Exposure to environmental stressors during pregnancy plays an important role in influencing subsequent susceptibility to certain chronic diseases through the modulation of epigenetic mechanisms, including DNA methylation. Our aim was to explore the connections between environmental exposures during gestation with DNA methylation of placental cells, maternal and neonatal buccal cells by applying artificial neural networks (ANNs). A total of 28 mother-infant pairs were enrolled. Data on gestational exposure to adverse environmental factors and on mother health status were collected through the administration of a questionnaire. DNA methylation analyses at both gene-specific and global level were analyzed in placentas, maternal and neonatal buccal cells. In the placenta, the concentrations of various metals and dioxins were also analyzed. Analysis of ANNs revealed that suboptimal birth weight is associated with placental H19 methylation, maternal stress during pregnancy with methylation levels of NR3C1 and BDNF in placentas and mother's buccal DNA, respectively, and exposure to air pollutants with maternal MGMT methylation. Associations were also observed between placental concentrations of lead, chromium, cadmium and mercury with methylation levels of OXTR in placentas, HSD11B2 in maternal buccal cells and placentas, MECP2 in neonatal buccal cells, and MTHFR in maternal buccal cells. Furthermore, dioxin concentrations were associated with placental RELN, neonatal HSD11B2 and maternal H19 gene methylation levels. Current results suggest that exposure of pregnant women to environmental stressors during pregnancy could induce aberrant methylation levels in genes linked to several pathways important for embryogenesis in both the placenta, potentially affecting foetal development, and in the peripheral tissues of mothers and infants, potentially providing peripheral biomarkers of environmental exposure.
Prenatal Environmental Stressors and DNA Methylation Levels in Placenta and Peripheral Tissues of Mothers and Neonates Evaluated by Applying Artificial Neural Networks
Burgio, Ernesto;Fanos, Vassilios;
2023-01-01
Abstract
Exposure to environmental stressors during pregnancy plays an important role in influencing subsequent susceptibility to certain chronic diseases through the modulation of epigenetic mechanisms, including DNA methylation. Our aim was to explore the connections between environmental exposures during gestation with DNA methylation of placental cells, maternal and neonatal buccal cells by applying artificial neural networks (ANNs). A total of 28 mother-infant pairs were enrolled. Data on gestational exposure to adverse environmental factors and on mother health status were collected through the administration of a questionnaire. DNA methylation analyses at both gene-specific and global level were analyzed in placentas, maternal and neonatal buccal cells. In the placenta, the concentrations of various metals and dioxins were also analyzed. Analysis of ANNs revealed that suboptimal birth weight is associated with placental H19 methylation, maternal stress during pregnancy with methylation levels of NR3C1 and BDNF in placentas and mother's buccal DNA, respectively, and exposure to air pollutants with maternal MGMT methylation. Associations were also observed between placental concentrations of lead, chromium, cadmium and mercury with methylation levels of OXTR in placentas, HSD11B2 in maternal buccal cells and placentas, MECP2 in neonatal buccal cells, and MTHFR in maternal buccal cells. Furthermore, dioxin concentrations were associated with placental RELN, neonatal HSD11B2 and maternal H19 gene methylation levels. Current results suggest that exposure of pregnant women to environmental stressors during pregnancy could induce aberrant methylation levels in genes linked to several pathways important for embryogenesis in both the placenta, potentially affecting foetal development, and in the peripheral tissues of mothers and infants, potentially providing peripheral biomarkers of environmental exposure.File | Dimensione | Formato | |
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