Genetic Variants in Antioxidant Genes Are Associated With Diisocyanate-Induced Asthma
Bibliographic record
Abstract
Diisocyanates are a common cause of occupational asthma, but risk factors are not well defined. A case-control study was conducted to investigate whether genetic variants of antioxidant defense genes, glutathione S-transferases (GSTM1, GSTT1, GSTM3, GSTP1), manganese superoxide dismutase (SOD2), and microsomal epoxide hydrolase (EPHX1) are associated with increased susceptibility to diisocyanate-induced asthma (DA). The main study population consisted of 353 Caucasian French-Canadians from among a larger sample of 410 diisocyanate-exposed workers in three groups: workers with specific inhalation challenge (SIC) confirmed DA (DA(+), n = 95); symptomatic diisocyanate workers with a negative SIC (DA(-), n = 116); and asymptomatic exposed workers (AW, n = 142). Genotyping was performed on genomic DNA, using a 5'-nuclease PCR assay. The SOD2 rs4880, GSTP1 rs1695, and EPHX1 rs2740171 variants were significantly associated with DA in both univariate and multivariate analyses. In the first logistic regression model comparing DA(+) and DA(-) groups, SOD2 rs4880, GSTM1 (null), GSTP1 rs762803, and EPHX1 rs2854450 variants were associated with DA (p = 0.004, p = 0.047, p = 0.021, p <0.001, respectively). Genotype combinations GSTT1*GSTP1 rs762803, GSTM1*EPHX1 rs2854450, EPHX1 rs2740168*EPHX1 rs1051741, and GSTP1 rs762803*EPHX1 rs2740168 were also associated with DA in this model (p = 0.027, p = 0.002, p = 0.045, p = 0.044, respectively). The GSTP1 rs1695 and EPHX1 rs1051741 and rs2740171 variants showed an association with DA in the second model comparing DA(+) and AW groups (p = 0.040, p = 0.019, p = 0.002, respectively). The GSTM3 rs110913*EPHX1 rs1051741 genotype combination was also associated with DA under this model (p = 0.042). The results suggest that variations in SOD2, GST, and EPHX1 genes and their interactions contribute to DA susceptibility.
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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 | 0.001 |
| 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) | 0.000 | 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".