Epigenetic timing effects on child developmental outcomes: a longitudinal meta-regression of findings from the Pregnancy And Childhood Epigenetics Consortium
Bibliographic record
Abstract
BACKGROUND: DNA methylation (DNAm) is a developmentally dynamic epigenetic process; yet, most epigenome-wide association studies (EWAS) have examined DNAm at only one timepoint or without systematic comparisons between timepoints. Thus, it is unclear whether DNAm alterations during certain developmental periods are more informative than others for health outcomes, how persistent epigenetic signals are across time, and whether epigenetic timing effects differ by outcome. METHODS: We applied longitudinal meta-regression models to published meta-analyses from the PACE consortium that examined DNAm at two timepoints-prospectively at birth and cross-sectionally in childhood-in relation to the same child outcome (ADHD symptoms, general psychopathology, sleep duration, BMI, asthma). These models allowed systematic comparisons of effect sizes and statistical significance between timepoints. Furthermore, we tested correlations between DNAm regression coefficients to assess the consistency of epigenetic signals across time and outcomes. Finally, we performed robustness checks, estimated between-study heterogeneity, and tested pathway enrichment. RESULTS: Our findings reveal three new insights: (i) across outcomes, DNAm effect sizes are consistently larger in childhood cross-sectional analyses compared to prospective analyses at birth; (ii) higher effect sizes do not necessarily translate into more significant findings, as associations also become noisier in childhood for most outcomes (showing larger standard errors in cross-sectional vs prospective analyses); and (iii) DNAm signals are highly time-specific, while also showing evidence of shared associations across health outcomes (ADHD symptoms, general psychopathology, and asthma). Notably, these observations could not be explained by sample size differences and only partly to differential study-heterogeneity. DNAm sites changing associations were enriched for neural pathways. CONCLUSIONS: Our results highlight developmentally-specific associations between DNAm and child health outcomes, when assessing DNAm at birth vs childhood. This implies that EWAS results from one timepoint are unlikely to generalize to another. Longitudinal studies with repeated epigenetic assessments are direly needed to shed light on the dynamic relationship between DNAm, development and health, as well as to enable the creation of more reliable and generalizable epigenetic biomarkers. More broadly, this study underscores the importance of considering the time-varying nature of DNAm in epigenetic research and supports the potential existence of epigenetic "timing effects" on child health.
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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 | 0.034 | 0.065 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.039 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".