Alterations in gut microbiota and their association with nutrition and disease progression in advanced schistosomiasis.

Gut microbiota may play an important role in the pathophysiology of Schistosoma japonicum infection, yet microbial signatures associated with advanced schistosomiasis remain poorly defined. In this matched case-control study, we compared gut microbiota profiles between 67 patients with advanced schistosomiasis and 67 age-, sex-, and region-matched chronic cases, and examined associations with nutritional indicators and dietary patterns. Fecal microbiota was characterized using 16S rRNA gene sequencing, and demographic, anthropometric, nutritional, and dietary data were concurrently collected. Microbial α-diversity (Chao1, ACE, Shannon, Simpson) and β-diversity (weighted Bray-Curtis distances) were assessed, differential taxa were identified using Kruskal-Wallis and LEfSe analyses, and their associations with nutritional phenotypes and dietary preferences were evaluated using Spearman correlation and redundancy analysis. A random forest model was applied to identify taxa predictive of advanced stage. Advanced schistosomiasis exhibited significantly lower β-diversity and reduced relative abundance of Bacteroidetes (all p < 0.05), with enrichment of several opportunistic pathogens. Microbial composition was significantly associated with preferences for staple foods, edible oils, vegetables/fruits, whole grains/tubers, age and sex (all p < 0.05). Genera including Veillonella, Actinomyces, and Streptococcus showed negative correlations with oil preference. Patients with nutritional risk or protein depletion displayed smaller microbial variation and increased abundance of opportunistic bacteria. The random forest model identified Veillonella as the most discriminative genus separating advanced from chronic schistosomiasis. These findings indicate that gut microbiota alterations are closely associated with schistosomiasis progression and nutritional status, and support further investigation of Veillonella as a potential noninvasive biomarker.