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

Advanced schistosomiasis showed significantly lower β-diversity compared to chronic schistosomiasis.

• Study design: matched case-control with 67 advanced schistosomiasis patients and 67 age-, sex-, and region-matched chronic cases
• β-diversity was assessed using weighted Bray-Curtis distances
• α-diversity metrics included Chao1, ACE, Shannon, and Simpson indices
• All p < 0.05 for diversity comparisons
• Fecal microbiota was characterized using 16S rRNA gene sequencing

Advanced schistosomiasis was associated with reduced relative abundance of Bacteroidetes and enrichment of opportunistic pathogens.

• Reduced Bacteroidetes relative abundance was significant at p < 0.05
• Several opportunistic pathogens were enriched in advanced schistosomiasis patients
• Differential taxa were identified using Kruskal-Wallis and LEfSe analyses
• The shift in microbial composition distinguished advanced from chronic disease stages

Microbial composition was significantly associated with dietary preferences and demographic variables.

• Significant associations were found with preferences for staple foods, edible oils, vegetables/fruits, and whole grains/tubers (all p < 0.05)
• Age and sex were also significantly associated with microbial composition (all p < 0.05)
• Associations were evaluated using Spearman correlation and redundancy analysis
• 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.

• Nutritional indicators and dietary patterns were concurrently collected alongside microbiota data
• Patients with nutritional risk showed smaller microbial variation compared to those without nutritional risk
• Protein depletion was associated with increased abundance of opportunistic bacteria
• Demographic, anthropometric, nutritional, and dietary data were all collected for correlation analyses

A random forest model identified Veillonella as the most discriminative genus for separating advanced from chronic schistosomiasis.

• Random forest modeling was applied to identify taxa predictive of advanced disease stage
• Veillonella was ranked as the top discriminative genus between the two disease stages
• The finding supports Veillonella as a potential noninvasive biomarker for advanced schistosomiasis
• The model was applied to data from 67 advanced and 67 chronic schistosomiasis cases