期刊
AMERICAN JOURNAL OF EPIDEMIOLOGY
卷 175, 期 3, 页码 203-207出版社
OXFORD UNIV PRESS INC
DOI: 10.1093/aje/kwr365
关键词
epidemiologic research design; genetic epidemiology; genome-wide association study; genotype-environment interaction; polymorphisms, single nucleotide
资金
- NHLBI NIH HHS [R01HL087680, R01 HL087680, RC2HL101651, RC2 HL101651] Funding Source: Medline
- NICHD NIH HHS [U01 HD061968, U01HD061968] Funding Source: Medline
- NIEHS NIH HHS [P01ES011627, R01 ES019876, R01ES019876, P30ES007048, P30 ES007048, P01 ES011627] Funding Source: Medline
One goal in the post-genome-wide association study era is characterizing gene-environment interactions, including scanning for interactions with all available polymorphisms, not just those showing significant main effects. In recent years, several approaches to such gene-environment-wide interaction studies have been proposed. Two contributions in this issue of the American Journal of Epidemiology provide systematic comparisons of the performance of these various approaches, one based on simulation and one based on application to 2 real genome-wide association study scans for type 2 diabetes. The authors discuss some of the broader issues raised by these contributions, including the plausibility of the gene-environment independence assumption that some of these approaches rely upon, the need for replication, and various generalizations of these approaches.
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