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

Scientists Discover One of the Longest-Lasting Cases of COVID-19

Scientists Discover One of the Longest-Lasting Cases of COVID-19

© iStock

An international team, including researchers from HSE University, examined an unusual SARS-CoV-2 sample obtained from an HIV-positive patient. Genetic analysis revealed multiple mutations and showed that the virus had been evolving inside the patient’s body for two years. This finding supports the theory that the virus can persist in individuals for years, gradually accumulate mutations, and eventually spill back into the population. The study's findings have been published in Frontiers in Cellular and Infection Microbiology.

Although COVID-19 typically presents as an acute disease, rare cases of persistent, asymptomatic SARS-CoV-2 infection have been documented, most often in immunocompromised patients. Scientists hypothesise that such cases can give rise to dangerous viral variants, defined by the WHO as variants of concern (VOCs).

A team of researchers from Russia, Italy, Switzerland, the UK, and South Africa—including scientists from HSE University—identified a SARS-CoV-2 sample that had accumulated 89 mutations since diverging from its closest known relative. The sample was collected in 2022, while its nearest sequenced neighbour in the phylogenetic tree, obtained in September 2020 and belonging to the B.1.1 lineage, had largely disappeared by 2022. This indicates that SARS-CoV-2 had been persisting, evolving, and accumulating mutations in a single individual’s body for two years—one of the longest documented cases of COVID-19.  

Galya Klink

'The sample came from an HIV-positive patient in Kaluga who had never received highly active antiretroviral therapy (HAART). We had only one sample from her, and in theory, it could have been assumed that this was an acute infection caused by a previously unknown coronavirus variant. However, our analysis showed that such a large number of mutations could have accumulated through acute infections only over roughly seven years of viral circulation in the population—longer than SARS-CoV-2 has existed. Using phylodynamic analysis, we established that the patient had already been living with COVID-19 for two years by the time the sample was collected,' explains Galya Klink, Senior Research Fellow of the International Laboratory of Statistical and Computational Genomics at the HSE University Faculty of Computer Science.

The scientists also found that the virus had been evolving three to four times faster than typical SARS-CoV-2 strains; of the 89 mutations detected, 33 occurred in the spike protein, including changes characteristic of variants with increased transmissibility and antibody resistance. 

In addition, some of the mutations matched those found in wastewater-derived coronavirus variants. Wastewater analysis is routinely used during periods of rising infections, as it often allows new viral variants to be detected earlier than in the population. The presence of mutations in this sample that are characteristic of wastewater rather than the respiratory tract suggests that the virus may have undergone adaptation to the gastrointestinal tract. 

The researchers emphasise that persistent infections are typical in immunosuppressed patients. This highlights the need for close monitoring of such individuals to identify potentially dangerous viral variants in a timely manner.

'Our patient did not infect anyone during the course of her illness. Over time, the sample accumulated mutations that overlapped with those later seen in the Omicron variant, even though Omicron had not yet emerged or spread at that point. This means that the natural selection acting within a single patient differs from that between individuals,' says Klink. 'At the same time, the mutations we observed in the sample support the theory that new, potentially dangerous coronavirus variants can emerge in individuals with weakened immune systems, and that the virus may circulate through different parts of the host’s body.'

See also:

Russian Scientists Propose Method to Speed Up Microwave Filter Design

Researchers at HSE MIEM, in collaboration with colleagues from the Moscow Technical University of Communications and Informatics (MTUCI), have implemented a novel approach to designing microwave filters—generative synthesis using machine learning tools. The proposed method reduces the filter development cycle from several days to just a few minutes and in the future could be applied to the design of other microwave electronic devices. The results were presented at the IEEE International Conference '2026 Systems of Signals Generating and Processing in the Field of on Board Communications.'

Scientists Find That Only Technological Innovations Consistently Advance Environmental Sustainability

Renewable energy and labour productivity do not always contribute to environmental sustainability. Technological innovation is the only factor that consistently has a positive effect. This is the conclusion reached by an international team of researchers, including Natalia Veselitskaya, Leading Research Fellow at the HSE ISSEK Foresight Centre. The study has been published in Sustainable Development.

HSE’s CardioLife Test Among Winners of Data Fusion Awards 2026

The CardioLife genetic test—a development by the Centre for Biomedical Research and Technologies of the AI and Digital Science Institute at HSE University’s Faculty of Computer Science—has won the All-Russian cross-industry Data Fusion Awards, which recognise achievements in data and AI technologies. The project took first place in the Science–Business Partnership category, demonstrating a successful model for transferring technology from university research into the real healthcare sector.

HSE Researchers Train Neural Network to Predict Protein–Protein Interactions More Accurately

Scientists at the AI and Digital Science Institute of the HSE Faculty of Computer Science have developed a model capable of predicting protein–protein interactions with 95% accuracy. GSMFormer-PPI integrates three types of protein data (including information about protein surface properties) to analyse relationships between proteins, rather than simply combining datasets as in previous models. The solution could accelerate the discovery of disease molecular mechanisms, biomarkers, and potential therapeutic targets. The paper has been published in Scientific Reports.

HSE University Installs Geoscan Station at IIT Bombay

A Russian ground station for receiving SONIKS satellite data has been installed on the campus of the Indian Institute of Technology Bombay (IIT Bombay). Developed by Geoscan, the system will become part of a mirror laboratory project run jointly by HSE University and one of India’s leading universities.

HSE MIEM and MTS Launch Workshop on Innovative Solutions in Communication Networks

The HSE Tikhonov Moscow Institute of Electronics and Mathematics (MIEM) and MTS are launching a joint workshop in which students will work at the intersection of communications network engineering, data analysis, and digital technologies. The project is designed as a practice-oriented learning format, enabling students to tackle real industry challenges alongside company engineers and MIEM specialists. Registration to participate in the workshop is open until April 15, 2026.

HSE Scientists Uncover Mechanism Behind Placental Lipid Metabolism Disorders in Preeclampsia

Scientists at HSE University have discovered that in preeclampsia—one of the most severe complications of pregnancy—the placenta remodels its lipid metabolism, reducing its own cholesterol synthesis while increasing cholesterol transfer to the foetus. This compensatory mechanism helps sustain foetal nutrition but accelerates placental deterioration and may lead to preterm birth. The study findings have been published in Frontiers in Molecular Biosciences.

HSE Experts Reveal Low Accuracy of Technology Forecasts in Transportation

HSE researchers evaluated the accuracy of technology forecasts in the transportation sector over the past 50 years and found that the average accuracy rate does not exceed 25%, with the lowest accuracy observed in aviation and rail transport. According to the scientists, this is due to limitations of the forecasting method and the inherent complexities of the sector. The study findings have been published in Technological Forecasting and Social Change.

Wearable Device Data and Saliva Biomarkers Help Assess Stress Resilience

A team of scientists, including researchers from HSE University, has proposed a method for assessing stress resilience using physiological markers derived from wearable devices and saliva samples. The participants who adapted better to stress showed higher heart rate variability, higher zinc concentrations in saliva, and lower potassium levels.  The findings were published in the Journal of Molecular Neuroscience.

HSE Unveils Anthropomorphic Courier Robot

From April 1 to 3, 2026, the Fourth Robotics Festival took place, with the HSE Faculty of Computer Science acting as the main organiser. The event featured the presentation of the anthropomorphic courier robot Arkus. The humanoid was introduced by the Institute for Robotic Systems, established jointly by HSE University and the EFKO Group of Companies.