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Hermetz, K.

Publications and source records attributed to Hermetz, K..

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Placental microRNA Expression Associates with Birthweight through Control of Adipokines: Results from Two Independent Cohorts

MicroRNAs are non-coding RNAs that regulate gene expression post-transcriptionally. In the placenta, the master regulator of fetal growth and development, microRNAs shape the basic processes of trophoblast biology and specific microRNA have been associated with fetal growth. To comprehensively assess the role of microRNAs in placental function and fetal development, we have performed small RNA sequencing to profile placental microRNAs from two independent mother-infant cohorts: the Rhode Island Child Health Study (n=225) and the New Hampshire Birth Cohort Study (n=317). We modeled microRNA counts on infant birthweight percentile (BWP) in each cohort, while accounting for race, sex, parity and technical factors, using negative binomial generalized linear models. We identified microRNAs that were differentially expressed (DEmiRs) with BWP at false discovery rate (FDR) less than 0.05 in both cohorts. hsa-miR-532-5p (miR-532) was positively associated with BWP in both cohorts. By integrating parallel whole transcriptome and small RNA sequencing in the RICHS cohort, we identified putative targets of miR-532. These targets are enriched for pathways involved in adipogenesis, adipocytokine signaling, energy metabolism and hypoxia response, and included Leptin, which we further demonstrated to have decreasing expression with increasing BWP, particularly in male infants. Overall, we have shown a robust and reproducible association of miR-532 with BWP, which could influence BWP through regulation of adipocytokines Leptin and Adiponectin.

genetics

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