medscape.com
Machine Learning Model Identifies Gut Biomarkers That May Help Diagnose IBD Patients
This study suggests machine learning of stool microbiome data could eventually help distinguish IBD (especially Crohn’s) from healthy people and some other bowel or systemic conditions.
For people with IBD, better biomarkers might improve diagnosis or disease classification, but more validation is needed before clinical use.
Researchers working on microbiome biomarkers, clinicians interested in IBD diagnostics, and patients following developments in noninvasive IBD testing or microbiome research.
What To Know
Researchers presented ECCO 2025 data showing that machine learning applied to stool 16S rRNA profiles identified microbial biomarker sets that distinguished IBD (Crohn’s disease and ulcerative colitis) from healthy controls and from several non-IBD conditions.
The study tested four analytic approaches and found supervised machine learning produced the most discriminative biomarker panels, which were validated in three independent cohorts.
Experts at the session cautioned that most IBD patients in the study were already diagnosed and likely treated, which could alter microbiomes and limit the panel’s diagnostic use in untreated individuals.
These results suggest machine learning can find reproducible microbiome patterns linked to IBD and to Crohn’s disease specifically, but the authors and session discussants emphasize that further validation is needed—especially in cohorts not yet exposed to treatments that affect the gut microbiome.
The study used stool 16S sequencing across large Korean and external cohorts and compared performance (AUC) across methods and datasets. If you want to read the original report, the article summarizes the ECCO 2025 presentation and includes direct quotes from the presenter and session discussants.
The report does not provide clinical recommendations or imply current clinical availability of a diagnostic microbiome test.
Findings come from an ECCO conference presentation using 16S rRNA sequencing and machine learning; they were validated in independent cohorts but most IBD participants were already diagnosed and likely treated, which can change microbiome profiles.
The article is a medical-news report of a conference abstract rather than a peer-reviewed full study; further peer-reviewed validation in treatment-naïve cohorts would be needed before clinical translation.
