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Updated: Oct 12, 2025
Author Spotlight: Modeling an Aspect of Preeclampsia in Female Mice Using Hypoxic Human Placenta-Derived Small Extracellular Vesicles
Published on: January 26, 2024
Technologies for Prediction of Preeclampsia
E A Rokоtyanskаya1, I A Panova2, A I Malyshkina3
1Associate Professor, Department of Obstetrics and Gynecology, Neonatology, Anesthesiology, and Reanimatology; Ivanovo Research Institute of Motherhood and Childhood named after V.N. Gorodkov, Ministry of Health of the Russian Federation, 20 Pobeda St., Ivanovo, 153045, Russia.
This study developed a predictive model for preeclampsia (PE) using biomedical and genetic factors. The technology identifies high-risk pregnancies for timely intervention and personalized care.
Area of Science:
- Obstetrics and Gynecology
- Medical Genetics
- Cardiovascular Medicine
Background:
- Preeclampsia (PE) is a serious pregnancy complication.
- Identifying predictors for PE, especially in women with chronic arterial hypertension (CAH), is crucial for maternal health.
- Existing prediction methods may not fully capture the multifactorial nature of PE.
Purpose of the Study:
- To develop technologies for predicting preeclampsia (PE) development.
- To utilize biomedical and molecular-genetic predictors for individual risk assessment.
- To create a computational tool for early PE risk identification in pregnant women.
Main Methods:
- Retrospective analysis of 457 pregnant women, including those with CAH and PE.
- Risk factor calculation using Open Epi and logistic regression.
- Identification of gene polymorphisms (NOS3, AGTR2, AGT, CYP11B2, GNB3) associated with vascular tone.
Main Results:
- Identified clinical risk factors for PE, including in women with CAH (e.g., pyelonephritis, high BMI, family history).
- Discovered genetic predictors: NOS3, AGTR2, AGT, CYP11B2, GNB3 polymorphisms are associated with CAH and PE risk.
- Developed a predictive method and risk calculation model for PE in women with CAH, forming the basis for a computer program.
Conclusions:
- The developed technologies enable timely identification of high-risk pregnancies for PE.
- Individual risk calculation facilitates a personalized approach to preventive measures.
- The system supports the need for additional examinations in high-risk pregnant individuals.
