Association of Single-Nucleotide Polymorphisms With Chronic Rhinosinusitis in a Southwestern Han Chinese Population: A Replication Study
Bibliographic record
Abstract
Background Chronic rhinosinusitis (CRS) is a multifactorial inflammatory disease. The role of genetic variations of related genes in the development of CRS and severity of symptoms is unknown in Southwestern Chinese populations. Objective We selected candidate CRS-related genetic polymorphisms and evaluated the associations that were different according to the presence of nasal polyp, asthma, and allergic rhinitis (AR) in a Southwestern Chinese population. Detailed phenotypes were compared among different genotypes. Methods In 452 CRS patients and 591 healthy controls, clinico-epidemiological information was collected and 23 previously reported CRS-related single-nucleotide polymorphisms (SNPs) were genotyped. Genotypes were determined using a Sequenom MassARRAY SNP genotyping system. Clinical disease measures including the sinonasal outcome test, visual analogue scale (VAS), and symptom severity VAS were evaluated for each patient. The association between CRS, genotypes, asthma, AR, and symptoms was analyzed. The effect of sex, age, body mass index, and status of smoking was considered. Results Statistically significant genotypic association with CRS was observed with an IL1RL1 genetic polymorphism (rs13431828; odds ratio [OR] = 1.45; 95% confidence interval [CI], 1.06–1.99; P = .02). Similar association was observed with rs13431828 in subgroups of CRS with nasal polyps (OR = 1.53; 95% CI, 1.03–2.29; P = .04), asthma (OR = 2.08; 95% CI, 1.14–3.79; P = .02), and AR (OR = 1.59; 95% CI, 1.06–2.39; P = .02). No significant association with other SNPs was observed. The evaluated genetic polymorphisms were not associated with clinical symptom scores. Conclusion This study replicated rs13431828 as being associated with CRS in Southwestern Chinese. rs13431828 was also significantly associated with CRS patients who have concurrent allergic nasal diseases.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".