Gut microbiota signatures differentiate trajectory-defined response phenotypes and predict self-management outcomes in irritable bowel syndrome.

INTRODUCTION: Heterogeneity in symptom presentation and treatment response in irritable bowel syndrome (IBS) remains poorly understood. This analysis from a randomized controlled trial (NCT03332537) aims to identify symptom-trajectory phenotypes and determine whether gut microbiota composition and function distinguish these phenotypes and predict multidimensional responses to IBS pain self-management interventions. METHODS: Participants with longitudinal data (n = 62) were analyzed using longitudinal k-means clustering based on trajectories of measures in IBS quality of life (QOL), Brief Pain Inventory (BPI), and neuropsychological outcomes (anxiety, applied cognition, depression, fatigue, global health, positive affect, and sleep disturbance) over 12 weeks. Bayesian Additive Regression Trees (BART) models were used to identify baseline microbial taxa and pathways predictive of longitudinal changes in QOL, BPI pain interference, and severity. RESULTS: Two distinct trajectory-defined response phenotypes were identified: a Constrained Response Phenotype (Phenotype A, n = 35) and an Adaptive Multidomain Response Phenotype (Phenotype B, n = 27). At baseline, Phenotype B showed lower pain severity and interference, but higher levels of anxiety, depression, and fatigue compared to Phenotype A. Over 12 weeks, both phenotypes showed improvements in pain outcomes (all p < 0.05), but only Phenotype B demonstrated broad improvements across neuropsychological domains and QOL (all p < 0.05). Phenotype A exhibited more limited improvements and worsening in several neuropsychological domains. Nominal differences in predicted functional pathways were observed, including pathways related to xenobiotic degradation, amino acid metabolism, bile secretion, and immune-related processes (all raw p < 0.05). Although predicted functional pathway differences were not significant after correction for multiple testing, phenotype-specific microbial taxa and functional features were identified as predictors of treatment response in BART models. In Phenotype A, genera such as Alistipes and Sutterella were consistently identified across models, whereas in Phenotype B, predictors included Phascolarctobacterium, Collinsella, and Parabacteroides. CONCLUSIONS: IBS patients exhibit distinct multidimensional response patterns associated with distinct clinical and microbiome profiles. Baseline gut microbial characteristics may serve as potential biomarkers of heterogeneous treatment response in young adults with IBS, supporting a microbiome-based approach to categorize patients and improve personalized self-management strategies in IBS.