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

Research output: Contribution to journalJournal articlepeer-review

  • Jonathan R.I. Coleman
  • Héléna A. Gaspar
  • Julien Bryois
  • Enda M. Byrne
  • Andreas J. Forstner
  • Peter A. Holmans
  • Christiaan A. de Leeuw
  • Manuel Mattheisen
  • Andrew McQuillin
  • Jennifer M. Whitehead Pavlides
  • Pers, Tune H
  • Stephan Ripke
  • Eli A. Stahl
  • Stacy Steinberg
  • Vassily Trubetskoy
  • Maciej Trzaskowski
  • Yunpeng Wang
  • Liam Abbott
  • Abdel Abdellaoui
  • Mark J. Adams
  • Annelie Nordin Adolfsson
  • Esben Agerbo
  • Huda Akil
  • Diego Albani
  • Ney Alliey-Rodriguez
  • Thomas D. Als
  • Till F.M. Andlauer
  • Adebayo Anjorin
  • Verneri Antilla
  • Sandra Van der Auwera
  • Swapnil Awasthi
  • Silviu Alin Bacanu
  • Judith A. Badner
  • Marie Bækvad-Hansen
  • Jack D. Barchas
  • Nicholas Bass
  • Michael Bauer
  • Aartjan T.F. Beekman
  • Richard Belliveau
  • Sarah E. Bergen
  • Tim B. Bigdeli
  • Elisabeth B. Binder
  • Erlend Bøen
  • Christine Søholm Hansen
  • Hansen, Thomas Folkmann
  • Krogh, Jesper
  • Carsten Bøcker Pedersen
  • Marianne Giørtz Pedersen
  • Nordentoft, Merete
  • Werge, Thomas
  • Bipolar Disorder Working Group of the Psychiatric Genomics Consortium
  • Major Depressive Disorder Working Group of the Psychiatric Genomics Consortium

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
JournalBiological Psychiatry
Issue number2
Pages (from-to)169-184
Number of pages16
Publication statusPublished - 2020

    Research areas

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

ID: 259052709