Gut Microbial Metabolic Disorder in Depression: Insights from Computational Modeling and Mediation Analysis

BackgroundDepression is a common mental disorder worldwide, and its pathogenesis remains incompletely understood. However, increasing evidence suggests that gut microbiota play a significant role in the development of depression through the gut-brain-microbiota axis. However, due to the substantial individual variability in gut microbiota, while metabolic functions and metabolites between individuals are relatively similar, analyzing functional profiles and metabolic products yields more accurate results. ResultsIn this study, gut microbiota abundance data were collected from 354 depression patients and 5575 healthy individuals in the GMrepo v2 database. After matching for age and BMI, 271 paired samples from each group were retained. Alpha diversity analysis revealed significant differences between the two groups in the Observed, Shannon, and Chao1 indices, while beta diversity analysis indicated only subtle differences in gut microbiota composition. LEfSe analysis identified 23 differential species, with 18 enriched in the healthy group and 5 in the depression group. Further alpha diversity analysis of reaction abundance showed significant differences in the Observed and Chao1 indices, while beta diversity analysis did not reveal significant differences in reaction abundance. Differential and enrichment analyses identified 89 reactions that were significantly different between the groups, which were enriched in 4 metabolic pathways. Wilcoxon signed-rank test of COBRA-predicted metabolic fluxes revealed significant differences in the fluxes of 21 metabolites. Although the abundance of six species did not differ significantly between the two groups, their contributions to metabolic fluxes were significantly different. Mediation analysis indicated that gut microbiota influence the progression of depression by modulating various metabolites. ConclusionsThis study combined species abundance with COBRA metabolic flux predictions and mediation analysis, identified several differential species, as well as multiple differential metabolic fluxes, such as Cu2+ and L-Dopa, which were attributed to species like Dorea. Species such as Acholeplasma and Acidovorax were found to influence the progression of depression by affecting various metabolites, including Cu2+. These findings contribute to a deeper understanding of the relationship between gut microbiota and depression, offering new directions for the diagnosis and treatment of depression.