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Systematic characterization of human placenta-derived circRNAs and identification of autophagy-related circRNAs in gestational diabetes mellitus [lncRNA]

ABSTRACT: The objective of this study was to identify and investigate the roles of circRNAs in GDM. In the current study, placental circRNA expression profiles of normal controls and GDM patients were analyzed using high-throughput sequencing. Bioinformatics analysis identified a total of 4955 circRNAs, of which 37 circRNAs were significantly deregulated in GDM placentas compared with NC placentas. GO and KEGG enrichment analyses demonstrated that metabolic process-associated terms and metabolic pathways that may be related to GDM were significantly enriched. The biological characteristics of placenta-derived circRNAs, such as their stability and RNase R resistance, were also validated.Our study indicates that aberrant expression of circRNAs may play roles in autophagy in GDM placentas, providing new insights into GDM.

ORGANISM(S): Homo sapiens

PROVIDER: GSE206041 | GEO | 2022/11/23

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.

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Systematic characterization of human placenta-derived circRNAs and identification of autophagy-related circRNAs in gestational diabetes mellitus [lncRNA]

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