Abstract

The prevalence and clinical characteristics of depressive disorders differ between women and men; however, the genetic contribution to sex differences in depressive disorders has not been elucidated. To evaluate sex-specific differences in the genetic architecture of depression, whole exome sequencing of samples from 1000 patients (70.7% female) with depressive disorder was conducted. Control data from healthy individuals with no psychiatric disorder (n = 72, 26.4% female) and East-Asian subpopulation 1000 Genome Project data (n = 207, 50.7% female) were included. The genetic variation between men and women was directly compared using both qualitative and quantitative research designs. Qualitative analysis identified five genetic markers potentially associated with increased risk of depressive disorder in females, including three variants (rs201432982 within PDE4A, and rs62640397 and rs79442975 within FDX1L) mapping to chromosome 19p13.2 and two novel variants (rs820182 and rs820148) within MYO15B at the chromosome 17p25.1 locus. Depressed patients homozygous for these variants showed more severe depressive symptoms and higher suicidality than those who were not homozygotes (i.e., heterozygotes and homozygotes for the non-associated allele). Quantitative analysis demonstrated that the genetic burden of protein-truncating and deleterious variants was higher in males than females, even after permutation testing. Our study provides novel genetic evidence that the higher prevalence of depressive disorders in women may be attributable to inherited variants.

Details

Title
Sex differences in the genetic architecture of depression
Author
Hee-Ju, Kang 1 ; Park Yoomi 2 ; Kyung-Hun, Yoo 2 ; Ki-Tae, Kim 2 ; Eun-Song, Kim 1 ; Ju-Wan, Kim 1 ; Sung-Wan, Kim 1 ; Il-Seon, Shin 1 ; Jin-Sang, Yoon 1 ; Han, Kim Ju 2 ; Jae-Min, Kim 1 

 Chonnam National University Medical School, Departments of Psychiatry, Gwangju, Korea (GRID:grid.14005.30) (ISNI:0000 0001 0356 9399) 
 Seoul National University Biomedical Informatics (SNUBI), Division of Biomedical Informatics, Seoul National University College of Medicine, Seoul, Korea (GRID:grid.31501.36) (ISNI:0000 0004 0470 5905) 
Publication year
2020
Publication date
2020
Publisher
Nature Publishing Group
e-ISSN
20452322
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2414579600
Copyright
© The Author(s) 2020. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.