Genome-wide association analysis accounting for environmental factors through propensity-score matching: Application to stressful live events in major depressive disorder

Authors


  • Conflicts of interest: Aitchison, Farmer, and McGuffin have received consultancy fees and honoraria for participating in expert panels for pharmaceutical companies including GlaxoSmithKline. Aitchison's declares interests through Advisory Boards for Johnson & Johnson, Lundbeck, Roche Diagnostics, and Bristol-Myers Squibb; membership of Bristol-Myers Squibb UK Steering group 2003 to present; consultancy work for Roche Diagnostics, Johnson & Johnson Pharmaceutical Research and Development, Lundbeck, and Bristol-Myers Squibb Pharmaceuticals Limited; grants awarded by Johnson & Johnson Pharmaceutical Research & Development, Bristol-Myers Squibb Pharmaceuticals Limited, and E Merck Pharmaceuticals. Tozzi and Muglia were employees of GlaxoSmithKline when the research was performed. All other authors (Power, Butler, Ng, Cohen-Woods, Craddock, Korszun, Jones I, Jones L, Gill, Rice, Maier, Zobel, Mors, Placentino, Rietschel, Breen, Craig, Lewis, and Uher) declare no conflicts of interest.
  • Cathryn M. Lewis and Rudolf Uher contributed equally to this work.

Correspondence to:

Robert A. Power, MRC Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, London SE5 8AF, United Kingdom.

E-mail: robert.r.power@kcl.ac.uk

Abstract

Stressful life events are an established trigger for depression and may contribute to the heterogeneity within genome-wide association analyses. With depression cases showing an excess of exposure to stressful events compared to controls, there is difficulty in distinguishing between “true” cases and a “normal” response to a stressful environment. This potential contamination of cases, and that from genetically at risk controls that have not yet experienced environmental triggers for onset, may reduce the power of studies to detect causal variants. In the RADIANT sample of 3,690 European individuals, we used propensity score matching to pair cases and controls on exposure to stressful life events. In 805 case–control pairs matched on stressful life event, we tested the influence of 457,670 common genetic variants on the propensity to depression under comparable level of adversity with a sign test. While this analysis produced no significant findings after genome-wide correction for multiple testing, we outline a novel methodology and perspective for providing environmental context in genetic studies. We recommend contextualizing depression by incorporating environmental exposure into genome-wide analyses as a complementary approach to testing gene-environment interactions. Possible explanations for negative findings include a lack of statistical power due to small sample size and conditional effects, resulting from the low rate of adequate matching. Our findings underscore the importance of collecting information on environmental risk factors in studies of depression and other complex phenotypes, so that sufficient sample sizes are available to investigate their effect in genome-wide association analysis. © 2013 Wiley Periodicals, Inc.

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