Introduction <p>Monitoring training for optimal performance outcomes requires input information for decision-making. Identifying quantitative variables that can predict exercise-induced adaptations asynchronously is methodologically challenging and likely requires a large matrix of data.</p> Objectives <p>This study aimed to track early metabolite changes as potential predictors of improvements in performance-related variables following a 5-week military training program.</p> Methods <p>We performed metabolomic analysis using <sup>1</sup>H-nuclear magnetic resonance to quantify 82 urinary metabolites in young cadets before and during the first week of a five-week military training program. Performance-related variables were measured pre- and post-training. Statistical analyses were performed using parametric or non-parametric tests, depending on data distribution, with adjustments for multiple comparisons. Relationships between early changes in metabolites (on days 2 and 7) and performance outcomes were assessed using correlation analysis. Multiple regression models were developed, excluding highly correlated variables, to predict performance outcomes at the end of the training.</p> Results <p>Fifteen metabolites whose early changes (on days 2 and 7) significantly predicted gains in performance variables (body mass index, R<sup>2</sup> = 0.48; body mass, R<sup>2</sup> = 0.60; jump power, R<sup>2</sup> = 0.60; jump height, R<sup>2</sup> = 0.69; VO<sub>2max</sub>, R<sup>2</sup> = 0.83) assessed four weeks later were identified. Except for an increase in trigonelline, the other 14 metabolites showed significant decreases (50–90%) from pre-training values. Among these, citrate, 4-pyridoxate, and ascorbate were most important for the predictive models.</p> Conclusions <p>Urinary metabolomics can suggest changes in metabolites that predict later performance gains. The identified metabolites are associated with vitamins, coenzymes, or energy metabolism intermediates.</p>

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Early changes in urine 1H-NMR metabolomics profile predict cadet’s performance gains after 5 weeks of military training

  • Diego F. Salgueiro,
  • Warley Barbosa,
  • Tiago Vieira,
  • Pedro Balikian,
  • Orival Júnior,
  • Tiago R. Figueira

摘要

Introduction

Monitoring training for optimal performance outcomes requires input information for decision-making. Identifying quantitative variables that can predict exercise-induced adaptations asynchronously is methodologically challenging and likely requires a large matrix of data.

Objectives

This study aimed to track early metabolite changes as potential predictors of improvements in performance-related variables following a 5-week military training program.

Methods

We performed metabolomic analysis using 1H-nuclear magnetic resonance to quantify 82 urinary metabolites in young cadets before and during the first week of a five-week military training program. Performance-related variables were measured pre- and post-training. Statistical analyses were performed using parametric or non-parametric tests, depending on data distribution, with adjustments for multiple comparisons. Relationships between early changes in metabolites (on days 2 and 7) and performance outcomes were assessed using correlation analysis. Multiple regression models were developed, excluding highly correlated variables, to predict performance outcomes at the end of the training.

Results

Fifteen metabolites whose early changes (on days 2 and 7) significantly predicted gains in performance variables (body mass index, R2 = 0.48; body mass, R2 = 0.60; jump power, R2 = 0.60; jump height, R2 = 0.69; VO2max, R2 = 0.83) assessed four weeks later were identified. Except for an increase in trigonelline, the other 14 metabolites showed significant decreases (50–90%) from pre-training values. Among these, citrate, 4-pyridoxate, and ascorbate were most important for the predictive models.

Conclusions

Urinary metabolomics can suggest changes in metabolites that predict later performance gains. The identified metabolites are associated with vitamins, coenzymes, or energy metabolism intermediates.