Literature DB >> 32516008

The potential for metabolomics in the study and treatment of major depressive disorder and related conditions.

Jiajia Duan1,2, Peng Xie1,2,3.   

Abstract

INTRODUCTION: Major depressive disorder (MDD) is a common mental disease, associated with a debilitating condition and high prevalence. Although the underlying mechanism of MDD remains to be elucidated, several factors, including social, biological, and psychological factors, have been associated with disease pathogenesis. Metabolomics can provide new insights into the prognosis, treatment response, and related biomarkers associated with MDD at the metabolic level. AREAS COVERED: In this review, we investigated the metabolic changes identified in different bio-samples from animal models of depression and MDD patients. Moreover, we summarized the metabolites associated with antidepressant treatment responses. Keywords used for the literature searches were 'depression' [MeSH] and 'metabolomics' [MeSH], in PubMed. EXPERT OPINION: Metabolomic evidence in humans has indicated that amino acid metabolism, energy metabolism, and lipid metabolism are the primary metabolic alterations that are observed in the etiology of MDD, and animal models serve as an important theoretical reference in this field. Metabolomics has shed new light on the pathogenic mechanisms and treatment responses during MDD; however, study results are not always consistent. The application of metabolomic results to clinical practice will require the integration of different biological samples and other omics studies, as well as the clinical validation of study findings.

Entities:  

Keywords:  Major depressive disorder; biomarkers; differential metabolites; metabolomics; treatment response

Mesh:

Substances:

Year:  2020        PMID: 32516008     DOI: 10.1080/14789450.2020.1772059

Source DB:  PubMed          Journal:  Expert Rev Proteomics        ISSN: 1478-9450            Impact factor:   3.940


  5 in total

1.  Serum metabolomic responses to aerobic exercise in rats under chronic unpredictable mild stress.

Authors:  Xiangyu Liu; Yumei Han; Shi Zhou; Junsheng Tian; Xuemei Qin; Cui Ji; Weidi Zhao; Anping Chen
Journal:  Sci Rep       Date:  2022-03-22       Impact factor: 4.379

2.  LC-MS-based lipidomic analysis of liver tissue sample from spontaneously hypertensive rats treated with extract hawthorn fruits.

Authors:  Luping Sun; Bingqing Chi; Mingfeng Xia; Zhen Ma; Hongbin Zhang; Haiqiang Jiang; Fang Zhang; Zhenhua Tian
Journal:  Front Pharmacol       Date:  2022-08-09       Impact factor: 5.988

3.  Integrated network pharmacology and hepatic metabolomics to reveal the mechanism of Acanthopanax senticosus against major depressive disorder.

Authors:  Xinyi Gu; Guanying Zhang; Qixue Wang; Jing Song; Ying Li; Chenyi Xia; Ting Zhang; Li Yang; Jijia Sun; Mingmei Zhou
Journal:  Front Cell Dev Biol       Date:  2022-08-05

4.  Systematic metabolic characterization of mental disorders reveals age-related metabolic disturbances as potential risk factors for depression in older adults.

Authors:  Yu Liu; Wanyu Zhao; Ying Lu; Yunli Zhao; Yan Zhang; Miao Dai; Shan Hai; Ning Ge; Shuting Zhang; Mingjin Huang; Xiaohui Liu; Shuangqing Li; Jirong Yue; Peng Lei; Biao Dong; Lunzhi Dai; Birong Dong
Journal:  MedComm (2020)       Date:  2022-09-30

5.  Potential biomarkers of major depression diagnosis and chronicity.

Authors:  Ana Cecília de Menezes Galvão; Raíssa Nobrega Almeida; Geovan Menezes de Sousa Júnior; Mário André Leocadio-Miguel; Fernanda Palhano-Fontes; Dráulio Barros de Araujo; Bruno Lobão-Soares; João Paulo Maia-de-Oliveira; Emerson Arcoverde Nunes; Jaime Eduardo Cecilio Hallak; Jerome Sarris; Nicole Leite Galvão-Coelho
Journal:  PLoS One       Date:  2021-09-29       Impact factor: 3.240

  5 in total

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