ArticleIntestinal research2026
Cross-ethnic evaluation of gut microbial signatures reveal increased colonization with oral pathobionts in the north Indian inflammatory bowel disease cohort.
Article in Intestinal research, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers, 1 of them a synthesis that pooled it.
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Who cites it
3 citing papers in PubMed, 1 synthesis or guideline pooled it.
- A systematic review and meta-analysis reveals enrichment of pro-inflammatory and bacterial immunity-modulating taxa in oral squamous cell carcinoma.Frontiers in immunology · 2026Pooled it
- Integrated Multi-Omics Reveals Complementary Luminal and Mucosal Host-Microbiome Interactions Associated with Disease Activity and Phenotype in Paediatric Inflammatory Bowel Disease.Microorganisms · 2026Article
- Rhamnocitrin Ameliorates the Intestinal Fibrosis in DSS-Induced Colitis Mice by Modulating Host-Metabolites and Remodeling the Gut Microbiome.Antioxidants (Basel, Switzerland) · 2026Article
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Authors and funding
8 authors.
Funding
Abstract
BACKGROUND/
aimsInflammatory bowel disease (IBD) has become a global health concern. With the growing evidence of the gut microbiota's role in IBD, studying microbial compositions across ethnic cohorts is essential to identify unique, populationspecific microbial signatures.
methodsWe analyzed stool samples and clinical data from 254 IBD patients (226 ulcerative colitis, 28 Crohn's disease) and 66 controls in northern India using metagenomic shotgun sequencing to assess microbiota diversity, composition, and function. Results were replicated in 436 IBD patients and 903 controls from the Netherlands using identical workflows. Using machine learning, we evaluated the generalizability of Indian IBD signals to the Dutch cohort, and vice versa.
resultsIndian IBD patients exhibited reduced bacterial diversity and an abundance of opportunistic pathogens, including Clostridium, Streptococcus, and oral bacteria like Streptococcus oralis and Bifidobacterium dentium. There was a significant loss of energy metabolic pathways and distinct co-occurrence patterns among microbial species. Notably, 39% of these signals replicated in the Dutch cohort. Unique to the Indian cohort were oral pathobionts such as Scardovia, Oribacterium, Actinomyces dentalis, and Klebsiella pneumoniae. Both Indian and Dutch IBD patients shared reduced butyrate producers. Machine-learning diagnostic models trained on the Indian cohort achieved high predictive accuracy (sensitivity 0.84, specificity 0.95) and moderately generalized to the Dutch cohort (sensitivity 0.77, specificity 0.69).
conclusionsIBD patients across populations exhibit shared and unique microbial signatures, suggesting a role for the oral-gut microbiome axis in IBD. Crossethnic diagnostic models show promise for broader applications in identifying IBD.
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