Gut microbiome signatures predict 5-ASA efficacy in ulcerative colitis

Area of Science:

• Gastroenterology
• Microbiome Research
• Computational Biology

Background:

• Ulcerative colitis (UC) affects millions globally, with limited treatment success.
• First-line 5-aminosalicylic acid (5-ASA) therapy fails in over 50% of UC patients.
• Predicting treatment response in UC is crucial for effective management.

Purpose of the Study:

• To identify gut microbial signatures predicting 5-ASA treatment efficacy in UC.
• To develop a predictive model for non-response to 5-ASA therapy.
• To explore the role of the gut microbiome in UC treatment outcomes.

Main Methods:

• Prospective enrollment of active UC patients undergoing 5-ASA treatment.
• Shotgun metagenomic sequencing for taxonomic and functional profiling.
• Random forest modeling to predict treatment response based on microbial species.

Main Results:

• Distinct microbial signatures were identified at baseline differentiating responders from non-responders.
• Faecalibacterium prausnitzii, Blautia massiliensis, and Phascolarctobacterium faecium were depleted in non-responders.
• A predictive model achieved high accuracy (AUC=0.80-0.82) in identifying patients likely to have ineffective 5-ASA treatment.

Conclusions:

• Gut microbiome composition can predict 5-ASA treatment efficacy in UC patients.
• Specific bacterial species may serve as non-invasive biomarkers for treatment response.
• Microbiome-based prediction could guide personalized therapeutic strategies in UC.