Abstract
With case–parent triad data, one can frequently deduce parent of origin of the child's alleles. This allows a parent‐of‐origin (PoO) effect to be estimated as the ratio of relative risks associated with the alleles inherited from the mother and the father, respectively. A possible cause of PoO effects is DNA methylation, leading to genomic imprinting. Because environmental exposures may influence methylation patterns, gene–environment interaction studies should be extended to allow for interactions between PoO effects and environmental exposures (i.e., PoOxE). One should thus search for loci where the environmental exposure modifies the PoO effect.We have developed an extensive framework to analyze PoOxE effects in genome‐wide association studies (GWAS), based on complete or incomplete case–parent triads with or without independent control triads. The interaction approach is based on analyzing triads in each exposure stratum using maximum likelihood estimation in a log‐linear model. Interactions are then tested applying a Wald‐based posttest of parameters across strata. Our framework includes a complete setup for power calculations. We have implemented the models in the R software package Haplin.To illustrate our PoOxE test, we applied the new methodology to top hits from our previous GWAS, assessing whether smoking during the periconceptional period modifies PoO effects on cleft palate only.
Highlights
A large number of human traits can be classified as complex, in the sense that they are assumed to be influenced by multiple genes and their interactions with environmental or behavioral factors (Pasaniuc & Price, 2016)
We have developed an extensive framework to analyze PoOxE effects in genome-wide association studies (GWAS), based on complete or incomplete case–parent triads with or without independent control triads
Thousands of genome-wide association studies (GWAS) have been conducted since the turn of the millennium, for most complex traits the genetic variants identified far explain only a small fraction of the phenotypic variation attributed to genetic effects (Manolio et al, 2009)
Summary
A large number of human traits can be classified as complex, in the sense that they are assumed to be influenced by multiple genes and their interactions with environmental or behavioral factors (Pasaniuc & Price, 2016). Thousands of genome-wide association studies (GWAS) have been conducted since the turn of the millennium, for most complex traits the genetic variants identified far explain only a small fraction of the phenotypic variation attributed to genetic effects (Manolio et al, 2009). This has underscored the need to investigate disease mechanisms beyond simple genetic effects alone. One example is gene–environment interactions (GxE), where the genetic effects are modified by Shi et al (2007) have shown that maternal cigarette smoking in the periconceptional period can modify the association between single nucleotide polymorphisms (SNPs) and orofacial clefts
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