Predicting Risk of Post-Treatment Relapse in Patients with Inflammatory Bowel Disease Based on Intestinal Microbiota

Area of Science:

• Gastroenterology
• Microbiology
• Immunology

Background:

• Inflammatory bowel disease (IBD) presents a chronic challenge due to post-treatment relapse.
• Gut microbiota dysbiosis is a suspected factor in IBD recurrence.

Purpose of the Study:

• To investigate gut microbiota features associated with post-treatment relapse in IBD patients.
• To develop a predictive model for IBD recurrence using microbial signatures.

Main Methods:

• Analyzed fecal samples from 88 IBD patients (46 UC, 42 CD) using 16S rRNA sequencing.
• Employed a random forest (RF) model to assess the predictive value of microbiota for recurrence.

Main Results:

• Significant differences in gut microbiota composition were observed between UC and CD patients at baseline.
• Post-treatment, beta-diversity shifts were noted, with specific bacteria enriched in remission or recurrence groups.
• The RF model achieved an AUC of 0.721 (validation) and 0.861 (test) for predicting recurrence.

Conclusions:

• Gut microbiota composition shows potential for predicting IBD relapse.
• The developed RF model serves as a proof-of-concept, requiring external validation for clinical use.