The downregulation of miR-22 and miR-372 may contribute to gestational diabetes mellitus through regulating glucose metabolism via the PI3K/AKT/GLUT4 pathway

Bioinformatic identification of signature miRNAs associated with fetoplacental vascular dysfunction in gestational diabetes mellitus

Background

Intrauterine exposure to gestational diabetes mellitus (GDM) poses significant risks to fetal development and future metabolic health. Despite its clinical importance, the role of microRNAs (miRNAs) in fetoplacental vascular endothelial cell (VEC) programming in the context of GDM remains elusive. This study aims to identify signature miRNA genes involved in this process using bioinformatics analysis via multiple algorithms.

Methods

The dataset used in this study was acquired from Gene Expression Omnibus (GEO). Firstly, differentially expressed miRNA genes (DEMGs) were evaluated using limma package. Thereafter, an enrichment analysis of DEMGs was performed. Then, the least absolute shrinkage and selection operator (LASSO) and support vector machine (SVM) were used as the other algorithms for screening candidate signature miRNA genes. Genes from the intersection of limma, LASSO, and SVM genes were used as the final signature miRNA genes. The receiver operator characteristic curve (ROC), the nomogram diagram, gene set enrichment analysis (GSEA), and signature miRNAs-target genes interaction network were implemented further to explore the features and functions of signature genes.

Results

A total of 32 DEMGs, with 21 upregulated and 11 downregulated miRNA genes, were obtained from limma analysis. LASSO and SVM analyses identified 15 and 12 candidate signature miRNA genes, respectively. After the intersection of genes from limma, LASSO, and SVM analyses, MIR34A and MIR186 were found as the final signature genes related to fetoplacental VEC programming. MIR34A and MIR186 were highly expressed and were associated with an increased risk of fetoplacental VEC programming in GDM mothers. The area under the curve (AUC) of ROC for MIR34A and MIR186 were 0.960 and 0.935, respectively. GSEA analysis revealed that these signature genes positively participate in cellular processes related to VEC migration, cell differentiation, angiogenesis, programmed cell death, and inflammatory response. Finally, miRNAs-target genes interaction network analysis provides the interaction of signature miRNAs and their critical target genes, which may help further studies for miR-34a and miR-186 in GDM.

Conclusions

MIR34A and MIR186 are novel signature miRNA genes related to fetoplacental VEC programming that may represent critical genes associated with placental function and fetal programming under GDM conditions.

Effects of asiaticoside on the model of gestational diabetes mellitus in HTR-8/svneo cells via PI3K/AKT pathway

BACKGROUND

Asiaticoside (AS) has been reported to improve the changes induced by high glucose stimulation, and it may have potential therapeutic effects on gestational diabetes mellitus (GDM). This study aims to explore the effect of AS on the cell model of GDM and the action mechanism of the PI3K/AKT pathway.

METHODS

The GDM model was established in HTR-8/Svneo cells with a high glucose (HG) medium. After the cytotoxicity assay of AS, cells were divided into the control group, HG group and HG + AS group to conduct control experiment in cells. The cell proliferation and migration were detected by CCK-8 assay and scratch test, respectively. The mRNA levels of PI3K, AKT2, mTORC1, and GLUT4 in PI3K/AKT signalling pathway were measured by RT-PCR, and the protein expressions of these signalling molecules were monitored by western blot.

RESULTS

AS showed a promotion effect on the cell proliferation rate of HTR-8/Svneo cells, and 80 μmol/L AS with a treatment time of 48 h had no cytotoxicity. The cell proliferation rate, migration rate, mRNA levels and protein expressions of PI3K, AKT2, mTORC1, and GLUT4 in the HG group were significantly lower than those in the control group, which were significantly increased in the HG + AS group (p < 0.05).

CONCLUSIONS

AS can facilitate the cell proliferation and migration in the cell model of GDM, and might play a role in GDM treatment via PI3K/AKT pathway.

The role of microRNAs in pregnancies complicated by maternal diabetes

With the global prevalence of diabetes increasing, more people of reproductive age are experiencing hyperglycaemic pregnancies. Maternal Type 1 (T1DM) or Type 2 (T2DM) diabetes mellitus, and gestational diabetes mellitus (GDM) are associated with maternal cardiovascular and metabolic complications. Pregnancies complicated by maternal diabetes also increase the risk of short- and long-term health complications for the offspring, including altered fetal growth and the onset of T2DM and cardiometabolic diseases throughout life. Despite advanced methods for improving maternal glucose control, the prevalence of adverse maternal and offspring outcomes associated with maternal diabetes remains high. The placenta is a key organ at the maternal-fetal interface that regulates fetal growth and development. In pregnancies complicated by maternal diabetes, altered placental development and function has been linked to adverse outcomes in both mother and fetus. Emerging evidence suggests that microRNAs (miRNAs) are key molecules involved in mediating these changes. In this review, we describe the role of miRNAs in normal pregnancy and discuss how miRNA dysregulation in the placenta and maternal circulation is associated with suboptimal placental development and pregnancy outcomes in individuals with maternal diabetes. We also discuss evidence demonstrating that miRNA dysregulation may affect the long-term health of mothers and their offspring. As such, miRNAs are potential candidates as biomarkers and therapeutic targets in diabetic pregnancies at risk of adverse outcomes.

The role of ncRNA regulatory mechanisms in diseases-case on gestational diabetes

Non-coding RNAs (ncRNAs) are a class of RNA molecules that do not have the potential to encode proteins. Meanwhile, they can occupy a significant portion of the human genome and participate in gene expression regulation through various mechanisms. Gestational diabetes mellitus (GDM) is a pathologic condition of carbohydrate intolerance that begins or is first detected during pregnancy, making it one of the most common pregnancy complications. Although the exact pathogenesis of GDM remains unclear, several recent studies have shown that ncRNAs play a crucial regulatory role in GDM. Herein, we present a comprehensive review on the multiple mechanisms of ncRNAs in GDM along with their potential role as biomarkers. In addition, we investigate the contribution of deep learning-based models in discovering disease-specific ncRNA biomarkers and elucidate the underlying mechanisms of ncRNA. This might assist community-wide efforts to obtain insights into the regulatory mechanisms of ncRNAs in disease and guide a novel approach for early diagnosis and treatment of disease.