Large-scale genome-wide association studies consortia: blessing, burden, or necessity?

In the current issue of Circulation: Cardiovascular Genetics, Preuss and colleagues1 describe the design of the Coronary ARtery DIsease Genome-wide Replication And Meta-Analysis (CARDIoGRAM) consortium. CARDIoGRAM is one of several consortia that have formed in the past few years in order to combine data from different genome-wide association studies (GWAS) in large-scale metaanalyses. Many of these consortia have focused their efforts on traits from the cardiovascular and type 2 diabetes domains. In addition to CARDIoGRAM, other examples of trait-specific consortia in this field include the Meta-Analysis of Glucose and InsulinRelated Traits Consortium,2 the Global Lipids Genetics Consortium,3 the Diabetes Genetics Replication and Metaanalysis consortium,4 and the Genetic Investigation of Anthropometric Traits5 consortium. There are also examples of consortia that have a wider scope, with phenotypes ranging over the whole cardiovascular field, such as the Cohorts for Heart and Aging Research in Genomic Epidemiology (http:// web.chargeconsortium.com/), European Network of Genomic and Genetic Epidemiology (http://www.euengage.org/), and Candidate Gene Association Resource6 consortia. The largescale GWAS consortia have many things in common, such as: (1) rigorous and robust methods with greater statistical power than single-center studies, as exemplified in the current article from the CARDIoGRAM consortium; (2) researchers being involved in several consortia, leading to cross-fertilization, quicker development and implementation of new methods; and (3) study samples being used for different traits in different consortia for increased cost-effectiveness.