Prospecting of exosomal-miRNA signatures as prognostic marker for gestational diabetes mellitus and other adverse pregnancy outcomes

Abstract

Exosomal microRNA (ExomiRs) serves as potential cargo molecules responsible for post-translation of gene expression and intracellular communication playing a vital role in acting as clinically relevant prognostic biomarkers for identifying pregnancy-associated complications in patients. ExomiRs are associated with Gestational Diabetes Mellitus (GDM) as potential targets for understanding the pathophysiology of beta-cell dysfunction. ExomiRs (ExomiR 122, ExomiR 16-5p, ExomiR 215-5p, ExomiR 450b-3p, ExomiR 122-5p) aid to act as biomarkers and regulate the progression of diabetes and its related complication. These ExomiRshave been reported to interfere with the regulation of various genes such as ZEB2, IRS1, IRS2, GLUT1, GLUT4, etc. and inhibition of several pathways like PI3K/AKT, Wnt, and mTOR signaling pathways leading to the modulation in the development of GDM affecting the clinical and pathological features of women. These ExomiRs have also been associated with other pregnancy-associated complications, including preeclampsia, hypothyroidism, pregnancy loss, and ectopic pregnancies. On the other hand, overexpression of certain ExomiRs such as Exomir-515-5p, ExomiR-221, and ExomiR-96 serve a regulatory role in overcoming insulin resistance. Taken together, the current review focuses on the prospective capabilities of ExomiRs for diagnosis and clinical prognosis of GDM women with respect to pregnancy outcomes.

Keywords: clinical prognosis; exosomal microRNA; gestational diabetes mellitus; pregnancy outcomes; signaling pathways.

Figure 1

Depicts the packaging of miRNAs into exosomes during exosomal biogenesis resulting in the formation of ExomiRs, which helps in the biodelivery of miRNAs. (A) The miRNAs packaging during Exosome biogenesis occurs by sumoylated hnRNPA2B with the help of hnRNPA1 and hnRNPC. (B) Packagingof miRNA can also be done alternatively by nsMase2 with the help of hnRNPA1 and hnRNPC.

Figure 2

Depicts the association between the concentration of ExomiRs in maternal peripheral blood, which serves as a marker for placental health. (A) The concentration of ExomiRs in the maternal circulatory system is normal before pregnancy. (B) During complicated pregnancies like in GDM patients, the ExomiR concentrations, beginning from the first trimester, are observed to be altered, with most being upregulated and few being downregulated. (C) The ExomiR concentration is observed to be decreased after delivery and gets back to normal 48 hours postpartum.

Figure 3

Depicts the overexpression of ExomiR in GDM patients, which results in their interference with the regulation of various genes and signaling pathways leading to several maternal and teratogenic outcomes thereby also acting as prognostic biomarkers for the GDM and its associated complications.

Figure 4

Shows the integration of digitized signals from the molecular markers, epidemiological data, as well as clinical data for the development of AI-enabled nowcasting and forecasting system, which when combined with the mobile-health-based health literacy modules, will help in the deployment of the federated learning-based detection of emergent hotspots of the Gestational diabetes (GDM)and its associated complications among pregnant women for the precision-oriented clinical management of the disease. This AI-enabled platform also forms the rationale for niche-specific allocation of the clinical resources at the community level.