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

Abstract

36Background & Objectives: Neonatal neurobehavioral performance measures, such as the NICU Network 37 Neurobehavioral Scale (NNNS), have been developed to assess the neurobehavioral characteristics of 38 infants and provide insights into future developmental trajectories. The identification of molecular 39 biomarkers of very early life neurobehavioral experiences could lead to better predictions of the long-term 40 developmental outcomes of high-risk infants including preterm infants. To this end, we aimed to examine 41 whether variability in DNA methylation (DNAm) or epigenetic age from surrogate tissues are associated 42 with NNNS profiles in a cohort of infants born less than 30 weeks postmenstrual age (PMA). 43Methods: This study was performed within the Neonatal Neurobehavior and Outcomes in Very Preterm 44 Infants (NOVI) Study and included those infants with complete NNNS assessment data and DNAm 45 measured from buccal cells, collected at near term-equivalent age using the Illumina EPIC array (N=536). 46We tested whether epigenetic age and age acceleration differed between infants based on their NNNS 47 profile classifications. Then we performed an epigenome-wide association study, to test whether DNAm at 48 individual epigenetic loci varied between these NNNS profile groupings. Models were adjusted for 49 recruitment site, infant sex, postmenstrual age, and estimated tissue heterogeneity. 50Results: We found that infants with an optimal NNNS profile had slightly older epigenetic age than other 51 NOVI infants (β1 = 0.201, p-value = 0.026), and that infants with an atypical NNNS profile had differential 52 methylation at 29 CpG sites (FDR < 10%). The genes annotated to these differentially methylated CpGs 53 included PLA2G4E, TRIM9, GRIK3, and MACROD2, which have previously been associated with 54 neurological structure and function, or with neurobehavioral disorders. 55Conclusions: Greater epigenetic age is associated with optimal NNNS responses while altered DNAm of 56 multiple genes are associated with an atypical neurobehavioral profile at near-term equivalent age. These 57 findings build upon the existing evidence that epigenetic variations in buccal cells may serve as markers of 58 neonatal neurobehavior and might facilitate early identification of children at risk for abnormal 59 developmental outcome. are born less than 37 weeks of gestation (1). Survival of infants born extremely preterm, less than 30 week 63 postmenstrual age (PMA), has improved due to technological and medical advancements (1-3). 64Nonetheless, these infants have increased risk for morbidity and mortality. Children born extremely preterm 65 term are more likely to suffer from chronic illnesses, potentially devastating brain injuries, and adverse 66 neuromotor, cognitive, and behavioral outcomes that persist through adulthood (4-15). These serious health 67 consequences require extensive healthcare, educational and psychosocial community resources, in addition 68 to increased burden on the families and caregivers of these childre...

Serious neonatal morbidities are associated with differences in DNA methylation among very preterm infants

“…We estimated the proportions of epithelial, fibroblast, and immune cells in our buccal samples using reference methylomes [ 29 ]. As demonstrated in our prior work, epithelial cells made up 95.7% of the cells in 95% of our samples, while immune cells made up the majority of the remaining cell types [ 30 ]. The proportions of individual immune cell subtypes were strongly inversely correlated with the proportions of epithelial cells, and very few samples had any estimated fibroblasts.…”

“…While our study focused on epigenetic variation that is associated with the burden of multiple neonatal morbidities in very preterm infants, other studies have previously shown that preterm birth itself is associated with differential DNAm in several different tissues, including placenta [ 61 ], neonatal blood [ 9 – 11 ], and neonatal saliva [ 37 ]. Many of the CpG sites that have been associated with preterm birth in these prior studies are within genes that are involved in neuronal development and/or neurodegenerative disorders, and we have previously found that neonatal neurobehavioral responses in preterm infants are associated with differences in DNAm [ 30 ]. Furthermore, some of the CpGs associated with preterm birth have been shown to be differentially methylated in adult blood, suggesting that DNAm could potentially mediate some of the long-term health consequences that are associated with prematurity [ 9 , 12 ].…”

Environment-driven reprogramming of gamete DNA methylation occurs during maturation and is transmitted intergenerationally in salmon

“…Glutamatergic signalling is an important excitory driver of the hypothalamic-pituitary-adrenal (HPA) axis that, among other functions, mediates organismal stress responses and aggression and it has been hypothesized that selection on these pathways underlies “tameness” in domesticated animals and attenuated stress responses under crowded conditions (O’Rourke and Boeckx 2020). Furthermore, differential methylation of glutamate receptors has been reported in response to prenatal stress in cows (Littlejohn et al 2018) and is associated with adverse behavioural phenotypes in preterm infant humans (Everson et al 2019). This raises the hypothesis that adult SAS fish could transmit information about the crowding they experienced prior to spawning to their offspring in order to prime them for a highly competitive environment upon hatching (Christie et al 2012).…”

mRNA and microRNA profiles in the amygdala are relevant to Susceptible and Resilient mice induced by psychological stress

“…Pla2g4e belongs to cytosolic phospholipase A2 (cPLA2), which selectively catalyzes the hydrolysis of the sn-2 site of the glycerol portion of the membrane phospholipid to break the ester bond [59]. It is considered to be related to neural structure and function, a neurobehavioral disorder in research [60]. Some literature suggests that this gene may be a risk gene for panic disorder [61], there is also some literature indicating that there is a certain relationship between the occurrence of depression [62].…”