Defining the Pre-clinical state of Crohn's Disease as a Window into Pathogenesis
Bibliographic record
Abstract
Introduction: Despite advances in understanding mechanisms underlying mucosal inflammation, we are still unable to identify the cause of inflammatory bowel disease (IBD). We aimed to identify the risk factors and develop multi-dimensional risk models defining the future risk of Crohn’s disease (CD) in a cohort of healthy at-risk individuals. Methods: As part of the global multicenter Crohn’s Colitis Canada Genetic Environmental Microbial (CCC-GEM) Project, more than 5000 healthy first-degree relatives (FDRs) of patients with CD were prospectively followed until CD development. Cox-proportional hazards models, conditional logistic regression models (for the nested case-control cohort) and random survival forest (RSF) models were used to assess the association of baseline variables with future risk of CD. Results: Increased intestinal permeability was associated with increased risk of CD (hazard ratio 3.03, 95% confidence interval 1.64-5.63, p=3.97x10-4, as defined by urinary fractional excretion of mannitol to lactulose ratio≥0.03 vs <0.03). Also, increased serum anti-microbial antibodies were associated with increased risk of CD development (adjusted odds ratio 6.5, 95% CI 3.4-12.7, p<0.001, 2-6 vs 0-1 positive antibodies); this association remained significant when adjusted for other CD-risk markers (i.e., gut barrier function, fecal calprotectin, C-reactive protein, and CD-polygenic risk score). Using 16s rRNA sequencing, a microbiome composition-based risk score that was developed using a RSF model showed a significant association with risk of CD (HR 2.34, 95% CI 1.04-5.27 p=0.039, 4th quartile vs 1st-3rd quartile) in the validation cohort. Lastly, a multidimensional integrative risk score (GEM-IRS) that combined demographic information, biomarkers of subclinical inflammation, gut barrier function, microbial composition and imputed microbial function was significantly associated with onset of CD (HR 2.67 per SD, 95% CI 2.06-3.53) in the validation cohorts; the association remained significant even in subgroups with minimal subclinical inflammation, normal barrier function, and in a subset of FDRs with more than 7 years before diagnosis. Conclusions: In a healthy at-risk population, we show evidence that impaired gut barrier function, increased anti-microbial immune response, altered microbial composition/functions are associated with increased risk of CD onset. Importantly, integrating these multi-dimensional risk factors enables early stratification of individuals’ future risk of developing CD among healthy FDRs.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".