Clinical gastroenterology and hepatology : the official clinical practice journal of the American Gastroenterological Association · 2026
Microscopic Colitis Beyond Histology: Biomarkers and Candidate Endotypes.
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Bencardino Sarah, Lo Bello Antonio, Majumder Snehali, Hughes Robert, Das Santanu, Zammarchi Irene, Pugliano Cecilia Lina, Iacucci Marietta
Аннотация
Microscopic colitis (MC) is a chronic inflammatory bowel disorder characterised by chronic watery diarrhoea in the setting of a normal or near-normal endoscopic appearance, with diagnosis relying on histologic evaluation of colonic biopsies. It is traditionally divided into lymphocytic colitis (LC), defined by an increased intraepithelial lymphocyte count, and collagenous colitis (CC), characterised by a thickened subepithelial collagen band. However, these categories do not fully capture the biological heterogeneity of the disease. Conventional histology remains crucial for diagnosis yet provides only a static morphological assessment of a biologically dynamic disease and offers limited prognostic or treatment-predictive information. Nevertheless, several clinically recognisable mechanisms and phenotypes already provide opportunities for patient stratification and, in selected cases, mechanism-informed management, including medication-associated MC, bile acid malabsorption, immune checkpoint inhibitor-associated MC, coexistent coeliac disease, and smoking-related risk. Beyond these clinically identifiable phenotypes, emerging OMICS evidence reveals heterogeneity across immune, epithelial barrier, stromal, microbial-metabolic, and genetic domains. Importantly, these molecular domains currently represent candidate mechanistic phenotypes rather than validated endotypes, as patient-level reproducibility and associations with disease trajectory or differential treatment response remain insufficiently established. This narrative review critically appraises current histological and molecular biomarkers in MC and their potential to improve disease stratification. Moreover, artificial intelligence-driven multimodal approaches may ultimately complement morphological assessment, improve patient characterisation and support the prediction of treatment response. We further define the validation steps required to translate emerging biological signatures into clinically meaningful endotypes and precision medicine.