Interferon-γ Promoter Is Hypermethylated in Blood DNA from Workers with Confirmed Diisocyanate Asthma
Bibliographic record
Abstract
Risk factors have not been identified that determine susceptibility for development of diisocyanate-induced occupational asthma (DA). We hypothesized that diisocyanate (DI) exposure could modify gene promoter regions regulating transcription of cytokine mediators and thereby influence expression of DA. A cross-sectional study was designed to investigate the promoter methylation status of candidate genes in DI-exposed workers. Subjects consisted of 131 workers in three groups: 40 cases with DA confirmed by a positive specific inhalation challenge (SIC) (DA+), 41 exposed workers with lower respiratory symptoms and negative SIC (DA-), and 50 asymptomatic exposed workers (AWs). We studied four candidate genes (GSTM1, DUSP22, IFN-γ, and IL-4) for which altered promoter methylation has been previously investigated for relationships with a variety of other environmental exposures. Methylation status was determined using methylation-specific quantitative PCR performed on genomic DNA extracted from whole blood. Results showed that relative methylation of IFN-γ promoter was significantly increased in DA+ in comparison with both comparator groups (DA- and AW), and it exhibited good sensitivity (77.5%) and specificity (80%) for identifying DA workers in a multivariate predictive model after adjusting for type of DI exposure, smoking status, methacholine PC₂₀, and gender. IL-4 promoter was slightly less methylated only in DA+ compared with AW among nonsmoking workers. Both GSTM1 and DUSP22 promoter methylations were found not associated with DA. Our finding suggests that exposure to occupational chemicals could play a heretofore undefined mechanistic role via epigenetic modification of specific genes in the promoter region.
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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 | 0.000 | 0.001 |
| 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 | 0.000 |
| 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".