Polymorphisms in the SERPINA1 (Alpha-1-Antitrypsin) Gene are Associated with Severe Chronic Rhinosinusitis Unresponsive to Medical Therapy
Bibliographic record
Abstract
BACKGROUND: Alpha-1-antitrypsin (AAT) is a serine protease inhibitor that blocks the protease, neutrophil elastase. Previous population studies have suggested that heterozygote status for the AAT gene (SERPINA1) is a risk factor for chronic rhinosinusitis with nasal polyposis (CRSwNP). This implies a potential genetic predisposition to CRS tied to AAT deficiency. The purpose of this study was to investigate the association between single nucleotide polymorphisms (SNPs) in the SERPINA1 gene and CRS. METHODS: DNA extracted from a population of 206 patients diagnosed with CRSwNPs and 196 postal code-matched controls was used. A maximally informative set of tagging SNPs from SERPINA1 on chromosome 14q were selected from the HapMap data set (International HapMap Consortium, Nature 437:1299-1320, 2005) and genotyped on the Sequenom platform (Sequenom, San Diego, CA). RESULTS: Successful genotyping was performed for 32 of 33 SNPs. Two SNPs (rs1243168 and rs4900229) located upstream of the SERPINA1gene, were associated with CRS. Individuals homozygous (TT) for these SNPs had an increased probability of having CRS with an odds ratio of 5.95 and 1.49, respectively. Subgroup analysis according to severity of disease identified each SNP to be increasingly common in individuals as disease severity increased (p < 0.001). These individuals were also less likely to be responsive to medical therapy (p < 0.001). CONCLUSION: Polymorphisms of the SERPINA1 gene are associated with clinically severe CRS. These results, from a small subset of individuals with CRS, suggest that defects in AAT may be implicated in a subset of individuals unresponsive to conventional therapy and suggests that alternate therapies may be required for their management.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".