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

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  • Jude Gibson
  • Jonathan R. I. Coleman
  • Saskia P. Hagenaars
  • Joey Ward
  • Eleanor M. Wigmore
  • Clara Alloza
  • Miruna C. Barbu
  • Eileen Y. Xu
  • Gibran Hemani
  • 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
  • Patrick F. Sullivan
  • Naomi R. Wray
  • Gerome Breen
  • Cathryn M. Lewis

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    Rights statement: This is an Accepted Manuscript of an article published in Nature Neuroscience on 4.2.2019, available online: https://www.nature.com/articles/s41593-018-0326-7

    Accepted author manuscript, 763 KB, PDF-document

http://www.nature.com/articles/s41593-018-0326-7
Original languageEnglish
Pages (from-to)343–352
Number of pages10
JournalNature Neuroscience
Volume22
Issue number3
DOIs
Publication statusPublished - 4 Feb 2019

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.

    Research areas

  • Cohort Studies, Depression/genetics, Depressive Disorder, Major/genetics, Female, Genetic Predisposition to Disease, Genetic Variation, Genome-Wide Association Study, Humans, Male, Multifactorial Inheritance, Polymorphism, Single Nucleotide, Prefrontal Cortex/metabolism

ID: 79770332