• A
  • A
  • A
  • ABC
  • ABC
  • ABC
  • А
  • А
  • А
  • А
  • А
Regular version of the site

Biologists Discover 'Molecular Fingerprint' of Preeclampsia

Biologists Discover 'Molecular Fingerprint' of Preeclampsia

© iStock

Researchers at HSE University employed a new method to model hypoxia in placental cells during pregnancies complicated by preeclampsia and identified molecular markers of tissue hypoxia. Since hypoxia is one of the key mechanisms underlying preeclampsia, these findings are important for a more accurate and timely diagnosis of the disease and for the development of effective treatment methods. The paper has been published in Placenta.

Preeclampsia is a dangerous pregnancy complication affecting 2–8% of pregnancies worldwide and one of the leading causes of maternal and perinatal mortality. Because the disorder does not manifest immediately, timely diagnosis is often difficult. Symptoms include elevated blood pressure, protein in the urine, and impaired organ function. The early-onset form of preeclampsia, which develops before the 34th week of pregnancy, is particularly dangerous.

Despite many years of research, the mechanisms underlying the disease are still not fully understood, but scientists believe that its origins lie in the early stages of placental development. Direct studies of the placenta are difficult because of technical and ethical limitations, so biologists rely on cellular models to reproduce these processes in the laboratory.

Hypoxia, or oxygen deficiency in placental tissues, is considered one of the key mechanisms underlying preeclampsia. Researchers from the HSE Faculty of Biology and Biotechnology reproduced a hypoxic state using a placenta-on-a-chip model and compared the results with clinical data obtained from women with early- and late-onset preeclampsia. This allowed them to identify molecular changes characteristic of the disease and discover potential biomarkers. 

First, the scientists analysed real-world RNA sequencing data from single placental cells collected from women with early- and late-onset preeclampsia, as well as from women with normal pregnancies. This made it possible to determine which placental cells change their activity during the disease. The researchers compared different types of trophoblast cells—specialised embryonic cells that form the placenta. The results showed that signs of hypoxia are most pronounced in early preeclampsia. Particularly strongly affected are the extravillous trophoblast cells, which are responsible for remodelling the uterine vessels during pregnancy. 

The researchers then identified nine genes whose activity consistently increased across all cell types in preeclampsia, establishing a kind of molecular signature for the disease.

To assess how reliably this molecular signature can be reproduced in the laboratory, the researchers compared two approaches for modelling preeclampsia in a placenta-on-a-chip model based on the BeWo b30 cell line. The first was the conventional method of inducing hypoxia using cobalt chloride. The second was an alternative approach involving an oxyquinoline derivative. They found that the latter more accurately replicated the molecular profile of preeclampsia. Unlike cobalt chloride, which induced numerous non-specific cellular changes, the oxyquinoline-based compound triggered a more targeted and physiologically relevant response.

Evgeny Knyazev

'We wanted to test how closely the laboratory model resembles real preeclampsia. This is very important because we cannot continuously take placental samples from pregnant women, we cannot experiment on patients, and, generally, the placenta is a unique, complex, and highly variable organ,' explains the lead author of the paper, Evgeny Knyazev, Head of the HSE Laboratory of Molecular Physiology. 'We have shown that the widely used cobalt chloride model does not always adequately reflect the processes occurring in the placenta during preeclampsia. In some cases, it even produces opposite changes in the activity of key genes.'

A comparison of the sequencing data with the on-chip cellular model confirmed the key role of hypoxia in triggering changes associated with early-onset preeclampsia. The scientists were able to identify potential molecular factors involved in this process. Of particular interest were the EBI3 and COL17A1 genes, which were identified as universal markers of placental stress. In addition, the researchers discovered hypoxia-associated microRNAs, including miR-27a-5p and miR-193b-5p, as well as several isoforms of microRNA molecules. 

'This is the first time we have conducted such a detailed comparative analysis of real patient samples and laboratory models, which has allowed us to obtain a "molecular fingerprint" of early-onset preeclampsia. Changes in the EBI3 and COL17A1 genes, as well as in certain microRNA molecules, clearly indicate placental dysfunction and can be considered molecular markers of the disease,' emphasises Knyazev.

According to the authors, these findings may contribute to the development of methods for early diagnosis of preeclampsia. In addition, a more accurate cellular model based on oxyquinoline derivatives may help more reliably identify new disease biomarkers and potential therapeutic targets.

The study was conducted with support from the HSE Basic Research Programme as part of the Centres of Excellence project, as well as with support from the Russian Science Foundation (grant 24-14-00382).

See also:

HSE University to Develop Predictive Analytics System for Icebreaker Motors

Industrial automation is one of the key applications of artificial intelligence. A predictive analytics system for large electric motors is among the solutions being developed for the industry as part of HSE University’s Strategic Technological Project ‘Multi-Agent Platform of AI Solutions for Industry-Specific Tasks.’ What is predictive analytics, how can it improve the operation of electric motors, and what specialists joined forces to develop this technology? Anton Zarubin, Dean of the School of Computer Science, Physics, and Technology at HSE University–St Petersburg and the project development coordinator, explains in this interview with the HSE News Service.

Scientific Expedition to Hainan: HSE Scientists Organise Conference on Statistical AI in China

The Statistical AI Conference was held in Sanya, Hainan Island, China, from 24 to 28 August 2026. The international event brought together leading experts in statistics, machine learning, and applied AI. Alexey Naumov, Director of the AI and Digital Science Institute at the HSE Faculty of Computer Science, and Sergey Samsonov, Head of the International Laboratory of Stochastic Algorithms and High-Dimensional Inference, were among the conference organisers.

How to Assess Students’ Knowledge in the Age of AI

A researcher at HSE University has proposed a flowchart to help lecturers decide how to assess students who use artificial intelligence. It shows where the use of AI should be restricted and where it can be incorporated into the learning process. The article has been published in IT Professional.

5th Fall into ML Conference to Bring Together Leading AI Researchers

The AI and Digital Science Institute at the HSE Faculty of Computer Science invites researchers, developers and everyone shaping the future of technology to the fifth, anniversary edition of the Fall into Machine Learning conference (Fall into ML 2026). The event will take place on October 23–24, 2026, at the HSE Cultural Centre in Moscow and will become the key meeting point for Russia’s AI community.

HSE University Expands Cooperation with Malaysia in Technology Foresight

HSE University researchers will take part in a study of the future of engineering education in Malaysia, while the Malaysian Industry-Government Group for High Technology (MIGHT) will use the iFORA big-data analysis system to validate the findings of its foresight research. These are the outcomes of a visit by HSE representatives to Kuala Lumpur.

Scientists Train Neural Network to Generate Process Plans from 3D Models

Researchers at the HSE FCS AI and Digital Science Institute have developed CAD2TechSpec, a framework that converts 3D models of mechanical parts into machining process plans—step-by-step instructions for machine tools. The solution aims to reduce the time required for the design and preparation of technical process documentation in mechanical engineering, aircraft manufacturing, and other high-tech industries. The study findings have been published in PeerJ Computer Science.

Laboratory of Future Networks: HSE Telecommunications Research Institute Develops 5G/6G Research Testbed

The 5G/6G testbed at the HSE Telecommunications Research Institute is becoming a research platform, an educational laboratory, and a foundation for developing new software components for future networks. It makes it possible not only to observe how a mobile network operates, but also to change its operating conditions and measure the results: data-transmission speed, latency, errors, radio-resource utilisation, and other parameters. Based on the testbed, researchers plan to develop MIMO, O-RAN, xApp, and IAB technologies, as well as experiment with artificial intelligence.

‘Hedgehog’ Versus ‘Relatives’: Researchers Measure How the Brain Responds to Unexpected Words During Natural Speech

Russian neurophysiologists, including researchers from HSE University, have demonstrated the feasibility of using event-related fields (ERFs) to study brain activity during natural speech perception. The researchers showed that this approach can be applied not only to individual words but also to continuous speech. Their findings indicate that words whose meanings differ significantly from the preceding context require longer processing times. The study also reveals that the brain processes function words in two stages: first, it identifies their grammatical role and then uses this information to predict the next word. The study has been published in Frontiers in Human Neuroscience.

HSE Researchers Create New Corpus of Early Child Speech in Russian

Researchers at the HSE Centre for Language and Brain have presented RusLan-M, an open multimedia corpus that makes it possible to trace the development of early child speech in Russian from first words to the emergence of complex grammatical constructions. The database contains around 41 hours of video recordings and more than 35,000 child utterances. The new resource will help researchers study more precisely how children acquire Russian and, in the longer term, develop more reliable tools for assessing speech development. The study has been published in Language Resources and Evaluation.

Hybrid Intelligence: Competencies in the Age of AI Discussed at Technoprom-2026

Artificial intelligence is not creating new professions, but rather transforming the nature of existing ones. This was the conclusion reached by participants in the panel session ‘Hybrid Intelligence: Digital and Human Drivers of Development,’ organised by the Institute for Statistical Studies and Economics of Knowledge (ISSEK) at HSE University as part of the 13th International Forum of Technological Development (Technoprom-2026). The experts discussed how the nature of work is changing, which skills are becoming increasingly sought after, and what prevents companies from fully capitalising on new technologies.