Innovative approach to interpret the variability of biomarkers after ultra-endurance exercise: the multifactorial analysis

Abstract

Aims: We assessed the inter-relationship that exists between variations of different biochemical and hematological parameters following strenuous endurance exercise in Ironmen by using multiple factor analysis (MFA). MFA was used to estimate the associations among groups of parameters in order to identify concurrent changes in many different biochemical variables. Materials & methods: In total, 14 Ironman athletes were followed before and early after a race. MFA was applied to the parameters that showed a significant variation after the race, as we previously described in detail. Specifically, MFA standardizes data in each group and calculates the global axes (GAs), which are the linear combination of original parameters that maximize the global data variance. Results: MFA identified three global axes (GAs) as significant, explaining approximately 62% of the global data variance. The first GA contained NT-proBNP, IL-1ra, IL-6, IL-8 and the oxidative index. The second and third GAs included calcium, creatinine, potassium, uric acid, hemoglobin, hematocrit and glucose. Analysis of the first two GAs showed that changes in the oxidative index were associated with variations in IL-8 and NT-proBNP. Conclusion: Among all the variables considered, MFA evidenced a close relationship between variations in oxidative stress, IL-8 and NT-proBNP, which may have a meaning in the mechanisms related to the physiological response after strenuous acute exercise.