Researchers Reveal Genetic Predisposition to Severe COVID-19
HSE University researchers have become the first in the world to discover genetic predisposition to severe COVID-19. The results of the study were published in the journal Frontiers in Immunology.
T-cell immunity is one of the key mechanisms used by the human body to fight virus infections. The staging ground for cell immunity development is the presentation of virus peptides on the surface of infected cells. This is followed by activation of T lymphocytes, which start to destroy the infected cells.
The ability to successfully present virus peptides is largely determined by genetics. In human cells, human leukocyte antigen class I (HLA-I) molecules are responsible for this presentation. The set of six such molecules is unique in every human and is inherited from an individual’s parents. In simple terms, if the set of alleles detects the virus well, then the immune cells will detect and destroy the infected cells fast; if a person has a set that is bad at such detection, a more severe case of disease is more likely to be observed.
Researchers from the HSE Faculty of Biology and Biotechnology–Maxim Shkurnikov, Stepan Nersisyan, Alexei Galatenko and Alexander Tonevitsky–joined their peers from Pirogov Russian National Research Medical University and Filatov City Clinical Hospital (Tatjana Jankevic, Ivan Gordeev, Valery Vechorko) to study the correlation between HLA-I genotype and the severity of COVID-19.
Using machine learning, they built a model that provides an integral assessment of the possible power of T-cell immune response to COVID-19: if the set of HLA-I alleles allows for effective presentation of the SARS-CoV-2 virus peptides, those individuals received low risk score, while people with lower presentation capability received higher risk scores (in the range from 0 to 100). To validate the model, genotypes of over 100 patients who had suffered from COVID-19 and over 400 healthy people (the control group) were analysed. It turned out that the modelled risk score is highly effective in predicting the severity of COVID-19.
In addition to analysing the Moscow population, the researchers used their model on a sample of patients from Madrid, Spain. The high precision of prediction was confirmed on this independent sample as well: the risk score of patients suffering severe COVID-19 was considerably higher than in patients with moderate and mild cases of the disease.
‘In addition to the discovered correlations between the genotype and COVID-19 severity, the suggested approach also helps to evaluate how a certain COVID-19 mutation can affect the development of T-immunity to the virus. For example, we will be able to detect groups of patients for whom infection with new strains of SARS-CoV-2 can lead to more severe forms of the disease,’ Alexander Tonevitsky said.
A team of researchers, including scientists of the HSE Faculty of Biology and Biotechnology, have analysed the evolutionary path of the coronavirus from the Wuhan variant to Omicron. Their findings indicate that many genomic mutations in SARS-CoV-2 are shaped by processes occurring in the intestines and lungs, where the virus acquires the ability to evade the inhibitory effects of microRNA molecules. The study findings have been published in the Journal of Medical Virology.
HSE researchers, in collaboration with their colleagues from Skoltech and the Central Research Institute for Epidemiology, have uncovered the mechanisms behind the emergence of new and dangerous coronavirus variants, such as Alpha, Delta, Omicron, and others. They have discovered that the likelihood of a substitution occurring at a specific site of the SARS-CoV-2 genome is dependent on concordant substitutions occurring at other sites. This explains why new and more contagious variants of the virus can emerge unexpectedly and differ significantly from those that were previously circulating. The study’s findings have been published in eLife.
Russian researchers have developed a strategy to create a cheap and rapid COVID-19 test based on isothermal amplification. According to their publication in Applied Biochemistry and Microbiology, use of this strategy will make it possible to create universal test systems for any of the COVID-19 variants.
HSE social and political analysts have established which value models and circumstances promote support for restrictive government policies aimed at combatting the coronavirus pandemic. The research is published in Plos One.
Researchers from the HSE Faculty of Economic Sciences have proposed a mathematical model that describes the course of the COVID-19 pandemic, taking into account the restrictions applied in different countries. The model will help governments make reasonable and timely decisions on introducing or lifting restrictions. The paper was published in Eurasian Economic Review.
HSE University researchers assessed the effectiveness of the T-cell immune response to 11 variants of SARS-CoV-2. Their findings have been published in Nucleic Acids Research.
The new regulations ‘On the Organization of Studies for the 2021/2022 Academic Year’ feature in detail what will change for first-year students in the new academic year. HSE University will be organizing a vaccination drive in September for students aged 18 and over who are unvaccinated. Younger students will be eligible for vaccination once they turn 18.
Starting September 1, 2021, HSE University-Moscow is introducing new safety policies on campus to prevent the spread of COVID-19. They apply to students over 18 years old who have not had COVID during the last six months, have not been vaccinated (with a Russian or a foreign vaccine), nor have a medical exemption from vaccination. Free vaccination will be available on campus to all arriving students.
Researchers of HSE Tikhonov Moscow Institute of Electronics and Mathematics (MIEM), in cooperation with their colleagues from the University of California, Santa Cruz (UCSC), and The European Bioinformatics Institute (EMBL-EBI), have developed software to model the spread of the COVID-19 global pandemic. This is the world’s fastest Viral Genealogy Simulator (VGsim). For more details about this scalable simulator, read the reprint on medRxiv. The code is freely available at GitHub.