Integrated Metabolomics and Microbial Profiling in Patients with Irritable Bowel Syndrome.

IBS patients showed no significant difference in overall microbial diversity compared to healthy controls, but exhibited relatively higher abundance of specific bacterial taxa.

• Overall microbial diversity was not significantly different between IBS patients and healthy controls (HC).
• IBS patients showed relatively higher abundance of Christensenellaceae R-7 group, Clostridium sensu stricto 1, and Negativibacillus.
• These discriminating microbial features were identified by comparing gut microbiota composition between HC and IBS patients.

Metabolite analysis identified 34 statistically significant plasma metabolites distinguishing IBS patients from healthy controls.

• 34 plasma metabolites met significance thresholds of VIP > 1.2 and q < 0.05.
• Plasma metabolite profiles were compared between healthy controls and IBS patients.
• These metabolites were identified through an approach that included variable importance in projection (VIP) scoring and false discovery rate correction (q-value).

Metabolic pathway analysis revealed that carbohydrate, amino acid, and fatty acid metabolism were commonly disturbed pathways in both plasma and urinary metabolites of IBS patients.

• Metabolite set abundance analysis was used to identify disturbed metabolic pathways.
• Commonly disturbed pathways were identified across both plasma and urinary metabolite datasets.
• The analysis integrated two metabolomics datasets (plasma and urinary) to identify overlapping pathway disturbances.

Fatty acid metabolism was specifically linked to three metabolites that showed significant correlations with discriminating gut microbial features.

• Three metabolites within the fatty acid metabolism pathway showed significant correlations with gut microbial features.
• The correlated microbial features were Clostridium sensu stricto 1, Negativibacillus, and Klebsiella.
• This finding was derived from cross-dataset integration of gut microbial communities with plasma and urinary metabolite profiles.

Integration of three datasets—plasma metabolites, urinary metabolites, and gut microbial communities—provided a comprehensive overview of IBS pathophysiology.

• The study employed a multi-omics approach combining plasma metabolomics, urinary metabolomics, and gut microbiota profiling.
• The integrated analysis identified functional interactions between discriminative gut microbial features and systemic metabolic alterations.
• The study compared profiles between healthy controls (HC) and IBS patients to identify disease-associated changes.