Genome‐wide interaction study of early‐life smoking exposure on time‐to‐asthma onset in childhood
Bibliographic record
Abstract
Abstract Background Asthma, a heterogeneous disease with variable age of onset, results from the interplay between genetic and environmental factors. Early‐life tobacco smoke (ELTS) exposure is a major asthma risk factor. Only a few genetic loci have been reported to interact with ELTS exposure in asthma. Objective Our aim was to identify new loci interacting with ELTS exposure on time‐to‐asthma onset (TAO) in childhood. Methods We conducted genome‐wide interaction analyses of ELTS exposure on time‐to‐asthma onset in childhood in five European‐ancestry studies (totalling 8273 subjects) using Cox proportional‐hazard model. The results of all five genome‐wide analyses were meta‐analysed. Results The 13q21 locus showed genome‐wide significant interaction with ELTS exposure ( P = 4.3 × 10 −8 for rs7334050 within KLHL1 with consistent results across the five studies). Suggestive interactions ( P < 5 × 10 −6 ) were found at three other loci: 20p12 (rs13037508 within MACROD2 ; P = 4.9 × 10 −7 ), 14q22 (rs7493885 near NIN ; P = 2.9 × 10 −6 ) and 2p22 (rs232542 near CYP1B1 ; P = 4.1 × 10 −6 ). Functional annotations and the literature showed that the lead SNPs at these four loci influence DNA methylation in the blood and are located nearby CpG sites reported to be associated with exposure to tobacco smoke components, which strongly support our findings. Conclusions and Clinical Relevance We identified novel candidate genes interacting with ELTS exposure on time‐to‐asthma onset in childhood. These genes have plausible biological relevance related to tobacco smoke exposure. Further epigenetic and functional studies are needed to confirm these findings and to shed light on the underlying mechanisms.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 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) | 0.002 | 0.001 |
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; both teacher heads agree on what is shown here.
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".