Project description:Objective: To explore the characteristics and underlying molecular mechanisms of genome-scale expression profiles of women with- or without- GDM and their offspring. Materials and Methods: We recruited a group of 21 pregnant women with GDM and 20 healthy pregnant women as controls. For each pregnant women, RNA-seq were performed using the placenta and paired neonatal umbilical cord blood specimens. Differentially expressed genes (DEGs) were identified with BMI of pregnant women as covariates. Then, functional enrichment analysis was performed separately or interactively in placenta and umbilical cord blood. Results: Through the comparison of GDM and healthy samples, 1442 and 488 DEGs were identified from placenta and umbilical cord blood, respectively. Functional enrichment analysis showed that the placenta expression profiles of GDM women mirrored the molecular characteristics of type II diabetes and insulin resistance patients. DEGs illustrated significant overlaps among placenta and umbilical cord blood samples, and the overlapping DEGs were associated with endocrine resistance and insulin resistance. Conclusions: Our research demonstrated the transcriptomic alternations of GDM mothers and offspring. Our findings emphasized the importance of epigenetic modifications in the communication between pregnant women with GDM and offspring, and provided reference for the prevention, control, treatment, and intervention of perinatal deleterious events of GDM and neonatal complications.
Project description:Genome wide DNA methylation profiling of cord blood cells obtained from gestational diabetes mellitus (GDM) pregnancies. The Illumina EPIC methylation beadchip array was used to obtain DNA methylation profiles across approximately 850,000 CpG dinucleotide methylation loci in DNA isolated from cord blood. Samples include 165 GDM subjects.
Project description:Objective: Early life is a critical period for gut microbial development. It is still controversial whether there is placental microbiota during a healthy pregnancy. Gestational diabetes mellitus (GDM) is associated with increased risk of metabolic syndrome in the offspring, and the mechanisms are unclear. We sought to explore whether microbiota in placenta and cord blood may be altered in GDM. Methods: Placenta and cord blood samples were collected from eight GDM and seven euglycemic (control) term pregnancies in cesarean deliveries without evidence of clinical infections. The Illumina MiSeq Sequencing System was used to detect the microbiota based on the V3-V4 hypervariable regions of the 16S ribosomal RNA gene. Results: The microbiota were detectable in all placental samples. Comparing GDM vs. controls, there were more operational taxonomic units (OTUs) (mean ± SE = 373.63 ± 14.61 vs. 332.43 ± 9.92, P = 0.024) and higher ACE index (395.15 ± 10.56 vs. 356.27 ± 8.47, P = 0.029) and Chao index (397.67 ± 10.24 vs. 361.32 ± 8.87, P = 0.04). The placental microbiota was mainly composed of four phyla: Bacteroidetes, Firmicutes, Actinobacteria, and Proteobacteria at the phylum level and 10 dominant genera at the genus level in both GDM and controls. Despite the dominant similarity in microbiota composition, at the OTU level, the abundance of Ruminococcus, Coprococcus, Paraprevotella, and Lactobacillus were higher, whereas Veillonella was lower in the placentas of GDM vs. controls. The microbiota was detected in one of the 15 cord blood samples, and its components were similar as to the corresponding placental microbiota at both phylum and genus levels suggesting placental microbiota as the potential source. Conclusions: The most abundant phyla and genus of placental microbiota were similar in GDM and euglycemic pregnancies, but GDM was associated with higher diversity of placental microbiota. Further study is needed to confirm the existence of microbiota in cord blood in pregnancies without clinical infection.
Project description:BackgroundIntrauterine exposure to gestational diabetes mellitus (GDM) confers a lifelong increased risk for metabolic and other complex disorders to the offspring. GDM-induced epigenetic modifications modulating gene regulation and persisting into later life are generally assumed to mediate these elevated disease susceptibilities. To identify candidate genes for fetal programming, we compared genome-wide methylation patterns of fetal cord bloods (FCBs) from GDM and control pregnancies.Methods and resultsUsing Illumina's 450K methylation arrays and following correction for multiple testing, 65 CpG sites (52 associated with genes) displayed significant methylation differences between GDM and control samples. Four candidate genes, ATP5A1, MFAP4, PRKCH, and SLC17A4, from our methylation screen and one, HIF3A, from the literature were validated by bisulfite pyrosequencing. The effects remained significant after adjustment for the confounding factors maternal BMI, gestational week, and fetal sex in a multivariate regression model. In general, GDM effects on FCB methylation were more pronounced in women with insulin-dependent GDM who had a more severe metabolic phenotype than women with dietetically treated GDM.ConclusionsOur study supports an association between maternal GDM and the epigenetic status of the exposed offspring. Consistent with a multifactorial disease model, the observed FCB methylation changes are of small effect size but affect multiple genes/loci. The identified genes are primary candidates for transmitting GDM effects to the next generation. They also may provide useful biomarkers for the diagnosis, prognosis, and treatment of adverse prenatal exposures.
Project description:In this retrospective study, a diverse set of biological specimens was assembled, consisting of maternal blood, umbilical cord blood, and placenta tissue, from a cohort of 22 mothers with gestational diabetes mellitus and a matched group of 19 healthy mothers. Integrated proteomic characterization of these samples were performed, and functional enrichments based on GO and KEGG database, as well as Gene Set Enrichment Analysis were used to elucidate the pathways involved in the pathophysiology of gestational diabetes mellitus. Moreover, a weighted protein co-expression network was constructed to analysis the correlation of expression modules with clinical traits.
