Improved two‐step testing of genome‐wide gene–environment interactions
Eric S. Kawaguchi, Andre E. Kim, Juan Pablo Lewinger, W. James Gauderman
Abstract
Abstract Two‐step tests for gene–environment () interactions exploit marginal single‐nucleotide polymorphism (SNP) effects to improve the power of a genome‐wide interaction scan. They combine a screening step based on marginal effects used to “bin” SNPs for weighted hypothesis testing in the second step to deliver greater power over single‐step tests while preserving the genome‐wide Type I error. However, the presence of many SNPs with detectable marginal effects on the trait of interest can reduce power by “displacing” true interactions with weaker marginal effects and by adding to the number of tests that need to be corrected for multiple testing. We introduce a new significance‐based allocation into bins for Step‐2 testing that overcomes the displacement issue and propose a computationally efficient approach to account for multiple testing within bins. Simulation results demonstrate that these simple improvements can provide substantially greater power than current methods under several scenarios. An application to a multistudy collaboration for understanding colorectal cancer reveals a G × Sex interaction located near the SMAD7 gene.