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Responsivity Biomarkers of Maximum Oxygen Consumption in Aerobic Training: A Metabolomics Approach


Maximal Oxygen Consumption (VO2MAX) is the gold standard measurement of cardiorespiratory fitness levels, and is positively associated with maintenance and health enhancement. Even though the recommendations for aerobic levels enhancements can promote benefits for the great majority of people, the responses may vary from individual to individual, who will be classified as either high or low responders. The understanding of factors related to aerobic training responsivity, as well as identification of specific biomarkers that can assist in individual response capacity diagnosis, may contribute to an adoption of more efficient and biologically individualized training strategies. Thus, the current study will investigate metabolic biomarkers in skeletal muscles and blood samples related to the responsivity of 68 healthy young men (18-30 years old) to VO2MAX. Subjects will undergo 8 weeks of continuous aerobic training (TAC - 40 min/day, 3-4 times/week with 70% heart rate reserve, n=34) and high intensity interval training (HIIT - 40 min/day, 3-4 times/week with 50-90% heart rate reserve, n=34) using a cycle ergometer. Blood samples and muscle tissue (vastus lateralis) will be collected pre and post training protocol. All samples will be analyzed through metabolomics method (1H NMR spectroscopy). The main goal is identifying metabolites that can be predictors of enhancement in VO2MAX due to individual responses. After the training protocol, based on the changing magnitude of VO2MAX the individuals will be classified as either "high" or "low" responders after. Finally, metabolites identification will be used to explain differences in VO2MAX of "high" and "low" responders after TAC and HIIT program. Identification will be found through correlations and multivariate statistical analysis such as principal components analysis (PCA), partial least squares discriminant analysis (PLS-DA) and linear regressions. Receiver operating characteristic curve (ROC) will be utilized to characterize metabolites and biomarkers, their accuracy will be assessed through sensibility and specificity tests. (AU)

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