DOP133 Spatiotemporal analysis of Crohn’s disease reveals PECAM2 signaling at the basis of inflammation-to-fibrosis transition
Bibliographic record
Abstract
Abstract Background Crohn’s disease is a chronic inflammatory disease of the bowel often complicated by fibrotic strictures(1,2,3). Medical treatment is lacking, and surgery is commonly required(3). The mechanisms underlying the progression from chronic inflammation to fibrosis are not yet defined. We aim to unravel Crohn’s disease pathogenesis using cutting-edge computational and bioinformatics tools (Figure 1). Methods Spatial transcriptomics was performed on 13 surgical specimens of inflamed and fibrotic Crohn’s disease and healthy controls. Spatial transcriptomics results were integrated with single-cell data to track the cellular and molecular evolution from healthy intestine to fibrosis by employing CellChat(4) and pseudotime analysis. Computational data were confirmed by immunostaining of tissues from an independent cohort of Crohn’s patients. Results We demonstrated that intestinal cytoarchitecture was rearranged while chronic inflammation progressed. Crohn’s disease-associated fibrosis evolved within the mesenchymal compartment, driven by PECAM2 signaling through PECAM1-CD38 interaction. Notably, CD38 positivity was found in the mesenchymal compartment in an independent cohort of Crohn’s disease patients. In parallel, ApoA signaling, particularly APOA1-ABCA interaction, emerged as relevant for maintaining epithelial and stromal homeostasis, while its downregulation was associated with fibrosis development (Figure 2). Conclusion Our results provide insights into CD38-driven fibrosis and suggest that PECAM2 signaling blockade could reduce the development of strictures in patients with Crohn’s disease, potentially offering a new treatment target. References 1.Torres J, Mehandru S, Colombel J-F, et al. Crohn’s disease. Lancet 2017;389:1741–1755. 2.Lichtenstein GR, Loftus EV, Isaacs KL, et al. ACG clinical guideline: management of crohn’s disease in adults. Am. J. Gastroenterol. 2018;113:481–517. 3.Rieder F, Kessler S, Sans M, et al. Animal models of intestinal fibrosis: new tools for the understanding of pathogenesis and therapy of human disease. Am. J. Physiol. Gastrointest. Liver Physiol. 2012;303:G786-801. 4.Jin S, Plikus MV, Nie Q. CellChat for systematic analysis of cell-cell communication from single-cell and spatially resolved transcriptomics. BioRxiv 2023.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".