Evidence of Association of Interleukin-1 Receptor-Like 1 Gene Polymorphisms with Chronic Rhinosinusitis
Bibliographic record
Abstract
BACKGROUND: Chronic rhinosinusitis (CRS) is a common complex respiratory disease, with a potential genetic component to its development. The protein encoded by the Interleukin-1 receptor-like 1 (IL1RL1) gene is an important effector molecule of T-helper type 2 responses and may potentially be involved in the persistent inflammatory process observed in CRS. We investigated whether certain polymorphisms in the IL1RL1 gene are differentially present in patients with surgery-unresponsive CRS and in control subjects. METHODS: DNA extracted from an existing population of 206 adult patients with surgery-unresponsive CRS and 196 postal-code-matched controls was used. A set of 15 tagging single nucleotide polymorphisms (SNPs) was selected from the HapMap data set and genotyped. DNA sequencing was performed in a subgroup of 15 CRS patients. RESULTS: Statistically significant allelic associations with CRS were noted for 5 SNPs (rs10204137, p = 0.04; rs10208293, p = 0.03; rs13431828, p = 0.008; rs2160203, p = 0.03, and rs4988957, p = 0.03). The analysis showed a consistent significant protective effect against CRS for all the SNPs, yielding an odds ratio (OR) ranging from 0.56 to 0.72. The loci rs13431828 showed the highest association with CRS (p = 0.008; OR = 0.56; 95% CI, 0.36-0.86). A subanalysis revealed that the observed associations were stronger among patients with more severe disease. Sequencing identified five additional known nonsynonymous coding SNPs in linkage disequilibrium with genotyped SNPs. CONCLUSION: Pending replication of these results, this study suggests that polymorphisms within the IL1RL1 gene may be associated with CRS, conferring a protective effect, particularly among those with severe disease.
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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 | 0.004 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".