Background Insulin resistance (IR) during gestational diabetes mellitus (GDM) has been linked to dysregulated insulin-PI3K/Akt pathway. A defective insulin-PI3K/Akt pathway and dysregulated circular RNA (circRNA) levels have been observed in the placentas of patients with GDM; however, the mechanisms underlying this association remain unclear. Methods circRNAs potentially associated with GDM were selected through bioinformatics analysis and initially identified by quantitative real-time PCR (qPCR) in 9 GDM patients and 9 healthy controls, of which circMAP3K4 was further validated in additional 84 samples by qPCR. circMAP3K4 identity and localization were verified. Pearson correlation analysis was applied to evaluate the correlation between circMAP3K4 expression in the placental tissues of GDM patients and IR-related indicators. An IR model of trophoblasts was constructed using glucosamine. Interactions between miR-6795-5p and circMAP3K4 or PTPN1 were confirmed using a dual-luciferase reporter assay. The circMAP3K4/miR-6795-5p/PTPN1 axis and key markers in the insulin-PI3K/Akt pathway in placentas and trophoblasts were evaluated through qRT-PCR, immunofluorescence, and western blotting. The role of circMAP3K4 in glucose metabolism and cell growth in trophoblasts was determined using the glucose uptake and CCK8 assay, respectively. Results circMAP3K4 was highly expressed in the placentas of patients with GDM and the IR trophoblast model; this was associated with a dysregulated insulin-PI3K/Akt pathway. circMAP3K4 in the placentas of GDM patients was positively correlated with weight gain during pregnancy and time-glucose area under the curve of OGTT. circMAP3K4 and PTPN1 could both bind to miR-6795-5p. miR-6795-5p and PTPN1 were downregulated and upregulated, respectively, in the placentas of GDM patients and the IR trophoblast model. circMAP3K4 silencing or miR-6795-5p overexpression partially reversed the decrease in glucose uptake, inhibition in cell growth, and downregulated IRS1 and Akt phosphorylation in IR-trophoblasts; this restoration was reversed upon co-transfection with an miR-6795-5p inhibitor or PTPN1. Conclusion circMAP3K4 could suppress the insulin-PI3K/Akt signaling pathway via miR-6795-5p/PTPN1 axis, probably contributing to GDM-related IR.

It is necessary to actively control blood glucose and avoid significant glucose fluctuation. PKCβII/JNK may serve as a target, and inhibitors of PKCβII/JNK may be used to help prevent cardiovascular diseases in patients with poor glucose control or significant glucose fluctuation.

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Background Gestational diabetes mellitus (GDM) is one of the most common complications of pregnancy. The mechanism underlying the crosstalk between long non-coding RNAs (lncRNAs) and N6-methyladenine (m6A) modification in GDM remain unclear. Methods We generated a lncRNA-mediated competitive endogenous RNA (ceRNA) network using comprehensive data from the Gene Expression Omnibus database, published data, and our preliminary findings. m6A-related lncRNAs were identified based on Pearson correlation coefficient (PCC) analysis using our previous profiles. An integrated pipeline was established to constructed a m6A-related subnetwork thereby predicting the potential effects of the m6A-related lncRNAs. Results The ceRNA network was composed of 16 lncRNAs, 17 microRNAs, 184 mRNAs, and 338 edges. Analysis with the Kyoto Encyclopedia of Genes and Genomes database demonstrated that genes in the ceRNA network were primarily involved in the development and adverse outcomes of GDM, such as those in the fatty acid-metabolism pathway, the peroxisome proliferator-activated receptor signaling pathway, and thyroid hormone signaling pathway. Four m6A-related lncRNAs were involved in the ceRNA network, including LINC00667, LINC01087, AP000350.6, and CARMN. The m6A-related subnetwork was generated based on these four lncRNAs, their ceRNAs, and their related m6A regulators. Genes in the subnetwork were enriched in certain GDM-associated hormone (thyroid hormone and oxytocin) signaling pathways. LINC00667 was positively correlated with an m6A “reader” (YTHDF3; PCC = 0.95) and exhibited the highest node degree in the ceRNA network. RIP assays showed that YTHDF3 directly bind LINC00667. We further found that MYC possessed the highest node degree in a protein–protein interaction network and competed with LINC00667 for miR-33a-5p. qPCR analysis indicated that LINC00667, YTHDF3 and MYC levels were upregulated in the GDM placentas, while miR-33a-5p was downregulated. In a support-vector machine classifier, an m6A-related module composed of LINC00667, YTHDF3, MYC, and miR-33a-5p showed excellent classifying power for GDM in both the training and the testing dataset, with an accuracy of 76.19 and 71.43%, respectively. Conclusions Our results shed insights into the potential role of m6A-related lncRNAs in GDM and have implications in terms of novel therapeutic targets for GDM.

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Purpose This study sought to develop a nomogram for the prediction of insulin requirement in a Chinese population with gestational diabetes mellitus (GDM). Materials and Methods We performed a retrospective cohort study involving 626 Chinese women with GDM, of whom 188 were treated with insulin. “Least absolute shrinkage and selection operator” regression was used to optimize the independent predictors of insulin requirement during pregnancies complicated with GDM. Cox proportional hazards regression analysis was performed to establish a prediction model incorporating the selected predictors, and the nomogram was constructed to achieve individual prediction. The C-index, calibration plot and decision curve analysis were used to validate the model. Results Maternal age, family history of type 2 diabetes mellitus in a first-degree relative, a prior GDM history, fasting plasma glucose, hemoglobin A1c, gestational age, and body mass index values at the time of GDM diagnosis were the risk factors for insulin treatment. The model displayed medium predictive power with a C-index of 0.77 (95% confidence interval: 0.73–0.81) and relatively good calibration accuracies. The decision curve demonstrated a positive net benefit with a threshold between 0.09 and 0.70. Conclusion The findings suggest that our nomogram, incorporating seven indicators, is useful in predicting individualized survival probabilities of insulin requirement.

Gestational diabetes mellitus (GDM) is a metabolic disorder whose major pathophysiological basis is demonstrated as placental insulin resistance (IR), while Smad4 always functions in the signal transduction of transforming growth factor beta (TGF‐β) pathway. Our study aims to figure out the role of Smad4 in an insulin resistance (IR) cellular model using placental trophoblast cell line. Importantly, HTR8‐Svneo cells, in the status of IR, indicated a significant increase in the expression of Smad4. Subsequently, the HTR8‐Svneo cell line with up‐regulated or depleted Smad4 was respectively achieved by the effective over‐expressed plasmid or siRNA of Smad4. We found out that the deficiency of Smad4 could promote the insulin sensitivity and restrict the inflammatory response in IR group of cells with significant augment in glucose uptake, up‐regulation of insulin signalling‐related molecules and attenuation in inflammatory biomarker expressions. On the contrary, the over‐expression of Smad4 showed a reversal effect on these alterations in IR group of cells. Besides, the positive effect of Smad4 on cell viability was also observed in our study. Significance of the study Gestational diabetes mellitus (GDM) is a metabolic disorder whose major pathophysiological basis is demonstrated as insulin resistance (IR). Importantly, our findings indicate that the deficiency of Smad4 significantly improves the insulin sensitivity and relieves the inflammation in the cellular model of IR. Besides, the positive effect of Smad4 on cell viability was also observed in our study. Our present findings provide novel insights for the investigation on molecular details about the GDM pathogenesis.

The epidemic studies have demonstrated an excessively increase of diabetic patients in recent years, who are at high risk of developing microvascular complications. Those microvascular complications usually lead to chronic health problems, e.g. diabetic retinopathy (DR), thus early and regular screening is indeed necessary. Retinal vascular tortuosity, which is one of geometrical parameters related to microvascular morphological changes, has been investigated in many studies related to diabetes, diabetic risk factors and diabetic complications. However, the global tortuosity of retinal vessels in DR progression is quantified either subjectively or imprecisely in those previous studies. Furthermore, to our best knowledge, the association of tortuosity, diabetes and DR has never been investigated based on a Chinese population-based cohort, even though it accounts for more than 30% of diabetic patients worldwide. Therefore, it is of great necessary and clinical significance to extract retinal tortuosity in a more reliable way and explore its associations with diabetic risk factors and DR severity in China. In this study, high contrast retinal images from 495 Chinese patients with type 2 diabetes were acquired by confocal scanning laser ophthalmoscope and the global tortuosity was extracted from main and branching arterioles, venules in the whole retinal image based on the theory of best-fit exponential curves in the roto-translation group SE(2). The statistical analysis results show that retinal arteriolar and venular tortuosity might be remarkable indices for assessing retinopathy severity and identifying individuals with high-risk of renal disease in diabetes, which may provide additional insights on microvascular changes for diabetic retina and kidney diseases. INDEX TERMS Diabetes, diabetic retinopathy, tortuosity, main and branching vessels, confocal scanning laser ophthalmoscope.