The gene, environment association studies consortium (GENEVA): Maximizing the knowledge obtained from GWAS by collaboration across studies of multiple conditions

Marilyn C. Cornelis, Arpana Agrawal, John W. Cole, Nadia N. Hansel, Kathleen C. Barnes, Terri H. Beaty, Siiri N. Bennett, Laura J. Bierut, Eric Boerwinkle, Kimberly F. Doheny, Bjarke Feenstra, Eleanor Feingold, Myriam Fornage, Christopher A. Haiman, Emily L. Harris, M. Geoffrey Hayes, John A. Heit, Frank B. Hu, Jae H. Kang, Cathy C. LaurieHua Ling, Teri A. Manolio, Mary L. Marazita, Rasika A. Mathias, Daniel B. Mirel, Justin Paschall, Louis R. Pasquale, Elizabeth W. Pugh, John P. Rice, Jenna Udren, Rob M. Van Dam, Xiaojing Wang, Janey L. Wiggs, Kayleen Williams, Kai Yu

Research output: Contribution to journalArticlepeer-review

131 Scopus citations

Abstract

Genome-wide association studies (GWAS) have emerged as powerful means for identifying genetic loci related to complex diseases. However, the role of environment and its potential to interact with key loci has not been adequately addressed in most GWAS. Networks of collaborative studies involving different study populations and multiple phenotypes provide a powerful approach for addressing the challenges in analysis and interpretation shared across studies. The Gene, Environment Association Studies (GENEVA) consortium was initiated to: identify genetic variants related to complex diseases; identify variations in gene-trait associations related to environmental exposures; and ensure rapid sharing of data through the database of Genotypes and Phenotypes. GENEVA consists of several academic institutions, including a coordinating center, two genotyping centers and 14 independently designed studies of various phenotypes, as well as several Institutes and Centers of the National Institutes of Health led by the National Human Genome Research Institute. Minimum detectable effect sizes include relative risks ranging from 1.24 to 1.57 and proportions of variance explained ranging from 0.0097 to 0.02. Given the large number of research participants (N>80,000), an important feature of GENEVA is harmonization of common variables, which allow analyses of additional traits. Environmental exposure information available from most studies also enables testing of gene-environment interactions. Facilitated by its sizeable infrastructure for promoting collaboration, GENEVA has established a unified framework for genotyping, data quality control, analysis and interpretation. By maximizing knowledge obtained through collaborative GWAS incorporating environmental exposure information, GENEVA aims to enhance our understanding of disease etiology, potentially identifying opportunities for intervention.

Original languageEnglish
Pages (from-to)364-372
Number of pages9
JournalGenetic Epidemiology
Volume34
Issue number4
DOIs
StatePublished - May 2010

Keywords

  • Complex disease
  • Gene-environment interaction
  • Genome-wide association
  • Phenotype harmonization
  • Quantitative traits

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