Epigenome‐Wide Association Study of Asthma Exacerbations in Europeans
Bibliographic record
Abstract
ABSTRACT Background Asthma exacerbations (AEs) represent the major contributor to the global asthma burden. Although genetic and environmental factors have been associated with AEs, the role of epigenetics remains uncovered. Objective This study aimed to identify whole blood DNA methylation (DNAm) markers associated with AEs in Europeans. Methods DNAm was assessed in 406 blood samples from Spanish individuals using the Infinium MethylationEPIC microarray (Illumina). An epigenome‐wide association study was conducted to test the association of DNAm with AEs at differentially methylated positions, regions, and epigenetic modules. CpGs suggestively associated with AEs (false discovery rate [FDR] < 0.1) were followed up for replication in 222 European individuals, and the genome‐wide significance ( p < 9 × 10 −8 ) was declared after meta‐analyzing the discovery and replication samples. Additional assessment was performed using nasal tissue DNAm data from 155 Spanish individuals. The effects of genetic variation on DNAm were assessed through cis‐methylation quantitative trait loci (meQTL) analysis. Enrichment analyses of previous EWAS signals were conducted. Results Four CpGs were associated with AEs, and two were replicated and reached genomic significance in the meta‐analysis (annotated to ZBTB16 and BAIAP2 ). Of those, CpG cg25345365 ( ZBTB16 ) was cross‐tissue validated in nasal epithelium ( p = 0.003) and associated with five independent meQTLs (FDR < 0.05). Additionally, four differentially methylated regions and one module were significantly associated with AEs. Enrichment analyses revealed an overrepresentation of prior epigenetic associations with prenatal and environmental exposures, immune‐mediated diseases, and mortality. Conclusions DNAm in whole blood and nasal samples may contribute to AEs in Europeans, capturing genetic and environmental risk factors.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".