Lester, B. M. | bioRxiv Science

bioRxiv2021

NEOage clocks - Epigenetic clocks to estimate post-menstrual and postnatal age in preterm infants

Epigenetic clocks based on DNA methylation (DNAm) can to accurately predict chronological age and are thought to capture biological aging. A variety of epigenetic clocks have been developed for different tissue types and age ranges, but none has focused on age prediction for preterm infants. Epigenetic estimators of biological age might be especially informative in epidemiologic studies of neonates, particularly those born preterm, since this is a key developmental window. Neonatal DNAm is dynamic and preterm infants are at heightened risk of developmental impairments. We aimed to fill this gap by developing epigenetic clocks for neonatal aging in preterm infants. As part of the Neonatal Neurobehavior and Outcomes in Very Preterm Infants (NOVI) study, buccal cells were collected at NICU discharge to profile DNAm levels in 542 very preterm infants. We applied elastic net regression to identify four epigenetic clocks (NEOage) predictive of post-menstrual and postnatal age, compatible with the Illumina EPIC and 450K arrays. We observed high correlations between predicted and reported ages (0.93 - 0.94) with root mean squared errors (1.28 - 1.63 weeks). Epigenetic estimators of neonatal aging in preterm infants can be useful tools to evaluate biological maturity and associations with neonatal and long-term morbidities.

genomics↗

bioRxiv2018

Epigenome-wide Analysis Identifies Genes and Pathways Linked to Neurobehavioral Variation in Preterm Infants

Background & ObjectivesNeonatal neurobehavioral performance measures, such as the NICU Network Neurobehavioral Scale (NNNS), have been developed to assess the neurobehavioral characteristics of infants and provide insights into future developmental trajectories. The identification of molecular biomarkers of very early life neurobehavioral experiences could lead to better predictions of the long-term developmental outcomes of high-risk infants including preterm infants. To this end, we aimed to examine whether variability in DNA methylation (DNAm) or epigenetic age from surrogate tissues are associated with NNNS profiles in a cohort of infants born less than 30 weeks postmenstrual age (PMA).\n\nMethodsThis study was performed within the Neonatal Neurobehavior and Outcomes in Very Preterm Infants (NOVI) Study and included those infants with complete NNNS assessment data and DNAm measured from buccal cells, collected at near term-equivalent age using the Illumina EPIC array (N=536). We tested whether epigenetic age and age acceleration differed between infants based on their NNNS profile classifications. Then we performed an epigenome-wide association study, to test whether DNAm at individual epigenetic loci varied between these NNNS profile groupings. Models were adjusted for recruitment site, infant sex, postmenstrual age, and estimated tissue heterogeneity.\n\nResultsWe found that infants with an optimal NNNS profile had slightly older epigenetic age than other NOVI infants ({beta}1 = 0.201, p-value = 0.026), and that infants with an atypical NNNS profile had differential methylation at 29 CpG sites (FDR < 10%). The genes annotated to these differentially methylated CpGs included PLA2G4E, TRIM9, GRIK3, and MACROD2, which have previously been associated with neurological structure and function, or with neurobehavioral disorders.\n\nConclusionsGreater epigenetic age is associated with optimal NNNS responses while altered DNAm of multiple genes are associated with an atypical neurobehavioral profile at near-term equivalent age. These findings build upon the existing evidence that epigenetic variations in buccal cells may serve as markers of neonatal neurobehavior and might facilitate early identification of children at risk for abnormal developmental outcome.

epidemiology↗