 (non-cancer)","data_type":"Clinical, Genomics","primary_site":"Lung","tags":[{"name":"COVID-19 (non-cancer)","category":"disease_type"},{"name":"Clinical, Genomics","category":"data_type"},{"name":"Lung","category":"primary_site"}],"commons_name":"CRDC Cancer Imaging Data Commons"}}},{"nsclc_radiomics_genomics":{"gen3_discovery":{"commons":"CRDC Cancer Imaging Data Commons","_unique_id":"nsclc_radiomics_genomics","study_title":"nsclc_radiomics_genomics","accession_number":"nsclc_radiomics_genomics","short_name":"NSCLC_RADIOMICS_GENOMICS","full_name":"NSCLC_RADIOMICS_GENOMICS","dbgap_accession_number":"NSCLC_RADIOMICS_GENOMICS","study_description":"This collection contains images from 89 non-small cell lung cancer (NSCLC) patients that were treated with surgery. For these patients pretreatment CT scans, gene expression, and clinical data are available. This dataset refers to the Lung3 dataset of the study published in Nature Communications.Please see the NSCLC Radiomics Genomics page to learn more about the images and to obtain any supporting metadata for this collection. ","image_types":"CT","_subjects_count":89,"doi":"10.7937/K9/TCIA.2015.L4FRET6Z","species":"Human","disease_type":"Lung Cancer","data_type":"Clinical, Genomics, Microarray","primary_site":"Lung","tags":[{"name":"Lung Cancer","category":"disease_type"},{"name":"Clinical, Genomics, Microarray","category":"data_type"},{"name":"Lung","category":"primary_site"}],"commons_name":"CRDC Cancer Imaging Data Commons"}}},{"lungct_diagnosis":{"gen3_discovery":{"commons":"CRDC Cancer Imaging Data Commons","_unique_id":"lungct_diagnosis","study_title":"lungct_diagnosis","accession_number":"lungct_diagnosis","short_name":"LUNGCT_DIAGNOSIS","full_name":"LUNGCT_DIAGNOSIS","dbgap_accession_number":"LUNGCT_DIAGNOSIS","study_description":"This is a small set of 61 diagnostic contrast enhanced CT scans with known tumors. The images were retrospectively acquired, to ensure sufficient patient follow-up. Slice thickness is variable : between 3 and 6 mm. All images were done at diagnosis and prior to surgery. Please see the LungCT-Diagnosis page to learn more about the images and to obtain any supporting metadata for this collection.","image_types":"CT","_subjects_count":61,"doi":"10.7937/K9/TCIA.2015.A6V7JIWX","species":"Human","disease_type":"Lung Cancer","data_type":"Clinical, Image Analyses","primary_site":"Lung","tags":[{"name":"Lung Cancer","category":"disease_type"},{"name":"Clinical, Image Analyses","category":"data_type"},{"name":"Lung","category":"primary_site"}],"commons_name":"CRDC Cancer Imaging Data Commons"}}},{"spie_aapm_lung_ct_challenge":{"gen3_discovery":{"commons":"CRDC Cancer Imaging Data Commons","_unique_id":"spie_aapm_lung_ct_challenge","study_title":"spie_aapm_lung_ct_challenge","accession_number":"spie_aapm_lung_ct_challenge","short_name":"SPIE_AAPM_LUNG_CT_CHALLENGE","full_name":"SPIE_AAPM_LUNG_CT_CHALLENGE","dbgap_accession_number":"SPIE_AAPM_LUNG_CT_CHALLENGE","study_description":" As part of the 2015 SPIE Medical Imaging Conference, SPIE – with the support of American Association of Physicists in Medicine (AAPM) and the National Cancer Institute (NCI) – conducted a “Grand Challenge” on quantitative image analysis methods for the diagnostic classification of malignant and benign lung nodules. The LUNGx Challenge provided a unique opportunity for participants to compare their algorithms to those of others from academia, industry, and government in a structured, direct way using the same data sets. Please see the SPIE-AAPM Lung CT Challenge page to learn more about the images and to obtain any supporting metadata for this collection.","image_types":"CT, SEG","_subjects_count":70,"doi":"10.7937/K9/TCIA.2015.UZLSU3FL 10.5281/ZENODO.8345959","species":"Human","disease_type":"Lung Cancer","data_type":"Clinical, Image Analyses","primary_site":"Lung","tags":[{"name":"Lung Cancer","category":"disease_type"},{"name":"Clinical, Image Analyses","category":"data_type"},{"name":"Lung","category":"primary_site"}],"commons_name":"CRDC Cancer Imaging Data Commons"}}},{"breast_mri_nact_pilot":{"gen3_discovery":{"commons":"CRDC Cancer Imaging Data Commons","_unique_id":"breast_mri_nact_pilot","study_title":"breast_mri_nact_pilot","accession_number":"breast_mri_nact_pilot","short_name":"BREAST_MRI_NACT_PILOT","full_name":"BREAST_MRI_NACT_PILOT","dbgap_accession_number":"BREAST_MRI_NACT_PILOT","study_description":"This pilot study to investigate the use of serial DCE MRI examinations during neoadjuvant chemotherapy (NACT) for invasive breast cancer recruited 68 patients with stage II or III locally advanced breast cancer. Longitudinal DCE MRI studies of 64 patients are available.Please see the wiki page Breast-MRI-NACT-Pilot to learn more about the images and to obtain any supporting metadata for this collection.","image_types":"SR, MR, SEG","_subjects_count":64,"doi":"10.7937/K9/TCIA.2016.QHSYHJKY 10.7937/TCIA.2019.WGLLSSG1","species":"Human","disease_type":"Breast Cancer","data_type":"Clinical, Image Analyses","primary_site":"Breast","tags":[{"name":"Breast Cancer","category":"disease_type"},{"name":"Clinical, Image Analyses","category":"data_type"},{"name":"Breast","category":"primary_site"}],"commons_name":"CRDC Cancer Imaging Data Commons"}}},{"qin_breast_dce_mri":{"gen3_discovery":{"commons":"CRDC Cancer Imaging Data Commons","_unique_id":"qin_breast_dce_mri","study_title":"qin_breast_dce_mri","accession_number":"qin_breast_dce_mri","short_name":"QIN_BREAST_DCE_MRI","full_name":"QIN_BREAST_DCE_MRI","dbgap_accession_number":"QIN_BREAST_DCE_MRI","study_description":"This collection of breast dynamic contrast-enhanced (DCE) MRI data contains images from a longitudinal study to assess breast cancer response to neoadjuvant chemotherapy. Images were acquired at four time points: prior to the start of treatment (Visit 1, V1), after the first cycle of treatment (Visit 2, V2), at midpoint of treatment course (Visit 3, V3), and after completion of treatment (prior to surgery) (Visit 4, V4). The value of this collection is to provide clinical imaging data for the development and validation of quantitative imaging methods for assessment of breast cancer response to treatment.Please see the QIN Breast DCE-MRI page to learn more about the images and to obtain any supporting metadata for this collection.","image_types":"KO, MR","_subjects_count":10,"doi":"10.7937/K9/TCIA.2014.A2N1IXOX","species":"Human","disease_type":"Breast Cancer","data_type":"Clinical, Image Analyses","primary_site":"Breast","tags":[{"name":"Breast Cancer","category":"disease_type"},{"name":"Clinical, Image Analyses","category":"data_type"},{"name":"Breast","category":"primary_site"}],"commons_name":"CRDC Cancer Imaging Data Commons"}}},{"breast_diagnosis":{"gen3_discovery":{"commons":"CRDC Cancer Imaging Data Commons","_unique_id":"breast_diagnosis","study_title":"breast_diagnosis","accession_number":"breast_diagnosis","short_name":"BREAST_DIAGNOSIS","full_name":"BREAST_DIAGNOSIS","dbgap_accession_number":"BREAST_DIAGNOSIS","study_description":"The Breast-Diagnosis collection contains cases that are high-risk normals, DCIS, fibroids and lobular carcinomas. Each case has 3 or more distinct MR pulse sequences from a Phillips 1.5 T (usual sequences are labeled T2, STIR and BLISS but may occasionally include other pulse sequences and digital mammogram of tumor specimen). Multiple time point studies on the same patient are possible. Please see the BREAST-DIAGNOSIS page to learn more about the images and to obtain any supporting metadata for this collection.","image_types":"SR, CT, MG, MR, PT","_subjects_count":88,"doi":"10.7937/K9/TCIA.2015.SDNRQXXR 10.7937/TCIA.2019.WGLLSSG1","species":"Human","disease_type":"Breast Cancer","data_type":"Clinical, Image Analyses","primary_site":"Breast","tags":[{"name":"Breast Cancer","category":"disease_type"},{"name":"Clinical, Image Analyses","category":"data_type"},{"name":"Breast","category":"primary_site"}],"commons_name":"CRDC Cancer Imaging Data Commons"}}},{"prostate_diagnosis":{"gen3_discovery":{"commons":"CRDC Cancer Imaging Data Commons","_unique_id":"prostate_diagnosis","study_title":"prostate_diagnosis","accession_number":"prostate_diagnosis","short_name":"PROSTATE_DIAGNOSIS","full_name":"PROSTATE_DIAGNOSIS","dbgap_accession_number":"PROSTATE_DIAGNOSIS","study_description":"Prostate, cancer-confirmed, MRIs obtained using endorectal and phased array surface coils at 1.5T (Philips Achieva). Pulse sequences include T1, T2 and DCE (“BLISS” sequence using Magnevist injected i.v.). Linked clinical information, including matched patient demographics, radiology and pathology reports in XLS format are available.Please see the Prostate-Diagnosis page to learn more about the images and to obtain any supporting metadata for this collection.Data was provided by Boston Medical Center courtesy Dr. Nicolas Bloch. ","image_types":"MR","_subjects_count":92,"doi":"10.7937/K9/TCIA.2015.FOQEUJVT","species":"Human","disease_type":"Prostate Cancer","data_type":"Clinical, Image Analyses","primary_site":"Prostate","tags":[{"name":"Prostate Cancer","category":"disease_type"},{"name":"Clinical, Image Analyses","category":"data_type"},{"name":"Prostate","category":"primary_site"}],"commons_name":"CRDC Cancer Imaging Data Commons"}}},{"cptac_lscc":{"gen3_discovery":{"commons":"CRDC Cancer Imaging Data Commons","_unique_id":"cptac_lscc","study_title":"cptac_lscc","accession_number":"cptac_lscc","short_name":"CPTAC_LSCC","full_name":"CPTAC_LSCC","dbgap_accession_number":"CPTAC_LSCC","study_description":" This collection contains subjects from the National Cancer Institute’s Clinical Proteomic Tumor Analysis Consortium Lung Squamous Cell Carcinoma (CPTAC-LSCC) cohort. CPTAC is a national effort to accelerate the understanding of the molecular basis of cancer through the application of large-scale proteome and genome analysis, or proteogenomics. Radiology and pathology images from CPTAC Phase 3 patients are being collected and made publicly available by The Cancer Imaging Archive to enable researchers to investigate cancer phenotypes which may correlate to corresponding proteomic, genomic and clinical data. Please see the CPTAC-LSCC wiki page to learn more about the radiology images and to obtain any supporting metadata for this collection.Please see the DICOM converted Slide Microscopy images for the CPTAC-LSCC collection page to learn more about the histopathology images and to obtain any supporting metadata for this collection.","image_types":"SM, CT, PT","_subjects_count":212,"doi":"10.5281/ZENODO.12666807 10.7937/K9/TCIA.2018.6EMUB5L2","species":"Human","disease_type":"Squamous Cell Carcinoma","data_type":"Clinical, Genomics, Proteomics","primary_site":"Lung","tags":[{"name":"Squamous Cell Carcinoma","category":"disease_type"},{"name":"Clinical, Genomics, Proteomics","category":"data_type"},{"name":"Lung","category":"primary_site"}],"commons_name":"CRDC Cancer Imaging Data Commons"}}},{"cptac_gbm":{"gen3_discovery":{"commons":"CRDC Cancer Imaging Data Commons","_unique_id":"cptac_gbm","study_title":"cptac_gbm","accession_number":"cptac_gbm","short_name":"CPTAC_GBM","full_name":"CPTAC_GBM","dbgap_accession_number":"CPTAC_GBM","study_description":" This collection contains subjects from the National Cancer Institute’s Clinical Proteomic Tumor Analysis Consortium Glioblastoma Multiforme (CPTAC-GBM) cohort. CPTAC is a national effort to accelerate the understanding of the molecular basis of cancer through the application of large-scale proteome and genome analysis, or proteogenomics. Radiology and pathology images from CPTAC Phase 3 patients are being collected and made publicly available by The Cancer Imaging Archive to enable researchers to investigate cancer phenotypes which may correlate to corresponding proteomic, genomic and clinical data. Please see the CPTAC-GBM wiki page to learn more about the radiology images and to obtain any supporting metadata for this collection.Please see the DICOM converted Slide Microscopy images for the CPTAC-GBM collection page to learn more about the histopathology images and to obtain any supporting metadata for this collection.","image_types":"SM","_subjects_count":178,"doi":"10.5281/ZENODO.12666788","species":"Human","disease_type":"Glioblastoma Multiforme","data_type":"Clinical, Genomics, Proteomics","primary_site":"Brain","tags":[{"name":"Glioblastoma Multiforme","category":"disease_type"},{"name":"Clinical, Genomics, Proteomics","category":"data_type"},{"name":"Brain","category":"primary_site"}],"commons_name":"CRDC Cancer Imaging Data Commons"}}},{"cptac_hnscc":{"gen3_discovery":{"commons":"CRDC Cancer Imaging Data Commons","_unique_id":"cptac_hnscc","study_title":"cptac_hnscc","accession_number":"cptac_hnscc","short_name":"CPTAC_HNSCC","full_name":"CPTAC_HNSCC","dbgap_accession_number":"CPTAC_HNSCC","study_description":" This collection contains subjects from the National Cancer Institute’s Clinical Proteomic Tumor Analysis Consortium Head-and-Neck cancer (CPTAC-HNSCC) cohort. CPTAC is a national effort to accelerate the understanding of the molecular basis of cancer through the application of large-scale proteome and genome analysis, or proteogenomics. Radiology and pathology images from CPTAC Phase 3 patients are being collected and made publicly available by The Cancer Imaging Archive to enable researchers to investigate cancer phenotypes which may correlate to corresponding proteomic, genomic and clinical data. Please see the CPTAC-HNSCC wiki page to learn more about the radiology images and to obtain any supporting metadata for this collection.Please see the DICOM converted Slide Microscopy images for the CPTAC-HNSCC collection page to learn more about the histopathology images and to obtain any supporting metadata for this collection.","image_types":"SM","_subjects_count":112,"doi":"10.5281/ZENODO.12666803","species":"Human","disease_type":"Head and Neck Cancer","data_type":"Clinical, Genomics, Proteomics","primary_site":"Head-Neck","tags":[{"name":"Head and Neck Cancer","category":"disease_type"},{"name":"Clinical, Genomics, Proteomics","category":"data_type"},{"name":"Head-Neck","category":"primary_site"}],"commons_name":"CRDC Cancer Imaging Data Commons"}}},{"cptac_luad":{"gen3_discovery":{"commons":"CRDC Cancer Imaging Data Commons","_unique_id":"cptac_luad","study_title":"cptac_luad","accession_number":"cptac_luad","short_name":"CPTAC_LUAD","full_name":"CPTAC_LUAD","dbgap_accession_number":"CPTAC_LUAD","study_description":" This collection contains subjects from the National Cancer Institute’s Clinical Proteomic Tumor Analysis Consortium Lung Adenocarcinoma (CPTAC-LUAD) cohort. CPTAC is a national effort to accelerate the understanding of the molecular basis of cancer through the application of large-scale proteome and genome analysis, or proteogenomics. Radiology and pathology images from CPTAC Phase 3 patients are being collected and made publicly available by The Cancer Imaging Archive to enable researchers to investigate cancer phenotypes which may correlate to corresponding proteomic, genomic and clinical data. Please see the CPTAC-LUAD wiki page to learn more about the radiology images and to obtain any supporting metadata for this collection.Please see the DICOM converted Slide Microscopy images for the CPTAC-LUAD collection page to learn more about the histopathology images and to obtain any supporting metadata for this collection.","image_types":"SM, CT, MR, PT","_subjects_count":244,"doi":"10.5281/ZENODO.12666813 10.7937/K9/TCIA.2018.PAT12TBS","species":"Human","disease_type":"Lung Adenocarcinoma","data_type":"Clinical, Genomics, Proteomics","primary_site":"Lung","tags":[{"name":"Lung Adenocarcinoma","category":"disease_type"},{"name":"Clinical, Genomics, Proteomics","category":"data_type"},{"name":"Lung","category":"primary_site"}],"commons_name":"CRDC Cancer Imaging Data Commons"}}},{"cptac_ccrcc":{"gen3_discovery":{"commons":"CRDC Cancer Imaging Data Commons","_unique_id":"cptac_ccrcc","study_title":"cptac_ccrcc","accession_number":"cptac_ccrcc","short_name":"CPTAC_CCRCC","full_name":"CPTAC_CCRCC","dbgap_accession_number":"CPTAC_CCRCC","study_description":" This collection contains subjects from the National Cancer Institute’s Clinical Proteomic Tumor Analysis Consortium Clear Cell Renal Cell Carcinoma (CPTAC-CCRCC) cohort. CPTAC is a national effort to accelerate the understanding of the molecular basis of cancer through the application of large-scale proteome and genome analysis, or proteogenomics. Radiology and pathology images from CPTAC Phase 3 patients are being collected and made publicly available by The Cancer Imaging Archive to enable researchers to investigate cancer phenotypes which may correlate to corresponding proteomic, genomic and clinical data. Please see the CPTAC-CCRCC wiki page to learn more about the radiology images and to obtain any supporting metadata for this collection.Please see the DICOM converted Slide Microscopy images for the CPTAC-CCRCC collection page to learn more about the histopathology images and to obtain any supporting metadata for this collection.","image_types":"SM, RTSTRUCT, CT, MR, SEG","_subjects_count":233,"doi":"10.7937/SKQ4-QX48 10.7937/K9/TCIA.2018.OBLAMN27 10.5281/ZENODO.8345959 10.5281/ZENODO.12666768","species":"Human","disease_type":"Clear Cell Carcinoma","data_type":"Clinical, Genomics, Proteomics","primary_site":"Kidney","tags":[{"name":"Clear Cell Carcinoma","category":"disease_type"},{"name":"Clinical, Genomics, Proteomics","category":"data_type"},{"name":"Kidney","category":"primary_site"}],"commons_name":"CRDC Cancer Imaging Data Commons"}}},{"cptac_ucec":{"gen3_discovery":{"commons":"CRDC Cancer Imaging Data Commons","_unique_id":"cptac_ucec","study_title":"cptac_ucec","accession_number":"cptac_ucec","short_name":"CPTAC_UCEC","full_name":"CPTAC_UCEC","dbgap_accession_number":"CPTAC_UCEC","study_description":"This collection contains subjects from the National Cancer Institute''s Clinical Proteomic Tumor Analysis Consortium Uterine Corpus Endometrial Carcinoma (CPTAC-UCEC) cohort. CPTAC is a national effort to accelerate the understanding of the molecular basis of cancer through the application of large-scale proteome and genome analysis, or proteogenomics. Radiology and pathology images from CPTAC Phase 3 patients are being collected and made publicly available by The Cancer Imaging Archive to enable researchers to investigate cancer phenotypes which may correlate to corresponding proteomic, genomic and clinical data.Please see the CPTAC-UCEC wiki page to learn more about the radiologyimages and to obtain any supporting metadata for this collection.Please see the DICOM converted Slide Microscopy images for the CPTAC-UCEC collection page to learn more about the histopathology images and to obtain any supporting metadata for this collection.","image_types":"RTSTRUCT, SM, CT, MR, PT, US","_subjects_count":254,"doi":"10.5281/ZENODO.12666865 10.7937/K9/TCIA.2018.3R3JUISW 10.7937/89M3-KQ43","species":"Human","disease_type":"Corpus Endometrial Carcinoma","data_type":"Clinical, Genomics, Proteomics","primary_site":"Uterus","tags":[{"name":"Corpus Endometrial Carcinoma","category":"disease_type"},{"name":"Clinical, Genomics, Proteomics","category":"data_type"},{"name":"Uterus","category":"primary_site"}],"commons_name":"CRDC Cancer Imaging Data Commons"}}},{"nsclc_radiogenomics":{"gen3_discovery":{"commons":"CRDC Cancer Imaging Data Commons","_unique_id":"nsclc_radiogenomics","study_title":"nsclc_radiogenomics","accession_number":"nsclc_radiogenomics","short_name":"NSCLC_RADIOGENOMICS","full_name":"NSCLC_RADIOGENOMICS","dbgap_accession_number":"NSCLC_RADIOGENOMICS","study_description":"This collection contains images from patients with non-small cell lung cancer imaged prior to surgical excision with both thin-section CT and whole body PET/CT scans acquired under IRB approval from Stanford University and the Veterans Administration Palo Alto Health Care System.The first installment of 26 cases (see shared list "NSCLC Radiogenomics: Initial Stanford Study of 26 Cases") corresponds to microarray data acquired from the excised samples, which is available on the NCBI Gene Expression Omnibus (http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE28827), where DICOM patient names are identical to microarray sample names.Please see the NSCLC Radiogenomics wiki page to learn more about the images and to obtain any supporting metadata for this collection.","image_types":"SEG, CT, PT, SEG","_subjects_count":211,"doi":"10.7937/K9/TCIA.2017.7HS46ERV 10.5281/ZENODO.8345959","species":"Human","disease_type":"Non-small Cell Lung Cancer","data_type":"Clinical, Image Analyses, Genomics","primary_site":"Chest","tags":[{"name":"Non-small Cell Lung Cancer","category":"disease_type"},{"name":"Clinical, Image Analyses, Genomics","category":"data_type"},{"name":"Chest","category":"primary_site"}],"commons_name":"CRDC Cancer Imaging Data Commons"}}},{"soft_tissue_sarcoma":{"gen3_discovery":{"commons":"CRDC Cancer Imaging Data Commons","_unique_id":"soft_tissue_sarcoma","study_title":"soft_tissue_sarcoma","accession_number":"soft_tissue_sarcoma","short_name":"SOFT_TISSUE_SARCOMA","full_name":"SOFT_TISSUE_SARCOMA","dbgap_accession_number":"SOFT_TISSUE_SARCOMA","study_description":"In this study, a cohort of 51 patients with histologically proven soft-tissue sarcomas (STSs) of the extremities was retrospectively evaluated. During the follow-up period, 19 patients developed lung metastases. Patients with metastatic and/or recurrent STSs at presentation were excluded from the study. All patients had pre-treatment FDG-PET/CT and MRI scans.Please see the Soft Tissue Sarcoma page to learn more about the images and to obtain any supporting metadata for this collection.","image_types":"CT, MR, PT, RTSTRUCT","_subjects_count":51,"doi":"10.7937/K9/TCIA.2015.7GO2GSKS","species":"Human","disease_type":"Soft-tissue Sarcoma","data_type":"Clinical, Image Analyses, Software/Source Code","primary_site":"Extremities","tags":[{"name":"Soft-tissue Sarcoma","category":"disease_type"},{"name":"Clinical, Image Analyses, Software/Source Code","category":"data_type"},{"name":"Extremities","category":"primary_site"}],"commons_name":"CRDC Cancer Imaging Data Commons"}}},{"nlst":{"gen3_discovery":{"commons":"CRDC Cancer Imaging Data Commons","_unique_id":"nlst","study_title":"nlst","accession_number":"nlst","short_name":"NLST","full_name":"NLST","dbgap_accession_number":"NLST","study_description":"This collection contains all CT exams from the National Lung Screening Trial (NLST), which was conducted to determine whether screening with low-dose CT could reduce mortality from lung cancer for persons at high risk for lung cancer at 33 U.S. medical centers. Participants were randomly assigned to undergo three annual screenings between 2002-2004. NOTE: The full dataset occupies over 11 Terabytes on disk. Ensure you have what you need before downloading.Please see the NLST wiki page to learn more about the radiology images and to obtain any supporting metadata for this collection.Please see the DICOM converted Slide Microscopy images for the NLST collection wiki page to learn more about the histopathology images and to obtain any supporting metadata for this collection.","image_types":"SM, SEG, SR, CT, SR, SEG","_subjects_count":26410,"doi":"10.5281/ZENODO.8347011 10.5281/ZENODO.12689650 10.5281/ZENODO.17362624 10.5281/ZENODO.7473970 10.5281/ZENODO.8345959 10.5281/ZENODO.15643334 10.7937/TCIA.HMQ8-J677","species":"Human","disease_type":"Lung Cancer, Non-Cancer","data_type":"Clinical","primary_site":"Chest","tags":[{"name":"Lung Cancer, Non-Cancer","category":"disease_type"},{"name":"Clinical","category":"data_type"},{"name":"Chest","category":"primary_site"}],"commons_name":"CRDC Cancer Imaging Data Commons"}}},{"qiba_ct_liver_phantom":{"gen3_discovery":{"commons":"CRDC Cancer Imaging Data Commons","_unique_id":"qiba_ct_liver_phantom","study_title":"qiba_ct_liver_phantom","accession_number":"qiba_ct_liver_phantom","short_name":"QIBA_CT_LIVER_PHANTOM","full_name":"QIBA_CT_LIVER_PHANTOM","dbgap_accession_number":"QIBA_CT_LIVER_PHANTOM","study_description":"This database contains a collection of three sets of CT scan images acquired from an anthropomorphic abdominal phantom with removable liver inserts.Please see the QIBA Anthropomorphic Abdominal Phantom CT Scans to learn more about the images and to obtain any supporting metadata for this collection.","image_types":"CT","_subjects_count":3,"doi":"10.7937/TCIA.RMV0-9Y95","species":"Human","disease_type":"Phantom","data_type":"Image Analyses","primary_site":"Liver Phantom","tags":[{"name":"Phantom","category":"disease_type"},{"name":"Image Analyses","category":"data_type"},{"name":"Liver Phantom","category":"primary_site"}],"commons_name":"CRDC Cancer Imaging Data Commons"}}},{"b_mode_and_ceus_liver":{"gen3_discovery":{"commons":"CRDC Cancer Imaging Data Commons","_unique_id":"b_mode_and_ceus_liver","study_title":"b_mode_and_ceus_liver","accession_number":"b_mode_and_ceus_liver","short_name":"B_MODE_AND_CEUS_LIVER","full_name":"B_MODE_AND_CEUS_LIVER","dbgap_accession_number":"B_MODE_AND_CEUS_LIVER","study_description":"This Collection contains contrast-enhanced ultrasound to a) characterize liver lesions and b) monitor treatment response. Sagittal and transverse plane ultrasound data was obtained with curvilinear probe.Please see the B-mode-and-CEUS-Liver wiki page to learn more about the images and to obtain any supporting metadata for this collection.","image_types":"US","_subjects_count":120,"doi":"10.7937/TCIA.2021.V4Z7-TC39","species":"Human","disease_type":"Liver Cancer","data_type":"Clinical","primary_site":"Liver","tags":[{"name":"Liver Cancer","category":"disease_type"},{"name":"Clinical","category":"data_type"},{"name":"Liver","category":"primary_site"}],"commons_name":"CRDC Cancer Imaging Data Commons"}}},{"cmmd":{"gen3_discovery":{"commons":"CRDC Cancer Imaging Data Commons","_unique_id":"cmmd","study_title":"cmmd","accession_number":"cmmd","short_name":"CMMD","full_name":"CMMD","dbgap_accession_number":"CMMD","study_description":"This collection contains clinical data and 3,728 mammographies (MG) from 1,775 patients, with biopsy-confirmed benign or malignant breast tumors. For a subset of 749 patients (D2-####), molecular subtype is included. Please see the CMMD  wiki page for further detail and associated metadata.","image_types":"MG","_subjects_count":1775,"doi":"10.7937/TCIA.EQDE-4B16","species":"Human","disease_type":"Breast Cancer","data_type":"Clinical","primary_site":"Breast","tags":[{"name":"Breast Cancer","category":"disease_type"},{"name":"Clinical","category":"data_type"},{"name":"Breast","category":"primary_site"}],"commons_name":"CRDC Cancer Imaging Data Commons"}}},{"covid_19_ny_sbu":{"gen3_discovery":{"commons":"CRDC Cancer Imaging Data Commons","_unique_id":"covid_19_ny_sbu","study_title":"covid_19_ny_sbu","accession_number":"covid_19_ny_sbu","short_name":"COVID_19_NY_SBU","full_name":"COVID_19_NY_SBU","dbgap_accession_number":"COVID_19_NY_SBU","study_description":" The collection of cases was acquired at Stony Brook University from patients who tested positive for COVID-19. The collection includes images from different modalities and organ sites (chest radiographs, chest CTs, brain MRIs, etc.). Radiology imaging data is extremely important in COVID-19 from both a diagnostic and a monitoring perspective, given the crucial nature of COVID-19 pulmonary disease and its rapid phenotypic changes. Please see the Stony Brook University COVID-19 Positive Cases  wiki page to learn more about the images and to obtain any supporting metadata for this collection. ","image_types":"CR, CT, DX, MR, NM, OT, PT, SR","_subjects_count":1384,"doi":"10.7937/TCIA.BBAG-2923","species":"Human","disease_type":"COVID-19 (non-cancer)","data_type":"Clinical, Image Analyses","primary_site":"Lung","tags":[{"name":"COVID-19 (non-cancer)","category":"disease_type"},{"name":"Clinical, Image Analyses","category":"data_type"},{"name":"Lung","category":"primary_site"}],"commons_name":"CRDC Cancer Imaging Data Commons"}}},{"duke_breast_cancer_mri":{"gen3_discovery":{"commons":"CRDC Cancer Imaging Data Commons","_unique_id":"duke_breast_cancer_mri","study_title":"duke_breast_cancer_mri","accession_number":"duke_breast_cancer_mri","short_name":"DUKE_BREAST_CANCER_MRI","full_name":"DUKE_BREAST_CANCER_MRI","dbgap_accession_number":"DUKE_BREAST_CANCER_MRI","study_description":"Dynamic contrast-enhanced magnetic resonance images of breast cancer patients with tumor locations (Duke-Breast-Cancer-MRI)This collection contains MRI imaging and other data for 922 patients with invasive breast cancer. Prone position axial breast MRI images were acquired by 1.5T or 3T scanners; non-fat saturated T1, fat-saturated gradient echo T1 pre-contrast, and 3-4 post-contrast sequences are included.Please see the Duke-Breast-Cancer-MRI wiki page to learn more about the images and to obtain the supporting metadata for this collection.","image_types":"MR, SEG, SEG","_subjects_count":922,"doi":"10.5281/ZENODO.8345959 10.7937/TCIA.E3SV-RE93","species":"Human","disease_type":"Breast Cancer","data_type":"Clinical, Genomics, Image Analyses","primary_site":"Breast","tags":[{"name":"Breast Cancer","category":"disease_type"},{"name":"Clinical, Genomics, Image Analyses","category":"data_type"},{"name":"Breast","category":"primary_site"}],"commons_name":"CRDC Cancer Imaging Data Commons"}}},{"cptac_aml":{"gen3_discovery":{"commons":"CRDC Cancer Imaging Data Commons","_unique_id":"cptac_aml","study_title":"cptac_aml","accession_number":"cptac_aml","short_name":"CPTAC_AML","full_name":"CPTAC_AML","dbgap_accession_number":"CPTAC_AML","study_description":" This collection contains subjects from the National Cancer Institute’s Clinical Proteomic Tumor Analysis Consortium Acute Myeloid Leukemia (CPTAC-AML) cohort. CPTAC is a national effort to accelerate the understanding of the molecular basis of cancer through the application of large-scale proteome and genome analysis, or proteogenomics. Please see the DICOM converted Slide Microscopy images for the CPTAC-AML collection wiki page to learn more about the histopathology images and to obtain any supporting metadata for this collection.","image_types":"CT, US, SM","_subjects_count":91,"doi":"10.5281/ZENODO.12666740 10.7937/TCIA.2019.B6FOE619","species":"Human","disease_type":"Acute Myeloid Leukemia","data_type":"Clinical","primary_site":"Marrow, Blood","tags":[{"name":"Acute Myeloid Leukemia","category":"disease_type"},{"name":"Clinical","category":"data_type"},{"name":"Marrow, Blood","category":"primary_site"}],"commons_name":"CRDC Cancer Imaging Data Commons"}}},{"cptac_brca":{"gen3_discovery":{"commons":"CRDC Cancer Imaging Data Commons","_unique_id":"cptac_brca","study_title":"cptac_brca","accession_number":"cptac_brca","short_name":"CPTAC_BRCA","full_name":"CPTAC_BRCA","dbgap_accession_number":"CPTAC_BRCA","study_description":" This collection contains subjects from the National Cancer Institute’s Clinical Proteomic Tumor Analysis Consortium CPTAC Breast Invasive Carcinoma cohort. CPTAC is a national effort to accelerate the understanding of the molecular basis of cancer through the application of large-scale proteome and genome analysis, or proteogenomics. Radiology and pathology images from CPTAC patients are being collected and made publicly available by The Cancer Imaging Archive to enable researchers to investigate cancer phenotypes which may correlate to corresponding proteomic, genomic and clinical data. Please see the DICOM converted Slide Microscopy images for the CPTAC-BRCA collection wiki page to learn more about the histopathology images and to obtain any supporting metadata for this collection.","image_types":"SM","_subjects_count":198,"doi":"10.5281/ZENODO.12666759","species":"Human","disease_type":"Breast Cancer","data_type":"Clinical, Genomics, Proteomics","primary_site":"Breast","tags":[{"name":"Breast Cancer","category":"disease_type"},{"name":"Clinical, Genomics, Proteomics","category":"data_type"},{"name":"Breast","category":"primary_site"}],"commons_name":"CRDC Cancer Imaging Data Commons"}}},{"cptac_coad":{"gen3_discovery":{"commons":"CRDC Cancer Imaging Data Commons","_unique_id":"cptac_coad","study_title":"cptac_coad","accession_number":"cptac_coad","short_name":"CPTAC_COAD","full_name":"CPTAC_COAD","dbgap_accession_number":"CPTAC_COAD","study_description":" This collection contains subjects from the National Cancer Institute’s Clinical Proteomic Tumor Analysis Consortium CPTAC Colon Adenocarcinoma cohort. CPTAC is a national effort to accelerate the understanding of the molecular basis of cancer through the application of large-scale proteome and genome analysis, or proteogenomics.Please see the DICOM converted Slide Microscopy images for the CPTAC-COAD collection page to learn more about the histopathology images and to obtain any supporting metadata for this collection.","image_types":"SM","_subjects_count":178,"doi":"10.5281/ZENODO.12666784","species":"Human","disease_type":"Colon Cancer","data_type":"Clinical, Genomics, Proteomics","primary_site":"Colon","tags":[{"name":"Colon Cancer","category":"disease_type"},{"name":"Clinical, Genomics, Proteomics","category":"data_type"},{"name":"Colon","category":"primary_site"}],"commons_name":"CRDC Cancer Imaging Data Commons"}}},{"cptac_ov":{"gen3_discovery":{"commons":"CRDC Cancer Imaging Data Commons","_unique_id":"cptac_ov","study_title":"cptac_ov","accession_number":"cptac_ov","short_name":"CPTAC_OV","full_name":"CPTAC_OV","dbgap_accession_number":"CPTAC_OV","study_description":" This collection contains subjects from the National Cancer Institute’s Clinical Proteomic Tumor Analysis Consortium CPTAC Ovarian Serous Cystadenocarcinoma cohort. CPTAC is a national effort to accelerate the understanding of the molecular basis of cancer through the application of large-scale proteome and genome analysis, or proteogenomics.Please see the DICOM converted Slide Microscopy images for the CPTAC-OV collection page to learn more about the histopathology images and to obtain any supporting metadata for this collection.","image_types":"SM","_subjects_count":73,"doi":"10.5281/ZENODO.12666842","species":"Human","disease_type":"Ovarian Cancer","data_type":"Clinical, Genomics, Proteomics","primary_site":"Ovary","tags":[{"name":"Ovarian Cancer","category":"disease_type"},{"name":"Clinical, Genomics, Proteomics","category":"data_type"},{"name":"Ovary","category":"primary_site"}],"commons_name":"CRDC Cancer Imaging Data Commons"}}},{"pancreatic_ct_cbct_seg":{"gen3_discovery":{"commons":"CRDC Cancer Imaging Data Commons","_unique_id":"pancreatic_ct_cbct_seg","study_title":"pancreatic_ct_cbct_seg","accession_number":"pancreatic_ct_cbct_seg","short_name":"PANCREATIC_CT_CBCT_SEG","full_name":"PANCREATIC_CT_CBCT_SEG","dbgap_accession_number":"PANCREATIC_CT_CBCT_SEG","study_description":"The objective of this dataset is to provide a means of evaluating the performance of CT-to-CBCT deformable registration and auto-segmentation algorithms for delineating OARs from 40 patients who received ablative radiation therapy for locally advanced pancreatic cancer.The images (one treatment planning CT and two CBCT scans for each of 40 patients) were acquired during a deep inspiration breath-hold verified with an external respiratory monitor.Please see the Pancreatic-CT-CBCT-SEG wiki page to learn more about the images and to obtain any supporting metadata for this collection.","image_types":"CT, RTDOSE, RTSTRUCT","_subjects_count":40,"doi":"10.7937/TCIA.ESHQ-4D90","species":"Human","disease_type":"Pancreatic Cancer","data_type":"Image Analyses","primary_site":"Pancreas","tags":[{"name":"Pancreatic Cancer","category":"disease_type"},{"name":"Image Analyses","category":"data_type"},{"name":"Pancreas","category":"primary_site"}],"commons_name":"CRDC Cancer Imaging Data Commons"}}},{"pediatric_ct_seg":{"gen3_discovery":{"commons":"CRDC Cancer Imaging Data Commons","_unique_id":"pediatric_ct_seg","study_title":"pediatric_ct_seg","accession_number":"pediatric_ct_seg","short_name":"PEDIATRIC_CT_SEG","full_name":"PEDIATRIC_CT_SEG","dbgap_accession_number":"PEDIATRIC_CT_SEG","study_description":"This dataset was collected by a collaboration of researchers from Children’s Wisconsin, Marquette University, Varian Medical Systems, Medical College of Wisconsin, and Stanford University as part of a project funded by the National Institute of Biomedical Imaging and Bioengineering (U01EB023822) to develop tools for rapid, patient-specific CT organ dose estimation. The collection consists of CT images in DICOM format of 359 pediatric chest-abdomen-pelvis or abdomen-pelvis exams acquired from three CT scanners. The datasets represent random pediatric cases based upon routine clinical indications. Each dataset contains expert contours of up to twenty-nine structures in DICOM RTSS format. Please see the Pediatric-CT-SEG page to learn more about the images and to obtain any supporting metadata for this collection.","image_types":"CT, RTSTRUCT","_subjects_count":359,"doi":"10.7937/TCIA.X0H0-1706","species":"Human","disease_type":"Non-Cancer","data_type":"","primary_site":"Various","tags":[{"name":"Non-Cancer","category":"disease_type"},{"name":"","category":"data_type"},{"name":"Various","category":"primary_site"}],"commons_name":"CRDC Cancer Imaging Data Commons"}}},{"tcga_acc":{"gen3_discovery":{"commons":"CRDC Cancer Imaging Data Commons","_unique_id":"tcga_acc","study_title":"tcga_acc","accession_number":"tcga_acc","short_name":"TCGA_ACC","full_name":"TCGA_ACC","dbgap_accession_number":"TCGA_ACC","study_description":" Adrenocortical carcinoma is a rare cancer that develops in the outer layer of tissue of the adrenal glands, organs that lie on top of each kidney. This outer layer known as the adrenal cortex produces important hormones called steroids that help the body deal with stress, regulate blood pressure and the amount of salt in the blood, as well as cause the body to acquire masculine or feminine characteristics. A tumor of the adrenal cortex can produce either no hormones or excess hormones. Please see the DICOM converted Slide Microscopy images for the TCGA-ACC collection page to learn more about the histopathology images and to obtain any supporting metadata for this collection.","image_types":"SEG, SM","_subjects_count":92,"doi":"10.5281/ZENODO.12690035 10.5281/ZENODO.16966285","species":"Human","disease_type":"Adrenocortical Carcinoma","data_type":"","primary_site":"Adrenal Glands","tags":[{"name":"Adrenocortical Carcinoma","category":"disease_type"},{"name":"","category":"data_type"},{"name":"Adrenal Glands","category":"primary_site"}],"commons_name":"CRDC Cancer Imaging Data Commons"}}},{"tcga_chol":{"gen3_discovery":{"commons":"CRDC Cancer Imaging Data Commons","_unique_id":"tcga_chol","study_title":"tcga_chol","accession_number":"tcga_chol","short_name":"TCGA_CHOL","full_name":"TCGA_CHOL","dbgap_accession_number":"TCGA_CHOL","study_description":" Cholangiocarcinoma is a cancer that develops in the bile duct. The bile duct is a network of tubes that carry bile from the liver and gallbladder to the small intestine. Tumors that start in bile duct branches that lie inside the liver are called intrahepatic bile duct cancer, while those that form outside the liver are called extrahepatic bile duct cancer. About 10% of all cholangiocarcinoma are intrahepatic and 90% are extrahepatic. TCGA studied both subtypes of cholangiocarcinoma. Although cholangiocarcinoma is a rare cancer, the incidence and mortality rates for the disease have been increasing worldwide in the last three decades. Between 2,000 and 3,000 Americans are diagnosed with cholangiocarcinoma each year, the majority of them with tumors at advanced stages. This cancer is more prevalent in Asia and the Middle East, where parasitic infection of the bile duct increases the risk of cholangiocarcinoma. Other diseases of the bile duct or liver, such as bile duct stones and liver disease, obesity, diabetes, and smoking are also risk factors. When intrahepatic and extrahepatic cholangiocarcinoma spread to other parts of the body, only 2% of patients survive five years after diagnosis. Please see the DICOM converted Slide Microscopy images for the TCGA-CHOL collection page to learn more about the histopathology images and to obtain any supporting metadata for this collection.","image_types":"SM","_subjects_count":51,"doi":"10.5281/ZENODO.12689990","species":"Human","disease_type":"Cholangiocarcinoma ","data_type":"","primary_site":"Bile Duct","tags":[{"name":"Cholangiocarcinoma ","category":"disease_type"},{"name":"","category":"data_type"},{"name":"Bile Duct","category":"primary_site"}],"commons_name":"CRDC Cancer Imaging Data Commons"}}},{"tcga_dlbc":{"gen3_discovery":{"commons":"CRDC Cancer Imaging Data Commons","_unique_id":"tcga_dlbc","study_title":"tcga_dlbc","accession_number":"tcga_dlbc","short_name":"TCGA_DLBC","full_name":"TCGA_DLBC","dbgap_accession_number":"TCGA_DLBC","study_description":" Please see the DICOM converted Slide Microscopy images for the TCGA-DLBC collection page to learn more about the histopathology images and to obtain any supporting metadata for this collection.","image_types":"SM","_subjects_count":48,"doi":"10.5281/ZENODO.12690047","species":"Human","disease_type":"Lymphoid Neoplasm Diffuse Large B-cell Lymphoma","data_type":"","primary_site":"Various","tags":[{"name":"Lymphoid Neoplasm Diffuse Large B-cell Lymphoma","category":"disease_type"},{"name":"","category":"data_type"},{"name":"Various","category":"primary_site"}],"commons_name":"CRDC Cancer Imaging Data Commons"}}},{"tcga_meso":{"gen3_discovery":{"commons":"CRDC Cancer Imaging Data Commons","_unique_id":"tcga_meso","study_title":"tcga_meso","accession_number":"tcga_meso","short_name":"TCGA_MESO","full_name":"TCGA_MESO","dbgap_accession_number":"TCGA_MESO","study_description":" Mesothelioma is a rare cancer that affects the thin layer of tissue that lines the chest, abdominal cavities, and most of the organs within them. This lining is called the mesothelium.In the United States, there are roughly 3,000 new cases diagnosed each year. Exposure to asbestos is the main risk factor for developing this disease, and men tend to be more commonly affected— a fact that most likely correlates with men holding jobs where they are more likely to come in contact with it. Please see the DICOM converted Slide Microscopy images for the TCGA-MESO collection page to learn more about the histopathology images and to obtain any supporting metadata for this collection.","image_types":"SM, SEG","_subjects_count":87,"doi":"10.5281/ZENODO.16966285 10.5281/ZENODO.12689966","species":"Human","disease_type":"Mesothelioma","data_type":"","primary_site":"Mesothelium","tags":[{"name":"Mesothelioma","category":"disease_type"},{"name":"","category":"data_type"},{"name":"Mesothelium","category":"primary_site"}],"commons_name":"CRDC Cancer Imaging Data Commons"}}},{"tcga_paad":{"gen3_discovery":{"commons":"CRDC Cancer Imaging Data Commons","_unique_id":"tcga_paad","study_title":"tcga_paad","accession_number":"tcga_paad","short_name":"TCGA_PAAD","full_name":"TCGA_PAAD","dbgap_accession_number":"TCGA_PAAD","study_description":" Pancreatic ductal adenocarcinoma is the most common form of pancreatic cancer, making up more than 80% of cases. The disease begins in the cells of the pancreas’s ducts, which transport juices containing digestive enzymes into the small intestine. Pancreatic cancer is the fourth most common cause of global cancer-related deaths and is almost always fatal. In 2012, it was estimated that around 44,000 new cases of pancreatic cancer were diagnosed and more than 37,000 deaths from this disease occurred in the United States alone, affecting both men and women. Please see the DICOM converted Slide Microscopy images for the TCGA-PAAD collection page to learn more about the histopathology images and to obtain any supporting metadata for this collection.","image_types":"SM, ANN, SEG, SEG","_subjects_count":185,"doi":"10.5281/ZENODO.12689972 10.5281/ZENODO.11099004 10.5281/ZENODO.16966285","species":"Human","disease_type":"Pancreatic ductal adenocarcinoma","data_type":"","primary_site":"Pancreas","tags":[{"name":"Pancreatic ductal adenocarcinoma","category":"disease_type"},{"name":"","category":"data_type"},{"name":"Pancreas","category":"primary_site"}],"commons_name":"CRDC Cancer Imaging Data Commons"}}},{"tcga_pcpg":{"gen3_discovery":{"commons":"CRDC Cancer Imaging Data Commons","_unique_id":"tcga_pcpg","study_title":"tcga_pcpg","accession_number":"tcga_pcpg","short_name":"TCGA_PCPG","full_name":"TCGA_PCPG","dbgap_accession_number":"TCGA_PCPG","study_description":" Paraganglioma is a rare cancer that originates in the nerve cells of the adrenal glands, organs on top of each kidney that produce important hormones. Paraganglioma that develops in the center of the adrenal gland is called pheochromocytoma. Paraganglioma that forms outside of the adrenal gland, often along blood vessels and nerves in the head and neck, is called extra-adrenal paraganglioma, or simply paraganglioma.Each year, between 2 and 8 people per million worldwide are diagnosed with paraganglioma and pheochromocytoma. 10% of all cases occur in children. In both adults and children, pheochromocytoma is more common than paraganglioma. No known environmental, dietary, or lifestyle risk factors have been associated with these cancers. Please see the DICOM converted Slide Microscopy images for the TCGA-PCPG collection page to learn more about the histopathology images and to obtain any supporting metadata for this collection.","image_types":"SM","_subjects_count":179,"doi":"10.5281/ZENODO.12689964","species":"Human","disease_type":"Paraganglioma, Pheochromocytoma","data_type":"","primary_site":"Adrenal Glands","tags":[{"name":"Paraganglioma, Pheochromocytoma","category":"disease_type"},{"name":"","category":"data_type"},{"name":"Adrenal Glands","category":"primary_site"}],"commons_name":"CRDC Cancer Imaging Data Commons"}}},{"tcga_skcm":{"gen3_discovery":{"commons":"CRDC Cancer Imaging Data Commons","_unique_id":"tcga_skcm","study_title":"tcga_skcm","accession_number":"tcga_skcm","short_name":"TCGA_SKCM","full_name":"TCGA_SKCM","dbgap_accession_number":"TCGA_SKCM","study_description":" Melanoma is a cancer in a type of skin cells called melanocytes. Melanocyes are the cells that produce melanin, which colors the skin. When exposed to sun, these cells make more melanin, causing the skin to darken or tan. Melanoma can occur anywhere on the body and risk factors include fair complexion, family history of melanoma, and being exposed to natural or artificial sunlight over long periods of time. Melanoma is most often discovered because it has metastasized, or spread, to another organ, such as the lymph nodes. In many cases, the primary skin melanoma site is never found. Because of this challenge, TCGA is studying primarily metastatic cases (in contrast to other cancers selected for study, where metastatic cases are excluded). For 2011, it was estimated that there were 70,230 new cases of melanoma and 8,790 deaths from the disease. Please see the DICOM converted Slide Microscopy images for the TCGA-SKCM collection page to learn more about the histopathology images and to obtain any supporting metadata for this collection.","image_types":"SM, SEG, ANN, SEG","_subjects_count":470,"doi":"10.5281/ZENODO.12690039 10.5281/ZENODO.16966285 10.5281/ZENODO.11099004","species":"Human","disease_type":"Cutaneous Melanoma","data_type":"","primary_site":"Skin","tags":[{"name":"Cutaneous Melanoma","category":"disease_type"},{"name":"","category":"data_type"},{"name":"Skin","category":"primary_site"}],"commons_name":"CRDC Cancer Imaging Data Commons"}}},{"tcga_tgct":{"gen3_discovery":{"commons":"CRDC Cancer Imaging Data Commons","_unique_id":"tcga_tgct","study_title":"tcga_tgct","accession_number":"tcga_tgct","short_name":"TCGA_TGCT","full_name":"TCGA_TGCT","dbgap_accession_number":"TCGA_TGCT","study_description":" More than 90% of testicular cancer start in the germ cells, which are cells in the testicles and develop into sperm. This type of cancer is known as testicular germ cell cancer. Testicular germ cell cancer can be classified as either seminomas or nonseminomas, which may be identified by microscopy. Nonseminomas typically grow and spread more quickly than seminomas. A testicular germ cell tumor that contains a mix of both these subtypes is classified as a nonseminoma. TCGA studied both seminomas and nonseminomas. Testicular germ cell cancer is rare, comprising 1-2% of all tumors in males. However, it is the most common cancer in men ages 15 to 35. The incidence of testicular germ cell cancer has been continuously rising in many countries, including Europe and the U.S. In 2013, about 8,000 American men were estimated to be diagnosed with the cancer. Of those, 370 are predicted to die from the disease. Men who are Caucasian, have an undescended testicle, abnormally developed testicles, or a family history of testicular cancer have a greater risk of developing testicular cancer. Fortunately, testicular germ cell cancer is highly treatable. Please see the DICOM converted Slide Microscopy images for the TCGA-TGCT collection page to learn more about the histopathology images and to obtain any supporting metadata for this collection.","image_types":"SEG, SM","_subjects_count":150,"doi":"10.5281/ZENODO.16966285 10.5281/ZENODO.12689995","species":"Human","disease_type":"Testicular Germ Cell","data_type":"","primary_site":"Testicles","tags":[{"name":"Testicular Germ Cell","category":"disease_type"},{"name":"","category":"data_type"},{"name":"Testicles","category":"primary_site"}],"commons_name":"CRDC Cancer Imaging Data Commons"}}},{"tcga_thym":{"gen3_discovery":{"commons":"CRDC Cancer Imaging Data Commons","_unique_id":"tcga_thym","study_title":"tcga_thym","accession_number":"tcga_thym","short_name":"TCGA_THYM","full_name":"TCGA_THYM","dbgap_accession_number":"TCGA_THYM","study_description":" This cancer develops in the outer surface of the thymus, a gland behind the breastbone that produces T-cells, a type of white blood cells. Thymoma is rare, but it is the most common tumor in adults affecting the mediastinum, which is the cavity between the lungs containing the heart, esophagus, and trachea. A tumor of the thymus tends to grow slowly and rarely spreads to other parts of the body. However, of the estimated 400 Americans who develop this cancer each year, half are diagnosed with metastatic thymoma. When the cancer metastasizes, only 45% of patients survive five years after their diagnosis. Please see the DICOM converted Slide Microscopy images for the TCGA-THYM collection page to learn more about the histopathology images and to obtain any supporting metadata for this collection.","image_types":"SM, SEG","_subjects_count":124,"doi":"10.5281/ZENODO.16966285 10.5281/ZENODO.12689913","species":"Human","disease_type":"Thymoma","data_type":"","primary_site":"Thymus","tags":[{"name":"Thymoma","category":"disease_type"},{"name":"","category":"data_type"},{"name":"Thymus","category":"primary_site"}],"commons_name":"CRDC Cancer Imaging Data Commons"}}},{"tcga_ucs":{"gen3_discovery":{"commons":"CRDC Cancer Imaging Data Commons","_unique_id":"tcga_ucs","study_title":"tcga_ucs","accession_number":"tcga_ucs","short_name":"TCGA_UCS","full_name":"TCGA_UCS","dbgap_accession_number":"TCGA_UCS","study_description":" Uterine carcinosarcoma (UCS) is a cancer that develops in the uterus. Carcinosarcoma signifies that, when looked at under a microscope, the tumor displays histological features of both endometrial carcinoma and sarcoma. Endometrial carcinoma starts in the endometrium, the inner layer of tissue lining the uterus, while sarcoma begins in the outer layer of muscle of the uterus. A rare cancer, UCS makes up less than 5% of all uterine cancers. In the U.S., about two per 100,000 women develop UCS annually. Roughly only 35% of patients survive five years after diagnosis. Please see the DICOM converted Slide Microscopy images for the TCGA-UCS collection page to learn more about the histopathology images and to obtain any supporting metadata for this collection.","image_types":"SM","_subjects_count":57,"doi":"10.5281/ZENODO.12689981","species":"Human","disease_type":"Uterine Carcinosarcoma","data_type":"","primary_site":"Uterus","tags":[{"name":"Uterine Carcinosarcoma","category":"disease_type"},{"name":"","category":"data_type"},{"name":"Uterus","category":"primary_site"}],"commons_name":"CRDC Cancer Imaging Data Commons"}}},{"tcga_uvm":{"gen3_discovery":{"commons":"CRDC Cancer Imaging Data Commons","_unique_id":"tcga_uvm","study_title":"tcga_uvm","accession_number":"tcga_uvm","short_name":"TCGA_UVM","full_name":"TCGA_UVM","dbgap_accession_number":"TCGA_UVM","study_description":" Uveal (intraocular or eye) melanoma develops in the pigment cells of the uvea, which is the middle layer of the eye. The uvea consists of three main parts: the iris, ciliary body, and choroid. Compared to tumors of the iris, tumors of the ciliary body and choroid tend to be larger and more likely to spread to other parts of the body. TCGA studied tumors from all three parts of the uvea. Please see the DICOM converted Slide Microscopy images for the TCGA-UVM collection page to learn more about the histopathology images and to obtain any supporting metadata for this collection.","image_types":"SM, ANN, SEG, SEG","_subjects_count":80,"doi":"10.5281/ZENODO.11099004 10.5281/ZENODO.12690041 10.5281/ZENODO.16966285","species":"Human","disease_type":"Uveal Melanoma","data_type":"","primary_site":"Intraocular","tags":[{"name":"Uveal Melanoma","category":"disease_type"},{"name":"","category":"data_type"},{"name":"Intraocular","category":"primary_site"}],"commons_name":"CRDC Cancer Imaging Data Commons"}}},{"acrin_contralateral_breast_mr":{"gen3_discovery":{"commons":"CRDC Cancer Imaging Data Commons","_unique_id":"acrin_contralateral_breast_mr","study_title":"acrin_contralateral_breast_mr","accession_number":"acrin_contralateral_breast_mr","short_name":"ACRIN_CONTRALATERAL_BREAST_MR","full_name":"ACRIN_CONTRALATERAL_BREAST_MR","dbgap_accession_number":"ACRIN_CONTRALATERAL_BREAST_MR","study_description":"Even after careful clinical and mammographic evaluation, cancer is found in the contralateral breast in up to 10% of women who have received treatment for unilateral breast cancer. ACRIN 6667 was conducted to determine whether magnetic resonance imaging (MRI) could improve on clinical breast examination and mammography in detecting contralateral breast cancer soon after the initial diagnosis of unilateral breast cancer. Please see the ACRIN Contralateral Breast MR (ACRIN 6667) wiki page to learn more about the images and to obtain any supporting metadata for this collection.","image_types":"CR, MR","_subjects_count":984,"doi":"10.7937/Q1EE-J082","species":"Human","disease_type":"Breast Cancer","data_type":"Clinical","primary_site":"Breast","tags":[{"name":"Breast Cancer","category":"disease_type"},{"name":"Clinical","category":"data_type"},{"name":"Breast","category":"primary_site"}],"commons_name":"CRDC Cancer Imaging Data Commons"}}},{"stageii_colorectal_ct":{"gen3_discovery":{"commons":"CRDC Cancer Imaging Data Commons","_unique_id":"stageii_colorectal_ct","study_title":"stageii_colorectal_ct","accession_number":"stageii_colorectal_ct","short_name":"STAGEII_COLORECTAL_CT","full_name":"STAGEII_COLORECTAL_CT","dbgap_accession_number":"STAGEII_COLORECTAL_CT","study_description":"This dataset includes abdominal or pelvic enhanced CT images within 10 days before surgery of 230 patients with stage II colorectal cancer (CRC). Images were acquired on Sensation 64 (Siemens Healthcare, Erlangen, Germany) CT scanner or Brilliance (Philips Healthcare, Best, The Netherlands) CT scanner. Please see the StageII-Colorectal-CT wiki to learn more about the images and to obtain any supporting metadata for this collection.","image_types":"CT","_subjects_count":230,"doi":"10.7937/P5K5-TG43","species":"Human","disease_type":"Colorectal Cancer","data_type":"Software/Source Code","primary_site":"Abdomen, Pelvis","tags":[{"name":"Colorectal Cancer","category":"disease_type"},{"name":"Software/Source Code","category":"data_type"},{"name":"Abdomen, Pelvis","category":"primary_site"}],"commons_name":"CRDC Cancer Imaging Data Commons"}}},{"acrin_6698":{"gen3_discovery":{"commons":"CRDC Cancer Imaging Data Commons","_unique_id":"acrin_6698","study_title":"acrin_6698","accession_number":"acrin_6698","short_name":"ACRIN_6698","full_name":"ACRIN_6698","dbgap_accession_number":"ACRIN_6698","study_description":"The American College of Radiology Imaging Network (ACRIN) trial 6698 was a multi-center study to evaluate the effectiveness of quantitative diffusion weighted imaging (DWI) for assessing breast cancer response to neoadjuvant chemotherapy (NAC).   ACRIN 6698 was performed as a sub-study of the ongoing I-SPY 2 TRIAL (Investigation of Serial studies to Predict Your Therapeutic Response with Imaging And moLecular Analysis 2), an adaptive, multi-agent phase II trial designed to quickly identify new agents for breast cancer.  Please see the ACRIN 6698/I-SPY2 Breast DWI  wiki page to learn more about the images and to obtain any supporting metadata for this collection.  ","image_types":"MR, SEG","_subjects_count":385,"doi":"10.7937/TCIA.KK02-6D95","species":"Human","disease_type":"Breast Cancer","data_type":"Clinical, Image Analyses","primary_site":"Breast","tags":[{"name":"Breast Cancer","category":"disease_type"},{"name":"Clinical, Image Analyses","category":"data_type"},{"name":"Breast","category":"primary_site"}],"commons_name":"CRDC Cancer Imaging Data Commons"}}},{"htan_hms":{"gen3_discovery":{"commons":"CRDC Cancer Imaging Data Commons","_unique_id":"htan_hms","study_title":"htan_hms","accession_number":"htan_hms","short_name":"HTAN_HMS","full_name":"HTAN_HMS","dbgap_accession_number":"HTAN_HMS","study_description":"We are constructing a multi-dimensional atlas of pre-melanoma focused on understanding genetic and epigenetic events that transform melanocytes into invasive tumors. Melanoma is a cancer of increasing prevalence that is curable with minor surgery if detected early but life-threatening when it metastasizes. Melanomas metastasize when still small, making early detection essential but challenging. Our atlas will delineate the precise sequence of events leading up to pre-melanoma through detailed spatial analysis of cell-autonomous events such as oncogene mutation and non-autonomous events such as escape from immune surveillance. The atlas is based on highly-multiplexed tissue imaging and single cell sequencing and focused on samples in which the full sequence of events from atypia to invasive melanoma can be visualized in a single specimen. The atlas will serve as a publicly accessible resource for research scientists, physicians, and patients and improve our ability to (i) highlight lesions likely to progress to cancer, (ii) identify high-risk patients to inform decisions on surgery, (iii) identify low-risk patients to reduce unnecessary procedures, (iv) design improved procedures for routine screening of all individuals, and (v) inform treatment options when surgery is insufficient. Complementary studies with similar goals (but not supported by HTAN) are studying later stage melanomas. Please see the DICOM converted Slide Microscopy images for the HTAN-HMS collection information page to learn more about the images and to obtain any supporting metadata for this collection.","image_types":"PR, SM","_subjects_count":16,"doi":"10.5281/ZENODO.12666872","species":"Human","disease_type":"Adenocarcinoma","data_type":"","primary_site":"Colon","tags":[{"name":"Adenocarcinoma","category":"disease_type"},{"name":"","category":"data_type"},{"name":"Colon","category":"primary_site"}],"commons_name":"CRDC Cancer Imaging Data Commons"}}},{"htan_ohsu":{"gen3_discovery":{"commons":"CRDC Cancer Imaging Data Commons","_unique_id":"htan_ohsu","study_title":"htan_ohsu","accession_number":"htan_ohsu","short_name":"HTAN_OHSU","full_name":"HTAN_OHSU","dbgap_accession_number":"HTAN_OHSU","study_description":"The overall goal of the HTAN OMS Atlas Center is to elucidate mechanisms by which metastatic breast cancers become resistant to current generation pathway- and immune checkpoint-targeted treatments. The OMS Atlas is motivated by the appreciation that these treatments are often effective in primary tumors but only transiently effective in the metastatic setting. Possible resistance mechanisms include tumor-intrinsic genomic instability and epigenomic plasticity, as well as events extrinsic to the cancer cells, including chemical and mechanical signals from the microenvironments, production of mechanical extracellular matrix barriers and/or changes in vasculature that reduce drug and/or immune cell access, nanoscale cancer cell-microenvironment interactions that reduce drug efficacy, and a plethora of immune resistance mechanisms, such as loss of HLA expression and antigen presentation, and immune exhaustion. These mechanisms likely vary between patients and within individual patients and change with time as tumors respond to therapeutic attack. The OMS Atlas will focus on elucidating resistance mechanisms in two specific current generation clinical trial scenarios: (a) hormone receptor-positive breast cancer (HRBC) undergoing treatment with a CDK4/6 inhibitor in combination with endocrine therapy and (b) triple negative breast cancer (TNBC) undergoing treatment with a PARP inhibitor and an immunomodulatory agent. Please see the DICOM converted Slide Microscopy images for the HTAN-OHSU collection information page to learn more about the images and to obtain any supporting metadata for this collection.","image_types":"PR, SM","_subjects_count":1,"doi":"10.5281/ZENODO.12689950","species":"Human","disease_type":"Breast Cancer","data_type":"","primary_site":"Breast","tags":[{"name":"Breast Cancer","category":"disease_type"},{"name":"","category":"data_type"},{"name":"Breast","category":"primary_site"}],"commons_name":"CRDC Cancer Imaging Data Commons"}}},{"htan_wustl":{"gen3_discovery":{"commons":"CRDC Cancer Imaging Data Commons","_unique_id":"htan_wustl","study_title":"htan_wustl","accession_number":"htan_wustl","short_name":"HTAN_WUSTL","full_name":"HTAN_WUSTL","dbgap_accession_number":"HTAN_WUSTL","study_description":" Please see the DICOM converted Slide Microscopy images for the HTAN-WUSTL collection information page to learn more about the images and to obtain any supporting metadata for this collection.","image_types":"PR, SM","_subjects_count":21,"doi":"10.5281/ZENODO.12689993","species":"Human","disease_type":"Ductal adenocarcinoma","data_type":"","primary_site":"Pancreas","tags":[{"name":"Ductal adenocarcinoma","category":"disease_type"},{"name":"","category":"data_type"},{"name":"Pancreas","category":"primary_site"}],"commons_name":"CRDC Cancer Imaging Data Commons"}}},{"ispy2":{"gen3_discovery":{"commons":"CRDC Cancer Imaging Data Commons","_unique_id":"ispy2","study_title":"ispy2","accession_number":"ispy2","short_name":"ISPY2","full_name":"ISPY2","dbgap_accession_number":"ISPY2","study_description":"I-SPY 2 (Investigation of Serial studies to Predict Your Therapeutic Response with Imaging And moLecular analysis 2) is an ongoing, multi-center trial designed to quickly evaluate the efficacy of new agents for breast cancer in neoadjuvant chemotherapy (NAC) setting. Women aged ≥18 years diagnosed with locally advanced breast cancer (tumor size ≥2.5 cm) without distant metastasis are eligible to enroll in the trial. Please see the I-SPY 2 Breast Dynamic Contrast Enhanced MRI (I-SPY2 TRIAL) wiki page to learn more about the images and to obtain any supporting metadata for this collection.","image_types":"MR, SEG","_subjects_count":719,"doi":"10.7937/TCIA.D8Z0-9T85","species":"Human","disease_type":"Breast Cancer","data_type":"Clinical, Image Analyses","primary_site":"Breast","tags":[{"name":"Breast Cancer","category":"disease_type"},{"name":"Clinical, Image Analyses","category":"data_type"},{"name":"Breast","category":"primary_site"}],"commons_name":"CRDC Cancer Imaging Data Commons"}}},{"upenn_gbm":{"gen3_discovery":{"commons":"CRDC Cancer Imaging Data Commons","_unique_id":"upenn_gbm","study_title":"upenn_gbm","accession_number":"upenn_gbm","short_name":"UPENN_GBM","full_name":"UPENN_GBM","dbgap_accession_number":"UPENN_GBM","study_description":" This collection comprises multi-parametric magnetic resonance imaging (mpMRI) scans for de novo Glioblastoma (GBM) patients coupled with patient demographics, clinical outcome (e.g., overall survival, genomic information, tumor progression), as well as computer-aided and manually-corrected segmentation labels of multiple histologically distinct tumor sub-regions, computer-aided and manually-corrected segmentations of the whole brain, a rich panel of radiomic features along with their corresponding co-registered mpMRI volumes in NIfTI format. Please see the Multi-parametric magnetic resonance imaging (mpMRI) scans for de novo Glioblastoma (GBM) patients from the University of Pennsylvania Health System wiki page to learn more about the images and to obtain any supporting metadata for this collection. ","image_types":"SEG, MR","_subjects_count":630,"doi":"10.7937/TCIA.709X-DN49 10.5281/ZENODO.8345959","species":"Human","disease_type":"Glioblastoma","data_type":"Clinical, Image Analyses","primary_site":"Brain","tags":[{"name":"Glioblastoma","category":"disease_type"},{"name":"Clinical, Image Analyses","category":"data_type"},{"name":"Brain","category":"primary_site"}],"commons_name":"CRDC Cancer Imaging Data Commons"}}},{"cmb_crc":{"gen3_discovery":{"commons":"CRDC Cancer Imaging Data Commons","_unique_id":"cmb_crc","study_title":"cmb_crc","accession_number":"cmb_crc","short_name":"CMB_CRC","full_name":"CMB_CRC","dbgap_accession_number":"CMB_CRC","study_description":"The Cancer Moonshot Biobank is a National Cancer Institute initiative to support current and future investigations into drug resistance and sensitivity and other NCI-sponsored cancer research initiatives, with an aim of improving researchers'' understanding of cancer and how to intervene in cancer initiation and progression. During the course of this study, biospecimens (blood and tissue removed during medical procedures) and associated data will be collected longitudinally from at least 1000 patients across at least 10 cancer types, who represent the demographic diversity of the U.S. and receiving standard of care cancer treatment at multiple NCI Community Oncology Research Program (NCORP) sites.This collection contains de-identified radiology and histopathology imaging procured from subjects in NCI’s Cancer Moonshot Biobank-Colorectal Cancer (CMB-CRC) cohort. Associated genomic, phenotypic and clinical data will be hosted by The Database of Genotypes and Phenotypes (dbGaP) and other NCI databases.Please see the Cancer Moonshot Biobank-Colorectal Cancer Collection (CMB-CRC)  page to learn more about the radiology images and to obtain any supporting metadata for this collection.Please see the CMB-CRC: DICOM converted Slide Microscopy images for the Cancer Moonshot Biobank initiative Colorectal Cancer collection page to learn more about the histopathology images and to obtain any supporting metadata for this collection.","image_types":"CT, DX, MR, NM, PT, US, XA, SM","_subjects_count":74,"doi":"10.7937/DJG7-GZ87 10.5281/ZENODO.13993769","species":"Human","disease_type":"Colorectal Cancer","data_type":"Clinical","primary_site":"Colon","tags":[{"name":"Colorectal Cancer","category":"disease_type"},{"name":"Clinical","category":"data_type"},{"name":"Colon","category":"primary_site"}],"commons_name":"CRDC Cancer Imaging Data Commons"}}},{"cmb_gec":{"gen3_discovery":{"commons":"CRDC Cancer Imaging Data Commons","_unique_id":"cmb_gec","study_title":"cmb_gec","accession_number":"cmb_gec","short_name":"CMB_GEC","full_name":"CMB_GEC","dbgap_accession_number":"CMB_GEC","study_description":"The Cancer Moonshot Biobank is a National Cancer Institute initiative to support current and future investigations into drug resistance and sensitivity and other NCI-sponsored cancer research initiatives, with an aim of improving researchers'' understanding of cancer and how to intervene in cancer initiation and progression. During the course of this study, biospecimens (blood and tissue removed during medical procedures) and associated data will be collected longitudinally from at least 1000 patients across at least 10 cancer types, who represent the demographic diversity of the U.S. and receiving standard of care cancer treatment at multiple NCI Community Oncology Research Program (NCORP) sites. This collection contains de-identified radiology and histopathology imaging procured from subjects in NCI’s Cancer Moonshot Biobank - Gastroesophageal Cancer  (CMB-GEC) cohort. Associated genomic, phenotypic and clinical data will be hosted by The Database of Genotypes and Phenotypes (dbGaP) and other NCI databases. Please see the Cancer Moonshot Biobank - Gastroesophageal Cancer Collection (CMB-GEC)  page to learn more about the radiology images and to obtain any supporting metadata for this collection.Please see the CMB-GEC: DICOM converted Slide Microscopy images for the Cancer Moonshot Biobank initiative Gastroesophageal Cancer collection page to learn more about the histopathology images and to obtain any supporting metadata for this collection.","image_types":"CT, MR, PT, SM","_subjects_count":16,"doi":"10.7937/E7KH-R486 10.5281/ZENODO.13993773","species":"Human","disease_type":"Gastroesophageal Cancer","data_type":"Clinical","primary_site":"Esophagus","tags":[{"name":"Gastroesophageal Cancer","category":"disease_type"},{"name":"Clinical","category":"data_type"},{"name":"Esophagus","category":"primary_site"}],"commons_name":"CRDC Cancer Imaging Data Commons"}}},{"cmb_lca":{"gen3_discovery":{"commons":"CRDC Cancer Imaging Data Commons","_unique_id":"cmb_lca","study_title":"cmb_lca","accession_number":"cmb_lca","short_name":"CMB_LCA","full_name":"CMB_LCA","dbgap_accession_number":"CMB_LCA","study_description":"The Cancer Moonshot Biobank is a National Cancer Institute initiative to support current and future investigations into drug resistance and sensitivity and other NCI-sponsored cancer research initiatives, with an aim of improving researchers'' understanding of cancer and how to intervene in cancer initiation and progression. During the course of this study, biospecimens (blood and tissue removed during medical procedures) and associated data will be collected longitudinally from at least 1000 patients across at least 10 cancer types, who represent the demographic diversity of the U.S. and receiving standard of care cancer treatment at multiple NCI Community Oncology Research Program (NCORP) sites.This collection contains de-identified radiology and histopathology imaging procured from subjects in NCI’s Cancer Moonshot Biobank-Colorectal Cancer (CMB-CRC) cohort. Associated genomic, phenotypic and clinical data will be hosted by The Database of Genotypes and Phenotypes (dbGaP) and other NCI databases.Please see the Cancer Moonshot Biobank-Lung Cancer Collection (CMB-LCA)  page to learn more about the radiology images and to obtain any supporting metadata for this collection.Please see the CMB-LCA: DICOM converted Slide Microscopy images for the Cancer Moonshot Biobank initiative Lung Cancer collection page to learn more about the histopathology images and to obtain any supporting metadata for this collection.","image_types":"SM, CT, DX, MR, NM, PT, US","_subjects_count":162,"doi":"10.7937/3CX3-S132 10.5281/ZENODO.13993776","species":"Human","disease_type":"Lung Cancer","data_type":"Clinical","primary_site":"Lung","tags":[{"name":"Lung Cancer","category":"disease_type"},{"name":"Clinical","category":"data_type"},{"name":"Lung","category":"primary_site"}],"commons_name":"CRDC Cancer Imaging Data Commons"}}},{"cmb_mel":{"gen3_discovery":{"commons":"CRDC Cancer Imaging Data Commons","_unique_id":"cmb_mel","study_title":"cmb_mel","accession_number":"cmb_mel","short_name":"CMB_MEL","full_name":"CMB_MEL","dbgap_accession_number":"CMB_MEL","study_description":"The Cancer Moonshot Biobank is a National Cancer Institute initiative to support current and future investigations into drug resistance and sensitivity and other NCI-sponsored cancer research initiatives, with an aim of improving researchers'' understanding of cancer and how to intervene in cancer initiation and progression. During the course of this study, biospecimens (blood and tissue removed during medical procedures) and associated data will be collected longitudinally from at least 1000 patients across at least 10 cancer types, who represent the demographic diversity of the U.S. and receiving standard of care cancer treatment at multiple NCI Community Oncology Research Program (NCORP) sites.This collection contains de-identified radiology and histopathology imaging procured from subjects in NCI’s Cancer Moonshot Biobank-Colorectal Cancer (CMB-CRC) cohort. Associated genomic, phenotypic and clinical data will be hosted by The Database of Genotypes and Phenotypes (dbGaP) and other NCI databases. Please see the Cancer Moonshot Biobank - Melanoma Collection (CMB-MEL)  page to learn more about the radiology images and to obtain any supporting metadata for this collection.Please see the CMB-MEL: DICOM converted Slide Microscopy images for the Cancer Moonshot Biobank initiative Melanoma collection page to learn more about the histopathology images and to obtain any supporting metadata for this collection.","image_types":"CT, MR, PT, US, SM","_subjects_count":54,"doi":"10.5281/ZENODO.13993787 10.7937/GWSP-WH72","species":"Human","disease_type":"Melanoma","data_type":"Clinical","primary_site":"Various","tags":[{"name":"Melanoma","category":"disease_type"},{"name":"Clinical","category":"data_type"},{"name":"Various","category":"primary_site"}],"commons_name":"CRDC Cancer Imaging Data Commons"}}},{"cmb_mml":{"gen3_discovery":{"commons":"CRDC Cancer Imaging Data Commons","_unique_id":"cmb_mml","study_title":"cmb_mml","accession_number":"cmb_mml","short_name":"CMB_MML","full_name":"CMB_MML","dbgap_accession_number":"CMB_MML","study_description":"The Cancer Moonshot Biobank is a National Cancer Institute initiative to support current and future investigations into drug resistance and sensitivity and other NCI-sponsored cancer research initiatives, with an aim of improving researchers'' understanding of cancer and how to intervene in cancer initiation and progression. During the course of this study, biospecimens (blood and tissue removed during medical procedures) and associated data will be collected longitudinally from at least 1000 patients across at least 10 cancer types, who represent the demographic diversity of the U.S. and receiving standard of care cancer treatment at multiple NCI Community Oncology Research Program (NCORP) sites.This collection contains de-identified radiology and histopathology imaging procured from subjects in NCI’s Cancer Moonshot Biobank-Colorectal Cancer (CMB-CRC) cohort. Associated genomic, phenotypic and clinical data will be hosted by The Database of Genotypes and Phenotypes (dbGaP) and other NCI databases.Please see the Cancer Moonshot Biobank-Multiple Myeloma Collection (CMB-MML)  page to learn more about the radiology images and to obtain any supporting metadata for this collection.Please see the CMB-MML: DICOM converted Slide Microscopy images for the Cancer Moonshot Biobank initiative Multiple Myeloma collection page to learn more about the histopathology images and to obtain any supporting metadata for this collection.","image_types":"CR, CT, DX, MR, PT, XA, SM","_subjects_count":138,"doi":"10.7937/SZKB-SW39 10.5281/ZENODO.13993792","species":"Human","disease_type":"Multiple Myeloma","data_type":"Clinical","primary_site":"Blood, Bone","tags":[{"name":"Multiple Myeloma","category":"disease_type"},{"name":"Clinical","category":"data_type"},{"name":"Blood, Bone","category":"primary_site"}],"commons_name":"CRDC Cancer Imaging Data Commons"}}},{"cmb_pca":{"gen3_discovery":{"commons":"CRDC Cancer Imaging Data Commons","_unique_id":"cmb_pca","study_title":"cmb_pca","accession_number":"cmb_pca","short_name":"CMB_PCA","full_name":"CMB_PCA","dbgap_accession_number":"CMB_PCA","study_description":"The Cancer Moonshot Biobank is a National Cancer Institute initiative to support current and future investigations into drug resistance and sensitivity and other NCI-sponsored cancer research initiatives, with an aim of improving researchers'' understanding of cancer and how to intervene in cancer initiation and progression. During the course of this study, biospecimens (blood and tissue removed during medical procedures) and associated data will be collected longitudinally from at least 1000 patients across at least 10 cancer types, who represent the demographic diversity of the U.S. and receiving standard of care cancer treatment at multiple NCI Community Oncology Research Program (NCORP) sites. This collection contains de-identified radiology and histopathology imaging procured from subjects in NCI’s Cancer Moonshot Biobank - Prostate Cancer (CMB-PCA) cohort. Associated genomic, phenotypic and clinical data will be hosted by The Database of Genotypes and Phenotypes (dbGaP) and other NCI databases. Please see the Cancer Moonshot Biobank-Prostate Cancer Collection (CMB-PCA)  page to learn more about the radiology images and to obtain any supporting metadata for this collection.Please see the CMB-PCA: DICOM converted Slide Microscopy images for the Cancer Moonshot Biobank initiative Prostate Cancer collection page to learn more about the histopathology images and to obtain any supporting metadata for this collection.","image_types":"SM, CT, DX, MR, NM, PT, RF","_subjects_count":51,"doi":"10.5281/ZENODO.13993798 10.7937/25T7-6Y12","species":"Human","disease_type":"Prostate Cancer","data_type":"Clinical","primary_site":"Prostate","tags":[{"name":"Prostate Cancer","category":"disease_type"},{"name":"Clinical","category":"data_type"},{"name":"Prostate","category":"primary_site"}],"commons_name":"CRDC Cancer Imaging Data Commons"}}},{"gbm_dsc_mri_dro":{"gen3_discovery":{"commons":"CRDC Cancer Imaging Data Commons","_unique_id":"gbm_dsc_mri_dro","study_title":"gbm_dsc_mri_dro","accession_number":"gbm_dsc_mri_dro","short_name":"GBM_DSC_MRI_DRO","full_name":"GBM_DSC_MRI_DRO","dbgap_accession_number":"GBM_DSC_MRI_DRO","study_description":"The standardization of dynamic susceptibility contrast (DSC)-magnetic resonance imaging (MRI) have been confounded by a lack of consensus on DSC-MRI methodology for preventing potential relative cerebral blood volume (CBV) inaccuracies, including the choice of acquisition protocols and postprocessing algorithms. Therefore, a digital reference object (DRO) was developed using physiological and kinetic parameters derived from a patient database, unique voxel-wise 3-dimensional tissue structures, and a validated MRI signal computational approach. The primary, intended use of the DRO is to validate image acquisition and analysis methods for accurately measuring relative cerebral blood volume in glioblastomas.Please see the GBM-DSC-MRI-DRO  wiki page to learn more about the images and to obtain any supporting metadata for this collection.","image_types":"MR","_subjects_count":3,"doi":"10.7937/TCIA.2020.RMWVZWIX","species":"Human","disease_type":"Phantom","data_type":"","primary_site":"Brain Phantom","tags":[{"name":"Phantom","category":"disease_type"},{"name":"","category":"data_type"},{"name":"Brain Phantom","category":"primary_site"}],"commons_name":"CRDC Cancer Imaging Data Commons"}}},{"hcc_tace_seg":{"gen3_discovery":{"commons":"CRDC Cancer Imaging Data Commons","_unique_id":"hcc_tace_seg","study_title":"hcc_tace_seg","accession_number":"hcc_tace_seg","short_name":"HCC_TACE_SEG","full_name":"HCC_TACE_SEG","dbgap_accession_number":"HCC_TACE_SEG","study_description":"Despite surveillance, the majority of HCC cases are diagnosed at advanced stages that can be treated only using (Transarterial chemoembolization) TACE, or systemic therapy. TACE failure can occur to 60% of patients receiving the procedure, with subsequent financial and emotional burden. Radiomics have emerged as a new tool capable of predicting tumor response to TACE from pre-procedural CT study.This retrospectively acquired data collection includes pre- and post-procedure CT imaging studies of 105 confirmed HCC patients who underwent TACE between 2002 and 2012 with an available treatment outcome, in the form of time-to-progression and overall survival.Please see the HCC-TACE-Seg wiki page to learn more about the images and to obtain any supporting metadata for this collection.","image_types":"SEG, CT, SEG","_subjects_count":105,"doi":"10.7937/TCIA.5FNA-0924 10.5281/ZENODO.8345959","species":"Human","disease_type":"Hepatocellular carcinoma","data_type":"Clinical, Image Analyses, Software/Source Code","primary_site":"Liver","tags":[{"name":"Hepatocellular carcinoma","category":"disease_type"},{"name":"Clinical, Image Analyses, Software/Source Code","category":"data_type"},{"name":"Liver","category":"primary_site"}],"commons_name":"CRDC Cancer Imaging Data Commons"}}},{"pdmr_521955_158_r4":{"gen3_discovery":{"commons":"CRDC Cancer Imaging Data Commons","_unique_id":"pdmr_521955_158_r4","study_title":"pdmr_521955_158_r4","accession_number":"pdmr_521955_158_r4","short_name":"PDMR_521955_158_R4","full_name":"PDMR_521955_158_R4","dbgap_accession_number":"PDMR_521955_158_R4","study_description":"We identified and characterized a patient derived xenograft model with metastatic potential, adenocarcinoma pancreas xenograft 521955-158-R4 from the National Cancer Institute Patient-Derived Models Repository (https://pdmr.cancer.gov/). In this study we performed a detailed imaging characterization of this model, which develops spontaneous lung metastases (bi-weekly MRI) and PET/CT characterization of the primary tumor.Please see the PDMR-521955-158-R4  wiki page to learn more about the images and to obtain any supporting metadata for this collection. ","image_types":"MR, SR","_subjects_count":20,"doi":"10.7937/Q37D-VH79","species":"Mouse","disease_type":"Pancreatic Adenocarcinoma","data_type":"Clinical","primary_site":"Abdomen","tags":[{"name":"Pancreatic Adenocarcinoma","category":"disease_type"},{"name":"Clinical","category":"data_type"},{"name":"Abdomen","category":"primary_site"}],"commons_name":"CRDC Cancer Imaging Data Commons"}}},{"ct_vs_pet_ventilation_imaging":{"gen3_discovery":{"commons":"CRDC Cancer Imaging Data Commons","_unique_id":"ct_vs_pet_ventilation_imaging","study_title":"ct_vs_pet_ventilation_imaging","accession_number":"ct_vs_pet_ventilation_imaging","short_name":"CT_VS_PET_VENTILATION_IMAGING","full_name":"CT_VS_PET_VENTILATION_IMAGING","dbgap_accession_number":"CT_VS_PET_VENTILATION_IMAGING","study_description":"The purpose of the CT Ventilation as a Functional Imaging Modality for Lung Cancer Radiotherapy study was to enable comparisons between: (i) CT ventilation images derived from exhale/inhale BHCT scans, (ii) CT ventilation images derived from free-breathing 4DCT scans, and (iii) Galligas PET (nuclear medicine) ventilation scans. This dataset can build the international capacity for prototyping and evaluating new CT ventilation imaging technologies. For this study, 20 lung cancer patients underwent exhale/inhale breath hold CT (BHCT), free-breathing four-dimensional CT (4DCT) and Galligas PET ventilation scans in a single session on a combined 4DPET/CT scanner.All image acquisitions were performed on a Siemens Biograph mCT.S/64 PET/CT scanner (Siemens, Knoxville, USA) at the Royal North Shore Hospital between 2013 and 2015. A total of 20 4DCT scans, 20 inhale/exhale BHCT scans, 20 Galligas PET scans and 19 attenuation CT scans (missing for CT-PET-VI-07) were successfully acquired for the 20 patients and included in this dataset.Please see the CT-vs-PET-Ventilation-Imaging wiki page to learn more about the images and to obtain any supporting metadata for this collection.","image_types":"CT, PT, RWV","_subjects_count":20,"doi":"10.7937/3PPX-7S22","species":"Human","disease_type":"Lung Cancer","data_type":"","primary_site":"Lung","tags":[{"name":"Lung Cancer","category":"disease_type"},{"name":"","category":"data_type"},{"name":"Lung","category":"primary_site"}],"commons_name":"CRDC Cancer Imaging Data Commons"}}},{"ctpred_sunitinib_pannet":{"gen3_discovery":{"commons":"CRDC Cancer Imaging Data Commons","_unique_id":"ctpred_sunitinib_pannet","study_title":"ctpred_sunitinib_pannet","accession_number":"ctpred_sunitinib_pannet","short_name":"CTPRED_SUNITINIB_PANNET","full_name":"CTPRED_SUNITINIB_PANNET","dbgap_accession_number":"CTPRED_SUNITINIB_PANNET","study_description":"The Prediction of Sunitinib Efficacy using Computed Tomography in Patients with Pancreatic Neuroendocrine Tumors study aimed to develop and validate a computed tomography (CT)-based method to predict the efficacy of sunitinib in Pretreatment CT images of 171 lesions from 38 patients with metastatic or locally advanced pancreatic neuroendocrine tumors (panNET).The dataset can be used to validate the findings of the study. More importantly, researchers can use this dataset to study the imaging characteristics of panNET.Please see the CTpred-Sunitinib-panNET wiki page to learn more about the images and to obtain any supporting metadata for this collection.","image_types":"CT","_subjects_count":38,"doi":"10.7937/SPGK-0P94","species":"Human","disease_type":"Pancreas Cancer","data_type":"","primary_site":"Pancreas","tags":[{"name":"Pancreas Cancer","category":"disease_type"},{"name":"","category":"data_type"},{"name":"Pancreas","category":"primary_site"}],"commons_name":"CRDC Cancer Imaging Data Commons"}}},{"adrenal_acc_ki67_seg":{"gen3_discovery":{"commons":"CRDC Cancer Imaging Data Commons","_unique_id":"adrenal_acc_ki67_seg","study_title":"adrenal_acc_ki67_seg","accession_number":"adrenal_acc_ki67_seg","short_name":"ADRENAL_ACC_KI67_SEG","full_name":"ADRENAL_ACC_KI67_SEG","dbgap_accession_number":"ADRENAL_ACC_KI67_SEG","study_description":"The Ki-67 index is one of the most important established prognostic markers for local recurrence of ACC. Radiomic feature extraction showed a significant association between radiomic signature and Ki-67 expression status in ACC.This retrospectively acquired data includes contrast enhanced CT imaging studies of 53 confirmed ACC patients between 2006 to 2018 with available clinical and pathological data, including Ki-67 index. Semi-automatic segmentation of the adrenal tumor was created using AMIRA, then manually refined by an experienced radiologist. The segmentations of each contrast-enhanced CT were done for the purpose of radiomic features extraction. Please see the Adrenal-ACC-Ki67-Seg wiki page to learn more about the images and to obtain any supporting metadata for this collection.","image_types":"CT, SEG","_subjects_count":53,"doi":"10.7937/1FPG-VM46","species":"Human","disease_type":"Adrenocortical Carcinoma","data_type":"Clinical, Image Analyses","primary_site":"Adrenal","tags":[{"name":"Adrenocortical Carcinoma","category":"disease_type"},{"name":"Clinical, Image Analyses","category":"data_type"},{"name":"Adrenal","category":"primary_site"}],"commons_name":"CRDC Cancer Imaging Data Commons"}}},{"cc_tumor_heterogeneity":{"gen3_discovery":{"commons":"CRDC Cancer Imaging Data Commons","_unique_id":"cc_tumor_heterogeneity","study_title":"cc_tumor_heterogeneity","accession_number":"cc_tumor_heterogeneity","short_name":"CC_TUMOR_HETEROGENEITY","full_name":"CC_TUMOR_HETEROGENEITY","dbgap_accession_number":"CC_TUMOR_HETEROGENEITY","study_description":"The functional and biological properties of the tumor microenvironment are fundamentally important determinants of tumor response and therapy outcome in cancer. Oxygenation status and vascularity are known to influence radiation response, and molecular energy metabolism and proliferation impact on recurrence and metastatic progression. Please see the Cervical Cancer – Tumor Heterogeneity: Serial Functional and Molecular Imaging Across the Radiation Therapy Course in Advanced Cervical Cancer Cervical Cancer  wiki page to learn more about the images and to obtain any supporting metadata for this collection. ","image_types":"CT, MR, PT, REG, RTSTRUCT","_subjects_count":23,"doi":"10.7937/ERZ5-QZ59","species":"Human","disease_type":"Cervical Cancer","data_type":"Clinical","primary_site":"Cervix","tags":[{"name":"Cervical Cancer","category":"disease_type"},{"name":"Clinical","category":"data_type"},{"name":"Cervix","category":"primary_site"}],"commons_name":"CRDC Cancer Imaging Data Commons"}}},{"colorectal_liver_metastases":{"gen3_discovery":{"commons":"CRDC Cancer Imaging Data Commons","_unique_id":"colorectal_liver_metastases","study_title":"colorectal_liver_metastases","accession_number":"colorectal_liver_metastases","short_name":"COLORECTAL_LIVER_METASTASES","full_name":"COLORECTAL_LIVER_METASTASES","dbgap_accession_number":"COLORECTAL_LIVER_METASTASES","study_description":"This collection consists of DICOM images and DICOM Segmentation Objects (DSOs) for 197 patients with Colorectal Liver Metastases (CRLM). The collection consists of a large, single-institution consecutive series of patients that underwent resection of CRLM and matched preoperative computed tomography (CT) scans for quantitative image analysis. Inclusion criteria were (a) pathologically confirmed resected CRLM, (b) available data from pathologic analysis of the underlying non-tumoral liver parenchyma and hepatic tumor, (c) available preoperative conventional portal venous contrast-enhanced multi-detector computed tomography (MDCT) performed within 6 weeks of hepatic resection. Patients with 90-day mortality or that had less than 24 months of follow-up were excluded. Please see the Preoperative CT and Recurrence for Patients Undergoing Resection of Colorectal Liver Metastases (Colorectal Liver Metastases)  wiki page to learn more about the images and to obtain any supporting metadata for this collection.","image_types":"CT, SEG, SEG","_subjects_count":197,"doi":"10.7937/QXK2-QG03 10.5281/ZENODO.8345959","species":"Human","disease_type":"Colorectal Cancer","data_type":"Clinical","primary_site":"Colon","tags":[{"name":"Colorectal Cancer","category":"disease_type"},{"name":"Clinical","category":"data_type"},{"name":"Colon","category":"primary_site"}],"commons_name":"CRDC Cancer Imaging Data Commons"}}},{"htan_vanderbilt":{"gen3_discovery":{"commons":"CRDC Cancer Imaging Data Commons","_unique_id":"htan_vanderbilt","study_title":"htan_vanderbilt","accession_number":"htan_vanderbilt","short_name":"HTAN_VANDERBILT","full_name":"HTAN_VANDERBILT","dbgap_accession_number":"HTAN_VANDERBILT","study_description":"Colorectal cancer (CRC) is among the top three most prevalent cancers in global incidence and mortality. Most of these cancers develop from pre-cancerous adenomas. There is an unmet need to develop new preventive strategies and risk stratification models to decrease incidence, improve early detection, and prevent deaths from CRC.We believe that the ability to provide the most effective precision diagnostics and preventive strategies can only be achieved with single-cell analysis. As such, we will map spatial relationships across the spectrum of normal colon, early polyps, and late adenomas, including their unique stromal and microbial microenvironments to identify unique molecular phenotypes.Our goal will be accomplished through prospective, standardized collection and analysis of colorectal tissue, associated biospecimens, and related clinical and epidemiological data from participants undergoing colonoscopy or surgical resection. The biospecimens from these participants will be used for single-cell RNA sequencing, whole exome sequencing, multiplex immunofluorescence, species-specific bacterial fluorescence in situ hybridization, and other approaches. Finally, the information from these approaches will be integrated to develop a single-cell pre-cancer atlas with defined molecular phenotypes for dissemination to the broader scientific community. Please see the DICOM converted Slide Microscopy images for the HTAN-Vanderbilt collection information page to learn more about the images and to obtain any supporting metadata for this collection.","image_types":"SM","_subjects_count":30,"doi":"10.5281/ZENODO.12690006","species":"Human","disease_type":"Colon Precancer","data_type":"","primary_site":"Colon","tags":[{"name":"Colon Precancer","category":"disease_type"},{"name":"","category":"data_type"},{"name":"Colon","category":"primary_site"}],"commons_name":"CRDC Cancer Imaging Data Commons"}}},{"nlm_visible_human_project":{"gen3_discovery":{"commons":"CRDC Cancer Imaging Data Commons","_unique_id":"nlm_visible_human_project","study_title":"nlm_visible_human_project","accession_number":"nlm_visible_human_project","short_name":"NLM_VISIBLE_HUMAN_PROJECT","full_name":"NLM_VISIBLE_HUMAN_PROJECT","dbgap_accession_number":"NLM_VISIBLE_HUMAN_PROJECT","study_description":"The NLM Visible Human Project has created publicly-available complete, anatomically detailed, three-dimensional representations of a human male body and a human female body. Specifically, the VHP provides a public-domain library of cross-sectional cryosection, CT, and MRI images obtained from one male cadaver and one female cadaver. The Visible Man data set was publicly released in 1994 and the Visible Woman in 1995.The data sets were designed to serve as (1) a reference for the study of human anatomy, (2) public-domain data for testing medical imaging algorithms, and (3) a test bed and model for the construction of network-accessible image libraries. The VHP data sets have been applied to a wide range of educational, diagnostic, treatment planning, virtual reality, artistic, mathematical, and industrial uses. About 4,000 licensees from 66 countries were authorized to access the datasets. As of 2019, a license is no longer required to access the VHP datasets. Courtesy of the U.S. National Library of Medicine. Release of this collection by IDC does not indicate or imply that NLM has endorsed its products/services/applications. Please see the DICOM converted images for the NLM-Visible-Human-Project collection information page to learn more about the images and to obtain any supporting metadata for this collection. Note that this collection may not reflect the most current/accurate data available from NLM.","image_types":"CT, MR, XC","_subjects_count":2,"doi":"10.5281/ZENODO.12690049","species":"Human","disease_type":"Normal (non-cancer)","data_type":"","primary_site":"Whole Body","tags":[{"name":"Normal (non-cancer)","category":"disease_type"},{"name":"","category":"data_type"},{"name":"Whole Body","category":"primary_site"}],"commons_name":"CRDC Cancer Imaging Data Commons"}}},{"prostate_anatomical_edge_cases":{"gen3_discovery":{"commons":"CRDC Cancer Imaging Data Commons","_unique_id":"prostate_anatomical_edge_cases","study_title":"prostate_anatomical_edge_cases","accession_number":"prostate_anatomical_edge_cases","short_name":"PROSTATE_ANATOMICAL_EDGE_CASES","full_name":"PROSTATE_ANATOMICAL_EDGE_CASES","dbgap_accession_number":"PROSTATE_ANATOMICAL_EDGE_CASES","study_description":"In this single institution retrospective study, we reviewed 950 consecutive patients with prostate adenocarcinoma receiving definitive radiotherapy between 2011 and 2019, and identified among them 112 patients with anatomic variations (edge cases) seen on simulation CT and/or MRI imaging. These variations included hip arthroplasty, prostate median lobe hypertrophy, so-called “droopy” seminal vesicles, presence of a urinary catheter, and others. A separate cohort of 19 “normal” cases were randomly selected for inclusion. Prostate, rectum, bladder, and bilateral femoral heads were manually segmented on all CT simulation images (where present) and were ultimately used clinically for radiation treatment planning. Please see the Stress-Testing Pelvic Autosegmentation Algorithms Using Anatomical Edge Cases (Prostate-Anatomical-Edge-Cases)  wiki page to learn more about the images and to obtain any supporting metadata for this collection.","image_types":"CT, RTSTRUCT","_subjects_count":131,"doi":"10.7937/QSTF-ST65","species":"Human","disease_type":"Prostate Cancer","data_type":"","primary_site":"Prostate","tags":[{"name":"Prostate Cancer","category":"disease_type"},{"name":"","category":"data_type"},{"name":"Prostate","category":"primary_site"}],"commons_name":"CRDC Cancer Imaging Data Commons"}}},{"rider_pilot":{"gen3_discovery":{"commons":"CRDC Cancer Imaging Data Commons","_unique_id":"rider_pilot","study_title":"rider_pilot","accession_number":"rider_pilot","short_name":"RIDER_PILOT","full_name":"RIDER_PILOT","dbgap_accession_number":"RIDER_PILOT","study_description":"This data collection was originally supported under supplemental funding for the Lung Image Database Consortium (LIDC) U01 project and focused on the collection of longitudinal studies using X-ray CT for monitoring the response to therapy. The data came primarily from the M.D. Anderson Cancer Center and several of the LIDC academic sites. The data is not annotated. A small subset of the RIDER Pilot data (8 subjects) which were analyzed in QIBA-VolCT-1B  have been re-released on TCIA.More information about the RIDER Pilot sub-collection page can be found in the corresponding section of the RIDER wiki page.","image_types":"PR, SEG, SR, CR, CT, DX","_subjects_count":8,"doi":"10.7937/M87F-MZ83 10.7937/TCIA.2020.1C3H-VP70","species":"Human","disease_type":"Lung Cancer","data_type":"","primary_site":"Lung","tags":[{"name":"Lung Cancer","category":"disease_type"},{"name":"","category":"data_type"},{"name":"Lung","category":"primary_site"}],"commons_name":"CRDC Cancer Imaging Data Commons"}}},{"pdmr_texture_analysis":{"gen3_discovery":{"commons":"CRDC Cancer Imaging Data Commons","_unique_id":"pdmr_texture_analysis","study_title":"pdmr_texture_analysis","accession_number":"pdmr_texture_analysis","short_name":"PDMR_TEXTURE_ANALYSIS","full_name":"PDMR_TEXTURE_ANALYSIS","dbgap_accession_number":"PDMR_TEXTURE_ANALYSIS","study_description":"This collection contains serial non-contrast T2w MRI of 18 patient derived xenograft cancer models (514 images) for researchers to develop various algorithms using neural networks, and classification techniques to improve tissue characterization (morphological changes).   Please see the PDMR-Texture-Analysis  wiki page to learn more about the images and to obtain any supporting metadata for this collection.","image_types":"MR, SR","_subjects_count":175,"doi":"10.7937/3KQ0-YK19","species":"Mouse","disease_type":"Ewing sarcoma - Peripheral PNET, Melanoma, Neuroendocrine cancer (NOS), Osteosarcoma, Anal Squamous Cell Carcinoma, Urothelial - bladder cancer (NOS), Pancreatic Adenocarcinoma, Rectal Adenocarcinoma, Colon adenocarcinoma, Lung Squamous Cell Carcinoma","data_type":"","primary_site":"Arm, Bladder, Buttock, Colon, Liver, Myometrium, Pancreas, Rectum, Shoulder, Scapula","tags":[{"name":"Ewing sarcoma - Peripheral PNET, Melanoma, Neuroendocrine cancer (NOS), Osteosarcoma, Anal Squamous Cell Carcinoma, Urothelial - bladder cancer (NOS), Pancreatic Adenocarcinoma, Rectal Adenocarcinoma, Colon adenocarcinoma, Lung Squamous Cell Carcinoma","category":"disease_type"},{"name":"","category":"data_type"},{"name":"Arm, Bladder, Buttock, Colon, Liver, Myometrium, Pancreas, Rectum, Shoulder, Scapula","category":"primary_site"}],"commons_name":"CRDC Cancer Imaging Data Commons"}}},{"rms_mutation_prediction":{"gen3_discovery":{"commons":"CRDC Cancer Imaging Data Commons","_unique_id":"rms_mutation_prediction","study_title":"rms_mutation_prediction","accession_number":"rms_mutation_prediction","short_name":"RMS_MUTATION_PREDICTION","full_name":"RMS_MUTATION_PREDICTION","dbgap_accession_number":"RMS_MUTATION_PREDICTION","study_description":"RMS is an aggressive soft tissue tumor which is associated with a broad range of pathological mutations. Multiple studies have identified recurrent mutations and chromosomal translocations which are associated with poor outcome in RMS patients. Since not all patients are screened for these mutations with molecular testing, there is a need to develop tools which accurately identify these alterations at diagnosis. Our study associated with these images applied deep learning with convolutional neural networks to learn mutation-associated histological features from H&E images from diagnostic RMS specimens. Please see the RMS-Mutation-Prediction information page to learn more about the images and to obtain any supporting metadata for this collection.","image_types":"SM, SEG, SR","_subjects_count":403,"doi":"10.5281/ZENODO.8225131 10.5281/ZENODO.10462857","species":"Human","disease_type":"Rhabdomyosarcoma","data_type":"Clinical, Genomics, Software source code","primary_site":"Various","tags":[{"name":"Rhabdomyosarcoma","category":"disease_type"},{"name":"Clinical, Genomics, Software source code","category":"data_type"},{"name":"Various","category":"primary_site"}],"commons_name":"CRDC Cancer Imaging Data Commons"}}},{"cmb_aml":{"gen3_discovery":{"commons":"CRDC Cancer Imaging Data Commons","_unique_id":"cmb_aml","study_title":"cmb_aml","accession_number":"cmb_aml","short_name":"CMB_AML","full_name":"CMB_AML","dbgap_accession_number":"CMB_AML","study_description":" The Cancer Moonshot Biobank is a National Cancer Institute initiative to support current and future investigations into drug resistance and sensitivity and other NCI-sponsored cancer research initiatives, with an aim of improving researchers' understanding of cancer and how to intervene in cancer initiation and progression. During the course of this study, biospecimens (blood and tissue removed during medical procedures) and associated data will be collected longitudinally from at least 1000 patients across at least 10 cancer types, who represent the demographic diversity of the U.S. and receiving standard of care cancer treatment at multiple NCI Community Oncology Research Program (NCORP) sites. This collection contains de-identified radiology and histopathology imaging procured from subjects in NCI’s Cancer Moonshot Biobank - Acute Myeloid Leukemia Cancer (CMB-AML) cohort. Associated genomic, phenotypic and clinical data will be hosted by The Database of Genotypes and Phenotypes (dbGaP) and other NCI databases.  A summary of Cancer Moonshot Biobank imaging efforts can be found on the Cancer Moonshot Biobank Imaging page. Please see the Cancer Moonshot Biobank - Acute Myeloid Leukemia Cancer Collection (CMB-AML) page to learn more about the images and to obtain any supporting metadata for this collection.Please see the CMB-AML: DICOM converted Slide Microscopy images for the Cancer Moonshot Biobank initiative Acute Myeloid Leukemia collection page to learn more about the pathology images and to obtain any supporting metadata for this collection.","image_types":"SM, CT, MR, XA","_subjects_count":11,"doi":"10.7937/PCTE-6M66 10.5281/ZENODO.13993759","species":"Human","disease_type":"Acute Myeloid Leukemia","data_type":"Clinical","primary_site":"Blood","tags":[{"name":"Acute Myeloid Leukemia","category":"disease_type"},{"name":"Clinical","category":"data_type"},{"name":"Blood","category":"primary_site"}],"commons_name":"CRDC Cancer Imaging Data Commons"}}},{"ct_phantom4radiomics":{"gen3_discovery":{"commons":"CRDC Cancer Imaging Data Commons","_unique_id":"ct_phantom4radiomics","study_title":"ct_phantom4radiomics","accession_number":"ct_phantom4radiomics","short_name":"CT_PHANTOM4RADIOMICS","full_name":"CT_PHANTOM4RADIOMICS","dbgap_accession_number":"CT_PHANTOM4RADIOMICS","study_description":"The aims of this dataset are to determine the stability of radiomics features against computed tomography (CT) parameter variations and to study their discriminative power concerning tissue classification using a 3D-printed CT phantom based on real patient data . 4 tissue types (normal, benign cyst, hemangioma, and metastasis) were manually annotated. 238 CT series with 8 parameter variations of reconstruction algorithms, reconstruction kernels, slice thickness, and slice spacing are available.Please see the CT-Phantom4Radiomics wiki page to learn more about the images and to obtain any supporting metadata for this collection.","image_types":"CT, SEG","_subjects_count":1,"doi":"10.7937/A1V1-RC66","species":"Human","disease_type":"Phantom","data_type":"Image Analyses, Software/Source Code","primary_site":"Phantom","tags":[{"name":"Phantom","category":"disease_type"},{"name":"Image Analyses, Software/Source Code","category":"data_type"},{"name":"Phantom","category":"primary_site"}],"commons_name":"CRDC Cancer Imaging Data Commons"}}},{"ea1141":{"gen3_discovery":{"commons":"CRDC Cancer Imaging Data Commons","_unique_id":"ea1141","study_title":"ea1141","accession_number":"ea1141","short_name":"EA1141","full_name":"EA1141","dbgap_accession_number":"EA1141","study_description":"This collection contains data from the Eastern Cooperative Oncology Group (ECOG) Clinical Trial NCT02933489, “Abbreviated Breast MRI and Digital Tomosynthesis Mammography in Screening Women With Dense Breasts". Principle Investigator: Christopher Comstock.  It was sponsored by NCI and performed by the Eastern Cooperative Oncology Group under study number EA1141. This randomized phase II trial enrolled 1,516 subjects to study how well abbreviated breast magnetic resonance imaging (MRI) and digital tomosynthesis mammography work in detecting cancer in women with dense breasts. Imaging and clinical data from 500 of those subjects are being made available through this collection. Please see the Abbreviated Breast MRI and Digital Tomosynthesis Mammography in Screening Women With Dense Breasts (EA1141) wiki page to learn more about the images and to obtain any supporting metadata for this collection.","image_types":"CT, MG, MR","_subjects_count":500,"doi":"10.7937/2BAS-HR33","species":"Human","disease_type":"Breast Cancer","data_type":"Clinical","primary_site":"Breast","tags":[{"name":"Breast Cancer","category":"disease_type"},{"name":"Clinical","category":"data_type"},{"name":"Breast","category":"primary_site"}],"commons_name":"CRDC Cancer Imaging Data Commons"}}},{"remind":{"gen3_discovery":{"commons":"CRDC Cancer Imaging Data Commons","_unique_id":"remind","study_title":"remind","accession_number":"remind","short_name":"REMIND","full_name":"REMIND","dbgap_accession_number":"REMIND","study_description":"The Brain Resection Multimodal Imaging Database (ReMIND) contains pre- and intra-operative data collected on 114 consecutive patients who were surgically treated with image-guided tumor resection between 2018 and 2022. For all patients, preoperative MRI, 3D intraoperative ultrasound series, and intraoperative MRI are available. Additionally, each case typically contains segmentations, including the preoperative tumor, the pre-resection cerebrum, the previous resection cavity derived from the preoperative MRI (if applicable), and any residual tumor identified on the intraoperative MRI. In total, this collection contains 369 preoperative MRI series, 320 3D intraoperative ultrasound series, 301 intraoperative MRI series, and 356 segmentations. We expect this data to be a resource for computational research in brain shift and image analysis as well as for neurosurgical training in the interpretation of intraoperative ultrasound and intraoperative MRI. Please see the The Brain Resection Multimodal Imaging Database (ReMIND) wiki page to learn more about the images and to obtain any supporting metadata for this collection.","image_types":"MR, SEG, US","_subjects_count":114,"doi":"10.7937/3RAG-D070","species":"Human","disease_type":"Brain Cancer","data_type":"Clinical","primary_site":"Brain","tags":[{"name":"Brain Cancer","category":"disease_type"},{"name":"Clinical","category":"data_type"},{"name":"Brain","category":"primary_site"}],"commons_name":"CRDC Cancer Imaging Data Commons"}}},{"vestibular_schwannoma_mc_rc":{"gen3_discovery":{"commons":"CRDC Cancer Imaging Data Commons","_unique_id":"vestibular_schwannoma_mc_rc","study_title":"vestibular_schwannoma_mc_rc","accession_number":"vestibular_schwannoma_mc_rc","short_name":"VESTIBULAR_SCHWANNOMA_MC_RC","full_name":"VESTIBULAR_SCHWANNOMA_MC_RC","dbgap_accession_number":"VESTIBULAR_SCHWANNOMA_MC_RC","study_description":"This multi-center routine clinical (MC-RC) dataset consists of 160 patients with a single sporadic Vestibular Schwannoma (VS) who were referred from 10 medical sites and consecutively seen at a single center. These routine clinical datasets are more diverse in terms of the tumor manifestation as well as the acquisition parameters. Using this dataset, researchers can develop and validate methods for automatic surveillance of Vestibular Schwannoma, which work robustly on images acquired at different hospitals. Patients had multiple time points resulting in a total of 428 timepoints and 487 3D-images. Manual ground truth segmentations were obtained in an iterative process in which segmentations were: 1) produced or amended by a specialized company; and 2) reviewed by one of three trained radiologists; and 3) validated by an expert team. Compared to the existing Vestibular-Schwannoma-SEG  dataset on TCIA that was obtained from a single scanner, this dataset was acquired from multiple scanners manufactured by different vendors. This dataset also provides a refined segmentation of intrameatal and extrameatal components of the VS. Please see the Segmentation of Vestibular Schwannoma from Magnetic Resonance Imaging: An Annotated Multi-Center Routine Clinical Dataset (Vestibular-Schwannoma-MC-RC)  wiki page to learn more about the images and to obtain any supporting metadata for this collection.","image_types":"MR","_subjects_count":124,"doi":"10.7937/HRZH-2N82","species":"Human","disease_type":"Vestibular Schwannoma (non-cancer)","data_type":"","primary_site":"Brain","tags":[{"name":"Vestibular Schwannoma (non-cancer)","category":"disease_type"},{"name":"","category":"data_type"},{"name":"Brain","category":"primary_site"}],"commons_name":"CRDC Cancer Imaging Data Commons"}}},{"advanced_mri_breast_lesions":{"gen3_discovery":{"commons":"CRDC Cancer Imaging Data Commons","_unique_id":"advanced_mri_breast_lesions","study_title":"advanced_mri_breast_lesions","accession_number":"advanced_mri_breast_lesions","short_name":"ADVANCED_MRI_BREAST_LESIONS","full_name":"ADVANCED_MRI_BREAST_LESIONS","dbgap_accession_number":"ADVANCED_MRI_BREAST_LESIONS","study_description":"The application of deep-learning methods to breast MRI has a potential to improve diagnosis as well as predict pathological features of the tumors and their response to therapy, and is currently widely investigated. Standard contrast-enhanced MRI of the breast provides high sensitivity but variable specificity in detecting breast cancer, and may lead to excessive benign biopsies. Large, well annotated datasets are needed to improve the current results in this field. This dataset is a single-institutional, retrospective collection of 632 breast-MRI imaging sessions acquired on a 1.5T MR system between 2018-2021. Supporting data, collected for 200 patients from clinical notes, radiology report and pathology reports, is included: patient age, lesion location, malignant/benign outcome, pathology and grade (if applicable), receptor status and KI67 (if applicable). The main uniqueness of this data is that it contains the standard protocol series (T1-weighted DCE sequence with 5 time points- before and 4 time points after contrast injection, and T2-weighted MRI with/without fat suppression) as well as the delayed contrast T1-images acquired 20-28 minutes after contrast administration and the calculated treatment response assessment maps (TRAMs).Please see the Advanced-MRI-Breast-Lesions collection page to learn more about the images and to obtain any supporting metadata for this collection.","image_types":"MR, SEG","_subjects_count":632,"doi":"10.7937/C7X1-YN57","species":"Human","disease_type":"Breast Cancer","data_type":"Clinical","primary_site":"Breast","tags":[{"name":"Breast Cancer","category":"disease_type"},{"name":"Clinical","category":"data_type"},{"name":"Breast","category":"primary_site"}],"commons_name":"CRDC Cancer Imaging Data Commons"}}},{"ccdi_mci":{"gen3_discovery":{"commons":"CRDC Cancer Imaging Data Commons","_unique_id":"ccdi_mci","study_title":"ccdi_mci","accession_number":"ccdi_mci","short_name":"CCDI_MCI","full_name":"CCDI_MCI","dbgap_accession_number":"CCDI_MCI","study_description":"The Molecular Characterization Initiative (MCI) is a component of the National Cancer Institute’s (NCI) Childhood Cancer Data Initiative (CCDI). It offers state-of-the-art molecular testing at no cost to newly diagnosed children, adolescents, and young adults (AYAs) with central nervous system (CNS) tumors, soft tissue sarcomas (STS), certain rare childhood cancers (RAR), and certain neuroblastomas (NBL) treated at a Children’s Oncology Group (COG)–affiliated hospital. The goal of MCI is to enhance the understanding of genetic factors in pediatric cancers and to provide timely, clinically relevant findings to doctors and families to aid in treatment decisions and determine eligibility for certain planned COG clinical trials.Please see the DICOM converted whole slide hematoxylin and eosin stained images from the Molecular Characterization Initiative of the National Cancer Institute's Childhood Cancer Data Initiative information page to learn more about the images and any supporting metadata for this collection, and to learn about attribution/citation requirements.","image_types":"SM","_subjects_count":4407,"doi":"10.5281/ZENODO.11099086","species":"Human","disease_type":"Various","data_type":"","primary_site":"Various","tags":[{"name":"Various","category":"disease_type"},{"name":"","category":"data_type"},{"name":"Various","category":"primary_site"}],"commons_name":"CRDC Cancer Imaging Data Commons"}}},{"gtex":{"gen3_discovery":{"commons":"CRDC Cancer Imaging Data Commons","_unique_id":"gtex","study_title":"gtex","accession_number":"gtex","short_name":"GTEX","full_name":"GTEX","dbgap_accession_number":"GTEX","study_description":"The Genotype-Tissue Expression (GTEx) Project established a data resource and tissue bank to study the relationship between genetic variants and gene expression in multiple human tissues and across individuals. The project included contributions from numerous groups with diverse expertise in biospecimen collection and processing, pathology review, molecular analysis, and data management. The contributors are collectively called the GTEx Consortium.GTEx collected a total of 26,468 unique tissue samples from 50+ different tissue types, from 956 healthy postmortem donors. The standardized biospecimen collection and analysis practices applied during the study served to minimize preanalytical variability associated with specimen-related factors and their potential impact on analytic endpoints. Each GTEx tissue was divided into two tissue blocks, one for histology and one for molecular analysis; both tissue blocks were preserved in PAXgene Tissue Fixative (Qiagen) solution for 6 to 24 hours, followed by PAXgene Tissue Stabilizer (Qiagen) as specified in the project-specific standard operating procedures . Tissue blocks were processed and embedded in paraffin at the GTEx central repository at the Van Andel Institute (MI) and hematoxylin and eosin–stained slides were generated from all GTEx donors. Digitally scanned whole slide images of PAXgene-fixed/stabilized, paraffin-embedded tissue sections were created using Aperio Scanscope software (Leica Biosystems). The digital images were then reviewed and annotated by one of four board-certified pathologists assigned to the GTEx study. There are a total of 25,503 digital histology images in the GTEx collection. Please see the GTEx information page to learn more about the images and to obtain any supporting metadata for this collection.","image_types":"SM","_subjects_count":971,"doi":"10.5281/ZENODO.11099099","species":"Human","disease_type":"Non-diseased","data_type":"Clinical, Genomics","primary_site":"Various","tags":[{"name":"Non-diseased","category":"disease_type"},{"name":"Clinical, Genomics","category":"data_type"},{"name":"Various","category":"primary_site"}],"commons_name":"CRDC Cancer Imaging Data Commons"}}},{"cmb_brca":{"gen3_discovery":{"commons":"CRDC Cancer Imaging Data Commons","_unique_id":"cmb_brca","study_title":"cmb_brca","accession_number":"cmb_brca","short_name":"CMB_BRCA","full_name":"CMB_BRCA","dbgap_accession_number":"CMB_BRCA","study_description":" The Cancer Moonshot Biobank is a National Cancer Institute initiative to support current and future investigations into drug resistance and sensitivity and other NCI-sponsored cancer research initiatives, with an aim of improving researchers' understanding of cancer and how to intervene in cancer initiation and progression. During the course of this study, biospecimens (blood and tissue removed during medical procedures) and associated data will be collected longitudinally from at least 1000 patients across at least 10 cancer types, who represent the demographic diversity of the U.S. and receiving standard of care cancer treatment at multiple NCI Community Oncology Research Program (NCORP) sites.This collection contains de-identified radiology and histopathology imaging procured from subjects in NCI's Cancer Moonshot Biobank-Invasive Breast Carcinoma Cancer (CMB-BRCA) cohort. Associated genomic, phenotypic and clinical data will be hosted by The Database of Genotypes and Phenotypes (dbGaP) and other NCI databases. A summary of Cancer Moonshot Biobank imaging efforts can be found on the Cancer Moonshot Biobank Imaging page. Please see the Cancer Moonshot Biobank-Colorectal Cancer Collection (CMB-BRCA) page to learn more about the radiology mages and to obtain any supporting metadata for this collection.Please see the CMB-BRCA: DICOM converted Slide Microscopy images for the Cancer Moonshot Biobank initiative Invasive Breast Carcinoma collection page to learn more about the pathology images and to obtain any supporting metadata for this collection.","image_types":"SM, CT, MG, MR, PT, US","_subjects_count":78,"doi":"10.7937/DX22-8J71 10.5281/ZENODO.13993761","species":"Human","disease_type":"Breast Invasive Carcinoma","data_type":"Clinical","primary_site":"Breast","tags":[{"name":"Breast Invasive Carcinoma","category":"disease_type"},{"name":"Clinical","category":"data_type"},{"name":"Breast","category":"primary_site"}],"commons_name":"CRDC Cancer Imaging Data Commons"}}},{"cmb_ov":{"gen3_discovery":{"commons":"CRDC Cancer Imaging Data Commons","_unique_id":"cmb_ov","study_title":"cmb_ov","accession_number":"cmb_ov","short_name":"CMB_OV","full_name":"CMB_OV","dbgap_accession_number":"CMB_OV","study_description":"The Cancer Moonshot Biobank is a National Cancer Institute initiative to support current and future investigations into drug resistance and sensitivity and other NCI-sponsored cancer research initiatives, with an aim of improving researchers'' understanding of cancer and how to intervene in cancer initiation and progression. During the course of this study, biospecimens (blood and tissue removed during medical procedures) and associated data will be collected longitudinally from at least 1000 patients across at least 10 cancer types, who represent the demographic diversity of the U.S. and receiving standard of care cancer treatment at multiple NCI Community Oncology Research Program (NCORP) sites.This collection contains de-identified histopathology imaging procured from subjects in NCI’s Cancer Moonshot Biobank-Ovarian Carcinoma Cancer (CMB-OV) cohort. Associated genomic, phenotypic and clinical data will be hosted by The Database of Genotypes and Phenotypes (dbGaP) and other NCI databases.13993796Please see the CMB-OV: DICOM converted Slide Microscopy images for the Cancer Moonshot Biobank initiative Ovarian Cancer collection page to learn more about the pathology images and to obtain any supporting metadata for this collection.","image_types":"CT, SM","_subjects_count":31,"doi":"10.5281/ZENODO.13993796 10.7937/4NX6-E061","species":"Human","disease_type":"Ovarian Cancer","data_type":"Clinical","primary_site":"Ovary","tags":[{"name":"Ovarian Cancer","category":"disease_type"},{"name":"Clinical","category":"data_type"},{"name":"Ovary","category":"primary_site"}],"commons_name":"CRDC Cancer Imaging Data Commons"}}},{"mediastinal_lymph_node_seg":{"gen3_discovery":{"commons":"CRDC Cancer Imaging Data Commons","_unique_id":"mediastinal_lymph_node_seg","study_title":"mediastinal_lymph_node_seg","accession_number":"mediastinal_lymph_node_seg","short_name":"MEDIASTINAL_LYMPH_NODE_SEG","full_name":"MEDIASTINAL_LYMPH_NODE_SEG","dbgap_accession_number":"MEDIASTINAL_LYMPH_NODE_SEG","study_description":"Accurate lymph node size estimation is critical for staging cancer patients, initial therapeutic management, and in longitudinal scans, assessing response to therapy. Machine learning models for medical image segmentation have shown remarkable progress in recent years, but we know of no tools available to fully quantify lymph nodes. Lymph nodes are often within the intensity profile of normal soft tissue and have ill-defined borders. Additionally, their presentation across subjects can vary significantly, making it difficult to scale from small datasets to a robust tool. This dataset contains chest CT scans from 540 patients acquired during treatment for various cancer types, curated for the LNQ2023 MICCAI Challenge to help develop new segmentation tools from weakly annotated cases. The dataset contains both partially annotated (i.e., one mediastinal lymph node out of several in the case are segmented) as well as fully annotated (i.e., all mediastinal lymph nodes are segmented) cases and clinical data (gender/cancer type). Please see the Mediastinal-Lymph-Node-SEG collection page to learn more about the images and to obtain any supporting metadata for this collection.","image_types":"CT, SEG","_subjects_count":513,"doi":"10.7937/QVAZ-JA09","species":"Human","disease_type":"Breast Cancer, Non-small Cell Lung Cancer, Hodgkin Lymphoma, Small Cell Lung Cancer, Thyroid Cancer, Adenocarcinoma, Melanoma, Head and Neck Cancer, Prostate Cancer, Mesothelioma, Ovarian Cancer, Colon Cancer","data_type":"Clinical","primary_site":"Lymph Node","tags":[{"name":"Breast Cancer, Non-small Cell Lung Cancer, Hodgkin Lymphoma, Small Cell Lung Cancer, Thyroid Cancer, Adenocarcinoma, Melanoma, Head and Neck Cancer, Prostate Cancer, Mesothelioma, Ovarian Cancer, Colon Cancer","category":"disease_type"},{"name":"Clinical","category":"data_type"},{"name":"Lymph Node","category":"primary_site"}],"commons_name":"CRDC Cancer Imaging Data Commons"}}},{"spine_mets_ct_seg":{"gen3_discovery":{"commons":"CRDC Cancer Imaging Data Commons","_unique_id":"spine_mets_ct_seg","study_title":"spine_mets_ct_seg","accession_number":"spine_mets_ct_seg","short_name":"SPINE_METS_CT_SEG","full_name":"SPINE_METS_CT_SEG","dbgap_accession_number":"SPINE_METS_CT_SEG","study_description":"This collection contains a dataset of 55 CT scans collected on patients with a large range of primary cancers and corresponding bone metastatic lesions obtained for patients with metastatic spine disease. It includes longitudinal CT imaging data set of patients' metastatic spines planned for and treated with radiotherapy and associated radiological delineations of lesion and vertebral features. In addition to the imaging, we provide demographic data, lesion, fracture annotations, and manually and semi-automated vertebral segmentation labels. This dataset may serve to promote automatic analysis of pathologic vertebrae from computed tomography (CT) scans to improve diagnostic management, and the advancement of machine-learning methods to analyze pathologic vertebral fracture risk drivers in patients with metastatic spine disease.Please see the Spine-Mets-CT-SEG page to learn more about the images and to obtain any supporting metadata for this collection.","image_types":"CT, SEG","_subjects_count":55,"doi":"10.7937/KH36-DS04","species":"Human","disease_type":"Metastatic disease, Bladder Cancer, Breast Cancer, Colon Cancer, Kidney Cancer, Lung Cancer, Prostate Cancer, Soft-tissue Sarcoma, Skin Cancer","data_type":"Clinical","primary_site":"Bone","tags":[{"name":"Metastatic disease, Bladder Cancer, Breast Cancer, Colon Cancer, Kidney Cancer, Lung Cancer, Prostate Cancer, Soft-tissue Sarcoma, Skin Cancer","category":"disease_type"},{"name":"Clinical","category":"data_type"},{"name":"Bone","category":"primary_site"}],"commons_name":"CRDC Cancer Imaging Data Commons"}}},{"bonemarrowwsi_pediatricleukemia":{"gen3_discovery":{"commons":"CRDC Cancer Imaging Data Commons","_unique_id":"bonemarrowwsi_pediatricleukemia","study_title":"bonemarrowwsi_pediatricleukemia","accession_number":"bonemarrowwsi_pediatricleukemia","short_name":"BONEMARROWWSI_PEDIATRICLEUKEMIA","full_name":"BONEMARROWWSI_PEDIATRICLEUKEMIA","dbgap_accession_number":"BONEMARROWWSI_PEDIATRICLEUKEMIA","study_description":"The dataset comprises bone marrow aspirate smear WSI for 246 pediatric cases (< 18 years) of leukemia, including acute lymphoid leukemia (ALL), acute myeloid leukemia (AML), and chronic myeloid leukemia (CML). The smears were prepared for the initial diagnosis (i.e., without prior treatment), stained in accordance with the Pappenheim method, and scanned at 40x magnification (without immersion), resulting in a resolution of 0.11x0.11 µm/pixel. Additionally, clinical information (age group, sex, diagnosis) and laboratory data (blasts, white blood cell count, thrombocytes, LDH, uric acid, hemoglobin) are available for each case.Please see the BoneMarrowWSI-PediatricLeukemia: A Comprehensive Dataset of Bone Marrow Aspirate Smear Whole Slide Images with Expert Annotations and Clinical Data in Pediatric Leukemia information page to learn more about the images and to obtain any supporting metadata for this collection.","image_types":"ANN, SM","_subjects_count":246,"doi":"10.5281/ZENODO.14933087","species":"Human","disease_type":"Leukemia","data_type":"Clinical","primary_site":"Bone Marrow","tags":[{"name":"Leukemia","category":"disease_type"},{"name":"Clinical","category":"data_type"},{"name":"Bone Marrow","category":"primary_site"}],"commons_name":"CRDC Cancer Imaging Data Commons"}}},{"ct4harmonization_multicentric":{"gen3_discovery":{"commons":"CRDC Cancer Imaging Data Commons","_unique_id":"ct4harmonization_multicentric","study_title":"ct4harmonization_multicentric","accession_number":"ct4harmonization_multicentric","short_name":"CT4HARMONIZATION_MULTICENTRIC","full_name":"CT4HARMONIZATION_MULTICENTRIC","dbgap_accession_number":"CT4HARMONIZATION_MULTICENTRIC","study_description":"This collection introduces an open-source, anthropomorphic phantom-based dataset of CT scans for developing harmonization methods for deep learning based models. The phantom mimics human anatomy, allowing repeated scans without radiation delivery to real patients and isolating scanner effects by removing inter- and intra-patient variations. The dataset includes 268 image series from 13 scanners, 4 manufacturers, and 8 institutions, repeated 18-30 times at a 10 mGy dose using a harmonized protocol. An additional 1,378 image series were acquired with the same 13 scanners and  harmonized protocol but including additional acquisition doses. The presented phantom scans consist of three compartments from thorax, liver and test patterns. 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It will extend the data from the International HapMap Project, which created a resource that has been used to find more than 100 regions of the genome that are associated with common human diseases such as coronary artery disease and diabetes. The goal of the 1000 Genomes Project is to provide a resource of almost all variants, including SNPs and structural variants, and their haplotype contexts. This resource will allow genome-wide association studies to focus on almost all variants that exist in regions found to be associated with disease. The genomes of over 1000 unidentified individuals from around the world will be sequenced using next generation sequencing technologies. The results of the study will be publicly accessible to researchers worldwide.","full_name":"1000 Genomes Project","short_name":"OpenAccess-1000_Genomes_Project","commons":"Open Access Data Commons","study_url":"https://www.genome.gov/27528684/1000-genomes-project","_subjects_count":0,"__manifest":[{"md5sum":"e1e56e29efad64c002e5e9749f85350f","file_name":"ALL.chrY.phase3_integrated_v2b.20130502.genotypes.vcf.gz","file_size":5656911,"object_id":"dg.OADC/60afa140-d2ab-4e32-bf73-40bf48787655","commons_url":"gen3.datacommons.io/"},{"md5sum":"b405180c1328a0fc93b668fa4d24c302","file_name":"ALL.chrY.phase3_integrated_v2b.20130502.genotypes.vcf.gz.tbi","file_size":8077,"object_id":"dg.OADC/fded0c2c-8a18-413f-91e2-f132853ed91a","commons_url":"gen3.datacommons.io/"},{"md5sum":"09158d4beeb679fa70a7cabd3fc504a5","file_name":"igsr_populations.tsv","file_size":30970,"object_id":"dg.OADC/9baeeb42-563f-47fe-87f7-a6ae17fc3d20","commons_url":"gen3.datacommons.io/"},{"md5sum":"435bbcd5f4b6e2ce2d07dbba4910b2ca","file_name":"integrated_call_samples_v3.20200731.ALL.ped","file_size":209431,"object_id":"dg.OADC/096880f8-07e4-4a76-ba53-b4b6402d4dc3","commons_url":"gen3.datacommons.io/"}],"commons_url":"gen3.datacommons.io","commons_name":"Open Access Data Commons"}}},{"ACCOuNT_Clopidogrel_Arm":{"gen3_discovery":{"authz":"/programs/discovery/projects/clopidogrel","tags":[{"name":"","category":""}],"_unique_id":null,"study_id":null,"study_description":"Pharmacogenomics is aimed at identifying genetic variation (SNPs) that influence inter-individual differences in drug response and adverse events and has widespread clinical relevance. Its application promises to enable targeted drug administration, improve therapeutic outcome, and inform drug development. Pharmacogenomic insights have improved our understanding of the underlying pathways and mechanisms behind adverse drug reactions, which account for approximately 100,000 deaths per year in the US and markedly increase healthcare costs. The vast majority of pharmacogenomic association studies, which are the drivers of discovery in the field of precision medicine, have been conducted on exclusively European populations, thereby precluding the discovery of African American specific genetic biomarkers that affect drug phenotypes. Without scientific inquiry on the presence and association of these SNPs to drug response, our ability to deliver precision medicine to 1 in 7 Americans is severely hampered. To close this growing heath disparity in African American precision medicine we formed ACCOuNT and are proposing a discovery project within cardiovascular pharmacogenomics. In our Discovery project, we hypothesize that through discovery efforts centered on African Americans, we will identify predictive biomarkers of cardiovascular drug response and disease susceptibility that can be investigated in translational outcome studies. We will test this hypothesis with the following aims: 1) Determine genetic predictors of drug response to thrombotic therapy using genome-wide association methodology, 2) Investigate the role of gene expression/splice variants and eQTLs on drug response phenotypes for elucidation of biological mechanisms and genetic regulation of these phenotypes, and 3) Create a publically available and searchable database to house the results of the genomic and transcriptomic studies in African Americans. Through the infrastructure of ACCOuNT we will conduct our discovery efforts with a patient-centered approach that incorporates the input of community partners, frontline physicians and African American patients. We anticipate that these studies will reveal novel SNP associations and gene regulation pathways. Several potential research areas/questions may develop from this work. Our proposed genomics database will serve as needed resource within the pharmacogenomics scientific community, which currently lacks comprehensive genomics and transcriptomic information on African Americans. 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Previous transcriptomic studies investigating the mechanisms of PTSD apply targeted approaches to identify individual genes under a cross-sectional framework lack a holistic view of the behaviours and properties of these genes at the system-level. Here we sought to apply an unsupervised gene-network-based approach to a prospective experimental design using whole-transcriptome RNA-Seq gene expression from peripheral blood leukocytes of U.S. Marines (N=188), obtained both pre- and post-deployment to conflict zones. We identified discrete groups of co-regulated genes (i.e., co-expression modules) and tested them for association to PTSD. We identified one module at both pre- and post-deployment containing putative causal signatures for PTSD development displaying an over-expression of genes enriched for functions of innate-immune response and interferon signalling (Type-I and Type-II). Importantly, these results were replicated in a second non-overlapping independent dataset of U.S. Marines (N=96), further outlining the role of innate immune and interferon signalling genes within co-expression modules to explain at least part of the causal pathophysiology for PTSD development. A second module, consequential of trauma exposure, contained PTSD resiliency signatures and an over-expression of genes involved in hemostasis and wound responsiveness suggesting that chronic levels of stress impair proper wound healing during/after exposure to the battlefield while highlighting the role of the hemostatic system as a clinical indicator of chronic-based stress. These findings provide novel insights for early preventative measures and advanced PTSD detection, which may lead to interventions that delay or perhaps abrogate the development of PTSD.\nWe used microarrays to characterize both prognostic and diagnostic molecular signatures associated to PTSD risk and PTSD status compared to control subjects.","full_name":"Gene Networks Specific for Innate Immunity Define Post-traumatic Stress Disorder [Affymetrix]","short_name":"GEO-GSE63878","commons":"Open Access Data 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