The high interindividual variability of exercise response complicates the efficient use of blood-based biomarkers in sports. To address this problem, a useful algorithm to characterize the individual regulation and predictive value of different candidate markers will be developed. Forty-nine participants completed two identical exercise trials. Blood samples were collected before, immediately after, 3 hours after, and 24 hours after completion of exercise. Plasma concentrations of interleukin (IL-) 1RA, IL-6, IL-8, IL-10, IL-15, creatine kinase (CK), cortisol, c-reactive protein (CRP), lactate dehydrogenase (LDH), and thiobarbituric acid reactive substances (TBARS) were measured. Individualized regulation was analyzed using k-means clustering and a Group Assignment Quality (GAQ) score. Regression trees with a bootstrapped-aggregated approach were used to assess the predictive qualities of the markers. For most of the markers studied, a distinction can be made between individuals who show a stronger or weaker response to a particular endurance training program. The regulation of IL-6, IL-8, IL-10, and CK exhibited a high degree of stability within the individuals. Regarding the predictive power of the markers, for all dependent variables, the most accurate predictions were obtained for cortisol and IL-8 based on the baseline value. For CK, a good prediction of recovery of maximal strength and subjective feeling of exhaustion can be made. For IL-1RA and TBARS, especially their reregulation can be predicted if the baseline level is known. Focusing individual variations in biomarker responses, our results suggest the combined use of IL-6, IL-8, IL-10, and CK for the personalized management of stress and recovery cycles following endurance exercise.
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