Spatiotemporal analysis of Crohn’s disease reveals PECAM2 signaling at the basis of the inflammation-to-fibrosis transition
Bibliographic record
Abstract
BACKGROUND AND AIMS: Crohn's disease (CD) is a chronic inflammatory disease of the bowel, often complicated by fibrotic strictures, for which medical treatment is lacking, and surgery is commonly required. The mechanisms underlying the progression from chronic inflammation to fibrosis are not yet defined. We aim to unravel CD pathogenesis using a cutting-edge computational pipeline combining several available tools. METHODS: Spatial transcriptomics was performed on 13 surgical specimens, including inflamed and fibrotic CD tissues and healthy controls. The resulting spatial data were integrated with single-cell RNA sequencing to trace the cellular and molecular transitions from healthy intestine to fibrotic tissue. Ligand-receptor interaction and pseudotime analyses were employed to infer dynamic cell-cell communication networks and lineage trajectories. Key computational findings were validated through immunostaining in an independent cohort of CD patients. Finally, the therapeutic relevance of the identified target was evaluated in a TNBS-induced chronic colitis mouse model upon CD38 inhibitor administration. RESULTS: We demonstrated that intestinal cytoarchitecture was rearranged while chronic inflammation progressed. CD-associated fibrosis evolved within the mesenchymal compartment, driven by PECAM2 signaling through the PECAM1-CD38 interaction. In parallel, ApoA signaling, particularly the APOA1-ABCA interaction, emerged as relevant for maintaining epithelial and stromal homeostasis, while its downregulation was associated with fibrosis development. Moreover, inhibition of CD38 signaling effectively reduced colitis symptoms and colon thickening in the experimental TNBS-induced model of chronic inflammation. CONCLUSIONS: Our results provide insights into CD38-driven fibrosis and indicate that blockade of PECAM2 signaling could reduce the development of strictures in patients with CD, potentially offering a new treatment target.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".