CARD15 and HLA DRB1 Alleles Influence Susceptibility and Disease Localization in Crohn's Disease
Bibliographic record
Abstract
OBJECTIVES: Crohn's disease (CD) is a chronic inflammatory disease of the gut associated with allelic variants of CARD15 and HLA-DRB1 genes. We investigated the prevalence and effects of these variants in a Canadian CD cohort. METHODS: 507 unrelated CD patients were genotyped for the three major CD-associated variants (Arg702Trp, Gly908Arg, and Leu1007fsinsC) and for thirteen HLA-DRB1 alleles. RESULTS: At least one CARD15 variant was present in 32.5% of the CD patients compared with 20% of controls. The prevalence of CARD15 mutation was similar in both sporadic and familial and Jewish and non-Jewish CD patients. The Gly908Arg variant was significantly higher and the Arg702Trp variant significantly lower in Jewish compared to non-Jewish patients. A positive association between the HLA-DRB1*0103 allele and CD was detected in non-Jewish, familial cases (p = 0.0002), with risk for CD increased by 6.7 fold by the presence of an HLA-DRB1*0103 allele as compared to 1.9 fold and 19 fold by a single or two CARD15 variant alleles, respectively. We show a significant association of ileal involvement with CARD15 variants (OR = 1.8; p = 0.02), HLA-DRB1*0701 (OR = 1.9; p = 0.006) and DRB1*04 (OR = 1.7; p = 0.02) alleles and demonstrate the capacity of combined CARD15 and HLA-DRB1 genotyping to predict ileal disease in CD patients. By contrast, the HLA-DRB1*0103 allele was associated with later age of diagnosis (p = 0.02) and pure colonic disease (p = 0.000013). CONCLUSIONS: These observations confirm the influence of CARD15 and HLA-DRB1 alleles on both CD susceptibility and site of disease and identify genotyping of these variants as a potential tool for improved diagnosis and risk prediction 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 | 0.000 | 0.002 |
| 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 | 0.001 | 0.000 |
| 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".