Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Consortium

Jerome I. Rotter, Vilmundur Guðnason, Tamara B. Harris, Kathryn L. Lunetta, Eric Boerwinkle, Bruce M. Psaty, Christopher J. O’Donnell, André G. Uitterlinden, Aaron R. Folsom, Jacqueline C.M. Witteman
2009-02-01

SCID:  54.1/zfj7u22u
BACKGROUND: The primary aim of genome-wide association studies is to identify novel genetic loci associated with interindividual variation in the levels of risk factors, the degree of subclinical disease, or the risk of clinical disease. The requirement for large sample sizes and the importance of replication have served as powerful incentives for scientific collaboration. Methods- The Cohorts for Heart and Aging Research in Genomic Epidemiology Consortium was formed to facilitate genome-wide association studies meta-analyses and replication opportunities among multiple large population-based cohort studies, which collect data in a standardized fashion and represent the preferred method for estimating disease incidence. The design of the Cohorts for Heart and Aging Research in Genomic Epidemiology Consortium includes 5 prospective cohort studies from the United States and Europe: the Age, Gene/Environment Susceptibility-Reykjavik Study, the Atherosclerosis Risk in Communities Study, the Cardiovascular Health Study, the Framingham Heart Study, and the Rotterdam Study. With genome-wide data on a total of about 38 000 individuals, these cohort studies have a large number of health-related phenotypes measured in similar ways. For each harmonized trait, within-cohort genome-wide association study analyses are combined by meta-analysis. A prospective meta-analysis of data from all 5 cohorts, with a properly selected level of genome-wide statistical significance, is a powerful approach to finding genuine phenotypic associations with novel genetic loci. CONCLUSIONS: The Cohorts for Heart and Aging Research in Genomic Epidemiology Consortium and collaborating non-member studies or consortia provide an excellent framework for the identification of the genetic determinants of risk factors, subclinical-disease measures, and clinical events.
Publication Details
Publication Date
2009-02-01
Journal
Publisher
ISSN
Access Type
Author Information
Authors
Jerome I. Rotter
Vilmundur Guðnason
Tamara B. Harris
Kathryn L. Lunetta
Eric Boerwinkle
Bruce M. Psaty
Christopher J. O’Donnell
André G. Uitterlinden
Aaron R. Folsom
Jacqueline C.M. Witteman
Explore More Research
Use the citation graph to discover related papers and expand your research horizons.
Click any node to explore
Download PDF
100%