Testing haplotype-environment interactions using case-parent triads.

Hum Hered

Biostatistics Branch, NIEHS, NIH, DHHS, Research Triangle Park, NC 27709, USA.

Published: October 2010

AI Article Synopsis

  • The study addresses the challenges of analyzing genetic markers (SNPs) and environmental factors together, highlighting the risk of bias from population structure in case-control studies.
  • A new procedure is proposed that uses case-parent triad data to test the interaction between haplotypes and environmental exposures, assuming that the haplotypes do not affect exposure likelihood.
  • Simulations indicate that this method maintains correct error rates and maintains power across scenarios, demonstrating its effectiveness in real-world cases, like examining the role of GSTP1 SNP variants in maternal smoking's effect on oral clefts.

Article Abstract

Objective: Joint analysis of multiple SNP markers can be informative, but studying joint effects of haplotypes and environmental exposures is challenging. Population structure can involve both genes and exposures and a case-control study is susceptible to bias from either source of stratification. We propose a procedure that uses case-parent triad data and, though not fully robust, resists bias from population structure.

Methods: Our procedure assumes that haplotypes under study have no influence on propensity to exposure. Then, under a no-interaction null hypothesis (multiplicative scale), transmission of a causative haplotype from parents to affected offspring might show distortion from Mendelian proportions but should be independent of exposure. We used this insight to develop a permutation test of no haplotype-by-exposure interaction.

Results: Simulations showed that our proposed test respects the nominal Type I error rate and provides good power under a variety of scenarios. We illustrate by examining whether SNP variants in GSTP1 modify the association between maternal smoking and oral clefting.

Conclusion: Our procedure offers desirable features: no need for haplotype estimation, validity under unspecified genetic main effects, tolerance to Hardy-Weinberg disequilibrium, ability to handle missing genotypes and a relatively large number of SNPs. Simulations suggest resistance to bias due to exposure-related population stratification.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2912643PMC
http://dx.doi.org/10.1159/000298326DOI Listing

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