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Type: Journal article
Title: A latent genetic subtype of major depression identified by whole-exome genotyping data in a Mexican-American cohort
Author: Yu, C.
Arcos-Burgos, M.
Licinio, J.
Wong, M.
Citation: Translational Psychiatry, 2017; 7(5):e1134-1-e1134-6
Publisher: Nature Publishing Group
Issue Date: 2017
ISSN: 2158-3188
Statement of
C Yu, M Arcos-Burgos, J Licinio and M-L Wong
Abstract: Identifying data-driven subtypes of major depressive disorder (MDD) is an important topic of psychiatric research. Currently, MDD subtypes are based on clinically defined depression symptom patterns. Although a few data-driven attempts have been made to identify more homogenous subgroups within MDD, other studies have not focused on using human genetic data for MDD subtyping. Here we used a computational strategy to identify MDD subtypes based on single-nucleotide polymorphism genotyping data from MDD cases and controls using Hamming distance and cluster analysis. We examined a cohort of Mexican-American participants from Los Angeles, including MDD patients (n=203) and healthy controls (n=196). The results in cluster trees indicate that a significant latent subtype exists in the Mexican-American MDD group. The individuals in this hidden subtype have increased common genetic substrates related to major depression and they also have more anxiety and less middle insomnia, depersonalization and derealisation, and paranoid symptoms. Advances in this line of research to validate this strategy in other patient groups of different ethnicities will have the potential to eventually be translated to clinical practice, with the tantalising possibility that in the future it may be possible to refine MDD diagnosis based on genetic data.
Keywords: Humans; Sleep Initiation and Maintenance Disorders; Cluster Analysis; Depersonalization; Paranoid Behavior; Anxiety Disorders; Depressive Disorder, Major; Genotype; Polymorphism, Single Nucleotide; Adult; Aged; Middle Aged; Mexican Americans; Los Angeles; Female; Male; Young Adult; Exome
Description: Published online 16 May 2017
Rights: © The Author(s) 2017. This work is licensed under a Creative Commons Attribution- NonCommercial-ShareAlike 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if thematerial is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://
RMID: 0030070997
DOI: 10.1038/tp.2017.102
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Appears in Collections:Medicine publications

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