Advances in extracellular vesicles as mediators of cell-to-cell communication in pregnancy.

Cell-to-cell communication mediated by Extracellular Vesicles (EVs) is a novel and emerging area of research, especially during pregnancy, in which placenta derived EVs can facilitate the feto-maternal communication. EVs comprise a heterogeneous group of vesicle sub-populations with diverse physical and biochemical characteristics and originate by specific biogenesis mechanisms. EVs transfer molecular cargo (including proteins, nucleic acids, and lipids) between cells and are critical mediators of cell communication. There is growing interest among researchers to explore into the molecular cargo of EVs and their functions in a physiological and pathological context. For example, inflammatory mediators such as cytokines are shown to be released in EVs and EVs derived from immune cells play key roles in mediating the immune response as well as immunoregulatory pathways. Pregnancy complications such as gestational diabetes mellitus, preeclampsia, intrauterine growth restriction and preterm birth are associated with altered levels of circulating EVs, with differential EV cargo and bioactivity in target cells. This implicates the intriguing roles of EVs in reprogramming the maternal physiology during pregnancy. Moreover, the capacity of EVs to carry bioactive molecules makes them a promising tool for biomarker development and targeted therapies in pregnancy complications. This review summarizes the physiological and pathological roles played by EVs in pregnancy and pregnancy-related disorders and describes the potential of EVs to be translated into clinical applications in the diagnosis and treatment of pregnancy complications.

Early-Pregnancy Serum Maternal and Placenta-Derived Exosomes miRNAs Vary Based on Pancreatic ß-Cell Function in GDM.

CONTEXT: Pancreatic ß-cell function impairment is a key mechanism for developing gestational diabetes mellitus (GDM). Maternal and placental exosomes regulate maternal and placental responses during hyperglycemia. Studies have associated exosomal micro-RNAs (miRNAs) with GDM development. To date, no studies have been reported that evaluate the profile of miRNAs present in maternal and placental exosomes in the early stages of gestation from pregnancies that develop GDM. OBJECTIVE: We assessed whether early-pregnancy serum maternal and placenta-derived exosomes miRNA profiles vary according to pancreatic ß-cell function in women who will develop GDM. METHODS: A prospective nested case-control study was used to identify exosomal miRNAs that vary in early-pregnancy stages (<18 weeks of gestation) from women with normoglycemia and those who developed GDM based on their pancreatic ß-cell function using the homeostasis model assessment of pancreatic ß-cell function (HOMA-%ß) index. Early-pregnancy serum maternal and placenta-derived exosomes were isolated to obtain miRNA profiles. Potential target and pathway analyses were performed to identify molecular and metabolic pathways associated with the exosomal miRNAs identified. RESULTS: In early-pregnancy stages, serum maternal exosome size and concentration are modified in GDM group and fluctuate according to HOMA-%ß index. Serum maternal exosomal hsa-miR-149-3p and hsa-miR-455-3p in GDM are related to insulin secretion and signaling, lipolysis, and adipocytokine signaling. Early-pregnancy serum placenta-derived exosomes hsa-miR-3665 and hsa-miR-6727-5p in GDM are related to regulating genes involved in response to immunological tolerance of pregnancy and pathways associated with placental dysfunction. CONCLUSION: Early serum exosomal miRNAs differ depending on their origin (maternal or placental) and pancreatic ß-cell function. This research provides insights into the interactions between maternal and placental exosomal miRNAs and may have implications for identifying potential biomarkers or therapeutic targets for GDM.

An early prediction model for gestational diabetes mellitus based on metabolomic biomarkers.

BACKGROUND: Gestational diabetes mellitus (GDM) represents the main metabolic alteration during pregnancy. The available methods for diagnosing GDM identify women when the disease is established, and pancreatic beta-cell insufficiency has occurred.The present study aimed to generate an early prediction model (under 18 weeks of gestation) to identify those women who will later be diagnosed with GDM. METHODS: A cohort of 75 pregnant women was followed during gestation, of which 62 underwent normal term pregnancy and 13 were diagnosed with GDM. Targeted metabolomics was used to select serum biomarkers with predictive power to identify women who will later be diagnosed with GDM. RESULTS: Candidate metabolites were selected to generate an early identification model employing a criterion used when performing Random Forest decision tree analysis. A model composed of two short-chain acylcarnitines was generated: isovalerylcarnitine (C5) and tiglylcarnitine (C5:1). An analysis by ROC curves was performed to determine the classification performance of the acylcarnitines identified in the study, obtaining an area under the curve (AUC) of 0.934 (0.873-0.995, 95% CI). The model correctly classified all cases with GDM, while it misclassified ten controls as in the GDM group. An analysis was also carried out to establish the concentrations of the acylcarnitines for the identification of the GDM group, obtaining concentrations of C5 in a range of 0.015-0.25 µmol/L and of C5:1 with a range of 0.015-0.19 µmol/L. CONCLUSION: Early pregnancy maternal metabolites can be used to screen and identify pregnant women who will later develop GDM. Regardless of their gestational body mass index, lipid metabolism is impaired even in the early stages of pregnancy in women who develop GDM.

Metabolic flexibility during normal pregnancy allows appropriate adaptation during gestation independently of BMI.

BACKGROUND & AIMS: Overweight and obesity in reproductive-age women hasten the development of insulin resistance and increase risk for deterioration of pregnancy metabolism. These pregnancy-associated metabolic changes are similar to those of the metabolic syndrome. Thus, some metabolic flexibility must allow appropriate adaptation to the metabolic load that pregnancy imposes. We evaluated metabolic flexibility during uncomplicated pregnancy in women with pre-gestational normal weight or overweight. METHODS: In 20 women with singleton pregnancies, pre-pregnancy BMI was categorized as normal-weight (Nw) or overweight (Ow). The women were seen quarterly, and fasting and postprandial blood samples were collected at each visit. Indirect fasting and/postprandial calorimetry was performed to evaluate metabolic flexibility (Δrespiratory quotient (RQ) = RQpostprandial - RQfasting). RESULTS: In the first trimester, metabolic flexibility was lower in the Ow group compared to the Nw group (0.031 ± 0.0131 vs 0.077 ± 0.018, respectively) without a statistically significant difference (p = 0.053). In the second trimester, the Ow group was significantly more flexible than the Nw group (0.190 ± 0.016 vs 0.077 ± 0.015, respectively (p = 0.004)). For the third trimester, the Ow and Nw groups did not differ in metabolic flexibility (0.074 ± 0.013 vs 0.087 ± 0.021, respectively) (p = 0.40). The most influential variables for metabolic flexibility during pregnancy were lactate, leptin, ß-hydroxybutyrate, glycerol, aromatic amino acids, medium and long chain acylcarnitine's. CONCLUSIONS: Our findings indicate that metabolic flexibility changes throughout pregnancy, independently of pre-pregnancy BMI. These changes maintain metabolic homeostasis between the mother and foetus, allowing for appropriate adjustments during pregnancy.