Automated real-time imaging of intestinal barrier integrity and molecular profiling for early outcome prediction in inflammatory bowel disease: endo-histo-barrier-omics study

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Date
2025
Authors
Iacucci, Marietta
Majumder, Snehali
Zammarchi, Irene
Santacroce, Giovanni
Capobianco, Ivan
Pugliano, Cecilia L.
Chaudari, Ujwala
Esbri, Pablo Meseguer
Hayes, Brian D.
Crotty, Rory K.
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Oxford University Press
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Abstract
Background: Barrier healing is an emerging therapeutic target in inflammatory bowel disease (IBD), though its assessment remains challenging. We evaluated automated advanced imaging for real-time barrier assessment, its correlation with epithelial/vascular barrier markers, and ability to predict adverse outcomes. Methods: IBD patients and healthy controls undergoing endoscopic assessment were prospectively enrolled.The intestinal barrier was evaluated using ultra-high-magnification endocytoscopy and probe-based confocal laser endomicroscopy. Targeted biopsies were obtained from inflamed and non-inflamed segments. Epithelial and vascular barriers were assessed through automated multiplex immunofluorescence for Claudin-2, ZO-1, E-cadherin, PV-1, and CD31. Gene expression profiling was performed in epithelial and lamina propria compartments. Artificial intelligence (AI)-based analysis was employed for automated evaluation of barrier features captured by advanced imaging. Results: In total, 103 patients were included (38 ulcerative colitis [UC], 54 Crohn’s disease [CD], 11 healthy controls). Advanced imaging revealed barrier healing in 21% (8/38) of UC and 30% (16/54) of CD patients. In UC, Claudin-2 moderately correlated with abnormal crypt architecture (ρ=0.49), goblet cell depletion (ρ=0.5), and overall endocytoscopy activity (ρ=0.49). In CD, PV-1 moderately correlated with altered blood flow (ρ=0.41) and vessel architecture (ρ=0.40). An integrated assessment of advanced imaging, combined with Claudin-2 and PV-1 expression, effectively predicted adverse outcomes in UC and CD, respectively. AI tools accurately classified epithelial and vascular barrier features captured by advanced imaging. Finally, gene expression confirmed upregulation of Claudin-2 and PV-1 in IBD. Conclusion: Automated advanced imaging enables real-time barrier assessment in IBD and correlates with markers of epithelial and vascular barrier impairment. AI integration can enhance standardization toward broader clinical applicability.
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Keywords
Advanced imaging , Artificial intelligence , Barrier impairment , Claudin-2 , Gene expression , Multiplex immunofluorescence , PV-1
Citation
Iacucci, M., Majumder, S., Zammarchi, I., Santacroce, G., Capobianco, I., Pugliano, C. L., Chaudari, U., Meseguer Esbri, P., Hayes, B., Crotty, R. and Aburto, M.R. (2025) 'Automated real-time imaging of intestinal barrier integrity and molecular profiling for early outcome prediction in inflammatory bowel disease: endo-histo-barrier-omics study', Journal of Crohn's and Colitis, 19(11), jjaf200 (11pp). https://doi.org/10.1093/ecco-jcc/jjaf200
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