Many complex diseases are likely to be a result of the interplay of genes and environmental exposures. The standard analysis in a genome-wide association study (GWAS) scans for main effects and ignores the potentially useful information in the available exposure data. Two recently proposed methods t
Sample size requirements for indirect association studies of gene–environment interactions (G × E)
✍ Scribed by Rebecca Hein; Lars Beckmann; Jenny Chang-Claude
- Publisher
- John Wiley and Sons
- Year
- 2008
- Tongue
- English
- Weight
- 329 KB
- Volume
- 32
- Category
- Article
- ISSN
- 0741-0395
No coin nor oath required. For personal study only.
✦ Synopsis
Abstract
Association studies accounting for gene–environment interactions (G × 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 × 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 × 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 × E. However, given weak true genetic main effects, moderate prevalence of environmental exposures, as well as strong interactions, G × 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 × E is included in the analyses. Thus, the analysis of G × 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. Genet. Epidemiol. 2007. © 2007 Wiley‐Liss, Inc.
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