Association Study of Genes Associated to Asthma in a Specific Environment, in an Asthma Familial Collection Located in a Rural Area Influenced by Different Industries
Bibliographic record
Abstract
Eight candidate genes selected in this study were previously associated with gene-environment interactions in asthma in an urban area. These genes were analyzed in a familial collection from a founder and remote population (Saguenay-Lac-Saint-Jean; SLSJ) located in an area with low air levels of ozone but with localized areas of relatively high air pollutant levels, such as sulphur dioxide, when compared to many urban areas. Polymorphisms (SNPs) were extracted from the genome-wide association study (GWAS) performed on the SLSJ familial collection. A transmission disequilibrium test (TDT) was performed using the entire family sample (1,428 individuals in 254 nuclear families). Stratification according to the proximity of aluminium, pulp and paper industries was also analyzed. Two genes were associated with asthma in the entire sample before correction (CAT and NQO1) and one was associated after correction for multiple analyses (CAT). Two genes were associated when subjects were stratified according to the proximity of aluminium industries (CAT and NQO1) and one according to the proximity of pulp and paper industries (GSTP1). However, none of them resisted correction for multiple analyses. Given that the spatial pattern of environmental exposures can be complex and inadequately represented by a few stationary monitors and that exposures can also come from sources other than the standard outdoor air pollution (e.g., indoor air, occupation, residential wood smoke), a new approach and new tools are required to measure specific and individual pollutant exposures in order to estimate the real impact of gene-environment interactions on respiratory health.
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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 | 0.001 | 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".