Alterations in gut microbiome and fecal metabolome in functional dyspepsia patients: insights into pathophysiological mechanisms

功能性消化不良患者肠道菌群和粪便代谢组的改变:对病理生理机制的深入理解

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Abstract

BACKGROUND: Gastrointestinal microbiota dysregulation is recognized as a key factor in the pathogenesis of functional dyspepsia (FD). Previous investigations have focused predominantly on the microbiota associated with the oral, gastric, and duodenal mucosa. However, the intestinal microbiome and fecal metabolome in FD patients remain poorly characterized. This study aims to evaluate their alterations, thereby providing novel insights into the pathophysiological mechanisms of FD. METHODS: Fecal samples from 30 FD patients and 19 healthy controls (HCs) were subjected to 16S rRNA sequencing and metabolomics to characterize microbial-metabolic profiles, followed by Spearman correlation analysis to explore the associations between differentially abundant taxa and metabolites. RESULTS: Compared with the HCs, the FD group presented greater microbial richness but comparable diversity, along with increased abundances of Akkermansia and Ruminococcus_gnavus_group and decreased levels of Dorea, Collinsella, and Agathobacter (p < 0.05). AUC analysis revealed Akkermansia as a potential biomarker for FD (AUC = 0.848, 95% CI: 0.708-0.988). Furthermore, the levels of the fecal metabolites phosphatidylglycerol (PG) and phosphatidylcholine (PC) were significantly reduced in the FD group (p < 0.05). KEGG enrichment analysis revealed that these metabolites were involved in glycerophospholipid metabolism. Spearman correlation analysis revealed negative associations between Ruminococcus_gnavus_group, Fusobacterium, Erysipelatoclostridium, and PG/PC (p < 0.05). CONCLUSIONS: The FD group presented concurrent alterations in the gut microbiome and fecal metabolites. Specifically, gut microbiota-derived metabolites, such as PG and PC, may disrupt host glycerophospholipid metabolism, contributing to FD pathogenesis. Given that this is an exploratory study with a small sample size and cross-sectional design, these results require validation in larger, longitudinal cohorts and should be interpreted with caution.

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