Institut for Biomedicin

Preben Bo Mortensen

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

Publikation: Bidrag til tidsskrift/Konferencebidrag i tidsskrift /Bidrag til avisTidsskriftartikelForskningpeer review

DOI

  • David M Howard, Division of Psychiatry, University of Edinburgh, Royal Edinburgh Hospital
  • ,
  • Mark J Adams, Division of Psychiatry, University of Edinburgh, Royal Edinburgh Hospital
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  • Toni-Kim Clarke, Division of Psychiatry, University of Edinburgh, Royal Edinburgh Hospital
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  • Jonathan D Hafferty, Division of Psychiatry, University of Edinburgh, Royal Edinburgh Hospital
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  • Jude Gibson, Division of Psychiatry, University of Edinburgh, Royal Edinburgh Hospital
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  • Masoud Shirali, Division of Psychiatry, University of Edinburgh, Royal Edinburgh Hospital
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  • Jonathan R I Coleman, King’s College London, NIHR Biomedical Research Centre for Mental Health, South London and Maudsley NHS Trust
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  • Saskia P Hagenaars, King’s College London, NIHR Biomedical Research Centre for Mental Health, South London and Maudsley NHS Trust
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  • Joey Ward, University of Glasgow
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  • Eleanor M Wigmore, Division of Psychiatry, University of Edinburgh, Royal Edinburgh Hospital
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  • Clara Alloza, Division of Psychiatry, University of Edinburgh, Royal Edinburgh Hospital
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  • Xueyi Shen, Division of Psychiatry, University of Edinburgh, Royal Edinburgh Hospital
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  • Miruna C Barbu, Division of Psychiatry, University of Edinburgh, Royal Edinburgh Hospital
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  • Eileen Y Xu, Division of Psychiatry, University of Edinburgh, Royal Edinburgh Hospital
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  • Heather C Whalley, Division of Psychiatry, University of Edinburgh, Royal Edinburgh Hospital
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  • Riccardo E Marioni, University of Edinburgh
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  • David J Porteous, University of Edinburgh
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  • Gail Davies, University of Edinburgh
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  • Ian J Deary, University of Edinburgh
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  • Gibran Hemani, University of Bristol
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  • Klaus Berger, University of Münster
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  • Henning Teismann, University of Münster
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  • Rajesh Rawal, University of Münster
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  • Volker Arolt, University of Münster
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  • Bernhard T Baune, University of Melbourne
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  • Udo Dannlowski, University of Münster
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  • Katharina Domschke, University of Freiburg
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  • Chao Tian, 23andMe, Inc., Mountain View, California, USA.
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  • David A Hinds, 23andMe, Inc., Mountain View, California, USA.
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  • Maciej Trzaskowski, University of Queensland
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  • Enda M. Byrne, University of Queensland
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  • Stephan Ripke, Charité Universitätsmedizin Berlin, Broad Institute, Massachusetts General Hospital
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  • Daniel J Smith, University of Glasgow
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  • Patrick F Sullivan, Karolinska Institutet, University of North Carolina
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  • Naomi R Wray, University of Queensland
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  • Gerome Breen, King’s College London, NIHR Biomedical Research Centre for Mental Health, South London and Maudsley NHS Trust
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  • Cathryn M Lewis, King’s College London, NIHR Biomedical Research Centre for Mental Health, South London and Maudsley NHS Trust
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  • Andrew M McIntosh, Division of Psychiatry, University of Edinburgh, Royal Edinburgh Hospital
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  • 23andMe Research Team

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.

OriginalsprogEngelsk
TidsskriftNature Neuroscience
Vol/bind22
Nummer3
Sider (fra-til)343-352
Antal sider10
ISSN1097-6256
DOI
StatusUdgivet - mar. 2019

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