Genome-Wide Meta-Analysis of Joint Tests for Genetic and Gene-Environment Interaction Effects

被引:59
作者
Aschard, Hugues [1 ]
Hancock, Dana B. [2 ]
London, Stephanie J. [2 ]
Kraft, Peter
机构
[1] Harvard Univ, Sch Publ Hlth, Dept Epidemiol, Program Mol & Genet Epidemiol, Boston, MA 02115 USA
[2] NIEHS, Epidemiol Branch, NIH, Dept Hlth & Human Serv, Res Triangle Pk, NC 27709 USA
关键词
Gene-environment interaction; Genome-wide scan; Meta-analysis; Case-control association analysis; Complex disease; ASSOCIATION; INDEPENDENCE;
D O I
10.1159/000323318
中图分类号
Q3 [遗传学];
学科分类号
071007 ; 090102 ;
摘要
Background: There is growing interest in the study of gene-environment interactions in the context of genome-wide association studies (GWASs). These studies will likely require meta-analytic approaches to have sufficient power. Methods: We describe an approach for meta-analysis of a joint test for genetic main effects and gene-environment interaction effects. Using simulation studies based on a meta-analysis of five studies (total n = 10,161), we compare the power of this test to the meta-analysis of marginal test of genetic association and the meta-analysis of standard 1 d.f. interaction tests across a broad range of genetic main effects and gene-environment interaction effects. Results: We show that the joint meta-analysis is valid and can be more powerful than classical meta-analytic approaches, with a potential gain of power over 50% compared to the marginal test. The standard interaction test had less than 1% power in almost all the situations we considered. We also show that regardless of the test used, sample sizes far exceeding those of a typical individual GWAS will be needed to reliably detect genes with subtle gene-environment interaction patterns. Conclusion: The joint meta-analysis is an attractive approach to discover markers which may have been missed by initial GWASs focusing on marginal marker-trait associations. Copyright (C) 2011 S. Karger AG, Basel
引用
收藏
页码:292 / 300
页数:9
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