Metabolomics reveal distinct molecular pathways associated with future risk of Crohn’s Disease
Bibliographic record
Abstract
Host - microbiome interactions are central to Crohn'sdisease (CD) pathogenesis; yet the early metabolic alterations that precededisease onset remain poorly defined. To explore preclinical metabolicsignatures of CD, we analyzed baseline serum metabolomic profiles in a nestedcase-control study within the Crohn's and Colitis Canada - Genetics, Environment, Microbiome (CCC-GEM) Project, a prospective cohort of 5,122 healthyfirst-degree relatives (FDRs) of CD patients. We included 78 individuals wholater developed CD and 311 matched FDRs who remained disease-free. In an untargetedassessment of metabolomic data, we identified 63 metabolites significantlyassociated with future CD risk. Integrative analyses further identifiedmultiple associations between CD-related metabolites and proteomic markers, gutmicrobiome composition, antimicrobial antibody, fecal calprotectin andC-reactive protein. Quinolinate, a tryptophan catabolite, was elevated inindividuals who later developed CD and showed strong positive correlations withC-reactive protein, fecal calprotectin, and C-X-C motif chemokine ligand 9 (CXCL9).In contrast, higher levels of ascorbate and isocitrate were associated withreduced CD risk and were negatively correlated with C-reactive protein and CD-associated proteins.These findings identify several distinct molecular pathways that contribute toCD pathogenesis.
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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 | 0.001 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 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".