Urine metabolomic analysis for monitoring internal load in professional football players

Quintás, Guillermo; Reche, Xavier; Sanjuan-Herráez, Juan Daniel; Martínez, Helena; Herrero, Marta; Valle, Xavier; Masa, Marc; Rodas, Gil

doi:10.1007/s11306-020-01668-0

Cited by 24 publications

(20 citation statements)

References 35 publications

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“…Nevertheless, saliva and urinary metabolome analyses have been employed to investigate performance testing in soccer players [ 15 ], pre- and post-match play [ 16 ], and during a season to examine fatigue [ 17 ] or physical load [ 18 ] as well as in basketball throughout match play [ 19 ]. Recent work in youth soccer analyzed blood plasma, urine, and saliva to observe the effect of short-term physical activity upon the metabolome [ 20 ].…”

Section: Introductionmentioning

confidence: 99%

“Fuel for the Damage Induced”: Untargeted Metabolomics in Elite Rugby Union Match Play

et al. 2021

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The metabolic perturbations caused by competitive rugby are not well characterized. Our aim is to utilize untargeted metabolomics to develop appropriate interventions, based on the metabolic fluctuations that occur in response to this collision-based team sport. Seven members of an English Premiership rugby squad consented to provide blood, urine, and saliva samples daily, over a competitive week including gameday (GD), with physical demands and dietary intake also recorded. Sample collection, processing and statistical analysis were performed in accordance with best practice set out by the metabolomics standards initiative employing 700 MHz NMR spectroscopy. Univariate and multivariate statistical analysis were employed to reveal the acute energy needs of this high intensity sport are met via glycolysis, the TCA cycle and gluconeogenesis. The recovery period after cessation of match play and prior to training recommencing sees a re-entry to gluconeogenesis, coupled with markers of oxidative stress, structural protein degradation, and reduced fatty acid metabolism. This novel insight leads us to propose that effective recovery from muscle damaging collisions is dependent upon the availability of glucose. An adjustment in the periodisation of carbohydrate to increase GD+1 provision may prevent the oxidation of amino acids which may also be crucial to allay markers of structural tissue degradation. Should we expand the ‘Fuel for the work required’ paradigm in collision-based team sports to include ‘Fuel for the damage induced’?

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Section: Introductionmentioning

confidence: 99%

“Fuel for the Damage Induced”: Untargeted Metabolomics in Elite Rugby Union Match Play

et al. 2021

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“…Bias was reported as absolute values in only two studies [127,129], and, in one study, it was reported as relative values ranging between 2.0-10.0%, with the SEE ranging between 4.0-22.0% for total and sprint distances between 19.8-25.2 and above 25.2 km/h, recorded with EPTS [133]. Precision ranged between 3.0-10.0% for urine metabolomic parameters in a single study [128]. In view of the definition itself, these three metrics are important for appropriately understanding veracity.…”

Section: Needs Limitations and Potential Of Big Data In Professional ...mentioning

confidence: 93%

The Role of Veracity on the Load Monitoring of Professional Soccer Players: A Systematic Review in the Face of the Big Data Era

et al. 2021

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Big Data has real value when the veracity of the collected data has been previously identified. However, data veracity for load monitoring in professional soccer players has not been analyzed yet. This systematic review aims to evaluate the current evidence from the scientific literature related to data veracity for load monitoring in professional soccer. Systematic searches through the PubMed, Scopus, and Web of Science databases were conducted for reports onthe data veracity of diverse load monitoring tools and the associated parameters used in professional soccer. Ninety-four studies were finally included in the review, with 39 different tools used and 578 associated parameters identified. The pooled sample consisted of 2066 footballers (95% male: 24 ± 3 years and 5% female: 24 ± 1 years). Seventy-three percent of these studies did not report veracity metrics for anyof the parameters from these tools. Thus, data veracity was found for 54% of tools and 23% of parameters. The current information will assist in the selection of the most appropriate tools and parameters to be used for load monitoring with traditional and Big Data approaches while identifying those still requiring the analysis of their veracity metrics or their improvement to acceptable veracity levels.

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“…Metabolomic assays were able to discriminate hormone-treated animals from controls. 2,6,7 In sports medicine, metabolomics is considered a potential method for the screening of prohibited substances (e.g., hormones) in athletes. Nuclear magnetic resonance (NMR) spectroscopy and mass spectrometry (MS) are the most often used techniques to perform metabolome profiling.…”

Section: Using "Omics" In Doping Detectionmentioning

confidence: 99%

“…For example, hormones have a wide impact on human metabolism, changing several physiological parameters in human fluids and organs. Metabolomic assays were able to discriminate hormone‐treated animals from controls 2,6,7 . In sports medicine, metabolomics is considered a potential method for the screening of prohibited substances (e.g., hormones) in athletes.…”

Section: Using “Omics” In Doping Detectionmentioning

confidence: 99%

Linking long noncoding RNAs (lncRNAs) and doping detection

Bonilauri

Dallagiovanna

2020

Drug Testing and Analysis

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Urine metabolomic analysis for monitoring internal load in professional football players

Cited by 24 publications

References 35 publications

“Fuel for the Damage Induced”: Untargeted Metabolomics in Elite Rugby Union Match Play

“Fuel for the Damage Induced”: Untargeted Metabolomics in Elite Rugby Union Match Play

The Role of Veracity on the Load Monitoring of Professional Soccer Players: A Systematic Review in the Face of the Big Data Era

Linking long noncoding RNAs (lncRNAs) and doping detection

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