Literature DB >> 26874244

Metabolite signature for diagnosing major depressive disorder in peripheral blood mononuclear cells.

Peng Zheng1, Zheng Fang1, Xue-Jiao Xu1, Mei-Ling Liu1, Xiangyu Du1, Xiaotong Zhang1, Haiyang Wang1, Jingjing Zhou1, Peng Xie2.   

Abstract

BACKGROUND: Major depressive disorder (MDD) is a serious debilitating psychiatric disorder. However, the molecular mechanisms of MDD remain largely unknown, and no objective laboratory-based tests are available to diagnose this disorder.
METHODS: A gas chromatography-mass spectrometry (GC-MS) based metabolomic approach was used to compare peripheral blood mononuclear cells (PBMC) metabolic profiling of 50 first onset drug-naïve MDD subjects and 50 healthy controls (training samples), to identify potential metabolite biomarkers for MDD. An independent sample cohort including 58 MDD patients, 40 schizophrenia (SCZ) patients and 56 healthy controls (test samples) was used to validate diagnostic generalizability and specificity of identified biomarkers.
RESULTS: 17 PBMC metabolites responsible for discriminating MDD group from healthy control group were identified. These metabolites were mainly involved in disturbances of energy and neurotransmitter metabolism. This PBMC metabolite signature could effectively discriminate MDD subjects from the healthy controls with an AUC of 0.926 in training samples and 0.870 in test samples. Moreover, this metabolite signature enabled distinguishing MDD subjects from schizophrenia subjects with an AUC of 0.899. LIMITATIONS: This study was limited by potential confounding effects of different drug treatments in some MDD and schizophrenia subjects, and lack of animal studies to further validate the identified metabolite pathways in MDD.
CONCLUSION: These findings suggest that early disturbances of PBMC energy and neurotransmitter metabolism may be associated with the onset of MDD. This PBMC metabolite signature may facilitate development of a laboratory-based diagnostic test for MDD.
Copyright © 2016 Elsevier B.V. All rights reserved.

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Year:  2016        PMID: 26874244     DOI: 10.1016/j.jad.2016.02.008

Source DB:  PubMed          Journal:  J Affect Disord        ISSN: 0165-0327            Impact factor:   4.839


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