Microbiota-Based Biomarkers in Irritable Bowel Syndrome Evidence, Limitations, and Translational Readiness
Molecular Mechanisms, Therapeutic Targets, and Clinical Challenges
Keywords:
Gut-Brain Axis,, Hypothalamus-Pituitary-Ovary axis, metabolomics, biomarkersAbstract
Irritable bowel syndrome (IBS), which is now classified as disorders of gut-brain interaction, is diagnosed mainly through the symptom-based Rome criteria. While gut microbiota dysbiosis has been repeatedly linked to IBS pathophysiology, no reproducible microbiota based diagnostic signature has been established yet for universal clinical application. This mini review critically evaluates microbiota associated biomarker research in IBS studies, distinguishing discovery stage microbial associations from clinically relevant biomarkers. Evidence was assessed across taxonomic signatures, microbiome diversity measurements, short-chain fatty acids, bile acid metabolism, tryptophan related metabolites, immune-associated markers, and multi-omics approaches. Current findings suggest that taxonomic markers alone remain inconsistent and greatly impacted by cohort, diet, geography, sequencing method, and analytical pipeline. Functional and multi-marker approaches, specifically the integration of metabolomic and host-response data appear more mechanistically plausible but remain limited by small cohorts, cross-sectional designs, incomplete external validation and lack of methodological standardisation. Commercial and research profiling platforms including dysbiosis testing approaches showcase translational potential but should not yet be considered validated diagnostic replacements for the Rome based clinical diagnosis. Overall, microbiota-based biomarkers are best understood as potential future adjuncts for patient stratification, mechanism-based subtyping, and treatment response prediction rather than singular diagnostic tools. Progress towards clinical implementation will need longitudinal, multi-center, standardised, and externally validated studies supporting the integration of microbial composition, function, individual host factors and patient level clinical data for adequate application
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