Genome-wide gene-environment interaction in depression: A systematic evaluation of candidate genes

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Publisher: Wiley Subscription Services, Inc.
Document Type: Report
Length: 497 words

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Byline: Sandra Van der Auwera, Wouter J. Peyrot, Yuri Milaneschi, Johannes Hertel, Bernhard Baune, Gerome Breen, Enda Byrne, Erin C. Dunn, Helen Fisher, Georg Homuth, Douglas Levinson, Cathryn Lewis, Natalie Mills, Niamh Mullins, Matthias Nauck, Giorgio Pistis, Martin Preisig, Marcella Rietschel, Stephan Ripke, Patrick Sullivan, Alexander Teumer, Henry Volzke,, Dorret I. Boomsma, Naomi R. Wray, Naomi R. Wray, Naomi R. Wray Gene by environment (GxE) interaction studies have investigated the influence of a number of candidate genes and variants for major depressive disorder (MDD) on the association between childhood trauma and MDD. Most of these studies are hypothesis driven and investigate only a limited number of SNPs in relevant pathways using differing methodological approaches. Here (1) we identified 27 genes and 268 SNPs previously associated with MDD or with GxE interaction in MDD and (2) analyzed their impact on GxE in MDD using a common approach in 3944 subjects of European ancestry from the Psychiatric Genomics Consortium who had completed the Childhood Trauma Questionnaire. (3) We subsequently used the genome-wide SNP data for a genome-wide case-control GxE model and GxE case-only analyses testing for an enrichment of associated SNPs. No genome-wide significant hits and no consistency among the signals of the different analytic approaches could be observed. This is the largest study for systematic GxE interaction analysis in MDD in subjects of European ancestry to date. Most of the known candidate genes/variants could not be supported. Thus, their impact on GxE interaction in MDD may be questionable. Our results underscore the need for larger samples, more extensive assessment of environmental exposures, and greater efforts to investigate new methodological approaches in GxE models for MDD. Article Note: Contributed equally to this study. Full list of Consortium members is given in the supplementary material. Supporting information: Additional Supporting Information may be found in the online version of this article Additional Supporting Information may be found online in the supporting information tab for this article. CAPTION(S): Figure S1. Manhattan-plots of the three main meta-analyses for the additive SNP effect including SHIP-0, SHIP-TREND, NESDA and Radiant-UK. Figure S2. Quantile-quantile plots of the three main meta-analyses for the additive SNP effect including SHIP-0, SHIP-TREND, NESDA and Radiant-UK. Figure S3. Venn diagram of the SNP overlap between three main analyses assuming an additive SNP effect (SNP included with p Table S1. Different childhood abuse assessments in the eleven PGC cohorts that assessed childhood trauma. Table S2. Power calculation input parameters for Quanto (case-control GxE and case-only GxE approach with abuse 0/1). Table S5. Top genes (p Table S6. List of 27 candidate genes for GxE analysis in MDD (from Mandelli and Serretti, 2013). Table S7. Verifying independence assumption *. Table S3. Top results (p0.05). Table S4. GxE results for the list of candidate SNPs for MDD for the three main approaches as well as for the dominant/recessive case-only models. Some of the candidate SNPs were not available due to our QC filters (especially MAF 5%).

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Gale Document Number: GALE|A518473349