First trimester plasma microRNAs levels predict Matsuda Index-estimated insulin sensitivity between 24th and 29th week of pregnancy

Pathophysiology from preconception, during pregnancy, and beyond

Gestational diabetes is the most common medical complication in pregnancy. Historically, gestational diabetes was considered a pregnancy complication involving treatment of rising glycaemia late in the second trimester. However, recent evidence challenges this view. Pre-pregnancy and pregnancy-specific factors influence gestational glycaemia, with open questions regarding roles of non-glycaemic factors in the aetiology and consequences of gestational diabetes. Varying patterns of insulin secretion and resistance in early and late pregnancy underlie a heterogeneity of gestational diabetes in the timing and pathophysiological subtypes with clinical implications: early gestational diabetes and insulin resistant gestational diabetes subtypes are associated with a higher risk of pregnancy complications. Metabolic perturbations of early gestational diabetes can affect early placental development, affecting maternal metabolism and fetal development. Fetal hyperinsulinaemia can affect the development of multiple fetal tissues, with short-term and long-term consequences. Pregnancy complications are prevented by managing glycaemia in early and late pregnancy in some, but not all women with gestational diabetes. A better understanding of the pathophysiology and heterogeneity of gestational diabetes will help to develop novel management approaches with focus on improved prevention of maternal and offspring short-term and long-term complications, from pre-conception, throughout pregnancy, and beyond.

First-Trimester Plasmatic microRNAs Are Associated with Fasting Glucose Levels in Late Second Trimester of Pregnancy

Maternal blood glucose regulation adaptation to pregnancy aims to support fetal growth but may also lead to the development of gestational diabetes mellitus, the most common pregnancy complication. MiRNAs are small RNA molecules secreted and stable in the blood, where they could have paracrine hormone-like functions (ribo-hormone) and regulate metabolic processes including fetal growth and glucose metabolism. The objective of this study was to identify plasmatic microRNA (miRNAs) measured during the first trimester of pregnancy that were associated with glucose levels during a 75 g oral glucose tolerance test (OGTT) at ~26 weeks of pregnancy. miRNAs were quantified using next-generation sequencing in 444 pregnant women and replicated in an independent cohort of 106 pregnant women. MiRNAs associated with glucose levels were identified with the DESeq2 package. We identified 24 miRNAs associated with fasting glycemia, of which 18 were common to both cohorts (q-value < 0.1). However, no association was found between miRNAs and 1 h or 2 h post OGTT glycemia. To conclude, we identified 18 miRNAs early in pregnancy that were associated with fasting blood glucose measured 3 months later. Our findings offer new insights into the mechanisms involved in fasting glucose homeostasis regulation in pregnancy, which is critical to understanding how gestational diabetes develops.

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.

Genetics and Epigenetics: Implications for the Life Course of Gestational Diabetes

Gestational diabetes (GDM) is one of the most common complications of pregnancy, affecting as many as one in six pregnancies. It is associated with both short- and long-term adverse outcomes for the mother and fetus and has important implications for the life course of affected women. Advances in genetics and epigenetics have not only provided new insight into the pathophysiology of GDM but have also provided new approaches to identify women at high risk for progression to postpartum cardiometabolic disease. GDM and type 2 diabetes share similarities in their pathophysiology, suggesting that they also share similarities in their genetic architecture. Candidate gene and genome-wide association studies have identified susceptibility genes that are shared between GDM and type 2 diabetes. Despite these similarities, a much greater effect size for MTNR1B in GDM compared to type 2 diabetes and association of HKDC1, which encodes a hexokinase, with GDM but not type 2 diabetes suggest some differences in the genetic architecture of GDM. Genetic risk scores have shown some efficacy in identifying women with a history of GDM who will progress to type 2 diabetes. The association of epigenetic changes, including DNA methylation and circulating microRNAs, with GDM has also been examined. Targeted and epigenome-wide approaches have been used to identify DNA methylation in circulating blood cells collected during early, mid-, and late pregnancy that is associated with GDM. DNA methylation in early pregnancy had some ability to identify women who progressed to GDM, while DNA methylation in blood collected at 26-30 weeks gestation improved upon the ability of clinical factors alone to identify women at risk for progression to abnormal glucose tolerance post-partum. Finally, circulating microRNAs and long non-coding RNAs that are present in early or mid-pregnancy and associated with GDM have been identified. MicroRNAs have also proven efficacious in predicting both the development of GDM as well as its long-term cardiometabolic complications. Studies performed to date have demonstrated the potential for genetic and epigenetic technologies to impact clinical care, although much remains to be done.

Analysis of Circulating C19MC MicroRNA as an Early Marker of Hypertension and Preeclampsia in Pregnant Patients: A Systematic Review

Preeclampsia and hypertension complicate several pregnancies. Identifying women at risk of developing these conditions is essential to establish potential treatment modalities. Biomarkers such as C19MC microRNA in pregnant patients wopuld assist in defining pregnancy surveillance and implementing interventions. This study sought to analyze circulating C19MC microRNA as an early marker of hypertension and preeclampsia in pregnant patients. A systematic review was undertaken using the following registers: disease registries, pregnancy registries, and pregnancy exposure registries, and the following databases: PubMed, CINAHL, Web of Science, Scopus, and EMBASE. The risk of bias was assessed using the Cochrane technique. From the 45 publications retrieved from the registers and databases, only 21 were included in the review after the removal of duplicates, screening, and eligibility evaluation. All 210 publications had a low risk of bias and illuminated the potential use of circulating C19MC microRNA as an early marker of hypertension and preeclampsia in pregnant patients. Therefore, it was concluded that C19MC microRNA can be used as an early marker of gestational preeclampsia and hypertension.

Cardiovascular Disease-Associated MicroRNAs as Novel Biomarkers of First-Trimester Screening for Gestational Diabetes Mellitus in the Absence of Other Pregnancy-Related Complications

We assessed the diagnostic potential of cardiovascular disease-associated microRNAs for the early prediction of gestational diabetes mellitus (GDM) in singleton pregnancies of Caucasian descent in the absence of other pregnancy-related complications. Whole peripheral venous blood samples were collected within 10 to 13 weeks of gestation. This retrospective study involved all pregnancies diagnosed with only GDM (n = 121) and 80 normal term pregnancies selected with regard to equality of sample storage time. Gene expression of 29 microRNAs was assessed using real-time RT-PCR. Upregulation of 11 microRNAs (miR-1-3p, miR-20a-5p, miR-20b-5p, miR-23a-3p, miR-100-5p, miR-125b-5p, miR-126-3p, miR-181a-5p, miR-195-5p, miR-499a-5p, and miR-574-3p) was observed in pregnancies destinated to develop GDM. Combined screening of all 11 dysregulated microRNAs showed the highest accuracy for the early identification of pregnancies destinated to develop GDM. This screening identified 47.93% of GDM pregnancies at a 10.0% false positive rate (FPR). The predictive model for GDM based on aberrant microRNA expression profile was further improved via the implementation of clinical characteristics (maternal age and BMI at early stages of gestation and an infertility treatment by assisted reproductive technology). Following this, 69.17% of GDM pregnancies were identified at a 10.0% FPR. The effective prediction model specifically for severe GDM requiring administration of therapy involved using a combination of these three clinical characteristics and three microRNA biomarkers (miR-20a-5p, miR-20b-5p, and miR-195-5p). This model identified 78.95% of cases at a 10.0% FPR. The effective prediction model for GDM managed by diet only required the involvement of these three clinical characteristics and eight microRNA biomarkers (miR-1-3p, miR-20a-5p, miR-20b-5p, miR-100-5p, miR-125b-5p, miR-195-5p, miR-499a-5p, and miR-574-3p). With this, the model identified 50.50% of GDM pregnancies managed by diet only at a 10.0% FPR. When other clinical variables such as history of miscarriage, the presence of trombophilic gene mutations, positive first-trimester screening for preeclampsia and/or fetal growth restriction by the Fetal Medicine Foundation algorithm, and family history of diabetes mellitus in first-degree relatives were included in the GDM prediction model, the predictive power was further increased at a 10.0% FPR (72.50% GDM in total, 89.47% GDM requiring therapy, and 56.44% GDM managed by diet only). Cardiovascular disease-associated microRNAs represent promising early biomarkers to be implemented into routine first-trimester screening programs with a very good predictive potential for GDM.

Maternal Body Mass Index Is Associated with Profile Variation in Circulating MicroRNAs at First Trimester of Pregnancy

Many women enter pregnancy with overweight and obesity, which are associated with complications for both the expectant mother and her child. MicroRNAs (miRNAs) are short non-coding RNAs that regulate many biological processes, including energy metabolism. Our study aimed to identify first trimester plasmatic miRNAs associated with maternal body mass index (BMI) in early pregnancy. We sequenced a total of 658 plasma samples collected between the 4th and 16th week of pregnancy from two independent prospective birth cohorts (Gen3G and 3D). In each cohort, we assessed associations between early pregnancy maternal BMI and plasmatic miRNAs using DESeq2 R package, adjusting for sequencing run and lane, gestational age, maternal age at the first trimester of pregnancy and parity. A total of 38 miRNAs were associated (FDR q < 0.05) with BMI in the Gen3G cohort and were replicated (direction and magnitude of the fold change) in the 3D cohort, including 22 with a nominal p-value < 0.05. Some of these miRNAs were enriched in fatty acid metabolism-related pathways. We identified first trimester plasmatic miRNAs associated with maternal BMI. These miRNAs potentially regulate fatty acid metabolism-related pathways, supporting the hypothesis of their potential contribution to energy metabolism regulation in early pregnancy.

First Trimester Plasma MicroRNA Levels Predict Risk of Developing Gestational Diabetes Mellitus

AIMS

Our objective is to identify first-trimester plasmatic miRNAs associated with and predictive of GDM.

METHODS

We quantified miRNA using next-generation sequencing in discovery (Gen3G: n = 443/GDM = 56) and replication (3D: n = 139/GDM = 76) cohorts. We have diagnosed GDM using a 75-g oral glucose tolerance test and the IADPSG criteria. We applied stepwise logistic regression analysis among replicated miRNAs to build prediction models.

RESULTS

We identified 17 miRNAs associated with GDM development in both cohorts. The prediction performance of hsa-miR-517a-3p|hsa-miR-517b-3p, hsa-miR-218-5p, and hsa-let7a-3p was slightly better than GDM classic risk factors (age, BMI, familial history of type 2 diabetes, history of GDM or macrosomia, and HbA1c) (AUC 0.78 vs. 0.75). MiRNAs and GDM classic risk factors together further improved the prediction values [AUC 0.84 (95% CI 0.73-0.94)]. These results were replicated in 3D, although weaker predictive values were obtained. We suggest very low and higher risk GDM thresholds, which could be used to identify women who could do without a diagnostic test for GDM and women most likely to benefit from an early GDM prevention program.

CONCLUSIONS

In summary, three miRNAs combined with classic GDM risk factors provide excellent prediction values, potentially strong enough to improve early detection and prevention of GDM.