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

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10 Scopus citations


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.

Original languageEnglish (US)
Pages (from-to)169-184
Number of pages16
JournalBiological psychiatry
Issue number2
StatePublished - Jul 15 2020

Bibliographical note

Funding Information:
This study represents independent research partly funded by the National Institute for Health Research (NIHR) Biomedical Research Centre (BRC) at South London and Maudsley National Health Service (NHS) Foundation Trust and King’s College London . High-performance computing facilities were funded with capital equipment grants from the Guy's and St. Thomas' Charity (Grant No. TR130505 ) and Maudsley Charity (Grant No. 980 ). The PGC has received major funding from the United States National Institute of Mental Health (NIMH) and the United States National Institute of Drug Abuse of the National Institutes of Health (NIH) (Grant Nos. U01 MH109528 [to PFS], U01MH109514 [to MCO], and U01 MH1095320 [to A Agrawal]). We acknowledge the continued support of the NL Genetic Cluster Computer ( ) hosted by SURFsara in the management and curation of PGC data, with funding from Scientific Organization Netherlands (Grant No. 480-05-003 [to DP]). Central analysis of PGC data was funded by UK Medical Research Council (MRC) Centre and Program Grants (Grant Nos. G0801418 and G0800509 [to PAH, MCO, MJO]) and grants from the Australian National Health and Medical Research Council (NHMRC) (Grant Nos. 1078901 and 108788 [to NRW]). GB, JRIC, HAG, and CL were supported in part by the NIHR as part of the Maudsley BRC. DP is funded by the Dutch Brain Foundation and the VU University Amsterdam Netherlands. PFS receives support from the Swedish Research Council ( Vetenskapsrådet ) (Grant No. D0886501 ).

Funding Information:
We are deeply indebted to the investigators who comprise the PGC, and to the hundreds of thousands of participants who have shared their life experiences with PGC investigators. BDRN acknowledges the research participants who continue to give their time to participate in our research. JMF thanks Janette M. O'Neil and Betty C. Lynch for their support. The deCODE authors are thankful to the participants and staff at the Patient Recruitment Center. GenPOD/Newmeds investigators are grateful to all the families who took part, the general practitioners and the Scottish School of Primary Care for their help in recruiting them, and the whole Generation Scotland team, which includes interviewers, computer and laboratory technicians, clerical workers, research scientists, volunteers, managers, receptionists, healthcare assistants, and nurses. GlaxoSmithKline Munich investigators thank all participants in the GSK-Munich study. We also thank numerous people at GSK and Max Planck Institute, BKH Augsburg, and Klinikum Ingolstadt in Germany who contributed to this project. Janssen investigators are grateful to the study volunteers for participating in the research studies and to the clinicians and support staff for enabling patient recruitment and blood sample collection. We also thank the staff in the former Neuroscience Biomarkers of Janssen Research and Development for laboratory and operational support (e.g., biobanking, processing, plating, and sample de-identification), and to the staff at Illumina for genotyping Janssen DNA samples. MARS/BiDirect investigators acknowledge all study participants. We thank numerous people at Max Planck Institute, and all study sites in Germany and Switzerland who contributed to this project. Michigan investigators thank the participants who donated their time and DNA to make this study possible. We thank members of the NIMH Human Genetics Initiative and the University of Michigan Prechter Bipolar DNA Repository for generously providing phenotype data and DNA samples. QIMR investigators thank the twins and their families for their willing participation in our studies. STAR*D authors appreciate the efforts of the STAR*D investigator team for acquiring, compiling, and sharing the STAR*D clinical dataset. SWEBIC investigators are deeply grateful for the participation of all participants contributing to this research, and to the collection team that worked to recruit them. We also wish to thank the Swedish National Quality Register for Bipolar Disorders: BipoläR. TwinGene investigators thank the Karolinska Institutet for infrastructural support of the Swedish Twin Registry. We thank the 23andMe research participants included in the analysis, all of whom provided informed consent and participated in the research online according to a human subjects protocol approved by an external AAHRPP-accredited institutional review board (Ethical & Independent Review Services), and the employees of 23andMe for making this work possible. 23andMe acknowledges the-invaluable contributions of Michelle Agee, Babak Alipanahi, Adam Auton, Robert K. Bell, Katarzyna Bryc, Sarah L. Elson, Pierre Fontanillas, Nicholas A. Furlotte, David A. Hinds, Bethann S. Hromatka, Karen E. Huber, Aaron Kleinman, Nadia K. Litterman, Matthew H. McIntyre, Joanna L. Mountain, Carrie A.M. Northover, Steven J. Pitts, J. Fah Sathirapongsasuti, Olga V. Sazonova, Janie F. Shelton, Suyash Shringarpure, Chao Tian, Joyce Y. Tung, Vladimir Vacic, and Catherine H. Wilson.

Publisher Copyright:
© 2019 Society of Biological Psychiatry


  • Affective disorders
  • Bipolar disorder
  • Genetic correlation
  • Genome-wide association study
  • Major depressive disorder
  • Mood disorders

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