Whole-exome sequencing in UK Biobank reveals rare genetic architecture for depression

Ruoyu Tian, Tian Ge, Hyeokmoon Kweon, Daniel B. Rocha, Max Lam, Jimmy Z. Liu, Kritika Singh, Daniel F. Levey, Joel Gelernter, Murray B. Stein, Ellen A. Tsai, Hailiang Huang, Christopher F. Chabris, Todd Lencz, Heiko Runz () and Chia-Yen Chen ()
Additional contact information
Ruoyu Tian: Biogen Inc
Tian Ge: Psychiatric and Neurodevelopmental Genetics Unit, Center for Genomic Medicine, Massachusetts General Hospital
Hyeokmoon Kweon: Vrije Universiteit Amsterdam
Daniel B. Rocha: Phenomics Analytics and Clinical Data Core, Geisinger Health System
Max Lam: Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard
Jimmy Z. Liu: Biogen Inc
Kritika Singh: Vanderbilt University Medical Center
Daniel F. Levey: Yale University School of Medicine
Joel Gelernter: VA Connecticut Healthcare Center
Murray B. Stein: VA San Diego Healthcare System
Ellen A. Tsai: Biogen Inc
Hailiang Huang: Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard
Christopher F. Chabris: Autism & Developmental Medicine Institute, Geisinger Health System
Todd Lencz: Division of Psychiatry Research, The Zucker Hillside Hospital, Northwell Health
Heiko Runz: Biogen Inc
Chia-Yen Chen: Biogen Inc

Nature Communications, 2024, vol. 15, issue 1, 1-12

Abstract: Abstract Nearly two hundred common-variant depression risk loci have been identified by genome-wide association studies (GWAS). However, the impact of rare coding variants on depression remains poorly understood. Here, we present whole-exome sequencing analyses of depression with seven different definitions based on survey, questionnaire, and electronic health records in 320,356 UK Biobank participants. We showed that the burden of rare damaging coding variants in loss-of-function intolerant genes is significantly associated with risk of depression with various definitions. We compared the rare and common genetic architecture across depression definitions by genetic correlation and showed different genetic relationships between definitions across common and rare variants. In addition, we demonstrated that the effects of rare damaging coding variant burden and polygenic risk score on depression risk are additive. The gene set burden analyses revealed overlapping rare genetic variant components with developmental disorder, autism, and schizophrenia. Our study provides insights into the contribution of rare coding variants, separately and in conjunction with common variants, on depression with various definitions and their genetic relationships with neurodevelopmental disorders.

Date: 2024
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DOI: 10.1038/s41467-024-45774-2

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