title: Empirical hierarchical bayes approach to gene-environment interactions: development and application to genome-wide association studies of lung cancer in TRICL.
abstract: The analysis of gene-environment (G × E) interactions remains one of the greatest challenges in the postgenome-wide association studies (GWASs) era. Recent methods constitute a compromise between the robust but underpowered case-control and powerful case-only methods. Inferences of the latter are biased when the assumption of gene-environment (G-E) independence in controls fails. We propose a novel empirical hierarchical Bayes approach to G × E interaction (EHB-GE), which benefits from greater rank power while accounting for population-based G-E correlation. Building on Lewinger et al.'s ([2007] Genet Epidemiol 31:871-882) hierarchical Bayes prioritization approach, the method first obtains posterior G-E correlation estimates in controls for each marker, borrowing strength from G-E information across the genome. These posterior estimates are then subtracted from the corresponding case-only G × E estimates. We compared EHB-GE with rival methods using simulation. EHB-GE has similar or greater rank power to detect G × E interactions in the presence of large numbers of G-E correlations with weak to strong effects or only a low number of such correlations with large effect. When there are no or only a few weak G-E correlations, Murcray et al.'s method ([2009] Am J Epidemiol 169:219-226) identifies markers with low G × E interaction effects better. We applied EHB-GE and competing methods to four lung cancer case-control GWAS from the Interdisciplinary Research in Cancer of the Lung/International Lung Cancer Consortium with smoking as environmental factor. A number of genes worth investigating were identified by the EHB-GE approach.
authors.affiliation: Department of Genetic Epidemiology, University Medical Center, Georg-August University of Goettingen, Goettingen, Germany.
authors.forename: Melanie
authors.initials: M
authors.lastname: Sohns
authors.affiliation: Department of Genetic Epidemiology, University Medical Center, Georg-August University of Goettingen, Goettingen, Germany.
authors.forename: Elena
authors.initials: E
authors.lastname: Viktorova
authors.affiliation: Department of Epidemiology, University of Texas M.D. Anderson Cancer Center, Houston, TX, USA.
authors.forename: Christopher I
authors.initials: CI
authors.lastname: Amos
authors.affiliation: International Agency for Research on Cancer (IARC), Lyon, France.
authors.forename: Paul
authors.initials: P
authors.lastname: Brennan
authors.affiliation: Prosserman Centre for Health Research, Samuel Lunenfeld Research Institute, Mount Sinai Hospital, Toronto, Ontario, Canada.
authors.forename: Gord
authors.initials: G
authors.lastname: Fehringer
authors.affiliation: International Agency for Research on Cancer (IARC), Lyon, France.
authors.forename: Valerie
authors.initials: V
authors.lastname: Gaborieau
authors.affiliation: Department of Epidemiology, University of Texas M.D. Anderson Cancer Center, Houston, TX, USA.
authors.forename: Younghun
authors.initials: Y
authors.lastname: Han
authors.affiliation: Institute of Epidemiology I, Helmholtz Zentrum München, Neuherberg, Germany.
authors.forename: Joachim
authors.initials: J
authors.lastname: Heinrich
authors.affiliation: Unit of Genetic Epidemiology, Division of Cancer Epidemiology, Deutsches Krebsforschungszentrum, Heidelberg, Germany.
authors.forename: Jenny
authors.initials: J
authors.lastname: Chang-Claude
authors.affiliation: Prosserman Centre for Health Research, Samuel Lunenfeld Research Institute, Mount Sinai Hospital, Toronto, Ontario, Canada.
authors.forename: Rayjean J
authors.initials: RJ
authors.lastname: Hung
authors.affiliation: Institute of Medical Informatics, Biometry and Epidemiology, Chair of Epidemiology and Chair of Genetic Epidemiology, Ludwig-Maximilians-Universität, Munich, Germany.|Institute of Genetic Epidemiology, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, Germany.
authors.forename: Martina
authors.initials: M
authors.lastname: Müller-Nurasyid
authors.affiliation: Division of Epigenomics and Cancer Risk Factors, German Cancer Research Center, Heidelberg, Germany.
authors.forename: Angela
authors.initials: A
authors.lastname: Risch
authors.affiliation: Department of Preventive Medicine, University of Southern California, Los Angeles, CA, USA.
authors.forename: Duncan
authors.initials: D
authors.lastname: Thomas
authors.affiliation: Department of Genetic Epidemiology, University Medical Center, Georg-August University of Goettingen, Goettingen, Germany.
authors.forename: Heike
authors.initials: H
authors.lastname: Bickeböller
mesh_terms: D001499:Bayes Theorem; D015982:Bias; D016022:Case-Control Studies; D003198:Computer Simulation; D059647:Gene-Environment Interaction; D015894:Genome, Human; D055106:Genome-Wide Association Study; D006801:Humans; D008175:Lung Neoplasms / Q000235:genetics*; D008957:Models, Genetic; D012907:Smoking
keywords: GEWIS; GWAS; lung cancer; population G-E correlation; rank power
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