Novel insights into the whole-blood DNA methylome of asthma in ethnically diverse children and youth
Bibliographic record
Abstract
Background The epigenetic mechanisms of asthma remain largely understudied in African Americans and Hispanics/Latinos, two populations disproportionately affected by asthma. We aimed to identify markers, regions and processes with differential patterns of DNA methylation (DNAm) in whole blood by asthma status in ethnically diverse children and youth, and to assess their functional consequences. Methods DNAm levels were profiled with the Infinium MethylationEPIC or HumanMethylation450 BeadChip arrays among 1226 African Americans or Hispanics/Latinos and assessed for differential methylation per asthma status at the CpG and region (differentially methylated region (DMR)) level. Novel associations were validated in blood and/or nasal epithelium from ethnically diverse children and youth. The functional and biological implications of the markers identified were investigated by combining epigenomics with transcriptomics from study participants. Results 128 CpGs and 196 DMRs were differentially methylated after multiple testing corrections, including 92.3% and 92.8% novel associations, respectively. 41 CpGs were replicated in other Hispanics/Latinos, prioritising cg17647904 ( NCOR2 ) and cg16412914 ( AXIN1 ) as asthma DNAm markers. Significant DNAm markers were enriched in previous associations for asthma, fractional exhaled nitric oxide, bacterial infections, immune regulation or eosinophilia. Functional annotation highlighted epigenetically regulated gene networks involved in corticosteroid response, host defence and immune regulation. Several implicated genes are targets for approved or experimental drugs, including TNNC1 and NDUFA12 . Many differentially methylated loci previously associated with asthma were validated in our study. Conclusions We report novel whole-blood DNAm markers for asthma underlying key processes of the disease pathophysiology and confirm the transferability of previous asthma DNAm associations to ethnically diverse populations.
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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 | 0.000 |
| 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".