Genome-wide association study of depression phenotypes in UK Biobank identifies variants in excitatory synaptic pathways

David M. Howard(University of Edinburgh), Mark J. Adams(University of Edinburgh), Masoud Shirali(University of Edinburgh), Toni‐Kim Clarke(University of Edinburgh), Riccardo E. Marioni(University of Edinburgh), Gail Davies(University of Edinburgh), Jonathan R. I. Coleman(King's College London), Clara Alloza(University of Edinburgh), Xueyi Shen(University of Edinburgh), Miruna C. Barbu(University of Edinburgh), Eleanor M. Wigmore(University of Edinburgh), Jude Gibson(University of Edinburgh), Michelle Agee(23andMe (United States)), Babak Alipanahi(23andMe (United States)), Adam Auton(23andMe (United States)), Robert K. Bell(23andMe (United States)), Katarzyna Bryc(23andMe (United States)), Sarah L. Elson(23andMe (United States)), Pierre Fontanillas(23andMe (United States)), Nicholas A. Furlotte(23andMe (United States)), David A. Hinds(23andMe (United States)), Karen E. Huber(23andMe (United States)), Aaron Kleinman(23andMe (United States)), Nadia K. Litterman(23andMe (United States)), Jennifer C. McCreight(23andMe (United States)), Matthew H. McIntyre(23andMe (United States)), Joanna L. Mountain(23andMe (United States)), Elizabeth S. Noblin(23andMe (United States)), Carrie A. M. Northover(23andMe (United States)), Steven J. Pitts(23andMe (United States)), J. Fah Sathirapongsasuti(23andMe (United States)), Olga V. Sazonova(23andMe (United States)), Janie F. Shelton(23andMe (United States)), Suyash Shringarpure(23andMe (United States)), Chao Tian(23andMe (United States)), Joyce Y. Tung(23andMe (United States)), Vladimir Vacic(23andMe (United States)), Catherine H. Wilson(23andMe (United States)), Saskia P. Hagenaars(King's College London), Cathryn M. Lewis(King's College London), Joey Ward(University of Glasgow), Daniel J. Smıth(University of Glasgow), Patrick F. Sullivan(University of North Carolina at Chapel Hill), Chris Haley(Institute of Genetics and Cancer), Gerome Breen(King's College London), Ian J. Deary(University of Edinburgh), Andrew M. McIntosh(University of Edinburgh)
Nature Communications
April 11, 2018
Cited by 660Open Access
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Abstract

Abstract Depression is a polygenic trait that causes extensive periods of disability. Previous genetic studies have identified common risk variants which have progressively increased in number with increasing sample sizes of the respective studies. Here, we conduct a genome-wide association study in 322,580 UK Biobank participants for three depression-related phenotypes: broad depression, probable major depressive disorder (MDD), and International Classification of Diseases (ICD, version 9 or 10)-coded MDD. We identify 17 independent loci that are significantly associated ( P < 5 × 10 −8 ) across the three phenotypes. The direction of effect of these loci is consistently replicated in an independent sample, with 14 loci likely representing novel findings. Gene sets are enriched in excitatory neurotransmission, mechanosensory behaviour, post synapse, neuron spine and dendrite functions. Our findings suggest that broad depression is the most tractable UK Biobank phenotype for discovering genes and gene sets that further our understanding of the biological pathways underlying depression.


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