A148 <i>NOD2</i> LIGAND AND PEPTIDOGLYCAN HYDROLASE GENE ABUNDANCES ARE ALTERED IN PRE-CROHN’S DISEASE
Bibliographic record
Abstract
Abstract Background Crohn’s disease (CD) is a chronic disorder of unknown etiology. Genome-wide association studies have revealed that NOD2 loss of function mutations are an important gene contributor to CD pathogenesis. NOD2 is a pattern recognition receptor that responds to phosphorylated muramyl-dipeptide (MDP), whose production from peptidoglycan (PGN) is dependent on the expression of specific microbial hydrolases in the lumen. While a variety of studies have shown that reductions in NOD2 ligand and corresponding hydrolases, particularly DL-endopeptidases, occur in active CD or as a consequence of inflammation, which may play a role in sustaining disease, the interplay between NOD2 ligands and PGN-hydrolases pre-disease is unknown. Aims We investigated whether stool NOD2 ligand concentration is altered in pre-CD individuals, and the associations of PGN-hydrolase abundances with NOD2 ligand and with other pre-disease biomarkers. Methods Fecal samples were collected from healthy first-degree relatives of CD patients who were followed prospectively as part of the CCC-GEM project nested case control cohort (n = 91 pre-CD, n = 242 matched controls, median time to diagnosis 3.2 years). Fecal calprotectin (FCP), urinary fractional excretion ratio of lactulose to mannitol (LMR), and C-reactive protein (CRP) from serum were measured. PGN-hydrolase gene abundances was assessed by shotgun sequencing of stool samples. NOD2 ligand abundance was measured by incubating diluted stool supernatant with human NOD2 reporter HEK293 cells overnight then measuring OD640. A database of PGN-hydrolase clusters was generated by sequentially clustering with MMseqs2 based on sequence identity, then with Foldseek based on the AlphaFold Protein Structure Database. Results NOD2 ligand concentration was significantly reduced in pre-CD compared to matched controls (p < 0.01). Although several PGN-hydrolase clusters were negatively associated with NOD2 ligand, the relative abundance of one DL-endopeptidase cluster expressed by the Firmicutes phylum was significantly positively associated with NOD2 ligand abundance (q < 0.05). A DD-carboxypeptidase cluster, an amidase cluster, and a muramidase cluster were each negatively associated with future diagnosis of CD (q < 0.05). While many clusters were positively and negatively associated with FCP and CRP, one DD-carboxypeptidase cluster was positively associated with LMR (gut barrier permeability, q < 0.05). Conclusions These results show that NOD2 ligand concentration and the PGN-hydrolases that produce it are altered in pre-CD stool, suggesting that this may contribute to disease onset, however further investigation is needed. Funding Agencies CCC, CIHRHelmsley Charitable Trust, Mount Sinai Hospital
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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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".