Gut microbiota and metabolic characteristics in subthreshold depression based on multi-omics

Subthreshold depression (SD) is an intermediate state between normal mood and major depressive disorder (MDD), but its biological underpinnings remain insufficiently understood. Increasing evidence suggests that gut microbiota and host metabolic alterations may contribute to early depressive pathophysiology.

We performed full-length 16S rRNA gene sequencing and LC-MS-based untargeted metabolomics on stool and plasma samples obtained from SD subjects and healthy controls. Microbial diversity, taxonomic composition, metabolic pathway alterations, and gut microbiota-metabolite associations were analyzed using bioinformatics pipelines, KEGG annotation, and Spearman correlation analysis.

SD patients exhibited marked gut microbial disturbances, including reduced microbial diversity and altered abundances of key genera such as decreased Eubacterium hallii group, Blautia, Dorea, and Agathobacter, and increased Escherichia-Shigella, Monoglobus, and Lachnoclostridium. Metabolomic profiling identified widespread metabolic perturbations, mainly affecting lipid metabolism, steroid hormone biosynthesis, and amino acid pathways. Exploratory correlation analysis indicated that beneficial taxa (e.g., Eubacterium hallii group and Blautia) were positively associated with specific glycerophospholipid and steroid hormone metabolites, whereas inverse associations were observed for other lipid-related metabolites.

This integrative microbiome-metabolome analysis demonstrates that SD is accompanied by early disruptions in gut microbial composition and systemic metabolism, particularly within lipid-related pathways. These findings suggest that gut microbiota dysbiosis may reflect early metabolic dysregulation and depression-related biological vulnerability in SD and highlight the gut microbiota as a candidate biological target for early identification and intervention.