Neural network modeling of the association of climate and non-contact injury with serum immunoglobulin A concentration in elite athletes: a retrospective cohort study

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Abstract

BACKGROUND: The role of serum immunoglobulin A is often underestimated; however, its functions in systemic protection and endotoxin clearance make it an important marker of the “cost of adaptation.” Serum immunoglobulin A concentration depends on sex and age, but the influence of contrast climate and the specifics of non-contact injury during the off-season has not been thoroughly studied before.

AIM: To assess the influence of climatic factors and the specifics of non-contact injury on the variability of serum immunoglobulin A levels, taking into account age and sex, in elite athletes during the off-season.

METHODS: A retrospective analysis of data from 7549 athletes (mean age 19.98 years) was performed. Comparative pairs were formed: “Biathlon–Triathlon” (climate influence with similar energy expenditure) and “Figure Skating–Speed Skating” (influence of biomechanics and injury patterns). Serum immunoglobulin A levels were measured using immunochemiluminescence analysis (g/L). Statistical analysis included estimation of 95% confidence intervals and neural network modeling (multilayer perceptron) to assess the contribution of factors.

RESULTS: Reduced serum IgA levels were observed in athletes participating in winter and impact-loading sports. In biathletes, the level (1.67 g/L) was lower than in triathletes (1.73 g/L); the weight of the cold factor was –0.443. The minimum value was recorded in figure skating (1.40 g/L), which was significantly lower than that in speed skating (1.68 g/L). Modeling showed that impact loads (weight: –0.548) were associated with a lower level of serum immunoglobulin A. Sexual dimorphism (males > females) and positive age-related trends were confirmed.

CONCLUSION: Serum immunoglobulin A serves as a sensitive integrated marker of allostatic load. Cold stress and chronic trauma resulting from impact loads act as independent factors contributing to its reduction. The risk group includes female and young athletes specializing in complex coordination and winter sports.

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About the authors

Natalia M. Buyanova

The Russian National Research Medical University named after N.I. Pirogov

Email: dpo.mkramn@inbox.ru
ORCID iD: 0000-0002-4073-475X
SPIN-code: 2806-6159

MD

Russian Federation, Moscow

Anatoly G. Kochetov

The Russian National Research Medical University named after N.I. Pirogov

Author for correspondence.
Email: kochetov.lab@yandex.ru
ORCID iD: 0000-0003-3632-291X
SPIN-code: 3370-2093

MD, Dr. Sci. (Medicine), Professor

Russian Federation, Moscow

Sergey P. Alpatov

The Russian National Research Medical University named after N.I. Pirogov

Email: immunosport@rambler.ru
ORCID iD: 0000-0003-2233-7301
SPIN-code: 2609-0174

MD, Cand. Sci. (Medicine)

Russian Federation, Moscow

Boris K. Romanov

The Russian National Research Medical University named after N.I. Pirogov

Email: romanov_bk@rsmu.ru
ORCID iD: 0000-0001-5429-9528
SPIN-code: 8453-9166

MD, Dr. Sci. (Medicine), Associate Professor

Russian Federation, Moscow

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Supplementary files

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2. Fig. 1. Sequence of formation of the research sample.

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3. Fig. 2. Gender and overall distribution of serum immunoglobulin A (IgA) concentrations in athletes included in the study, by sport. LL — lower limit; UL — upper limit; CI — confidence interval.

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4. Fig. 3. Multilayer perceptron topology and the strength of interneuronal connections when modeling the influence of a climate factor. The diagram demonstrates the influence of input variables on IgA concentration through the hidden layer of neurons. The intensity and thickness of the lines correspond to the strength of the synaptic connection.

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5. Fig. 4. Multilayer perceptron topology and the strength of interneuronal connections when modeling the impact of non-contact trauma. The diagram demonstrates the influence of input variables on IgA concentration through the hidden layer of neurons. The intensity and thickness of the lines correspond to the strength of synaptic connections.

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