ArticleInflammatory bowel diseases2025
Gut Microbial Signatures in Pediatric Crohn's Disease Vary According to Disease Activity Measures and Are Influenced by Proxies of Gastrointestinal Transit Time: An ImageKids Study.
Article in Inflammatory bowel diseases, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
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Who cites it
3 citing papers in PubMed.
- Tripartite Interplay of Epithelial, Immune, and Microbiota Dysregulation in Crohn's Disease: Mechanisms and Translational Strategies.Immunity, inflammation and disease · 2026Review
- Microbial and functional shifts between flare and remission in a single-center cohort of children with inflammatory bowel disease.World journal of clinical pediatrics · 2026Article
- Age-Related Microbiota Signatures in Inflammatory Diseases: Comparative Insights into Paediatric and Adult Crohn's Disease, Ulcerative Colitis, and Spondyloarthritis.Mediterranean journal of rheumatology · 2026Review
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Authors and funding
14 authors.
Funding
Abstract
introductionWe investigated relationships between disease activity measures and the gut microbiome in children with Crohn's disease (CD) and how these were confounded by gastrointestinal transit time.
methodsMicrobiome was profiled (16S rRNA sequencing) in feces from 196 children with CD. Sixty participants also provided samples after 18 months. Mural inflammation (Pediatric Inflammatory Crohn's Magnetic Resonance Enterography Index, PICMI), the simple endoscopic score for CD, and the weighted pediatric Crohn's disease activity index (wPCDAI) were assessed. Fecal calprotectin, plasma C-reactive protein (CRP), and fecal water content (FWC), a proxy of gastrointestinal transit time, were measured too.
resultsMicrobiome α diversity, clustering, and differential taxa were related to disease status, but varied remarkably by disease activity measure used. The strongest relationships between microbiome and disease activity status were observed using wPCDAI; fewer or no relationships were seen using more objective measures like PICMI. Taxa predictive of disease activity status were dependent on the disease activity measure used with negligible overlap. Active disease was associated with more pathobionts (eg, Viellonella, Enterobacterales) and fewer fiber-fermenting organisms. The effect FWC had on microbiome superseded the effect of active disease for all disease activity measures, particularly with wPCDAI. Accounting for FWC, the differences in microbial signatures explained by disease activity status were attenuated or lost.
conclusionsIn CD, microbiome signatures fluctuate depending on the measure used to assess disease severity; several of these signals might be secondary disease effects linked with changes in gut motility in active disease. PICMI appears to be less influenced when studying relationships between microbiome and mural inflammation in CD.
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Registered trials
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