Literature DB >> 18163529

Sample size requirements for indirect association studies of gene-environment interactions (G x E).

Rebecca Hein1, Lars Beckmann, Jenny Chang-Claude.   

Abstract

Association studies accounting for gene-environment interactions (G x E) may be useful for detecting genetic effects. Although current technology enables very dense marker spacing in genetic association studies, the true disease variants may not be genotyped. Thus, causal genes are searched for by indirect association using genetic markers in linkage disequilibrium (LD) with the true disease variants. Sample sizes needed to detect G x E effects in indirect case-control association studies depend on the true genetic main effects, disease allele frequencies, whether marker and disease allele frequencies match, LD between loci, main effects and prevalence of environmental exposures, and the magnitude of interactions. We explored variables influencing sample sizes needed to detect G x E, compared these sample sizes with those required to detect genetic marginal effects, and provide an algorithm for power and sample size estimations. Required sample sizes may be heavily inflated if LD between marker and disease loci decreases. More than 10,000 case-control pairs may be required to detect G x E. However, given weak true genetic main effects, moderate prevalence of environmental exposures, as well as strong interactions, G x E effects may be detected with smaller sample sizes than those needed for the detection of genetic marginal effects. Moreover, in this scenario, rare disease variants may only be detectable when G x E is included in the analyses. Thus, the analysis of G x E appears to be an attractive option for the detection of weak genetic main effects of rare variants that may not be detectable in the analysis of genetic marginal effects only.

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Year:  2008        PMID: 18163529     DOI: 10.1002/gepi.20298

Source DB:  PubMed          Journal:  Genet Epidemiol        ISSN: 0741-0395            Impact factor:   2.135


  21 in total

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Review 5.  A Review of the Genetics of Hypertension with a Focus on Gene-Environment Interactions.

Authors:  R J Waken; Lisa de Las Fuentes; D C Rao
Journal:  Curr Hypertens Rep       Date:  2017-03       Impact factor: 5.369

6.  Gene-environment interaction involving recently identified colorectal cancer susceptibility Loci.

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7.  Case-control studies of gene-environment interaction: Bayesian design and analysis.

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8.  The case-only test for gene-environment interaction is not uniformly powerful: an empirical example.

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Review 9.  The importance of gene-environment interactions in human obesity.

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Review 10.  Detecting gene-gene interactions that underlie human diseases.

Authors:  Heather J Cordell
Journal:  Nat Rev Genet       Date:  2009-06       Impact factor: 53.242

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