P0307Automated real-time imaging of intestinal barrier integrity and molecular profiling for early outcome prediction in inflammatory bowel disease - Endo-Histo-Barrier-Omics study

Background Intestinal 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 and vascular barrier markers and its ability to predict adverse outcomes. Barrier-related gene expression was also assessed. Methods IBD patients undergoing endoscopic assessment, along with healthy controls, were prospectively enrolled. Intestinal barrier was evaluated using ultra-high magnification endocytoscopy and probe-based confocal laser endomicroscopy. Targeted biopsies were obtained from inflamed and non-inflamed bowel 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 separately in epithelial and lamina propria compartments. AI-based analysis was employed for automated evaluation of barrier features captured by advanced imaging. Results 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) UC and 30% (16/54) CD patients. In UC, Claudin-2 moderately correlated with abnormal crypt architecture (r = 0.49), goblet cell depletion (r = 0.5), and overall endocytoscopy activity (r = 0.49). In CD, PV-1 moderately correlated with altered blood flow (r = 0.41) and vessel architecture (r = 0.40). Integrated assessment of advanced imaging 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. Conflict of interest: Iacucci, Marietta: No conflict of interest Majumder, Snehali: No conflict of interest Dr. Zammarchi, Irene: No conflict of interest Santacroce, Giovanni: No conflict of interest Capobianco, Ivan: No conflict of interest Pugliano, Cecilia: No conflict of interest Chaudari, Ujwala: No conflict of interest Meseguer, Pablo: No conflict of interest Hayes, Brian: No conflict of interest Crotty, Rory: No conflict of interest Aburto, Maria: No conflict of interest Del Amor, Maria Rocio: No conflict of interest Kolawole, Bisi Bode: No conflict of interest Eckenberger, Julia: No conflict of interest Amamou, Asma: No conflict of interest Naranjo, Valery: No conflict of interest Grisan, Enrico: No conflict of interest Ghosh, Subrata: No conflict of interest