A latent genetic subtype of major depression identified by whole-exome genotyping data in a Mexican-American cohort

Translational Psychiatry
C YuM-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...Continue Reading

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Citations

Jan 1, 2020·Asia-Pacific Psychiatry : Official Journal of the Pacific Rim College of Psychiatrists·Jianfei FengRuibin Mu
Jan 2, 2020·Journal of Biomedical Informatics·Omar Rafique, A H Mir
Nov 21, 2017·Journal of Affective Disorders·Chenglong YuJulio Licinio
Jun 16, 2021·Neuropsychopharmacology : Official Publication of the American College of Neuropsychopharmacology·Helena PelinTill F M Andlauer

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Methods Mentioned

BETA
genotyping
MDS

Clinical Trials Mentioned

NCT00265291

Software Mentioned

SVS
R
MEGA

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