Evidence of allelic heterogeneity for associations between the <i>NOD2/CARD15</i> gene and ulcerative colitis among North Indians
Bibliographic record
Abstract
BACKGROUND: Three common disease susceptibility variants in the NOD2 gene are associated with inflammatory bowel disease in Caucasians, but not in Asians. Aim To screen for NOD2 variants and examine susceptibility for inflammatory bowel disease in North Indians. METHODS: A case-control study was carried out in Punjab, India. Confirmed cases of ulcerative colitis and Crohn's disease and healthy controls matched for age (+/-10 years) and ethnicity were studied. Besides genotyping the three disease susceptibility variants (SNP8, SNP12 and SNP13), all 12 exons were resequenced to determine other potential single nucleotide polymorphisms. RESULTS: Two hundred and ninety-eight ulcerative colitis, 25 Crohn's disease and 262 controls were investigated. Median age (range) at diagnosis was 39 (7-78) years for ulcerative colitis and 40 (32-58) years for Crohn's disease. All three disease susceptibility variants were either monomorphic or rare in the population. Sequencing (n = 30) revealed two single nucleotide polymorphisms: SNP5 (268 Pro/Ser) and rs2067085 (178 Ser/Ser). The frequency of SNP5 was higher among ulcerative colitis (17% vs. 12% in controls, P = 0.016) and Crohn's disease cases (20% vs. 12%, P = 0.28). SNP5 carriers had elevated risks for ulcerative colitis (OR = 1.72, 95% CI = 1.17-2.52, P = 0.005). CONCLUSIONS: The absence of known inflammatory bowel disease susceptibility variants and potential associations between SNP5 and ulcerative colitis in North Indians suggests the presence of allelic heterogeneity for ulcerative colitis susceptibility.
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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 | 0.002 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".