Analysing Genetic Information Can Help Prevent Complications after Myocardial Infarction
Researchers at HSE University have developed a machine learning (ML) model capable of predicting the risk of complications—major adverse cardiac events—in patients following a myocardial infarction. For the first time, the model incorporates genetic data, enabling a more accurate assessment of the risk of long-term complications. The study has been published in Frontiers in Medicine.
Coronary artery disease (CAD), or ischaemic heart disease (IHD), is a condition characterised by insufficient blood and oxygen supply to the heart from narrowing or blockage of the coronary arteries. It is typically caused by plaques composed of fats and cholesterol that build up on the walls of blood vessels. Coronary heart disease may present as angina (chest pain), myocardial infarction (heart attack), or other problems.
According to WHO, ischaemic heart disease is the world’s biggest killer, responsible for 13% of the total deaths. Therefore, it is crucial to prescribe appropriate treatment to minimise the risks of complications and recurrences. Researchers at HSE University developed a model capable of predicting the probability of major adverse cardiac events following a myocardial infarction.
The scientists analysed data from patients admitted with myocardial infarction to the Surgut District Centre for Diagnostics and Cardiovascular Surgery between 2015 and 2024. Upon admission to the emergency department, medical researchers (cardiologists) explained the main points of the study protocol to the patients and obtained their informed consent to participate. The cardiologists then assessed the condition of the coronary arteries supplying the heart and based on their evaluation, either balloon angioplasty with stenting or coronary artery bypass grafting were performed. All patients received guideline-based therapy, including RAAS-blockers, beta-blockers, statins, and dual antiplatelet therapy. The information was documented in the patients' hospital medical records. For each patient, standard clinical measurements were taken, including blood pressure, body mass index, and cholesterol and glucose levels.
During the laboratory stage, DNA was isolated from the leukocyte rings in the collected blood samples and then frozen at −80°C for future genetic testing. The genotypes were determined based on a specific genetic variation (polymorphism) in the VEGFR-2 gene. The genetic marker VEGFR-2 is a component of the body's signalling system that regulates the growth of new blood vessels. There are three variations of the genotype—C/C, C/T, and T/T—differing in the variation of the DNA nucleotides cytosine (C) or thymine (T) in this region of the gene. Although the marker has been known for a long time, this was the first study to examine its impact on the prognosis of complications following myocardial infarction.
The authors evaluated the impact of 39 factors on the prognosis of risks such as cardiac death, recurrent acute coronary syndrome, stroke, and the need for repeat revascularisation, a procedure that helps restore blood flow in the arteries. To select the best model, the researchers trained and tested several machine learning algorithms: Gradient Boosting (CatBoost and LightGBM), Random Forest, Logistic Regression, and an AutoML approach.
The CatBoost model, a gradient boosting algorithm optimised for working with categorical data rather than numeric values, demonstrated the best performance. It makes predictions by sequentially building and training 'weak' decision trees, where each new tree corrects the errors of the previous ones. When building trees, the algorithm splits the data into two parts: the model is trained on one portion, while errors are calculated on the other. This reduces the risk of overfitting, where the model simply memorises the correct answers, and helps it identify general patterns for making predictions in new, unseen cases.
The influence of features on the model's accuracy was evaluated using the method of sequential feature addition, which assesses their contribution at each stage. The researchers selected the 9 most significant features: gender, body mass index, Charlson comorbidity index (which accounts for the presence of serious concomitant diseases), condition of the lateral wall of the left ventricle, degree of damage to the left coronary artery trunk, number of affected arteries, variant of the VEGFR-2 gene, choice between percutaneous coronary intervention or coronary artery bypass grafting, and statin dosage.
The results showed that the dose of statins, medications used to lower cholesterol levels in the blood, is the most important factor influencing the risk of complications. High doses of statins reduce this risk, particularly in patients with an unfavourable genotype. The VEGFR-2 polymorphism, specifically the presence of the T allele, was ranked fourth in terms of importance.
'Previously, genetic factors were not included in ML models, primarily because sequencing or even genotyping of individual nucleotides is not routinely performed in hospitals. In addition to standard measurements, we had access to data on polymorphism in the VEGFR-2 gene. This allowed us to compare this indicator with others and determine that the risk allele of the VEGFR-2 variant is one of the five most important factors for predicting long-term outcomes in patients with myocardial infarction,' explains Maria Poptsova, Head of the HSE International Laboratory of Bioinformatics and co-author of the paper.
The researchers emphasise that analysing genetic data contributes to creating more accurate and personalised models for predicting the risk of major adverse cardiovascular events in patients following a myocardial infarction.
'Cardiovascular diseases require resources for diagnosis, treatment, rehabilitation, and prevention, and therefore place a significant burden on the healthcare system. The introduction of such models into clinical practice could reduce mortality and the frequency of recurrent infarctions, optimise treatment, and ease the burden on healthcare professionals,' according to Alexander Kirdeev, Research Assistant at the International Laboratory of Bioinformatics and lead author of the paper.
The study was carried out in the framework of HSE University's 'Mirror Laboratories' project.
Alexander Kirdeev
See also:
Cerium Glows Yellow: Chemists Discover How to Control Luminescence of Rare Earth Elements
Researchers at HSE University and the Institute of Petrochemical Synthesis of the Russian Academy of Sciences have discovered a way to control both the colour and brightness of the glow emitted by rare earth elements. Their luminescence is generally predictable—for example, cerium typically emits light in the ultraviolet range. However, the scientists have demonstrated that this can be altered. They created a chemical environment in which a cerium ion began to emit a yellow glow. The findings could contribute to the development of new light sources, displays, and lasers. The study has been published in Optical Materials.
Genetic Prediction of Cancer Recurrence: Scientists Verify Reliability of Computer Models
In biomedical research, machine learning algorithms are often used to analyse data—for instance, to predict cancer recurrence. However, it is not always clear whether these algorithms are detecting meaningful patterns or merely fitting random noise in the data. Scientists from HSE University, IBCh RAS, and Moscow State University have developed a test that makes it possible to determine this distinction. It could become an important tool for verifying the reliability of algorithms in medicine and biology. The study has been published on arXiv.
Habits Stem from Childhood: School Years Found to Shape Leisure Preferences in Adulthood
Moving to a big city does not necessarily lead to dramatic changes in daily habits. A study conducted at HSE University found that leisure preferences in adulthood are largely shaped during childhood and are influenced by where individuals spent their school years. This conclusion was drawn by Sergey Korotaev, Research Fellow at the HSE Faculty of Economic Sciences, from analysing the leisure habits of more than 5,000 Russians.
Russian Scientists Reconstruct Dynamics of Brain Neuron Model Using Neural Network
Researchers from HSE University in Nizhny Novgorod have shown that a neural network can reconstruct the dynamics of a brain neuron model using just a single set of measurements, such as recordings of its electrical activity. The developed neural network was trained to reconstruct the system's full dynamics and predict its behaviour under changing conditions. This method enables the investigation of complex biological processes, even when not all necessary measurements are available. The study has been published in Chaos, Solitons & Fractals.
Researchers Uncover Specific Aspects of Story Comprehension in Young Children
For the first time, psycholinguists from the HSE Centre for Language and Brain, in collaboration with colleagues from the USA and Germany, recorded eye movements during a test to assess narrative skills in young children and adults. The researchers found that story comprehension depends on plot structure, and that children aged five to six tend to struggle with questions about protagonists' internal states. The study findings have been published in the Journal of Experimental Child Psychology.
Scientists Propose Novel Theory on Origin of Genetic Code
Alan Herbert, Scientific Supervisor of the HSE International Laboratory of Bioinformatics, has put forward a new explanation for one of biology's enduring mysteries—the origin of the genetic code. According to his publication in Biology Letters, the contemporary genetic code may have originated from self-organising molecular complexes known as ‘tinkers.’ The author presents this novel hypothesis based on an analysis of secondary DNA structures using the AlphaFold 3 neural network.
See, Feel, and Understand: HSE Researchers to Explore Mechanisms of Movement Perception in Autism
Scientists at the HSE Cognitive Health and Intelligence Centre have won a grant from the Russian Science Foundation (RSF) to investigate the mechanisms of visual motion perception in autism. The researchers will design an experimental paradigm to explore the relationship between visual attention and motor skills in individuals with autism spectrum disorders. This will provide insight into the neurocognitive mechanisms underlying social interaction difficulties in autism and help identify strategies for compensating for them.
Scholars Disprove Existence of ‘Crisis of Trust’ in Science
An international team of researchers, including specialists from HSE University, has conducted a large-scale survey in 68 countries on the subject of trust in science. In most countries, people continue to highly value the work of scientists and want to see them take a more active role in public life. The results have been published in Nature Human Behaviour.
Education System Reforms Led to Better University Performance, HSE Researchers Find
A study by researchers at the HSE Faculty of Economic Sciences and the Institute of Education have found that the number of academic papers published by research universities in international journals has tripled in the past eight years. Additionally, universities have developed more distinct specialisations. Thus, sectoral universities specialising in medical, pedagogical, technical, and other fields are twice as likely to admit students to target places. The study has been published in Vocation, Technology & Education.
Scientists Record GRB 221009A, the Brightest Gamma-Ray Burst in Cosmic History
A team of scientists from 17 countries, including physicists from HSE University, analysed early photometric and spectroscopic data of GRB 221009A, the brightest gamma-ray burst ever recorded. The data was obtained at the Sayan Observatory one hour and 15 minutes after the emission was registered. The researchers detected photons with an energy of 18 teraelectronvolts (TeV). Theoretically, such high-energy particles should not reach Earth, but data analysis has confirmed that they can. The results challenge the theory of gamma radiation absorption and may point to unknown physical processes. The study has been published in Astronomy & Astrophysics.