Tradeoffs in Modeling Context Dependency in Complex Trait Genetics

Abstract

AbstractGenetic effects on complex traits may depend on context, such as age, sex, environmental exposures or social settings. However, it is often unclear if the extent of context dependency, or Gene-by-Environment interaction (GxE), merits more involved models than the additive model typically used to analyze data from genomewide association studies (GWAS). Here, we derive governing principles for when modeling GxE in GWAS is useful. We derive a decision rule for choosing between competing models for the estimation of allelic effects. The rule weighs the increased noise of context-specific effect estimation against the potential bias when context dependency is ignored. In human GWAS, the increased noise of context-specific estimation often outweighs the bias reduction, rendering GxE models less useful when variants are considered independently. However, for complex traits, considering patterns of context dependency across many variants jointly can substantially improve estimation and trait prediction. Finally, we demonstrate via example that considering polygenic trends of GxE may also be important for interpretation, as analyses based on independently ascertained “top hits” alone can be misleading.