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Mendelian randomization integrating GWAS and eQTL data revealed genes pleiotropically associated with major depressive disorder

Authors :
Huarong Yang
Di Liu
Chuntao Zhao
Bowen Feng
Wenjin Lu
Xiaohan Yang
Minglu Xu
Weizhu Zhou
Huiquan Jing
Jingyun Yang
Source :
Translational Psychiatry, Vol 11, Iss 1, Pp 1-9 (2021)
Publication Year :
2021
Publisher :
Nature Publishing Group, 2021.

Abstract

Abstract Previous genome-wide association studies (GWAS) have identified potential genetic variants associated with the risk of major depressive disorder (MDD), but the underlying biological interpretation remains largely unknown. We aimed to prioritize genes that were pleiotropically or potentially causally associated with MDD. We applied the summary data-based Mendelian randomization (SMR) method integrating GWAS and gene expression quantitative trait loci (eQTL) data in 13 brain regions to identify genes that were pleiotropically associated with MDD. In addition, we repeated the analysis by using the meta-analyzed version of the eQTL summary data in the brain (brain-eMeta). We identified multiple significant genes across different brain regions that may be involved in the pathogenesis of MDD. The prime-specific gene BTN3A2 (corresponding probe: ENSG00000186470.9) was the top hit showing pleiotropic association with MDD in 9 of the 13 brain regions and in brain-eMeta, after correction for multiple testing. Many of the identified genes are located in the human major histocompatibility complex (MHC) region on chromosome 6 and are mainly involved in the immune response. Our SMR analysis indicated that multiple genes showed pleiotropic association with MDD across the brain regions. These findings provided important leads to a better understanding of the mechanism of MDD and revealed potential therapeutic targets for the prevention and effective treatment of MDD.

Details

Language :
English
ISSN :
21583188
Volume :
11
Issue :
1
Database :
Directory of Open Access Journals
Journal :
Translational Psychiatry
Publication Type :
Academic Journal
Accession number :
edsdoj.8b18990b3b2342d09de5ff18557d2ac9
Document Type :
article
Full Text :
https://doi.org/10.1038/s41398-021-01348-0