Personalized Profiles of Autonomic Regulation in Elite Athletes: Analysis of Genetic and Cardiorespiratory Determinants Using Decision Tree Modeling

Irina Bacheva, Lyazat Ibrayeva, Д. Х. Рыбалкина, Irina Kadyrova, Diana Zhumagaliyeva

2026

Full text Open access: Gold Metadata (CSL-JSON)
DOI 10.3390/jpm16040230
Data confidence 70 medium
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Abstract

Backgrounds: The aim of this pilot study was to evaluate the hierarchical contribution of individual genetic polymorphisms to the variability of autonomic regulation parameters and respiratory function in athletes of different sport specializations using Classification and Regression Tree (CRT) analysis. Methods: The study included athletes divided into two groups: hockey players (n = 48) and martial artists (n = 43). Heart rate variability (LF, HF) parameters and spirometric indices (FEV1) were assessed. Genetic analysis included 8 single nucleotide polymorphisms (SNPs): IL6 rs1800795, VDR rs731236, KCNJ11 rs5219, ADRB2 rs1042713, ADRB2 rs1042714, TRHR rs16892496, MSTN rs1805086, UCP3 rs1800849. Results: In martial artists, the main predictors were genes responsible for adrenoreceptor sensitivity (ADRB2) and neuroimmune interactions (IL6). In hockey players, the most significant predictors were genes involved in muscle growth (MSTN), energy metabolism (UCP3), and neuroendocrine regulation (TRHR). These findings indicate that similar resting HRV parameters in athletes from different sports may be associated with different genetic polymorphisms, reflecting sport-specific physiological adaptations to training loads. Conclusions: The results highlight the sport-specific nature of genetic determinants of autonomic regulation. In martial artists, genes related to the immuno-adrenergic axis (IL6, ADRB2) appear to play a dominant role, whereas in hockey players neuroendocrine, muscle-metabolic, and mitochondrial factors (TRHR, MSTN, UCP3) demonstrate greater influence. The observed interactions between genotypes and FEV1 emphasize the importance of transitioning from generalized approaches toward personalized monitoring strategies in sports science.