P006 Development of a Crohn's disease molecular activity score to identify region-specific chronically inflamed and non-inflamed processes
Bibliographic record
Abstract
Abstract Background Crohn’s disease (CD) is characterized by significant heterogeneity in disease location and other clinical factors, making it challenging to define the underlying molecular mechanisms associated with disease. Here, we provide a detailed molecular characterization of baseline ileal and colonic tissue from patients enrolled in the GALAXI Ph2b study of guselkumab in CD (NCT03466411) and explore the association of regional molecular profiles with endoscopic and histologic severity. Methods Baseline biopsies from 241 patients were obtained from rectum (R), splenic flexure (SF), and terminal ileum (TI). Paired biopsies within a region were processed for histology and RNA sequencing (RNAseq). Cell-type specific transcriptional modules were used to evaluate differential expression and to create a disease severity axis. Principal component analysis (PCA) was applied to modules with the highest correlation with paired Global Histologic Activity Scores (GHAS) per region and the resulting PC1 was used to define an objective tissue-based molecular activity score (MAS) to identify inflamed and uninflamed tissue. Inflamed tissue was used to assess regional molecular profiles which were correlated with paired regional histology scores defined by GHAS and endoscopic severity defined by Simple Endoscopic Score for CD (SES-CD). Results Modules specific to inflammatory myeloid and epithelial transcriptional states, and IL-23 and interferon response pathways, were highly correlated with paired GHAS. Applying this subset of modules as a MAS revealed a bimodal distribution of inflamed and non-inflamed biopsies. MAS identified 114/241 (47.3%), 85/229 (37.1%) and 114/229 (49.8%) inflamed biopsies in the R, SF, and TI, respectively. Regional molecular profiles of inflamed biopsies demonstrated increased mRNA expression of IL-23p19 (IL23A) and Fc-γ receptor 1 (CD64) (p<0.001), and enrichment of inflammatory modules across locations. Local MAS per region showed highest correlations with paired baseline GHAS, followed by SES-CD in the segment (Figure 1 and Table 1). Notably MAS provides higher resolution to identify representative biopsies for affected regions. Conclusion Application of the MAS to identify inflamed tissue enabled identification of key immune and inflammatory related processes across the ileum and colon that were associated with the IL-23 pathway, and baseline regional endoscopic and histologic severity. By identifying inflamed baseline samples, molecular changes associated with treatment can be more accurately defined in future analyses to better understand regional heterogeneity in CD.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".