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Office of Population Genomics

Overview A Catalog of Genome-Wide Association Studies Research Programs Recent Publications Meetings & Workshops Notices & Funding Opportunities Contact

Research Programs

  • The Genes, Environment and Health Initiative (GEI)
    Supports research that will lead to the understanding of genetic contributions and gene-environment interactions in common disease.

    • GENEVA [genevastudy.org] - Part of the Genetics Program of GEI, GENEVA (Gene Environment Association Studies) is using rapidly evolving technologies in Genome-Wide Association Studies (GWAS) to find genetic risk factors in common conditions, such as tooth decay, heart disease, cancer and diabetes, and assess their interplay with non-genetic risk factors.

  • The Genetic Association Information Network (GAIN)
    Supports a series of Genome-Wide Association Studies (GWAS) designed to identify specific points of DNA variation associated with the occurrence of a particular common disease.

  • eMERGE [gwas.net]
    The eMERGE (Electronic Medical Records and Genomics) Network is a five-member consortium formed to develop, disseminate, and apply approaches to research that combine DNA biorepositories with electronic medical record (EMR) systems for large-scale, high-throughput genetic research.

  • PhenX [phenx.org]
    The goal of PhenX is to develop consensus measures for phenotypes and exposures for use in genome-wide association studies (GWAS). PhenX will to identify up to 20 domains of high research and public health significance and then develop and disseminate 15 standard measures for each domain. The toolkit of phenotype and exposure measures produced by PhenX will facilitate integrated design and analysis of GWA studies as well as other genomics and epidemiology based studies.

  • Population Architecture of Genomics in Epidemiology (PAGE) New
    The goal of PAGE is to follow up promising genetic variants identified from genome-wide association studies in large, well-characterized epidemiological cohorts, with the aim of widespread sharing of the resulting population-based descriptive and association data to accelerate the understanding of genes related to complex diseases.


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Last Updated: March 30, 2009
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