Сluster analysis of immunograms of trainees with different levels of motor activity
- Authors: Kolupaev V.А.1, Sashenkov S.L.1, Kotova N.V.1
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Affiliations:
- South Ural State Medical University
- Issue: Vol 28, No 3 (2025)
- Pages: 861-866
- Section: SHORT COMMUNICATIONS
- URL: https://journals.rcsi.science/1028-7221/article/view/319946
- DOI: https://doi.org/10.46235/1028-7221-17183-CAO
- ID: 319946
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Abstract
The state of immune system may severely limit abilities of the body to adapt to physical exercises. Certain combinations of immunogram indexes associated with non-specific resistance when adapting to muscle work may prospectively reflect a significant decrease in reliable functioning of these protective mechanisms. In this case, systematization of immunogram-derived indices in persons with different motor habits is relevant to clarify the principles of dosing muscle loads adequate to the state of the non-specific resistance mechanisms and immunoreactivity. The purpose of the study was to reduce the number of studied variables by differentiating the sample into subgroups in order to identify similar patterns for the grouped objects. In students aged 18-24 years (boys n = 40 and girls n = 40) without any contraindications for exercise, leuko- and immunogram parameters were analyzed, along with determination of physical performance level by the PWC170 test. Students with an ordinary mode of motor activity made up the main group (n = 34); track-and-field athlets comprised an athletic group (n = 27); low-fitness scholars, prep group (n = 19). The study of phagocytic and NBT activity of neutrophils and the content of CD lymphocytes in the blood was carried out by immunophenotyping using flow cytometry. Results were compared by the Mann–Whitney U test with Statistica software. Grouping of subjects based on the state of the immunogram parameters was carried out using divisional clustering by the k-means method. Based on the results of 3 iterations of 65 leuko- and immunogram indices, 13 clusters were identified, the centroids of which were variables in the clustering of subjects. As a result of 4 iterations of 13 variables, 5 clusters of subjects were discerned. The first cluster included individuals with an excess value of body mass index and was characterized by a low level of induced NBT-test neutrophils and a high content of CD3+CD16+CD56+ and a double-negative CD3+CD4-CD8-CD45+ lymphocytes subset. The second cluster included the members of a study groups with a predominantly medium and low level of physical performance, characterized by low phagocytosis activity, of CD3-CD16+CD56+, and CD3+CD16+CD56+ numbers, double-negative CD3+CD4-CD8-CD45+ lymphocytes and a high content of T cytotoxic CD3+CD4-CD8+CD45+ lymphocytes. The third cluster, comprising predominantly athletes with high and medium levels of motor endurance, exhibited high levels of NBT-induced neutrophils and low cytotoxic T lymphocyte CD3+CD4-CD8+CD45+ counts. The fourth cluster included individuals with low and medium levels of physical performance, with high phagocytic and spontaneous NBT-activity of neutrophils, CD3-CD16+CD56+ cell content, CD3+CD19- and CD3+CD4+CD8-CD45+ lymphocytes. The fifth cluster included individuals of different study groups with varying levels of physical performance and was characterized by high counts of phagocytic neutrophils, low values of spontaneous NBT-test, CD3+CD16+CD56+ and CD3+CD4-CD8-CD45+.
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##article.viewOnOriginalSite##About the authors
V. А. Kolupaev
South Ural State Medical University
Author for correspondence.
Email: chel.med.fizkult@mail.ru
PhD, MD (Biology), Associate Professor, Head, Department of Physical Culture
Russian Federation, ChelyabinskS. L. Sashenkov
South Ural State Medical University
Email: chel.med.fizkult@mail.ru
PhD, MD (Medicine), Professor, Head, Department of Normal Physiology
Russian Federation, ChelyabinskN. V. Kotova
South Ural State Medical University
Email: chel.med.fizkult@mail.ru
Senior Lecturer, Department of Physical Culture
Russian Federation, ChelyabinskReferences
- Борисов А.Г. Кластерный анализ типов иммунных нарушений при инфекционно-воспалительных заболеваниях // Российский иммунологический журнал, 2014. Т. 8 (17), № 4. С. 1002-1011. [Borisov A.G. Cluster analysis of types of immune disorders in infectious-inflammatory diseases. Rossiyskiy immunologicheskiy zhurnal = Russian Journal of Immunology, 2014, Vol. 8 (17), no. 4, pp. 1002-1011. (In Russ.)]
- Зурочка А.В., Хайдуков С.В., Кудрявцев И.В., Черешнев В.А. Проточная цитометрия в биомедицинских исследованиях. Екатеринбург: УрО РАН, 2018. 720 с. [Zurochka A.V., Haidukov S.V., Kudryavtsev I.V., Chereshnev V.A. Flow cytometry in biomedical research]. Yekaterinburg: UrO RAS, 2018. 720 p.
- Касюк С.Т. Анализ данных на компьютере в пакете Statistica. Челябинск: Челябинский филиал РАНХиГС, 2018. 346 c. [Kasyuk S.T. Analysis of data on a computer in the Statistica package]. Chelyabinsk: Chelyabinsk branch of Russian Presidential Academy of National Economy and Public Administration, 2018. 346 p.
- Котова Н.В., Зурочка В.А., Сашенков С.Л., Колупаев В.А., Клочкова С.В. Физическая работоспособность и состояние иммунограммы обучающихся, перенесших COVID-19 // Человек. Спорт. Медицина, 2024. Т. 24, № S1. С. 20-28. [Kotova N.V., Zurochka V.A., Sashenkov S.L., Kolupaev V.A., Klochkova S.V. Physical performance and immunogram status of students who have had COVID-19. Chelovek. Sport. Meditsina = Human. Sport. Medicine, 2024, Vol. 24, no. S1, pp. 20-28. (In Russ.)]
- Zurochka A., Dobrinina M., Zurochka V, Hu D., Solovyev A., Ryabova L., Kritsky I., Ibragimov R., Sarapultsev A. Seroprevalence of SARS-CoV-2 antibodies in symptomatic individuals is higher than in persons who are at increased risk exposure: the results of the single-center, prospective, cross-sectional study. Vaccines, 2021, Vol. 9, no. 6, 627. doi: 10.3390/vaccines9060627.
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