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

Authors :
Tian, Ruoyu
Ge, Tian
Kweon, Hyeokmoon
Rocha, Daniel B.
Lam, Max
Liu, Jimmy Z.
Singh, Kritika
Levey, Daniel F.
Gelernter, Joel
Stein, Murray B.
Tsai, Ellen A.
Huang, Hailiang
Chabris, Christopher F.
Lencz, Todd
Runz, Heiko
Chen, Chia-Yen
Source :
Nature Communications; 2/27/2024, Vol. 15 Issue 1, p1-12, 12p
Publication Year :
2024

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. Despite many common genetic variants being linked to depression, the impact of rare coding variants on depression remains largely unknown. Here, the authors perform a whole-exome sequencing study of depression, providing insights into the rare genetic architecture of depression. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
20411723
Volume :
15
Issue :
1
Database :
Complementary Index
Journal :
Nature Communications
Publication Type :
Academic Journal
Accession number :
175797672
Full Text :
https://doi.org/10.1038/s41467-024-45774-2