Prospective cohort study examines oxidative stress markers in racehorses, suggesting training enhances biomarker coordination.
Background Oxidative stress is a major physiological challenge in racehorses and may be modulated through training-induced adaptation. Hypothesis/Objectives Repeated exercise will induce not only biomarker-specific changes but also will enhance coordination between oxidative and antioxidative responses in racehorses. Animals Thirty-one clinically healthy racehorses (9 Thoroughbreds, 22 Arabians; 12 mares, 19 stallions) from a single training center. Methods Prospective cohort study. Serum concentrations of oxidative stress markers (advanced oxidation protein products [AOPPs], superoxide dismutase [SOD], total antioxidant capacity [TAOC], and thiobarbituric acid reactive substances [TBARS]) were measured by enzyme-linked immunosorbent assay before and 30 min after standardized exercise at 3 time points: early training (T1), post-training (T2), and after a race (R). Univariate analysis assessed fold changes (FC), principal component analysis (PCA), and hierarchical clustering were used to examine inter-marker coordination. The primary outcome was systemic redox adaptation over time. Results Post-exercise, AOPP, and SOD increased (median log-fold change, 0.13 and 0.05; approximately 1.14× and 1.05×; P = .03 and P = .01), whereas TBARS and TAOC showed no significant univariate changes. Superoxide dismutase responses were larger after races than after training (P < .05). Principal component analysis and correlation matrices identified enhanced post-exercise coordination among TBARS, SOD and TAOC (eg, TBARS-SOD r = 071), whereas AOPP remained weakly correlated, consistent with distinct regulatory dynamics. Conclusions and clinical importance Structured training and racing were associated with a post-exercise reorganization of the redox profile (tighter coupling among SOD, TAOC and TBARS) with AOPP remaining relatively independent. These data strengthen existing evidence for training-related redox adaptation and highlight the added value of multivariate analysis for capturing inter-marker coordination beyond univariate trends.
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Kacprzyk et al. (2026) studied this question.
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