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

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; Klaus Berger; Henning Teismann; Rajesh Rawal; Volker Arolt; Bernhard T. Baune; Udo Dannlowski; Katharina Domschke; Chao Tian; David A. Hinds; 23andMe Research Team; Major Depressive Disorder Working Group of the Psychiatric Genomics Consortium; Maciej Trzaskowski; Enda M. Byrne; Stephan Ripke; Daniel J. Smith; Patrick F. Sullivan; Naomi R. Wray; Gerome Breen; Cathryn M. Lewis; Andrew M. McIntosh

doi:10.1038/s41593-018-0326-7

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

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 HemaniKlaus Berger, Henning Teismann, Rajesh Rawal, Volker Arolt, Bernhard T. Baune, Udo Dannlowski, Katharina Domschke, Chao Tian, David A. Hinds, 23andMe Research Team, Major Depressive Disorder Working Group of the Psychiatric Genomics Consortium, Maciej Trzaskowski, Enda M. Byrne, Stephan Ripke, Daniel J. Smith, Patrick F. Sullivan, Naomi R. Wray, Gerome Breen, Cathryn M. Lewis, Andrew M. McIntosh

Research output: Contribution to journal › Article › peer-review

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.

Original language	English
Pages (from-to)	343–352
Number of pages	10
Journal	Nature Neuroscience
Volume	22
Issue number	3
Early online date	4 Feb 2019
DOIs	https://doi.org/10.1038/s41593-018-0326-7
Publication status	Published - 31 Mar 2019

Keywords

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

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HowardEtal2019Genome-WideMetaAnalysisOfDepression
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1 Active
3 Finished

Stratifying Resilience and Depression Longitudinally
McIntosh, A., Deary, I., Evans, K., Haley, C. & Porteous, D.
UK-based charities
1/01/15 → 30/06/21
Project: Research
RA2661 Centre for Cognitive Ageing and Cognitive Epidemiology Phase 2. Main Budget.
Deary, I., Gale, C., Holmes, M., Logie, R., Maclullich, A., Porteous, D., Seckl, J., Starr, J., Wardlaw, J. & Okely, J.
1/09/13 → 31/08/19
Project: Research
Genetics and Healthcare Initiative
Porteous, D., Blackwood, D., Deary, I. & Ralston, S.
UK central government bodies/local authorities, health and hospital authorities, Other
1/06/05 → 31/03/10
Project: Research

1 Review article

Uncovering the genetic architecture of major depression
McIntosh, A., Sullivan, P. F. & Lewis, C. M., 3 Apr 2019, In: Neuron.
Research output: Contribution to journal › Review article › peer-review

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Genome-wide meta-analysis of depression identifies 102 independent variants and highlights the importance of the prefrontal brain regions
Howard, D. (Creator), Adams, M. (Creator), Clarke, T. (Creator), Hafferty, J. (Creator), Gibson, J. (Creator), Shirali, M. (Creator), Coleman, J. (Creator), Ward, J. (Creator), Wigmore, E. (Creator), Alloza, C. (Creator), Barbu, M. (Creator), Xu, E. (Creator), Whalley, H. (Creator), Marioni, R. (Creator), Porteous, D. (Creator), Davies, G. (Creator), Deary, I. (Creator), Hemani, G. (Creator), Tian, C. (Creator), Hinds, D. (Creator), Team, 2. R. (Creator), Consortium, M. D. D. W. G. O. T. P. G. (Creator), Trzaskowshi, M. (Creator), Byrne, E. (Creator), Ripke, S. (Creator), Smith, D. (Creator), Sullivan, P. (Creator), Wray, N. (Creator), Breen, G. (Creator), Shen, X. (Creator), Lewis, C. (Creator) & McIntosh, A. (Creator), Edinburgh DataShare, 30 Jan 2019
DOI: 10.7488/ds/2458
Dataset

4 Invited talk
1 Public Engagement – Festival/Exhibition
1 Public Engagement – Public lecture/debate/seminar
1 Providing oral or written evidence for non-academic board, committee, working group or advisory panel
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- 1 Research and Teaching at External Organisation

Combining genomic and imaging data in studies of depression
Andrew McIntosh (Keynote speaker)
15 Mar 2019
Activity: Academic talk or presentation types › Invited talk

File
The genetics of depression
Andrew McIntosh (Invited speaker)
26 Mar 2019
Activity: Academic talk or presentation types › Invited talk
Presentation on depression research to investment firm
Mark Adams (Advisor)
30 Jul 2019
Activity: Consultancy types › Providing oral or written evidence for non-academic board, committee, working group or advisory panel

Andrew McIntosh
- Deanery of Clinical Sciences - Chair of Biological Psychiatry
- Centre for Clinical Brain Sciences
- Edinburgh Neuroscience
- Edinburgh Imaging
- Health & Well-being
Person: Academic: Research Active
Heather Whalley
Person: Academic: Research Active

Cite this

Howard, D. M., Adams, M. J., Clarke, T-K., Hafferty, J. D., Gibson, J., Shirali, M., Coleman, J. R. I., Hagenaars, S. P., Ward, J., Wigmore, E. M., Alloza, C., Shen, X., Barbu, M. C., Xu, E. Y., Whalley, H. C., Marioni, R. E., Porteous, D. J., Davies, G., Deary, I. J., ... McIntosh, A. M. (2019). Genome-wide meta-analysis of depression identifies 102 independent variants and highlights the importance of the prefrontal brain regions. Nature Neuroscience, 22(3), 343–352. https://doi.org/10.1038/s41593-018-0326-7

Howard, David M. ; Adams, Mark J. ; Clarke, Toni-Kim ; 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. ; Hemani, Gibran ; 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. / Genome-wide meta-analysis of depression identifies 102 independent variants and highlights the importance of the prefrontal brain regions. In: Nature Neuroscience. 2019 ; Vol. 22, No. 3. pp. 343–352.

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

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.",

keywords = "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",

author = "Howard, {David M.} and Adams, {Mark J.} and Toni-Kim Clarke and Hafferty, {Jonathan D.} and Jude Gibson and Masoud Shirali and Coleman, {Jonathan R. I.} and Hagenaars, {Saskia P.} and Joey Ward and Wigmore, {Eleanor M.} and Clara Alloza and Xueyi Shen and Barbu, {Miruna C.} and Xu, {Eileen Y.} and Whalley, {Heather C.} and Marioni, {Riccardo E.} and Porteous, {David J.} and Gail Davies and Deary, {Ian J.} and Gibran Hemani and Klaus Berger and Henning Teismann and Rajesh Rawal and Volker Arolt and Baune, {Bernhard T.} and Udo Dannlowski and Katharina Domschke and Chao Tian and Hinds, {David A.} and {23andMe Research Team} and {Major Depressive Disorder Working Group of the Psychiatric Genomics Consortium} and Maciej Trzaskowski and Byrne, {Enda M.} and Stephan Ripke and Smith, {Daniel J.} and Sullivan, {Patrick F.} and Wray, {Naomi R.} and Gerome Breen and Lewis, {Cathryn M.} and McIntosh, {Andrew M.}",

year = "2019",

month = mar,

day = "31",

doi = "10.1038/s41593-018-0326-7",

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Howard, DM, Adams, MJ, Clarke, T-K, Hafferty, JD, Gibson, J, Shirali, M, Coleman, JRI, Hagenaars, SP, Ward, J, Wigmore, EM, Alloza, C, Shen, X, Barbu, MC, Xu, EY, Whalley, HC , Marioni, RE , Porteous, DJ , Davies, G , Deary, IJ, Hemani, G, Berger, K, Teismann, H, Rawal, R, Arolt, V, Baune, BT, Dannlowski, U, Domschke, K, Tian, C, Hinds, DA, 23andMe Research Team, Major Depressive Disorder Working Group of the Psychiatric Genomics Consortium, Trzaskowski, M, Byrne, EM, Ripke, S, Smith, DJ, Sullivan, PF, Wray, NR, Breen, G, Lewis, CM & McIntosh, AM 2019, 'Genome-wide meta-analysis of depression identifies 102 independent variants and highlights the importance of the prefrontal brain regions', Nature Neuroscience, vol. 22, no. 3, pp. 343–352. https://doi.org/10.1038/s41593-018-0326-7

Genome-wide meta-analysis of depression identifies 102 independent variants and highlights the importance of the prefrontal brain regions. / Howard, David M.; Adams, Mark J.; Clarke, Toni-Kim; 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.; Hemani, Gibran; 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.

In: Nature Neuroscience, Vol. 22, No. 3, 31.03.2019, p. 343–352.

Research output: Contribution to journal › Article › peer-review

TY - JOUR

T1 - Genome-wide meta-analysis of depression identifies 102 independent variants and highlights the importance of the prefrontal brain regions

AU - Howard, David M.

AU - Adams, Mark J.

AU - Clarke, Toni-Kim

AU - Hafferty, Jonathan D.

AU - Gibson, Jude

AU - Shirali, Masoud

AU - Coleman, Jonathan R. I.

AU - Hagenaars, Saskia P.

AU - Ward, Joey

AU - Wigmore, Eleanor M.

AU - Alloza, Clara

AU - Shen, Xueyi

AU - Barbu, Miruna C.

AU - Xu, Eileen Y.

AU - Whalley, Heather C.

AU - Marioni, Riccardo E.

AU - Porteous, David J.

AU - Davies, Gail

AU - Deary, Ian J.

AU - Hemani, Gibran

AU - Berger, Klaus

AU - Teismann, Henning

AU - Rawal, Rajesh

AU - Arolt, Volker

AU - Baune, Bernhard T.

AU - Dannlowski, Udo

AU - Domschke, Katharina

AU - Tian, Chao

AU - Hinds, David A.

AU - 23andMe Research Team

AU - Major Depressive Disorder Working Group of the Psychiatric Genomics Consortium

AU - Trzaskowski, Maciej

AU - Byrne, Enda M.

AU - Ripke, Stephan

AU - Smith, Daniel J.

AU - Sullivan, Patrick F.

AU - Wray, Naomi R.

AU - Breen, Gerome

AU - Lewis, Cathryn M.

AU - McIntosh, Andrew M.

PY - 2019/3/31

Y1 - 2019/3/31

N2 - 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.

AB - 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.

KW - Cohort Studies

KW - Depression/genetics

KW - Depressive Disorder, Major/genetics

KW - Female

KW - Genetic Predisposition to Disease

KW - Genetic Variation

KW - Genome-Wide Association Study

KW - Humans

KW - Male

KW - Multifactorial Inheritance

KW - Polymorphism, Single Nucleotide

KW - Prefrontal Cortex/metabolism

U2 - 10.1038/s41593-018-0326-7

DO - 10.1038/s41593-018-0326-7

M3 - Article

C2 - 30718901

VL - 22

SP - 343

EP - 352

JO - Nature Neuroscience

JF - Nature Neuroscience

SN - 1097-6256

IS - 3

ER -