Evidence map›Paper›PMID 40659339›Full record

ArticleIntestinal research2026

Cross-ethnic evaluation of gut microbial signatures reveal increased colonization with oral pathobionts in the north Indian inflammatory bowel disease cohort.

Arshdeep Singh, Garima Juyal, Ranko Gacesa, Mohan C Joshi, Vandana Midha, B K Thelma, Rinse K Weersma, Ajit Sood

Abstract read
In one paragraph

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.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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3 · Its place in the literature

Who cites it

3 citing papers in PubMed, 1 synthesis or guideline pooled it.

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4 · The record

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5 · Who and what money

Authors and funding

8 authors.

Arshdeep SinghDepartment of Gastroenterology, Dayanand Medical College and Hospital, Ludhiana, India.
Garima JuyalDepartment of Biotechnology, School of Engineering and Applied Sciences, Bennett University, Greater Noida, India.
Ranko GacesaDepartment of Gastroenterology and Hepatology, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands.
Mohan C JoshiMultidisciplinary Centre for Advance Research and Studies (MCARS), Jamia Millia Islamia, New Delhi, India.
Vandana MidhaDepartment of Internal Medicine, Dayanand Medical College and Hospital, Ludhiana, India.
B K ThelmaDepartment of Genetics, University of Delhi, South Campus, New Delhi, India.
Rinse K WeersmaDepartment of Gastroenterology and Hepatology, University Medical Center Groningen, University of Groningen, The Netherlands.
Ajit SoodDepartment of Gastroenterology, Dayanand Medical College and Hospital, Ludhiana, India.

Funding

CoE phase I BT/01/COE/07/UDSC/2008JC Bose Fellowship phase II, 2016-2021Research and Development Center, Dayanand Medical College and HospitalScience and Engineering Research Board SB/YS/LS-191/2014UGC FRP (236-FRP)/2015/BSR
6 · The paper itself

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.

Indexed as

DysbiosisGastrointestinal microbiomeInflammatory bowel diseasesMachine learningMicrobiota

Identifiers

PMID40659339
PMCPMC13153850

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