Interaction between the<i>DNAH9</i>gene and early smoke exposure in bronchial hyperresponsiveness
Bibliographic record
Abstract
A previous genome-wide linkage scan of bronchial hyperresponsiveness (BHR) in the French Epidemiological study on the Genetics and Environment of Asthma (EGEA) families, performed in the presence of a gene×early-life environmental tobacco smoke (ETS) exposure interaction, showed the strongest interaction in the 17p11 region where linkage was detected only among unexposed siblings. Our goal was to conduct fine-scale mapping of 17p11 to identify single nucleotide polymorphisms (SNPs) interacting with ETS that influence BHR.Analyses were performed in 388 French EGEA asthmatic families, using a two-step strategy: 1) selection of SNPs displaying family-based association test (FBAT) association signals (p≤0.01) with BHR in unexposed siblings, and 2) a FBAT homogeneity test between exposed and unexposed siblings plus a robust log-linear interaction test.A single SNP reached the threshold (p≤3×10(-3)) for significant interaction with ETS using both interaction tests, after accounting for multiple testing. Results were replicated in 253 French-Canadian families, but not in 341 UK families, probably due in part to differences in phenotypic features between datasets.The SNP showing significant interaction with ETS belongs toDNAH9(dynein, axonemal, heavy chain 9), a promising candidate gene involved in respiratory cilia mobility and associated with primary ciliary dyskinesia, a disease associated with abnormalities of pulmonary function.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".