Epigenetic timing effects on child developmental outcomes: a longitudinal meta-regression of findings from the Pregnancy And Childhood Epigenetics Consortium
Authors: Alexander Neumann, Sara Sammallahti, Marta Cosin-Tomas, Sarah E Reese, Matthew Suderman, Silvia Alemany, Catarina Almqvist, Sandra Andrusaityte, Syed H Arshad, Marian J Bakermans-Kranenburg, Lawrence Beilin, Carrie Breton, Mariona Bustamante, Darina Czamara, Dana Dabelea, Celeste Eng, Brenda Eskenazi, Bernard F Fuemmeler, Frank D Gilliland, Regina Grazuleviciene, Siri E Håberg, Gunda Herberth, Nina Holland, Amy Hough, Donglei Hu, Karen Huen, Anke Hüls, Marjo-Riitta Jarvelin, Jianping Jin, Jordi Julvez, Berthold V Koletzko, Gerard H Koppelman, Inger Kull, Xueling Lu, Léa Maitre, Dan Mason, Erik Melén, Simon K Merid, Peter L Molloy, Trevor A Mori, Rosa H Mulder, Christian M Page, Rebecca C Richmond, Stefan Röder, Jason P Ross, Laura Schellhas, Sylvain Sebert, Dean Sheppard, Harold Snieder, Anne P Starling, Dan J Stein, Gwen Tindula, Marinus H van IJzendoorn, Judith Vonk, Esther Walton, Jonathan Witonsky, Cheng-Jian Xu, Ivana V Yang, Paul D Yousefi, Heather J Zar, Ana C Zenclussen, Hongmei Zhang, Henning Tiemeier, Stephanie J London, Janine F Felix, Charlotte Cecil
Journal: Genome Medicine (2025)

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.