Literature DB >> 24607927

The gender-specific association of EHD3 polymorphisms with major depressive disorder.

Le Wang1, Cuijuan Shi2, Kerang Zhang3, Qi Xu4.   

Abstract

Recent work suggests that women have a higher liability to major depressive disorder (MDD) than men, but the mechanism for the gender difference remains unknown. Given a genetic component involved in MDD, genome-wide association studies (GWAS) have been performed to search for susceptibility loci for the diseases and several genes of interest have been reported, including the EH-domain containing 3 (EHD3) gene that encodes a protein participating in endosome protein trafficking. However, the polymorphism association of the EHD3 gene with MDD failed to be replicated in a Chinese Han population. In the present study, we stratified 517 MDD patients and 455 control subjects by gender and symptoms and found 3 SNPs present in the EHD3 gene, of which rs619002 and rs644926 were exclusively associated with female MDD (p=0.0045 and p=0.0074, respectively) and rs649729 (p=0.0029) was closely related to anxious mood of female patients, suggesting a gender-specific role of EHD3 in MDD. These positive findings help explain, at least from one aspect, the poor replication of GWAS results. Further functional analysis is needed to clarify how variants in EHD3 may play a female-specific role in the pathogenesis of MDD.
Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Entities:  

Keywords:  EHD3; Female; MDD

Mesh:

Substances:

Year:  2014        PMID: 24607927     DOI: 10.1016/j.neulet.2014.02.055

Source DB:  PubMed          Journal:  Neurosci Lett        ISSN: 0304-3940            Impact factor:   3.046


  5 in total

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Journal:  Sci Rep       Date:  2016-09-07       Impact factor: 4.379

Review 4.  Gender Differences in Depression: Evidence From Genetics.

Authors:  Lihong Zhao; Guanghong Han; Yinghao Zhao; Yang Jin; Tongtong Ge; Wei Yang; Ranji Cui; Songbai Xu; Bingjin Li
Journal:  Front Genet       Date:  2020-10-15       Impact factor: 4.599

5.  Prediction of Probable Major Depressive Disorder in the Taiwan Biobank: An Integrated Machine Learning and Genome-Wide Analysis Approach.

Authors:  Eugene Lin; Po-Hsiu Kuo; Wan-Yu Lin; Yu-Li Liu; Albert C Yang; Shih-Jen Tsai
Journal:  J Pers Med       Date:  2021-06-24
  5 in total

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