This study aims to analyze the composition, diversity, and metabolic functions of fecal microbiome (FM)-derived outer membrane vesicles (OMVs) in patients with vascular dementia (VaD), to identify potential biomarkers for VaD diagnosis. FM-derived OMVs were isolated from 29 VaD patients and 28 matched controls via ultracentrifugation and characterized using transmission electron microscopy and nanoparticle tracking analysis. PKH26-labeled OMVs were used for in vivo tracking in mouse brains. Microbial composition was profiled by 16 S rRNA sequencing, combined with diversity analysis and machine learning. VaD-OMVs were widely distributed in multiple cognitive function-related regions of mouse brains. The VaD group showed a decreased Chao1 index and increased coverage. β-diversity (PCoA/PLS-DA) revealed significant structural differences. Conditional pathogens (e.g., Pseudomonas, Acinetobacter) were enriched, while beneficial bacteria (e.g., Bifidobacterium) were reduced. Correlation analysis indicated promoting effects of Pseudomonadaceae and inhibitory effects of Faecalibacterium. Metabolic pathways including amino acid, carbohydrate, and nucleotide metabolism were enriched. A random forest model achieved an AUC of 0.74 (95% CI: 0.59–0.88) in classifying VaD. VaD is associated with distinct OMV microbial and functional profiles. OMV-based biomarkers show potential for VaD diagnosis.
Li et al. (Tue,) studied this question.