Cohorts for Heart and Aging Research in Genomic Epidemiology

Cohorts for Heart and Aging Research in Genomic Epidemiology
Name	Cohorts for Heart and Aging Research in Genomic Epidemiology
Abbreviation	CHARGE
Established	2008
Focus	cardiovascular disease, aging, genomics
Participants	multiple longitudinal cohorts
Headquarters	United States and Europe

Cohorts for Heart and Aging Research in Genomic Epidemiology is a multi‑consortium research initiative that aggregates longitudinal population cohorts to investigate genetic determinants of cardiovascular disease and aging‑related traits. The consortium integrates phenotypic, clinical, and genomic data across international studies to improve risk prediction, mechanistic understanding, and translational potential for complex diseases.

Overview and Objectives

CHARGE was formed to coordinate large‑scale genomic epidemiology across established longitudinal studies such as the Framingham Heart Study, Atherosclerosis Risk in Communities Study, Cardiovascular Health Study, Rotterdam Study, and Jackson Heart Study to discover loci associated with cardiovascular and aging phenotypes. Primary objectives include genome‑wide association discovery, replication, meta‑analysis, and integration with biomarker and imaging data from cohorts including Women's Health Initiative, Cardiovascular Disease in Sweden (MONICA), Baltimore Longitudinal Study of Aging, and NHLBI‑funded initiatives. The consortium emphasizes harmonization across heterogeneous datasets and collaboration with consortia like GIANT (consortium), ENCODE Project, 1000 Genomes Project, and UK Biobank.

Cohort Composition and Recruitment

Participating cohorts span diverse populations represented by studies such as Framingham Heart Study, Rotterdam Study, Atherosclerosis Risk in Communities Study, Cardiovascular Health Study, Jackson Heart Study, Multi-Ethnic Study of Atherosclerosis, Bogalusa Heart Study, Health ABC Study, HUNT Study, and WHI (Women's Health Initiative). Recruitment strategies followed protocols from institutions including National Heart, Lung, and Blood Institute, Erasmus MC, Johns Hopkins University, University of Minnesota, and University of Washington. Many cohorts include substudies linked to registries like Medicare or national biobanks such as Estonian Biobank. Populations cover European, African, Hispanic, and Asian ancestries, with contributions from centers associated with Harvard Medical School, University of California, San Francisco, Columbia University, and Mayo Clinic.

Study Design and Data Collection

CHARGE leverages prospective cohort designs, repeated measures, and event adjudication frameworks used in the Framingham Heart Study and Cardiovascular Health Study to ascertain outcomes like myocardial infarction, stroke, atrial fibrillation, and heart failure. Phenotypes were standardized using clinical criteria promulgated by organizations including the American Heart Association, World Health Organization, and European Society of Cardiology. Data collection incorporated electrocardiography, echocardiography, carotid ultrasonography, computed tomography, and biomarkers measured at centers such as Massachusetts General Hospital and Mayo Clinic. Longitudinal follow‑up linked to death registries like the National Death Index and hospitalization data from Centers for Medicare & Medicaid Services enhanced outcome capture.

Genomic and Biomarker Analyses

Genotyping platforms and imputation leveraged resources including Affymetrix, Illumina, the 1000 Genomes Project, and the Haplotype Reference Consortium. CHARGE conducted genome‑wide association studies and meta‑analyses, integrating expression quantitative trait loci and epigenetic annotations from projects like GTEx, ENCODE Project, and methylation studies from Roadmap Epigenomics to prioritize candidate genes. Biomarker assays included measurements of C‑reactive protein, lipid fractions, natriuretic peptides, and troponins performed in laboratories affiliated with Laboratory Corporation of America and academic centers such as Johns Hopkins Hospital. Downstream analyses connected loci to pathways cataloged in KEGG and Reactome and to drug targets referenced by Food and Drug Administration approvals.

Major Findings and Contributions

CHARGE contributed to the discovery of loci associated with coronary artery disease, atrial fibrillation, stroke, longevity, and blood pressure, complementing findings from the CARDIoGRAM and GIANT (consortium) collaborations. Notable contributions include genetic associations implicating genes such as those studied in work from Framingham Heart Study investigators and replication in cohorts like Rotterdam Study and Atherosclerosis Risk in Communities Study. Findings informed polygenic risk score development paralleling efforts in UK Biobank and influenced interpretation of biomarkers used in guidelines by the American College of Cardiology and European Society of Cardiology. CHARGE publications have been cited alongside landmark studies by groups at Harvard University, Stanford University, and Imperial College London.

Collaborations and Data Access

CHARGE operates through a steering committee model similar to consortia such as GIANT (consortium) and CARDIoGRAM. Collaborative partnerships include interactions with the National Human Genome Research Institute, National Heart, Lung, and Blood Institute, and international cohorts coordinated by Erasmus MC and University of Groningen. Data sharing follows controlled‑access models used by the Database of Genotypes and Phenotypes and complies with policies from funders including the National Institutes of Health. Investigators from institutions like Harvard Medical School, University of Washington, Columbia University, and Mayo Clinic have accessed harmonized summary statistics under consortium agreements.

Ethical, Legal, and Social Considerations

Ethical oversight was provided via institutional review boards at participating centers including Johns Hopkins University, Erasmus MC, University of Washington, and Mayo Clinic with informed consent frameworks aligned to guidance from the Belmont Report and Common Rule. Data governance addressed re‑identification risks highlighted in debates involving National Institutes of Health policies and initiatives such as Global Alliance for Genomics and Health. Return‑of‑results practices paralleled guidelines from the American College of Medical Genetics and Genomics, while efforts toward inclusion and equity engaged community partners from studies like Jackson Heart Study and Hispanic Community Health Study/Study of Latinos to mitigate disparities.

Category:Genomic epidemiology