Observational studyInflammatory bowel diseases2025
Fecal Microbiome Reflects Disease State and Prognosis in Inflammatory Bowel Disease in an Adult Population-Based Inception Cohort.
Observational study 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 4 papers, 1 of them a synthesis that pooled it.
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The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
4 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Molecular Mechanisms Underlying the Higher Prevalence of Anemia in Crohn's Disease Compared with Ulcerative Colitis: A Systematic Review.International journal of molecular sciences · 2026Pooled it
- Disentangling the gut microbiome and inflammation in inflammatory bowel diseases: longitudinal observations from the IBSEN III study.Inflammatory bowel diseases · 2026Article
- Review
- Bacterial clusters are associated with the risk of severe disease progression in inflammatory bowel disease irrespective of conventional disease categories.Microbiome research reports · 2026Article
Corrections and comments
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Authors and funding
33 authors.
Funding
Abstract
introductionWe aimed to determine the diagnostic and prognostic potential of baseline microbiome profiling in inflammatory bowel disease (IBD).
methodsParticipants with ulcerative colitis (UC), Crohn's disease (CD), suspected IBD, and non-IBD symptomatic controls were included in the prospective population-based cohort Inflammatory Bowel Disease in South-Eastern Norway III (third iteration) based on suspicion of IBD. The participants donated fecal samples that were analyzed with 16S rRNA sequencing. Disease course severity was evaluated at the 1-year follow-up. A stringent statistical consensus approach for differential abundance analysis with 3 different tools was applied, together with machine learning modeling.
resultsA total of 1404 individuals were included, where n = 1229 samples from adults were used in the main analyses (n = 658 UC, n = 324 CD, n = 36 IBD-U, n = 67 suspected IBD, and n = 144 non-IBD symptomatic controls). Microbiome profiles were compared with biochemical markers in machine learning models to differentiate IBD from non-IBD symptomatic controls (area under the receiver operating curve [AUC] 0.75-0.79). For UC vs controls, integrating microbiome data with biochemical markers like fecal calprotectin mildly improved classification (AUC 0.83 to 0.86, P < .0001). Extensive differences in microbiome composition between UC and CD were identified, which could be quantified as an index of differentially abundant genera. This index was validated across published datasets from 3 continents. The UC-CD index discriminated between ileal and colonic CD (linear regression, P = .008) and between colonic CD and UC (P = .005), suggesting a location-dependent gradient. Microbiome profiles outperformed biochemical markers in predicting a severe disease course in UC (AUC 0.72 vs 0.65, P < .0001), even in those with a mild disease at baseline (AUC 0.66 vs 0.59, P < .0001).
conclusionsFecal microbiome profiling at baseline held limited potential to diagnose IBD from non-IBD compared with standard-of-care. However, microbiome shows promise for predicting future disease courses in UC.
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