Epigenome‐wide association studies in asthma: A systematic review
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Bibliographic record
Abstract
OBJECTIVE: Asthma is a common chronic respiratory airway disease influenced by environmental factors and possibly their interaction with the human genome causing epigenetic changes. Epigenome-wide association studies (EWAS) have mainly investigated DNA methylation and its association with disease or traits, exposure factors or gene expression. This systematic review aimed to identify all EWAS assessing differentially methylated sites associated with asthma in humans. DESIGN: Structured systematic literature search following PRISMA guidelines, Newcastle-Ottawa Scale (NOS) for cohort studies was used for bias assessment. DATA SOURCES: We searched PubMed and Embase databases from 2005 to 2019. ELIGIBILITY CRITERIA: Epigenome-wide association studies testing association between differential methylation and asthma in humans. RESULTS: Overall, we identified 16 EWAS studies complying with our search criteria. Twelve studies were conducted on children, and 10 were conducted on sample sizes <150 subjects. Four hundred and nineteen CpGs were reported in children studies after correction for multiple testing. In the adult studies, thousands of differentially methylated sites were identified. Differential methylation in inflammatory-related genes correlated with higher levels of gene expressions of inflammatory modulators in asthma. Differentially methylated genes associated with asthma included SMAD3, SERPINC1, PROK1, IL13, RUNX3 and TIGIT. Forty-one CpGs were replicated at least once in blood samples, and 28 CpGs were replicated in nasal samples. CONCLUSION: Although many differentially methylated CpGs in genes known to be involved in asthma have been identified in EWAS to date, we conclude that further studies of larger sample sizes and analyses of differential methylation between different phenotypes are needed in order to comprehensively evaluate the role of epigenetic factors in the pathophysiology and heterogeneity of asthma, and the potential clinical utility to predict or classify patients with asthma.
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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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.009 | 0.002 |
| 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.002 |
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 it