King's College London

Research portal

Genome-wide meta-analysis of depression identifies 102 independent variants and highlights the importance of the prefrontal brain regions

Research output: Contribution to journalArticle

David M. Howard, Mark J. Adams, Toni-kim Clarke, Jonathan D. Hafferty, Jude Gibson, Masoud Shirali, Jonathan R. I. Coleman, Saskia P. Hagenaars, Joey Ward, Eleanor M. Wigmore, Clara Alloza, Xueyi Shen, Miruna C. Barbu, Eileen Y. Xu, Heather C. Whalley, Riccardo E. Marioni, David J. Porteous, Gail Davies, Ian J. Deary, Gibran Hemani & 18 others Klaus Berger, Henning Teismann, Rajesh Rawal, Volker Arolt, Bernhard T. Baune, Udo Dannlowski, Katharina Domschke, Chao Tian, David A. Hinds, Maciej Trzaskowski, Enda M. Byrne, Stephan Ripke, Daniel J. Smith, Patrick F. Sullivan, Naomi R. Wray, Gerome Breen, Cathryn M. Lewis, Andrew M. Mcintosh

Original languageEnglish
JournalNature Neuroscience
DOIs
StatePublished - 4 Feb 2019

King's Authors

Abstract

Major depression is a debilitating psychiatric illness that is typically associated with low mood and anhedonia. Depression has a heritable component that has remained difficult to elucidate with current sample sizes due to the polygenic nature of the disorder. To maximize sample size, we meta-analyzed 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 genesets associated with depression, including both genes and gene pathways associated with synaptic structure and neurotransmission. An enrichment analysis provided further evidence of the importance of prefrontal brain regions. 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 after multiple testing correction. These findings advance our understanding of the complex genetic architecture of depression and provide several future avenues for understanding etiology and developing new treatment approaches.

View graph of relations

© 2018 King's College London | Strand | London WC2R 2LS | England | United Kingdom | Tel +44 (0)20 7836 5454