Shared DNA methylation signatures in childhood allergy: The MeDALL study
Bibliographic record
Abstract
BACKGROUND: Differential DNA methylation associated with allergy might provide novel insights into the shared or unique etiology of asthma, rhinitis, and eczema. OBJECTIVE: We sought to identify DNA methylation profiles associated with childhood allergy. METHODS: Within the European Mechanisms of the Development of Allergy (MeDALL) consortium, we performed an epigenome-wide association study of whole blood DNA methylation by using a cross-sectional design. Allergy was defined as having symptoms from at least 1 allergic disease (asthma, rhinitis, or eczema) and positive serum-specific IgE to common aeroallergens. The discovery study included 219 case patients and 417 controls at age 4 years and 228 case patients and 593 controls at age 8 years from 3 birth cohorts, with replication analyses in 325 case patients and 1111 controls. We performed additional analyses on 21 replicated sites in 785 case patients and 2124 controls by allergic symptoms only from 8 cohorts, 3 of which were not previously included in analyses. RESULTS: We identified 80 differentially methylated CpG sites that showed a 1% to 3% methylation difference in the discovery phase, of which 21 (including 5 novel CpG sites) passed genome-wide significance after meta-analysis. All 21 CpG sites were also significantly differentially methylated with allergic symptoms and shared between asthma, rhinitis, and eczema. The 21 CpG sites mapped to relevant genes, including ACOT7, LMAN3, and CLDN23. All 21 CpG sties were differently methylated in asthma in isolated eosinophils, and 10 were replicated in respiratory epithelium. CONCLUSION: Reduced whole blood DNA methylation at 21 CpG sites was significantly associated with childhood allergy. The findings provide novel insights into the shared molecular mechanisms underlying asthma, rhinitis, and eczema.
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 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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".