Genome-Wide Association Analysis Accounting for Environmental Factors Through Propensity-Score Matching: Application to Stressful Live Events in Major Depressive Disorder

Robert Power, Sarah Cohen-Woods, Mandy Ng, Amy Butler, Nick Craddock, A. Korszun, Lisa Jones, Ian Jones, Michael Gill, John Rice, Wolfgang Maier, Astrid Zobel, Ole Mors, Anna Placentino, Marcella Rietschel, Katherine Aitchison, Ferderica Tozzi, Pierandrea Muglia, Gerome Breen, Anne FarmerPeter McGuffin, Cathryn Lewis, Rudolf Uher

    Research output: Contribution to journalArticle

    12 Citations (Scopus)

    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.

    Original languageEnglish
    Pages (from-to)521-529
    Number of pages9
    JournalAMERICAN JOURNAL OF MEDICAL GENETICS PART B-NEUROPSYCHIATRIC GENETICS
    Volume162
    Issue number6
    DOIs
    Publication statusPublished - 2013

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  • Cite this

    Power, R., Cohen-Woods, S., Ng, M., Butler, A., Craddock, N., Korszun, A., Jones, L., Jones, I., Gill, M., Rice, J., Maier, W., Zobel, A., Mors, O., Placentino, A., Rietschel, M., Aitchison, K., Tozzi, F., Muglia, P., Breen, G., ... Uher, R. (2013). Genome-Wide Association Analysis Accounting for Environmental Factors Through Propensity-Score Matching: Application to Stressful Live Events in Major Depressive Disorder. AMERICAN JOURNAL OF MEDICAL GENETICS PART B-NEUROPSYCHIATRIC GENETICS, 162(6), 521-529. https://doi.org/10.1002/ajmg.b.32180