Abstract

Major depression is a debilitating psychiatric illness that is typically associated with low mood, anhedonia and a range of comorbidities. Depression has a heritable component that has remained difficult to elucidate with current sample sizes due to the polygenic nature of the disorder. To maximise sample size, we meta-analysed data on 807,553 individuals (246,363 cases and 561,190 controls) from the three largest genome-wide association studies of depression. We identified 102 independent variants, 269 genes, and 15 gene-sets associated with depression, including both genes and gene-pathways associated with synaptic structure and neurotransmission. Further evidence of the importance of prefrontal brain regions in depression was provided by an enrichment analysis. In an independent replication sample of 1,306,354 individuals (414,055 cases and 892,299 controls), 87 of the 102 associated variants were significant following multiple testing correction. Based on the putative genes associated with depression this work also highlights several potential drug repositioning opportunities. These findings advance our understanding of the complex genetic architecture of depression and provide several future avenues for understanding aetiology and developing new treatment approaches.

Details

Title
Genome-wide meta-analysis of depression identifies 102 independent variants and highlights the importance of the prefrontal brain regions.
Author
Howard, David M; Adams, Mark J; Toni-Kim, Clarke; Hafferty, Jonathan D; Gibson, Jude; Shirali, Masoud; Coleman, Jonathan R I; Hagenaars, Saskia P; Ward, Joey; Wigmore, Eleanor M; Alloza, Clara; Shen, Xueyi; Barbu, Miruna C; Xu, Eileen Y; Whalley, Heather C; Marioni, Riccardo E; Porteous, David J; Davies, Gail; Deary, Ian J; Gibran Hemani; Berger, Klaus; Teismann, Henning; Rawal, Rajesh; Arolt, Volker; Baune, Bernhard T; Dannlowski, Udo; Domschke, Katharina; Tian, Chao; Hinds, David A; 23andme Research Team; Major Depressive Disorder Working Group Of The Psychiatric Genomics Consortium; Trzaskowski, Maciej; Byrne, Enda M; Ripke, Stephan; Smith, Daniel J; Sullivan, Patrick F; Wray, Naomi R; Breen, Gerome; Lewis, Cathryn M; Mcintosh, Andrew M
University/institution
Cold Spring Harbor Laboratory Press
Section
New Results
Publication year
2019
Publication date
Jan 8, 2019
Publisher
Cold Spring Harbor Laboratory Press
Source type
Working Paper
Language of publication
English
ProQuest document ID
2117261863
Copyright
© 2019. This article is published under http://creativecommons.org/licenses/by/4.0/ (“the License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.