title: Deciphering Genome Environment Wide Interactions Using Exposed Subjects Only.
abstract: 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.
authors.affiliation: Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA, United States of America.|School of Public Health Sciences, University of Washington, Seattle, WA, United States of America.
authors.forename: Lue Ping
authors.initials: LP
authors.lastname: Zhao
authors.affiliation: Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA, United States of America.
authors.forename: Wenhong
authors.initials: W
authors.lastname: Fan
authors.affiliation: Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA, United States of America.|Swedish Medical Center Cancer Institute, Seattle, WA, United States of America.
authors.forename: Gary
authors.initials: G
authors.lastname: Goodman
authors.affiliation: Division of Clinical Research, Fred Hutchinson Cancer Research Center, Seattle, WA, United States of America.
authors.forename: Jerry
authors.initials: J
authors.lastname: Radich
authors.affiliation: Division of Clinical Research, Fred Hutchinson Cancer Research Center, Seattle, WA, United States of America.
authors.forename: Paul
authors.initials: P
authors.lastname: Martin
mesh_terms: D000368:Aged; D016022:Case-Control Studies; D003198:Computer Simulation; D004843:Epistasis, Genetic; D005260:Female; D059647:Gene-Environment Interaction; D005819:Genetic Markers; D055106:Genome-Wide Association Study; D006801:Humans; D008175:Lung Neoplasms / Q000235:genetics* / Q000473:pathology; D008297:Male; D008875:Middle Aged; D008957:Models, Genetic; D020641:Polymorphism, Single Nucleotide / Q000235:genetics*; D012907:Smoking / Q000009:adverse effects*; D014029:Tobacco Use Disorder / Q000235:genetics* / Q000473:pathology
chemical_list: D005819:Genetic Markers
keywords: G × E; GEWIS; GWAS; case control; exposed subjects; genome scan