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The Genetics of the Mood Disorder Spectrum: Genome-wide Association Analyses of More Than 185,000 Cases and 439,000 Controls

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The Genetics of the Mood Disorder Spectrum : Genome-wide Association Analyses of More Than 185,000 Cases and 439,000 Controls. / Bipolar Disorder Working Group of the Psychiatric Genomics Consortium; Major Depressive Disorder Working Group of the Psychiatric Genomics Consortium.

In: Biological psychiatry, 01.01.2020.

Research output: Contribution to journalArticle

Harvard

Bipolar Disorder Working Group of the Psychiatric Genomics Consortium & Major Depressive Disorder Working Group of the Psychiatric Genomics Consortium 2020, 'The Genetics of the Mood Disorder Spectrum: Genome-wide Association Analyses of More Than 185,000 Cases and 439,000 Controls', Biological psychiatry. https://doi.org/10.1016/j.biopsych.2019.10.015

APA

Bipolar Disorder Working Group of the Psychiatric Genomics Consortium, & Major Depressive Disorder Working Group of the Psychiatric Genomics Consortium (2020). The Genetics of the Mood Disorder Spectrum: Genome-wide Association Analyses of More Than 185,000 Cases and 439,000 Controls. Biological psychiatry. https://doi.org/10.1016/j.biopsych.2019.10.015

Vancouver

Bipolar Disorder Working Group of the Psychiatric Genomics Consortium, Major Depressive Disorder Working Group of the Psychiatric Genomics Consortium. The Genetics of the Mood Disorder Spectrum: Genome-wide Association Analyses of More Than 185,000 Cases and 439,000 Controls. Biological psychiatry. 2020 Jan 1. https://doi.org/10.1016/j.biopsych.2019.10.015

Author

Bipolar Disorder Working Group of the Psychiatric Genomics Consortium ; Major Depressive Disorder Working Group of the Psychiatric Genomics Consortium. / The Genetics of the Mood Disorder Spectrum : Genome-wide Association Analyses of More Than 185,000 Cases and 439,000 Controls. In: Biological psychiatry. 2020.

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@article{0fbfff65f3654e159ccfe35e274faccd,
title = "The Genetics of the Mood Disorder Spectrum: Genome-wide Association Analyses of More Than 185,000 Cases and 439,000 Controls",
abstract = "Background: Mood disorders (including major depressive disorder and bipolar disorder) affect 10{\%} to 20{\%} of the population. They range from brief, mild episodes to severe, incapacitating conditions that markedly impact lives. Multiple approaches have shown considerable sharing of risk factors across mood disorders despite their diagnostic distinction. Methods: To clarify the shared molecular genetic basis of major depressive disorder and bipolar disorder and to highlight disorder-specific associations, we meta-analyzed data from the latest Psychiatric Genomics Consortium genome-wide association studies of major depression (including data from 23andMe) and bipolar disorder, and an additional major depressive disorder cohort from UK Biobank (total: 185,285 cases, 439,741 controls; nonoverlapping N = 609,424). Results: Seventy-three loci reached genome-wide significance in the meta-analysis, including 15 that are novel for mood disorders. More loci from the Psychiatric Genomics Consortium analysis of major depression than from that for bipolar disorder reached genome-wide significance. Genetic correlations revealed that type 2 bipolar disorder correlates strongly with recurrent and single-episode major depressive disorder. Systems biology analyses highlight both similarities and differences between the mood disorders, particularly in the mouse brain cell types implicated by the expression patterns of associated genes. The mood disorders also differ in their genetic correlation with educational attainment—the relationship is positive in bipolar disorder but negative in major depressive disorder. Conclusions: The mood disorders share several genetic associations, and genetic studies of major depressive disorder and bipolar disorder can be combined effectively to enable the discovery of variants not identified by studying either disorder alone. However, we demonstrate several differences between these disorders. Analyzing subtypes of major depressive disorder and bipolar disorder provides evidence for a genetic mood disorders spectrum.",
keywords = "Affective disorders, Bipolar disorder, Genetic correlation, Genome-wide association study, Major depressive disorder, Mood disorders",
author = "{Bipolar Disorder Working Group of the Psychiatric Genomics Consortium} and {Major Depressive Disorder Working Group of the Psychiatric Genomics Consortium} and Coleman, {Jonathan R.I.} and Gaspar, {H{\'e}l{\'e}na A.} and Julien Bryois and Byrne, {Enda M.} and Forstner, {Andreas J.} and Holmans, {Peter A.} and {de Leeuw}, {Christiaan A.} and Manuel Mattheisen and Andrew McQuillin and {Whitehead Pavlides}, {Jennifer M.} and Pers, {Tune H.} and Stephan Ripke and Stahl, {Eli A.} and Stacy Steinberg and Vassily Trubetskoy and Maciej Trzaskowski and Yunpeng Wang and Liam Abbott and Abdel Abdellaoui and Adams, {Mark J.} and Adolfsson, {Annelie Nordin} and Esben Agerbo and Huda Akil and Diego Albani and Ney Alliey-Rodriguez and Als, {Thomas D.} and Andlauer, {Till F.M.} and Adebayo Anjorin and Verneri Antilla and Clarke, {Toni Kim} and Craig, {David W.} and Eley, {Thalia C.} and Hansen, {Thomas F.} and {de Jong}, Simone and Radhika Kandaswamy and Peter McGuffin and Niamh Mullins and O'Reilly, {Paul F.} and Purcell, {Shaun M.} and Riley, {Brien P.} and Smith, {Daniel J.} and Tansey, {Katherine E.} and Matthew Traylor and Wei Xu and Young, {Allan H.} and Neale, {Benjamin M.} and Schofield, {Peter R.} and Rudolf Uher and Lewis, {Cathryn M.} and Gerome Breen",
year = "2020",
month = "1",
day = "1",
doi = "10.1016/j.biopsych.2019.10.015",
language = "English",
journal = "Biological psychiatry",
issn = "0006-3223",
publisher = "Elsevier",

}

RIS (suitable for import to EndNote) Download

TY - JOUR

T1 - The Genetics of the Mood Disorder Spectrum

T2 - Genome-wide Association Analyses of More Than 185,000 Cases and 439,000 Controls

AU - Bipolar Disorder Working Group of the Psychiatric Genomics Consortium

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

AU - Coleman, Jonathan R.I.

AU - Gaspar, Héléna A.

AU - Bryois, Julien

AU - Byrne, Enda M.

AU - Forstner, Andreas J.

AU - Holmans, Peter A.

AU - de Leeuw, Christiaan A.

AU - Mattheisen, Manuel

AU - McQuillin, Andrew

AU - Whitehead Pavlides, Jennifer M.

AU - Pers, Tune H.

AU - Ripke, Stephan

AU - Stahl, Eli A.

AU - Steinberg, Stacy

AU - Trubetskoy, Vassily

AU - Trzaskowski, Maciej

AU - Wang, Yunpeng

AU - Abbott, Liam

AU - Abdellaoui, Abdel

AU - Adams, Mark J.

AU - Adolfsson, Annelie Nordin

AU - Agerbo, Esben

AU - Akil, Huda

AU - Albani, Diego

AU - Alliey-Rodriguez, Ney

AU - Als, Thomas D.

AU - Andlauer, Till F.M.

AU - Anjorin, Adebayo

AU - Antilla, Verneri

AU - Clarke, Toni Kim

AU - Craig, David W.

AU - Eley, Thalia C.

AU - Hansen, Thomas F.

AU - de Jong, Simone

AU - Kandaswamy, Radhika

AU - McGuffin, Peter

AU - Mullins, Niamh

AU - O'Reilly, Paul F.

AU - Purcell, Shaun M.

AU - Riley, Brien P.

AU - Smith, Daniel J.

AU - Tansey, Katherine E.

AU - Traylor, Matthew

AU - Xu, Wei

AU - Young, Allan H.

AU - Neale, Benjamin M.

AU - Schofield, Peter R.

AU - Uher, Rudolf

AU - Lewis, Cathryn M.

AU - Breen, Gerome

PY - 2020/1/1

Y1 - 2020/1/1

N2 - Background: Mood disorders (including major depressive disorder and bipolar disorder) affect 10% to 20% of the population. They range from brief, mild episodes to severe, incapacitating conditions that markedly impact lives. Multiple approaches have shown considerable sharing of risk factors across mood disorders despite their diagnostic distinction. Methods: To clarify the shared molecular genetic basis of major depressive disorder and bipolar disorder and to highlight disorder-specific associations, we meta-analyzed data from the latest Psychiatric Genomics Consortium genome-wide association studies of major depression (including data from 23andMe) and bipolar disorder, and an additional major depressive disorder cohort from UK Biobank (total: 185,285 cases, 439,741 controls; nonoverlapping N = 609,424). Results: Seventy-three loci reached genome-wide significance in the meta-analysis, including 15 that are novel for mood disorders. More loci from the Psychiatric Genomics Consortium analysis of major depression than from that for bipolar disorder reached genome-wide significance. Genetic correlations revealed that type 2 bipolar disorder correlates strongly with recurrent and single-episode major depressive disorder. Systems biology analyses highlight both similarities and differences between the mood disorders, particularly in the mouse brain cell types implicated by the expression patterns of associated genes. The mood disorders also differ in their genetic correlation with educational attainment—the relationship is positive in bipolar disorder but negative in major depressive disorder. Conclusions: The mood disorders share several genetic associations, and genetic studies of major depressive disorder and bipolar disorder can be combined effectively to enable the discovery of variants not identified by studying either disorder alone. However, we demonstrate several differences between these disorders. Analyzing subtypes of major depressive disorder and bipolar disorder provides evidence for a genetic mood disorders spectrum.

AB - Background: Mood disorders (including major depressive disorder and bipolar disorder) affect 10% to 20% of the population. They range from brief, mild episodes to severe, incapacitating conditions that markedly impact lives. Multiple approaches have shown considerable sharing of risk factors across mood disorders despite their diagnostic distinction. Methods: To clarify the shared molecular genetic basis of major depressive disorder and bipolar disorder and to highlight disorder-specific associations, we meta-analyzed data from the latest Psychiatric Genomics Consortium genome-wide association studies of major depression (including data from 23andMe) and bipolar disorder, and an additional major depressive disorder cohort from UK Biobank (total: 185,285 cases, 439,741 controls; nonoverlapping N = 609,424). Results: Seventy-three loci reached genome-wide significance in the meta-analysis, including 15 that are novel for mood disorders. More loci from the Psychiatric Genomics Consortium analysis of major depression than from that for bipolar disorder reached genome-wide significance. Genetic correlations revealed that type 2 bipolar disorder correlates strongly with recurrent and single-episode major depressive disorder. Systems biology analyses highlight both similarities and differences between the mood disorders, particularly in the mouse brain cell types implicated by the expression patterns of associated genes. The mood disorders also differ in their genetic correlation with educational attainment—the relationship is positive in bipolar disorder but negative in major depressive disorder. Conclusions: The mood disorders share several genetic associations, and genetic studies of major depressive disorder and bipolar disorder can be combined effectively to enable the discovery of variants not identified by studying either disorder alone. However, we demonstrate several differences between these disorders. Analyzing subtypes of major depressive disorder and bipolar disorder provides evidence for a genetic mood disorders spectrum.

KW - Affective disorders

KW - Bipolar disorder

KW - Genetic correlation

KW - Genome-wide association study

KW - Major depressive disorder

KW - Mood disorders

UR - http://www.scopus.com/inward/record.url?scp=85078024661&partnerID=8YFLogxK

U2 - 10.1016/j.biopsych.2019.10.015

DO - 10.1016/j.biopsych.2019.10.015

M3 - Article

C2 - 31926635

AN - SCOPUS:85078024661

JO - Biological psychiatry

JF - Biological psychiatry

SN - 0006-3223

ER -

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