Background: Hypertension and atherosclerosis may partly originate in early life. Altered epigenetic aging may be a mechanism underlying associations of early-life exposures and the development of cardiovascular risk factors in childhood. A discrepancy between chronological age and age predicted from neonatal DNA methylation data is referred to as age acceleration. It may either be positive, if DNA methylation age is older than clinical age, or negative, if DNA methylation age is younger than chronological age. We examined associations of age acceleration at birth (‘gestational age acceleration’), and of age acceleration at school-age, with blood pressure and with intima-media thickness and distensibility of the common carotid artery, as markers of vascular structure and function, respectively, measured at age 10 years. Results: This study was embedded in the Generation R Study, a population-based prospective cohort study. We included 1115 children with information on cord blood DNA methylation and blood pressure, carotid intima-media thickness or carotid distensibility. Gestational age acceleration was calculated using the Bohlin epigenetic clock, which was developed specifically for cord blood DNA methylation data. It predicts gestational age based on methylation levels of 96 CpGs from HumanMethylation450 BeadChip. We observed no associations of gestational age acceleration with blood pressure, carotid intima-media thickness or carotid distensibility at age 10 years. In analyses among children with peripheral blood DNA methylation measured at age 6 (n = 470) and 10 (n = 449) years, we also observed no associations of age acceleration at these ages with the same cardiovascular outcomes, using the ‘skin and blood clock,’ which predicts age based on methylation levels at 391 CpGs from HumanMethylation450 BeadChip. Conclusions: Our findings do not provide support for the hypothesis that altered epigenetic aging during the earliest phase of life is involved in the development of cardiovascular risk factors in childhood.
Bibliographical noteFunding Information:
The general design of the Generation R Study is made possible by financial support from the Erasmus MC, University Medical Centre Rotterdam, Erasmus University Rotterdam, the Netherlands Organization for Health Research and Development (ZonMw), the Netherlands Organization for Scientific Research (NWO), the Ministry of Health, Welfare and Sport and the Ministry of Youth and Families. The EWAS data were funded by a grant to VWVJ from the Netherlands Genomics Initiative (NGI)/Netherlands Organization for Scientific Research (NWO) Netherlands Consortium for Healthy Aging (NCHA; project number 050-060-810), by funds from the Genetic Laboratory of the Department of Internal Medicine, Erasmus MC, and by a grant from the National Institute of Child and Human Development (R01HD068437). VWVJ received funding from the European Research Council (ERC-2014-CoG-648916). The project was supported by funding from the European Union's Horizon 2020 research and innovation program under grant agreements No 733206 (LifeCycle) and 874739 (LongITools), and from the European Joint Programming Initiative “A Healthy Diet for a Healthy Life” (JPI HDHL, NutriPROGRAM project, ZonMw the Netherlands no.529051022 and PREcisE project ZonMw the Netherlands no.529051023).
The Generation R Study is conducted by the Erasmus Medical Center in close collaboration with the School of Law and Faculty of Social Sciences of the Erasmus University Rotterdam, the Municipal Health Service Rotterdam area, Rotterdam, the Rotterdam Homecare Foundation, Rotterdam and the Stichting Trombosedienst & Artsenlaboratorium Rijnmond (STAR-MDC), Rotterdam. We gratefully acknowledge the contribution of children and parents, general practitioners, hospitals, midwives and pharmacies in Rotterdam. The generation and management of the Illumina 450K methylation array data (EWAS data) for the Generation R Study was executed by the Human Genotyping Facility of the Genetic Laboratory of the Department of Internal Medicine, Erasmus MC, and the Netherlands. We thank Mr. Michael Verbiest, Ms. Mila Jhamai, Ms. Sarah Higgins, Mr. Marijn Verkerk and Dr. Lisette Stolk for their help in creating the EWAS database. We thank Dr. Alexander Teumer for his work on the quality control and normalization scripts.
© 2021, The Author(s).