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Sex-stratified genome-wide association meta-analysis of major depressive disorder

  • Jodi T. Thomas*
  • , Jackson G. Thorp
  • , Floris Huider
  • , Poppy Z. Grimes
  • , Rujia Wang
  • , Pierre Youssef
  • , Jonathan R. I. Coleman
  • , Enda M. Byrne
  • , Mark Adams
  • , Brenda W. J. H. Penninx
  • , Hanna M. van Loo
  • , Sarah E. Medland
  • , Ian B. Hickie
  • , Catherine M. Olsen
  • , David C. Whiteman
  • , Heather C. Whalley
  • , Hanna M. van Loo
  • , Eske M. Derks
  • , Thalia C. Eley
  • , Gerome Breen
  • Dorret I. Boomsma, BIONIC consortium, The GLAD Study
*Corresponding author for this work
  • Queensland Institute of Medical Research
  • University of Queensland
  • Vrije Universiteit Amsterdam
  • Amsterdam UMC
  • University of Edinburgh
  • King's College London
  • South London and Maudsley NHS Foundation Trust
  • University of Groningen
  • The University of Sydney
  • University of Oxford
  • Queensland University of Technology

Research output: Contribution to journalArticleAcademicpeer-review

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Abstract

There are striking sex differences in the prevalence and symptomology of Major Depressive Disorder. Here, we conduct the largest sex-stratified genome wide association and genotype-by-sex interaction meta-analyses of Major Depressive Disorder to date (Females: 130,471 cases, 159,521 controls. Males: 64,805 cases, 132,185 controls). We identify 16 and eight independent genome-wide significant variants in females and males, respectively, including one novel variant on the X chromosome. Major Depressive Disorder in females and males shows substantial genetic overlap with a large proportion of variants displaying similar effect sizes across sexes. However, we also provide evidence for a higher burden of genetic risk in females which could be due to female-specific variants. Additionally, sex-specific pleiotropic effects may contribute to the higher prevalence of metabolic symptoms in females with Major Depressive Disorder. These findings underscore the importance of considering sex-specific genetic architectures in the study of health conditions, including Major Depressive Disorder, paving the way for more targeted treatment strategies.
Original languageEnglish
Article number7960
JournalNat. Commun.
Volume16
Issue number1
DOIs
Publication statusPublished - 1 Dec 2025

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