Structure of circulatory system diseases and their genetic predictors in athletes with high intensity of training and competitive load

Abstract

Introduction: Morphofunctional changes of the circulatory system organs detected in athletes may remain without due attention, as clinical (phenotypic) signs of pathological abnormalities are very similar to manifestations of cardiovascular system adaptation to intensive physical loads. The aim of the study is to propose a personalized algorithm for biomedical support of professional athletes with abnormalities and diseases of the circulatory organs based on clinical and genomic data.Materials and methods: The results of in-depth medical examination (2021-2023) of 15,464 athletes who are members of Russian sports teams were analyzed. The structure of circulatory system diseases according to the codes of the International Classification of Diseases, 10th revision (ICD-10), which were included in the summary report of the last examination, was analyzed. Fifty athletes with abnormalities and diseases of the circulatory system organs, experiencing different degrees of intensity of dynamic and static loads in accordance with the Mitchell classification, were selected from the study sample for full genome sequencing and subsequent clinical interpretation of the obtained data.Results: In the study sample the number of people with pathologic conditions of the circulatory system organs amounted to 6 946 people (45 %). Mitchell classification groups had statistically significant differences with respect to the prevalence of 10 diseases of the circulatory system organs. In 50 DNA samples of professional athletes, 5 probably pathogenic variants (10%), 19 variants with uncertain clinical significance (38%), relevant to the phenotype of a monogenic disease with circulatory system organ damage, were detected.Conclusion: Molecular genetic testing is an effective tool for differential diagnostics of pathologic and adaptive changes in the organs of the circulatory system. Carrying causative genes in combination with clinical signs allows to change the tactics of medical and biological support of an athlete according to the proposed algorithm.