TRAFFIC-RELATED AIR POLLUTION, CHILDHOOD ASTHMA AND THE INFLUENCE OF CANDIDATE GENES INVOLVED IN OXIDATIVE STRESS
Bibliographic record
Abstract
Background and Aims: We combined previously collected data from two Canadian and four European birth cohorts to examine whether exposure to traffic-related air pollution interacts with a child’s genetic profile to impact their risk of developing asthma. Methods: Logistic regression was used to evaluate the association between traffic-related NO2 (land use regression or dispersion model) and physician-diagnosed asthma or parent reported ‘ever wheeze’ at school age, stratified by glutathione S-transferase P1 (GSTP1) and tumor necrosis factor (TNF) genotypes. Interaction terms were included to test for interaction between genotype and NO2 in models for asthma and wheeze. Analyses were adjusted for gender, cohort, city, maternal age, parental atopic disease, and environmental tobacco smoke exposure (and intervention status for relevant studies). Results: The combined dataset contained information for 4,902 children (380 asthma cases; 2,182 wheeze cases) and included three single-nucleotide polymorphisms (SNPs): rs1799811 (GSTP1; C>T114), rs947894 (GSTP1; A>G105) and rs1800629 (TNF; G>A308). Pooled estimates for asthma by rs1799811 were elevated for carriers of the minor (CT,TT) alleles [OR per 10 µg/m3of NO2: 2.12(95%CI: 1.12-4.00)] but not for major (CC) allele carriers [1.12(0.80-1.56)]. Accordingly, the interaction between rs1799811 and NO2 was statistically significant (p-value=0.012) for asthma. The estimates for asthma for the remaining two SNPs were not statistically significant and interactions for both were also non-significant (p-value=0.152 for rs947894 and 0.051 for 1800629). Pooled estimates for wheeze, stratified by allele, were not statistically significant for any of the SNPs considered. Interactions for the GSTP1 SNPs were not statistically significant in models for wheeze (p-value=0.889 for rs1799811 and 0.819 for rs947894), but the interaction for rs1800629 was significant (p-value=0.008). Conclusions: In the largest study of its kind to date, we find that children with the rs1799811 minor alleles are at increased risk for developing asthma when exposed to traffic-related air pollution.
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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 | 0.001 | 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 | 0.000 |
| 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".