Epigenome-wide association study of asthma and wheeze characterizes loci within HK1
Bibliographic record
Abstract
To identify novel epigenetic markers of adolescent asthma and replicate findings in an independent cohort, then explore whether such markers are detectable at birth, predictive of early-life wheeze, and associated with gene expression in cord blood. We performed epigenome-wide screening with recursive random forest feature selection and internal validation in the IOW birth cohort. We then tested whether we could replicate these findings in the independent cohort ALSPAC and followed-up our top finding with children of the IOW cohort. We identified 10 CpG sites associated with adolescent asthma at a 5% false discovery rate (IOW, n = 370), five of which exhibited evidence of associations in the replication study (ALSPAC, n = 720). One site, cg16658191, within HK1 displayed particularly strong associations after cellular heterogeneity adjustments in both cohorts (OR IOW = 0.17, 95% CI 0.04–0.57) (OR ALSPAC = 0.57, 95% CI 0.38–0.87). Additionally, higher expression of HK1 (OR = 3.81, 95% CI 1.41–11.77) in cord blood was predictive of wheezing in infancy (n = 82). We identified novel associations between asthma and wheeze with methylation at cg16658191 and the expression of HK1 , which may serve as markers of, predictors of, and potentially etiologic factors involved in asthma and early life wheeze.
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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 | 0.001 |
| 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 | 0.000 |
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".