Deciphering Genome Environment Wide Interactions Using Exposed Subjects Only

The recent successes of genome‐wide association studies (GWAS) have renewed interest in genome environment wide interaction studies (GEWIS) to discover genetic factors that modulate penetrance of environmental exposures to human diseases. Indeed, gene‐environment interactions (G × E), which have not been emphasized in the GWAS era, could be a source contributing to the missing heritability, a major bottleneck limiting continuing GWAS successes. In this manuscript, we describe a design and analytic strategy to focus on G × E using only exposed subjects, dubbed as e‐GEWIS. Operationally, an e‐GEWIS analysis is equivalent to a GWAS analysis on exposed subjects only, and it has actually been used in some earlier GWAS without being explicitly identified as such. Through both analytics and simulations, e‐GEWIS has been shown better efficiency than the usual cross‐product‐based analysis of G × E interaction with both cases and controls (cc‐GEWIS), and they have comparable efficiency to case‐only analysis of G × E (c‐GEWIS), with potentially smaller sample sizes. The formalization of e‐GEWIS here provides a theoretical basis to legitimize this framework for routine investigation of G × E, for more efficient G × E study designs, and for improvement of reproducibility in replicating GEWIS findings. As an illustration, we apply e‐GEWIS to a lung cancer GWAS data set to perform a GEWIS, focusing on gene and smoking interaction. The e‐GEWIS analysis successfully uncovered positive genetic associations on chromosome 15 among current smokers, suggesting a gene‐smoking interaction. Although this signal was detected earlier, the current finding here serves as a positive control in support of this e‐GEWIS strategy.