Postpartum Circulating Cell-Free Insulin DNA Levels Are Higher in Women with Previous Gestational Diabetes Mellitus Who Develop Type 2 Diabetes in Later Life

Deciphering DNA Methylation in Gestational Diabetes Mellitus: Epigenetic Regulation and Potential Clinical Applications

Gestational diabetes mellitus (GDM) represents a prevalent complication during pregnancy, exerting both short-term and long-term impacts on maternal and offspring health. This review offers a comprehensive outline of DNA methylation modifications observed in various maternal and offspring tissues affected by GDM, emphasizing the intricate interplay between DNA methylation dynamics, gene expression, and the pathogenesis of GDM. Furthermore, it explores the influence of environmental pollutants, maternal nutritional supplementation, and prenatal gut microbiota on GDM development through alterations in DNA methylation profiles. Additionally, this review summarizes recent advancements in DNA methylation-based diagnostics and predictive models in early GDM detection and risk assessment for subsequent type 2 diabetes. These insights contribute significantly to our understanding of the epigenetic mechanisms underlying GDM development, thereby enhancing maternal and fetal health outcomes and advocating further efforts in this field.

Cell-free DNA as a plausible biomarker of chronic kidney disease

Circulating cell-free DNA (cf-DNA) is released from dead and/or apoptotic leukocytes and due to neutrophil extracellular traps contributing to an inflammatory response. Previous clinical studies have reported that the peak concentrations and dynamic changes of cf-DNA may be used as a noninvasive biomarker of worsening kidney function as well as a guide to the management of kidney allograft rejection. We hypothesized that the pattern and dynamic changes of cf-DNA might be a plausible predictive biomarker for patients at risk of chronic kidney disease (CKD), including individuals with type 2 diabetes mellitus, heart failure, cardiovascular disease and established CKD. Along with it, pre- and posthemodialysis levels of serum cf-DNA appear to be a independent predictor for all-cause mortality in patients with end-stage kidney disease.

Higher β cell death in pregnant women, measured by DNA methylation patterns of cell-free DNA, compared to new-onset type 1 and type 2 diabetes subjects: a cross-sectional study

Diabetes is a metabolic disorder of glucose homeostasis in which β cell destruction occurs silently and is detected mainly when symptoms appear. In the last few years, it has emerged a great interest in developing markers capable of detecting pancreatic β cell death focused on improving early diagnosis and getting a better treatment response, mainly in type 1 diabetes. But other types of diabetes would also benefit from early detection of β cell death. Differentially methylated circulating DNA is being studied as minimally invasive biomarker of cell death. We aimed to explore whether the unmethylated/methylated ratio of the insulin and amylin genes might be a good biomarker of β cell death in different types of diabetes. A lower index ∆Ct indicates a higher rate of β-cell death. Plasma samples from subjects without diabetes, pregnant women, pregnant with gestational diabetes (GDM), type 1 diabetes and type 2 diabetes were analyzed. A qPCR reaction with specific primers for both methylated and unmethylated fragments of insulin and amylin genes were carried out. Pregnant women, GDM and non- GDM, showed a higher β-cell death for both markers (∆INS = 3.8 ± 2.1 and ∆Amylin = 8.5 ± 3.6), whereas T1D presented lower rate (∆INS = 6.2 ± 2.1 and ∆Amylin = 10.7 ± 2.9) comparable to healthy subjects. The insulin methylation index was associated with the newborn birth weight (r = 0.46; p = 0.033) and with insulin resistance (r = -0.533; p = 0.027) in the GDM group. The higher rate of β-cell death was observed in pregnant women independently of their metabolic status. These indexes could be a good indicator of β cell death in processes caused by defects on insulin secretion, insulin action, or both.

Postpartum circulating microRNA enhances prediction of future type 2 diabetes in women with previous gestational diabetes

AIMS/HYPOTHESIS

Type 2 diabetes mellitus is a major cause of morbidity and death worldwide. Women with gestational diabetes mellitus (GDM) have greater than a sevenfold higher risk of developing type 2 diabetes in later life. Accurate methods for postpartum type 2 diabetes risk stratification are lacking. Circulating microRNAs (miRNAs) are well recognised as biomarkers/mediators of metabolic disease. We aimed to determine whether postpartum circulating miRNAs can predict the development of type 2 diabetes in women with previous GDM.

METHODS

In an observational study, plasma samples were collected at 12 weeks postpartum from 103 women following GDM pregnancy. Utilising a discovery approach, we measured 754 miRNAs in plasma from type 2 diabetes non-progressors (n = 11) and type 2 diabetes progressors (n = 10) using TaqMan-based real-time PCR on an OpenArray platform. Machine learning algorithms involving penalised logistic regression followed by bootstrapping were implemented.

RESULTS

Fifteen miRNAs were selected based on their importance in discriminating type 2 diabetes progressors from non-progressors in our discovery cohort. The levels of miRNA miR-369-3p remained significantly different (p < 0.05) between progressors and non-progressors in the validation sample set (n = 82; 71 non-progressors, 11 progressors) after adjusting for age and correcting for multiple comparisons. In a clinical model of prediction of type 2 diabetes that included six traditional risk factors (age, BMI, pregnancy fasting glucose, postpartum fasting glucose, cholesterol and triacylglycerols), the addition of the circulating miR-369-3p measured at 12 weeks postpartum improved the prediction of future type 2 diabetes from traditional AUC 0.83 (95% CI 0.68, 0.97) to an AUC 0.92 (95% CI 0.84, 1.00).

CONCLUSIONS

This is the first demonstration of miRNA-based type 2 diabetes prediction in women with previous GDM. Improved prediction will facilitate early lifestyle/drug intervention for type 2 diabetes prevention.