Transformations in plasma metabolic profiles of patients with major depression disorder during treatment

Metab Brain Dis. 2025 Sep 10;40(7):265. doi: 10.1007/s11011-025-01682-y.

ABSTRACT

Major depression disorder (MDD) is a mental condition that significantly threatens both physical and psychological health. This study aimed to discern variances in plasma metabolic profiles between MDD sufferers and healthy counterparts. Additionally, we tracked the hospitalization journey of MDD patients to investigate the normalization of metabolic irregularities through conventional treatment in the form of self-control. Ultra-Performance Liquid Chromatography – Mass Spectrometry was employed to analyze the metabolic profiles of 47 plasma samples, including 12 controls and 12 MDD patients at three distinct clinical stages (untreated baseline, 1-month post-treatment, and 2-month post-treatment). Multivariate statistical analysis and K-means clustering were executed to pinpoint significantly different metabolites between the groups and specific metabolites showing an ideal trend of variation. Subsequently, these metabolites were mapped onto Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways to preliminarily explore the potential mechanism of metabolic shifts in MDD. We identified 14 significantly different metabolites between MDD patients and controls. Among these, the relative levels of 9-hydroperoxy octadecadienoic acid, imidazoleacetic acid, thromboxane B2, and arachidonic acid displayed a regular trend of variation post-treatment. Further integration analysis yielded a novel metabolite-pathway network comprising these 4 specific metabolites and 8 pathways. These findings suggest that transitions in metabolic pathways during the onset and treatment of MDD are primarily governed by lipid metabolism and its associated signaling pathway system, with the involvement of histidine metabolism. The identified metabolites hold promise for diagnosing and evaluating the therapeutic efficacy of MDD, and provide a foundation for future research into the potential mechanisms underlying MDD.

PMID:40928689 | DOI:10.1007/s11011-025-01682-y