Diego F Salgueiro, Warley Barbosa, Tiago Vieira, Pedro Balikian, Orival Júnior, Tiago R Figueira
{"title":"尿液1H-NMR代谢组学的早期变化预测了学员在5周军事训练后的表现提高。","authors":"Diego F Salgueiro, Warley Barbosa, Tiago Vieira, Pedro Balikian, Orival Júnior, Tiago R Figueira","doi":"10.1007/s11306-025-02348-7","DOIUrl":null,"url":null,"abstract":"<p><strong>Introduction: </strong>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><p><strong>Objectives: </strong>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><p><strong>Methods: </strong>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><p><strong>Results: </strong>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><p><strong>Conclusions: </strong>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>","PeriodicalId":18506,"journal":{"name":"Metabolomics","volume":"21 5","pages":"145"},"PeriodicalIF":3.3000,"publicationDate":"2025-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Early changes in urine <sup>1</sup>H-NMR metabolomics profile predict cadet's performance gains after 5 weeks of military training.\",\"authors\":\"Diego F Salgueiro, Warley Barbosa, Tiago Vieira, Pedro Balikian, Orival Júnior, Tiago R Figueira\",\"doi\":\"10.1007/s11306-025-02348-7\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Introduction: </strong>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><p><strong>Objectives: </strong>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><p><strong>Methods: </strong>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><p><strong>Results: </strong>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><p><strong>Conclusions: </strong>Urinary metabolomics can suggest changes in metabolites that predict later performance gains. 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Early changes in urine 1H-NMR metabolomics profile predict cadet's performance gains after 5 weeks of military training.
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.
期刊介绍:
Metabolomics publishes current research regarding the development of technology platforms for metabolomics. This includes, but is not limited to:
metabolomic applications within man, including pre-clinical and clinical
pharmacometabolomics for precision medicine
metabolic profiling and fingerprinting
metabolite target analysis
metabolomic applications within animals, plants and microbes
transcriptomics and proteomics in systems biology
Metabolomics is an indispensable platform for researchers using new post-genomics approaches, to discover networks and interactions between metabolites, pharmaceuticals, SNPs, proteins and more. Its articles go beyond the genome and metabolome, by including original clinical study material together with big data from new emerging technologies.