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ORIGINAL RESEARCH article
Front. Cell Dev. Biol.
Sec. Molecular and Cellular Pathology
Volume 12 - 2024 |
doi: 10.3389/fcell.2024.1461547
This article is part of the Research Topic Advancements in Understanding and Managing Preeclampsia: Exploring Molecular Mechanisms, Biomarkers, and Clinical Implications View all articles
First-Trimester Predictive Models for Adverse Pregnancy Outcomes -A Base for Implementation of Strategies to Prevent Cardiovascular Disease Development
Provisionally accepted- 1 Dpt. of Molecular Biology and Cell Pathology, Third Faculty of Medicine, Charles University, Prague, Czechia
- 2 Institute for the Care of Mother and Child (Czechia), Prague, Prague, Czechia
- 3 Third Faculty of Medicine, Charles University, Prague, Prague, Czechia
Introduction: This study aimed to establish efficient, cost-effective, and early predictive models for adverse pregnancy outcomes based on the combinations of a minimum number of miRNA biomarkers, whose altered expression was observed in specific pregnancy-related complications and selected maternal clinical characteristics. Material and methods: This retrospective study included singleton pregnancies with gestational hypertension (GH, n=83), preeclampsia (PE, n=66), HELLP syndrome (n=14), fetal growth restriction (FGR, n=82), small for gestational age (SGA, n=37), gestational diabetes mellitus (GDM, n=121), preterm birth in the absence of other complications (n=106), late miscarriage (n= 34), stillbirth (n= 24), and 80 normal term pregnancies. MiRNA gene expression profiling was performed on the whole peripheral venous blood samples collected between 10 to 13 weeks of gestation using real-time reverse transcription polymerase chain reaction (RT-PCR). Results: Most pregnancies with adverse outcomes were identified using the proposed approach (the combinations of selected miRNAs and appropriate maternal clinical characteristics) (GH, 69.88%; PE, 83.33%; HELLP, 92.86%; FGR, 73.17%; SGA, 81.08%; GDM on therapy, 89.47%; and late miscarriage, 84.85%). In the case of stillbirth, no addition of maternal clinical characteristics to the predictive model was necessary because a high detection rate was achieved by a combination of miRNA biomarkers only 91.67% cases at 10.0% false positive rate (FPR) .The proposed models based on the combinations of selected cardiovascular disease-associated miRNAs and maternal clinical variables have a high predictive potential for identifying women at increased risk of adverse pregnancy outcomes; this can be incorporated into routine firsttrimester screening programs. Preventive programs can be initiated based on these models to lower cardiovascular risk and prevent the development of metabolic/cardiovascular/cerebrovascular diseases because timely implementation of beneficial lifestyle strategies may reverse the dysregulation of miRNAs maintaining and controlling the cardiovascular system.
Keywords: First-trimester screening, cardiovascular risk, miRNA, predictive models, Preventive program, Risk factors
Received: 08 Jul 2024; Accepted: 26 Aug 2024.
Copyright: © 2024 Hromadnikova, Kotlabova and Krofta. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence:
Ilona Hromadnikova, Dpt. of Molecular Biology and Cell Pathology, Third Faculty of Medicine, Charles University, Prague, Czechia
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