@article{07dba61ab8f04790a5fffb669908c96c,
title = "Incorporation of Biological Knowledge into the Study of Gene-Environment Interactions",
abstract = "A growing knowledge base of genetic and environmental information has greatly enabled the study of disease risk factors. However, the computational complexity and statistical burden of testing all variants by all environments has required novel study designs and hypothesis-driven approaches. We discuss how incorporating biological knowledge from model organisms, functional genomics, and integrative approaches can empower the discovery of novel gene-environment interactions and discuss specific methodological considerations with each approach. We consider specific examples where the application of these approaches has uncovered effects of gene-environment interactions relevant to drug response and immunity, and we highlight how such improvements enable a greater understanding of the pathogenesis of disease and the realization of precision medicine.",
author = "Ritchie, {Marylyn D.} and Davis, {Joe R.} and Hugues Aschard and Alexis Battle and David Conti and Mengmeng Du and Eleazar Eskin and Fallin, {M. Daniele} and Li Hsu and Peter Kraft and Moore, {Jason H.} and Pierce, {Brandon L.} and Bien, {Stephanie A.} and {Blair Thomas}, {Duncan C.} and Peng Wei and Montgomery, {Stephen B.}",
note = "Funding Information: Center, Houston, Texas (Peng Wei); Department of Genetics, Stanford University School of Medicine, Stanford, California (Stephen B. Montgomery); and Department of Pathology, Stanford University School of Medicine, Stanford, California (Stephen B. Montgomery). M.D.R. and S.B.M. contributed equally to this work. Research reported in this publication was supported by National Institute of Environmental Health Sciences; National Library of Medicine; National Institute of Allergy and Infectious Diseases; National Cancer Institute; National Heart, Lung and Blood Institute; National Human Genome Research Institute; and National Institute of Mental Health of the National Institutes of Health under award numbers R21HG007687 to H.A.; R01CA140561, R01CA201407, P01CA196569 to D.C.; P30CA008748, R25CA094880 to M.D.; R01CA189532, R01CA195789, and P01CA53996 to L.H.; R01LM010098, R01AI116794, and P30ES013508 to J.H.M.; R01ES023834, R21ES024834 to B.L.P.; R01CA169122, R01HL116720 and R21HL126032 to P.W. E.E. is supported by R01ES022282. S.B.M. is supported by the National Institutes of Health through R01HG008150, R01MH101814, U01HG007436, and U01HG009080. J.R. D. is supported by a Lucille P. Markey Biomedical Research Stanford Graduate Fellowship. J.R.D. acknowledges the Stanford Genome Training Program (SGTP; NIH/NHGRI T32HG000044). This work is funded, in part, under a grant with the Pennsylvania Department of Health (SAP 4100070267) to M.D.R. The Pennsylvania Department of Health specifically disclaims responsibility for any analyses, interpretations or conclusions. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. Conflict of interest: none declared. Publisher Copyright: {\textcopyright} The Author(s) 2017.",
year = "2017",
month = oct,
day = "1",
doi = "10.1093/aje/kwx229",
language = "English (US)",
volume = "186",
pages = "771--777",
journal = "American Journal of Epidemiology",
issn = "0002-9262",
publisher = "Oxford University Press",
number = "7",
}