CTNNA3 (α-Catenin) Gene Variants Are Associated With Diisocyanate Asthma: A Replication Study in a Caucasian Worker Population
Bibliographic record
Abstract
Recently, a genome-wide association study (GWAS) conducted in Korean subjects identified four CTNNA3 (alpha-T catenin) single nucleotide polymorphisms (SNPs) (rs10762058, rs7088181, rs1786929, and rs4378283) associated with diisocyanate-induced occupational asthma (DA). The CTNNA3 gene codes for a cadherin involved in formation of stretch-resistant cell-cell adhesions. We conducted a candidate gene association study to replicate these findings in Caucasian workers. Genotyping was performed on DNA using a 5' nuclease PCR assay collected from 410 diisocyanate-exposed and predominantly Canadian workers including 132 workers with DA confirmed by a specific inhalation challenge (DA+); 131 symptomatic workers in whom DA was excluded by a negative challenge (DA-); and 147 hexamethylene diisocyanate-exposed asymptomatic workers (AWs). As in the Korean study, highly linked CTNNA3 rs7088181 and rs10762058 SNPs (but not rs4378283 and rs1786929) were significantly associated with DA+ when compared with AWs but not in comparison with DA- workers (p ≤ 0.05). After adjusting for potentially confounding variables of age, smoking status, and duration of exposure, minor allele homozygotes of rs7088181 and rs10762058 SNPs were at increased risk for DA compared with AWs (OR = 9.05 [95% CI: 1.69, 48.54] and OR = 6.82 [95% CI: 1.65, 28.24], respectively). In conclusion, we replicated results from the only reported GWAS study of DA demonstrating an association between two closely linked CTNNA3 gene SNPs and DA. These findings lend further support to the clinical relevance of these genotypes in predicting susceptibility to DA and the potential importance of catenins in the disease process.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.001 | 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".