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IBDome: An integrated molecular, histopathological, and clinical atlas of inflammatory bowel diseases

Plattner, C.; Sturm, G.; Kuehl, A. A.; Atreya, R.; Carollo, S.; Gronauer, R.; Rieder, D.; Guenther, M.; Ormanns, S.; Manzl, C.; Meneghetti, A. R.; Hegazy, A.; Patankar, J.; Carrero, Z. I.; TRR241 IBDome Consortium, ; Neurath, M. F.; Kather, J. N.; Becker, C.; Siegmund, B.; Trajanoski, Z.

2025-03-26 molecular biology
10.1101/2025.03.26.645544 bioRxiv
Show abstract

Multi-omic and multimodal datasets with detailed clinical annotations offer significant potential to advance our understanding of inflammatory bowel diseases (IBD), refine diagnostics, and enable personalized therapeutic strategies. In this multi-cohort study, we performed an extensive multi-omic and multimodal analysis of 1,002 clinically annotated patients with IBD and non-IBD controls, incorporating whole-exome and RNA sequencing of normal and inflamed gut tissues, serum proteomics, and histopathological assessments from images of H&E-stained tissue sections. Transcriptomic profiles of normal and inflamed tissues revealed distinct site-specific inflammatory signatures in Crohns disease (CD) and ulcerative colitis (UC). Leveraging serum proteomics, we developed an inflammatory protein severity signature that reflects underlying intestinal molecular inflammation. Furthermore, foundation model-based deep learning accurately predicted histologic disease activity scores from images of H&E-stained intestinal tissue sections, offering a robust tool for clinical evaluation. Our integrative analysis highlights the potential of combining multi-omics and advanced computational approaches to improve our understanding and management of IBD.

Published in Gastroenterology (predicted rank #13) · training set

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