Robust Tests for Additive Gene-Environment Interaction in Case-Control Studies Using Gene-Environment Independence

Gang Liu; Bhramar Mukherjee; Seunggeun Lee; Alice W Lee; Anna H Wu; Elisa V Bandera; Allan Jensen; Mary Anne Rossing; Kirsten B Moysich; Jenny Chang-Claude; Jennifer A Doherty; Aleksandra Gentry-Maharaj; Lambertus Kiemeney; Simon A Gayther; Francesmary Modugno; Leon Massuger; Ellen L Goode; Brooke L Fridley; Kathryn L Terry; Daniel W Cramer; Susan J Ramus; Hoda Anton-Culver; Argyrios Ziogas; Jonathan P Tyrer; Joellen M Schildkraut; Susanne K Kjaer; Penelope M Webb; Roberta B Ness; Usha Menon; Andrew Berchuck; Paul D Pharoah; Harvey Risch; Celeste Leigh Pearce; Ovarian Canc Assoc Consortium

doi:10.1093/aje/kwx243

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Robust Tests for Additive Gene-Environment Interaction in Case-Control Studies Using Gene-Environment Independence

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Robust Tests for Additive Gene-Environment Interaction in Case-Control Studies Using Gene-Environment Independence

Gang Liu, Bhramar Mukherjee, Seunggeun Lee, Alice W Lee, Anna H Wu, Elisa V Bandera, Allan Jensen, Mary Anne Rossing, Kirsten B Moysich, Jenny Chang-Claude, …

American journal of epidemiology, Vol.187(2), pp.366-377

02/2018

DOI: https://doi.org/10.1093/aje/kwx243

PMCID: PMC5860584

PMID: 28633381

Abstract

bias-variance tradeoff

effect modification

empirical Bayes estimation

genetic risk score

Practice of Epidemiology

relative excess risk

shrinkage

There have been recent proposals advocating the use of additive gene-environment interaction instead of the widely used multiplicative scale, as a more relevant public health measure. Using gene-environment independence enhances statistical power for testing multiplicative interaction in case-control studies. However, under departure from this assumption, substantial bias in the estimates and inflated type I error in the corresponding tests can occur. In this paper, we extend the empirical Bayes (EB) approach previously developed for multiplicative interaction, which trades off between bias and efficiency in a data-adaptive way, to the additive scale. An EB estimator of the relative excess risk due to interaction is derived, and the corresponding Wald test is proposed with a general regression setting under a retrospective likelihood framework. We study the impact of gene-environment association on the resultant test with case-control data. Our simulation studies suggest that the EB approach uses the gene-environment independence assumption in a data-adaptive way and provides a gain in power compared with the standard logistic regression analysis and better control of type I error when compared with the analysis assuming gene-environment independence. We illustrate the methods with data from the Ovarian Cancer Association Consortium.

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Title: Robust Tests for Additive Gene-Environment Interaction in Case-Control Studies Using Gene-Environment Independence
Creators: Gang Liu - Department of Biostatistics, School of Public Health, University of Michigan, Ann Arbor, Michigan
Bhramar Mukherjee - Department of Biostatistics, School of Public Health, University of Michigan, Ann Arbor, Michigan
Seunggeun Lee - Department of Biostatistics, School of Public Health, University of Michigan, Ann Arbor, Michigan
Alice W Lee - Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, California
Anna H Wu - Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, California
Elisa V Bandera - Cancer Prevention and Control Research Program, Rutgers Cancer Institute of New Jersey, New Brunswick, New Jersey
Allan Jensen - Department of Virus, Lifestyle and Genes, Danish Cancer Society Research Center, Copenhagen, Denmark
Mary Anne Rossing - Program in Epidemiology, Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, Washington
Kirsten B Moysich - Department of Cancer Prevention and Control, Roswell Park Cancer Institute, Buffalo, New York
Jenny Chang-Claude - Division of Cancer Epidemiology, German Cancer Research Center, Heidelberg, Germany
Jennifer A Doherty - Department of Epidemiology, Geisel School of Medicine at Dartmouth, Dartmouth College, Hanover, New Hampshire
Aleksandra Gentry-Maharaj - Gynaecological Cancer Research Centre, Women’s Cancer, Institute for Women’s Health, University College London, London, United Kingdom
Lambertus Kiemeney - Radboud University Medical Center, Radboud Institute for Health Sciences, Nijmegen, the Netherlands
Simon A Gayther - Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, California
Francesmary Modugno - Department of Obstetrics, Gynecology, and Reproductive Sciences, Division of Gynecologic Oncology, School of Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania
Leon Massuger - Department of Obstetrics and Gynaecology, Radboud University Medical Center, Nijmegen, the Netherlands
Ellen L Goode - Department of Health Sciences Research, Division of Epidemiology, Mayo Clinic, Rochester, Minnesota
Brooke L Fridley - University of Kansas Medical Center, Kansas City, Kansas
Kathryn L Terry - Obstetrics and Gynecology Center, Brigham and Women’s Hospital and Harvard Medical School, Boston, Massachusetts
Daniel W Cramer - Obstetrics and Gynecology Center, Brigham and Women’s Hospital and Harvard Medical School, Boston, Massachusetts
Susan J Ramus - School of Women’s and Children’s Health, University of New South Wales, Sydney, New South Wales, Australia
Hoda Anton-Culver - Genetic Epidemiology Research Institute, Center for Cancer Genetics Research and Prevention, School of Medicine, University of California, Irvine, Irvine, California
Argyrios Ziogas - Genetic Epidemiology Research Institute, Center for Cancer Genetics Research and Prevention, School of Medicine, University of California, Irvine, Irvine, California
Jonathan P Tyrer - Strangeways Research Laboratory, Department of Public Health and Primary Care, School of Clinical Medicine, University of Cambridge, Cambridge, United Kingdom
Joellen M Schildkraut - Department of Public Health Sciences, School of Medicine, University of Virginia, Charlottesville, Virginia
Susanne K Kjaer - Department of Virus, Lifestyle and Genes, Danish Cancer Society Research Center, Copenhagen, Denmark
Penelope M Webb - QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
Roberta B Ness - Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health, University of Texas, Houston, Texas
Usha Menon - Gynaecological Cancer Research Centre, Women’s Cancer, Institute for Women’s Health, University College London, London, United Kingdom
Andrew Berchuck - Department of Obstetrics and Gynecology, Duke University Medical Center, Durham, North Carolina
Paul D Pharoah - Strangeways Research Laboratory, Department of Public Health and Primary Care, School of Clinical Medicine, University of Cambridge, Cambridge, United Kingdom
Harvey Risch - Department of Chronic Disease Epidemiology, School of Public Health, Yale University, New Haven, Connecticut
Celeste Leigh Pearce - Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, California
Ovarian Canc Assoc Consortium
Publication Details: American journal of epidemiology, Vol.187(2), pp.366-377
Date published: 02/2018
Publisher: Oxford University Press
Grant note: 94 222 52 / ; ; ; R01 CA076016; P30 CA046592 / ; ; ; LVS-39420 / ; ; ; ; ; P30 CA14089; R01 CA61132; P01 CA17054; N01 PC67010; R03 CA113148; N01 CN025403; R03 CA115195; K07 CA095666; R01 CA83918; K22 CA138563; P30 CA072720; R01 CA122443; P30 CA15083; P50 CA136393R01; R01 CA112523; R01 CA87538; R01 CA058860; R01 CA063678; R01 CA074850; R01 CA080742; R01 CA76016; R01 CA54419; P50 CA105009; R01 CA61107; R01 CA095023; R01 CA126841; M01 RR000056; P50 CA159981; K07 CA80668 / ; ; ; PPD/RPCI.07 / ; ; ; NSF DMS 1406712 / ; ; ; W81XWH-10-1-02802; DAMD17-02-1-0669; DAMD17-02-1-0666; DAMD17-01-1-0729 / ; ; 191; 211; 182 / ; ; T32 ES013678 / ; ; 223175 HEALTH F2 2009-223175 / ; ; NIH ES 20811 / ; ; ; 199600; 400281 / ; ; U19-CA148112 / ; ; R01 CA076016 / ; ; ; 0001389V20170; 2110200 / ; ; 01GB9401 / ; ; ; ;
Academic Unit: Cancer Epidemiology and Health Outcomes
Language: English
Resource Type: Journal article
Identifiers: 991031665005404646