Personality classification enhances blood metabolome analysis and biotyping for major depressive disorders: two-species investigation.
Journal
Journal of affective disorders
ISSN: 1573-2517
Titre abrégé: J Affect Disord
Pays: Netherlands
ID NLM: 7906073
Informations de publication
Date de publication:
15 01 2021
15 01 2021
Historique:
received:
07
05
2020
revised:
11
08
2020
accepted:
27
09
2020
pubmed:
11
10
2020
medline:
21
4
2021
entrez:
10
10
2020
Statut:
ppublish
Résumé
The relationship between depression and personality has long been suggested, however, biomarker investigations for depression have mostly overlooked this connection. We collected personality traits from 100 drug-free patients with major depressive disorders (MDD) and 100 healthy controls based on the Five-Factor Model (FFM) such as Neuroticism (N) and Extraversion (E), and also obtained 63 plasma metabolites profiles by LCMS-based metabolome analysis. Partitional clustering analysis using the NEO-FFI data classified all subjects into three major clusters. Eighty-six subjects belonging to Cluster 1 (C1: less personality-biased group) constituted half of MDD patients and half of healthy controls. C2 constituted 50 subjects mainly MDD patients (N A case-control study design and sample size is not large. Our results suggest that personality classification enhances blood biomarker analysis for MDD patients and further translational investigations should be conducted to clarify the biological relationship between personality traits, stress and depression.
Sections du résumé
BACKGROUND
The relationship between depression and personality has long been suggested, however, biomarker investigations for depression have mostly overlooked this connection.
METHODS
We collected personality traits from 100 drug-free patients with major depressive disorders (MDD) and 100 healthy controls based on the Five-Factor Model (FFM) such as Neuroticism (N) and Extraversion (E), and also obtained 63 plasma metabolites profiles by LCMS-based metabolome analysis.
RESULTS
Partitional clustering analysis using the NEO-FFI data classified all subjects into three major clusters. Eighty-six subjects belonging to Cluster 1 (C1: less personality-biased group) constituted half of MDD patients and half of healthy controls. C2 constituted 50 subjects mainly MDD patients (N
LIMITATIONS
A case-control study design and sample size is not large.
CONCLUSIONS
Our results suggest that personality classification enhances blood biomarker analysis for MDD patients and further translational investigations should be conducted to clarify the biological relationship between personality traits, stress and depression.
Identifiants
pubmed: 33038697
pii: S0165-0327(20)32814-7
doi: 10.1016/j.jad.2020.09.118
pii:
doi:
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
20-30Informations de copyright
Copyright © 2020 Elsevier B.V. All rights reserved.