Problems and Pit-Falls in Testing for G × E and Epistasis in Candidate Gene Studies of Human Behavior

Abstract

Conclusions about the genetic architecture of a phenotype relating to the contributions of genetic additivity, dominance, epistasis or genotype × environment interaction, depend upon the statistical and distributional properties of the measured trait. This dependence is frequently ignored in contemporary genetic studies and can radically change the conclusions that may be drawn from the data. The interdependence of the conclusions about genetic architecture and instruments used for behavioral measurement is explored by simulated studies of the interaction between candidate genes and measured environment in psychiatric genetics. Trait values are simulated (N = 100,000) under several commonly encountered scenarios and subjected to two simulated 20-item psychological tests each comprising items with different patterns of difficulty and sensitivity to variation (discriminating power) in the latent trait. Test scores are generated for each test by summing the binary responses across all items. The full model for digenic additive and non-additive genetic effects and G × E is fitted to the trait values and test scores under a range of different simulated genetic architectures. Untransformed test scores show complex patterns of epistasis and G × E even when the underlying effects of genes and environment are purely additive and the transformation of symptom counts does not fully recover the simulated underlying genetic architecture. Accordingly, failing to allow for the theory of measurement when analyzing details of genetic architecture may frequently lead to replicable over-reporting of interactions and mislead potential investigators and funding agencies.