| Literature DB >> 22199029 |
Duncan C Thomas1, Juan Pablo Lewinger, Cassandra E Murcray, W James Gauderman.
Abstract
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.Entities:
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Year: 2011 PMID: 22199029 PMCID: PMC3261438 DOI: 10.1093/aje/kwr365
Source DB: PubMed Journal: Am J Epidemiol ISSN: 0002-9262 Impact factor: 4.897