Combining mucosal microbiome and host multi-omics data shows prognostic potential in paediatric ulcerative colitis

Area of Science:

• Pediatric Gastroenterology
• Microbiome Research
• Immunology

Background:

• Current treatments for pediatric ulcerative colitis (UC) achieve remission in only 50% of cases.
• Early prediction of relapse could allow for timely immunosuppressant therapy.

Purpose of the Study:

• To identify predictive biomarkers for ulcerative colitis relapse in treatment-naïve children.
• To investigate the interplay between host factors and the gut microbiome in pediatric UC.

Main Methods:

• Collected intestinal biopsies from 56 treatment-naïve children.
• Performed quantitative microbial profiling, host epigenomics, transcriptomics, and genotyping.
• Conducted in vitro and in vivo experiments with selected bacteria.

Main Results:

• Lower baseline bacterial diversity and reduced butyrate producers were observed in relapsing children.
• Increased abundance of oral-associated bacteria, including *Veillonella parvula*, was linked to inflammation.
• Microbiota composition showed the strongest association with future relapse, followed by host epigenome and transcriptome.
• A machine learning model combining microbiome and epigenome data improved relapse prediction.

Conclusions:

• Host-microbe interactions hold significant prognostic potential for pediatric ulcerative colitis.
• Reduced colonic bacterial diversity in relapsing children may be exploited by pro-inflammatory oral bacteria.