Tumor Necrosis Factor Receptor Gene Polymorphisms in Crohn's Disease: Association with Clinical Phenotypes
Bibliographic record
Abstract
OBJECTIVES: Crohn's disease (CD) is a chronic multifactorial disorder with diverse clinical features that are influenced by a heterogeneous set of genetic factors. TNF-alpha/TNF receptor interactions play a pivotal role in the pathogenesis of the inflammatory response. Our purpose was to determine whether single nucleotide polymorphisms (SNPs) in the TNF receptors confer susceptibility to Crohn's disease and whether they are associated with clinical phenotype. METHODS: A cohort of 205 consecutively identified and unrelated patients with CD and 106 controls were recruited. Subjects were genotyped for polymorphisms in TNFRSF1A (position +36, -609), TNFRSF1B (+196, +1466), along with the three common CARD15 variants and phenotyped for disease behavior. Genotypic and allelic frequencies were compared between CD and controls and a logistic regression model was constructed to determine independent associations with specific clinical phenotypes. RESULTS: Only the TNFRSF1A +36 and TNFRSF1B +196 SNPs were associated with CD (p= 0.0019 and 0.034, respectively). The TNFRSF1A +36 mutation was negatively associated with stricturing disease phenotype (OR = 0.384; CI = 0.166-0.887). In contrast, the TNFRSF1B +196 was negatively associated with colitis (OR = 0.410; CI = 0.191-0.880). These associations were independent of CARD15 mutation status. Finally, TNFRSF1B +196 was negatively associated with surgery in CARD15 negative patients. CONCLUSIONS: These data constitute the first report of an association of TNFRSF1A and TNFRSF1B polymorphisms with CD in a Caucasian population and address the role of TNFR mutations in determining clinical heterogeneity 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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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".