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Genome-wide placental DNA methylations in fetal overgrowth and associations with fetal growth factors, leptin and adiponectin

ABSTRACT: This study aims to identify genome-wide placental DNA differential methylation positions (DMPs) in fetal overgrowth and the associations with fetal growth factors, leptin and adiponectin. In the Shanghai Birth Cohort, we studied 30 pairs of placentals of large-for-gestational-age (LGA, birth weight>90th percentile, an indicator of fetal overgrowth) and optimal-for-gestational-age (OGA, 25th-75th percentiles, control) newborns matched by sex and gestational age. Placental DNA methylations were measured by the Illumina Infinium Human Methylation-EPIC BeadChip. Cord blood insulin, C-peptide, proinsulin, IGF-1, IGF-2, leptin and adiponectin concentrations were measured. We identified 543 DMPs (397 hypermethylated, 146 hypomethylated) comparing LGA vs. OGA at false discovery rate <5% and absolute methylation difference >0.05 adjusting for placental cell type heterogeneity, maternal age, pre-pregnancy BMI and HbA1c levels during pregnancy. We validated a hyper-methylated gene - cadherin 13 (CDH13) reported in a previous epigenome-wide association study, and validated a newly discovered differentially (hyper-)methylated gene -visual system homeobox 1 (VSX1) in an independent pyrosequencing study sample (47 LGA-control pairs). Pathway analysis did not detect any statistically significant pathway correcting for multiple tests. Adiponectin in cord blood was correlated with its gene methylation in the placenta, while other observed biomarkers were not. Fetal overgrowth was associated with a large number of altered placental gene DNA methylations. The study provides robust evidence suggesting that placental CDH13 and VSX1 genes are hyper-methylated in LGA. Placental gene methylation was correlated with cord blood biomarker for adiponectin, but not for leptin and fetal growth factors.

ORGANISM(S): Homo sapiens

PROVIDER: GSE204977 | GEO | 2022/12/31

REPOSITORIES: GEO

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Project description:Gestational diabetes mellitus (GDM) “program” an elevated risk of metabolic syndrome in the offspring. Epigenetic alterations are a suspected mechanism. GDM has been associated with placental DNA methylation changes in some epigenome-wide association studies. It remains unclear which genes or pathways are affected, and whether any placental differential gene methylations are correlated to fetal growth or circulating metabolic health biomarkers. In an epigenome-wide association study using the Infinium MethylationEPIC Beadchip, we sought to identify genome-wide placental differentially methylated genes and enriched pathways in GDM, and to assess the correlations with fetal growth and metabolic health biomarkers in cord blood. The study samples were 30 pairs of term placentas in GDM vs. euglycemic pregnancies (controls) matched by infant sex and gestational age at delivery in the Shanghai Birth Cohort. Cord blood metabolic health biomarkers included insulin, C-peptide, proinsulin, IGF-I, IGF-II, leptin and adiponectin. Adjusting for maternal age, pre-pregnancy BMI, parity, mode of delivery and placental cell type heterogeneity, 256 differentially methylated positions (DMPs,130 hypermethylated and 126 hypomethylated) were detected between GDM and control groups accounting for multiple tests with false discovery rate <0.05 and beta-value difference >0.05. WSCD2 was identified as a differentially methylated gene in both site- and region-level analyses. We validated 7 hypermethylated (CYP1A2, GFRA1, HDAC4, LIMS2, NAV3, PAX6, UPK1B) and 10 hypomethylated (DPP10, CPLX1, CSMD2, GPR133, NRXN1, PCSK9, PENK, PRDM16, PTPRN2, TNXB) genes reported in previous epigenome-wide association studies. We did not find any enriched pathway accounting for multiple tests. DMPs in 11 genes (CYP2D7P1, PCDHB15, ERG, SIRPB1, DKK2, RAPGEF5, CACNA2D4, PCSK9, TSNARE1, CADM2, KCNAB2) were correlated with birth weight (z score) accounting for multiple tests. There were no significant correlations between placental gene methylations and cord blood biomarkers. In conclusions, GDM was associated with DNA methylation changes in a number of placental genes, but these placental gene methylations were uncorrelated to the observed metabolic health biomarkers (fetal growth factors, leptin and adiponectin) in cord blood. We validated 17 differentially methylated placental genes in GDM, and identified 11 differentially methylated genes relevant to fetal growth.

Project description:INTRODUCTION: Restricted or enhanced intrauterine growth is associated with elevated risks of early and late metabolic problems in humans. Metabolomics based on amino acid and carnitine/acylcarnitine profile may have a role in fetal and early postnatal energy metabolism. In this study, the relationship between intrauterine growth status and early metabolomics profile was evaluated.MATERIALS AND METHODS: A single center retrospective cohort study was conducted. Newborn infants were enrolled into the study and they were grouped according to their birth weight percentile as small for gestational age (SGA), appropriate for gestational age (AGA) and large for gestational age (LGA) infants. In all infants amino acid and carnitine/acylcarnitine profile with liquid chromatography-tandem mass spectrometry (LC-MS/MS) were recorded and compared between groups.RESULTS: LGA infants had higher levels of glutamic acid and lower levels of ornithine, alanine and glycine (p<0.05) when compared to AGA infants. SGA infants had higher levels of alanine and glycine levels when compared with AGA and LGA infants. Total carnitine, C0, C2, C4, C5, C10:1, C18:1, C18:2, C14-OH and C18:2-OH levels were significantly higher and C3 and C6-DC levels were lower in SGA infants (p<0.05). LGA infants had higher C3 and C5:1 level; and lower C18:2 and C16:1-OH levels (p<0.05). There were positive correlations between free carnitine and phenylalanine, arginine, methionine, alanine and glycine levels (p<0.05). Also a positive correlation between ponderal index and C3, C5-DC, C14, C14:1; and a negative correlation between ponderal index and ornithine, alanine, glycine, C16:1-OH, C18:2 were shown.CONCLUSION: We demonstrated differences in metabolomics possibly reflecting the energy metabolism in newborn infants with intrauterine growth problems in the early postnatal period. These differences might be the footprints of metabolic disturbances in future adulthood.

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Genome-wide placental DNA methylations in fetal overgrowth and associations with fetal growth factors, leptin and adiponectin

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