The dysbiosis of gut microbiota in major depressive disorder and comorbidity with overweight/obesity: unraveling biomarkers and metabolic pathways from a microbial perspective

BMC Psychiatry. 2025 Nov 7;25(1):1069. doi: 10.1186/s12888-025-07388-w.

ABSTRACT

BACKGROUND: Major depressive disorder (MDD), a leading global public health concern, exhibits high comorbidity with overweight/obesity. While emerging evidence implicates shared gut microbial dysregulation in both conditions, the identification of specific microbial biomarkers and their interaction with metabolic pathways in comorbid MDD-obesity remains poorly characterized. Our study investigated gut microbiota signatures in patients with MDD, and evaluated their modulation by overweight/obesity comorbidity.

METHOD: A total of 53 patients with MDD and 92 healthy controls (HCs) underwent 16 S rRNA gene sequencing. The KEGG function analysis was performed with potential differential microbiota. Correlation analysis related to bacterial taxa, biochemical parameters, and clinical indexes was aimed to indicate the specific metabolic dysregulation and gut microbiota imbalance in MDD, and whether these biomarkers were affected by the comorbidity of overweight/obesity.

RESULTS: Sixty-three bacterial genera showed differential abundance between MDD and HCs. Notably, Succinivibrio, Megamonas, and Bifidobacterium demonstrate significant distinctions between overweight-MDD and normal weight-MDD. The significantly altered metabolic pathways between MDD and HC primarily involve the biosynthesis and metabolism of long-chain unsaturated fatty acids. Within the MDD group, BMI demonstrated pairwise negative correlations with Bifidobacterium and total bilirubin (TBIL), while positively associating with Fusobacterium and alanine transaminase (ALT).

CONCLUSION: This study provides novel insights into the interplay between gut microbiota dysbiosis and metabolic perturbations in MDD. Despite intriguing associations between BMI and specific microbial taxa within the MDD group, the preliminary nature of these associations necessitates validation through larger cohorts, multi-omics approaches, and longitudinal designs.

PMID:41204410 | DOI:10.1186/s12888-025-07388-w