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Energetics of endurance exercise in young horses determined by nuclear magnetic resonance metabolomics.

Luck MM, Le Moyec L, Barrey E, Triba MN, Bouchemal N, Savarin P, Robert C - Front Physiol (2015)

Bottom Line: The statistical parameters showed the robustness of the model (R2Y = 0.947, Q2Y = 0.856 and cros-validated ANOVA p < 0.001).For confirmation of the predictive value of the model, a test set of 104 sample spectra were projected by the model, which provided perfect predictions as the area under the receiving-operator curve was 1.The metabolomic profile determined with the OPLS model showed that glycemia after the race was lower than glycemia before the race, despite the involvement of lipid and protein catabolism.

View Article: PubMed Central - PubMed

Affiliation: Unité de Biologie Intégrative et Adaptation à l'Exercice EA 7362, Université d'Evry Val D'Essonne Evry, France.

ABSTRACT
Long-term endurance exercise severely affects metabolism in both human and animal athletes resulting in serious risk of metabolic disorders during or after competition. Young horses (up to 6 years old) can compete in races up to 90 km despite limited scientific knowledge of energetic metabolism responses to long distance exercise in these animals. The hypothesis of this study was that there would be a strong effect of endurance exercise on the metabolomic profiles of young horses and that the energetic metabolism response in young horses would be different from that of more experienced horses. Metabolomic profiling is a powerful method that combines Nuclear Magnetic Resonance (NMR) spectrometry with supervised Orthogonal Projection on Latent Structure (OPLS) statistical analysis. (1)H-NMR spectra were obtained from plasma samples drawn from young horses (before and after competition). The spectra obtained before and after the race from the same horse (92 samples) were compared using OPLS. The statistical parameters showed the robustness of the model (R2Y = 0.947, Q2Y = 0.856 and cros-validated ANOVA p < 0.001). For confirmation of the predictive value of the model, a test set of 104 sample spectra were projected by the model, which provided perfect predictions as the area under the receiving-operator curve was 1. The metabolomic profile determined with the OPLS model showed that glycemia after the race was lower than glycemia before the race, despite the involvement of lipid and protein catabolism. An OPLS model was calculated to compare spectra obtained on plasma taken after the race from 6-year-old horses and from experienced horses (cross-validated ANOVA p < 0.001). The comparison of metabolomic profiles in young horses to those from experienced horses showed that experienced horses maintained their glycemia with higher levels of lactate and a decrease of plasma lipids after the race.

No MeSH data available.


Related in: MedlinePlus

(A) Score plot of the PCA model computed with all spectra from samples taken from young horses. Each dot corresponds to a spectrum, colored in blue for 2011 and 2013 samples and in red for 2012 samples. (B) Score plot of the PCA model computed with all spectra from samples taken from young horses after removing the effect of year. Each dot corresponds to a spectrum, colored in blue for 2011 and 2013 samples and in red for 2012 samples.
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Figure 2: (A) Score plot of the PCA model computed with all spectra from samples taken from young horses. Each dot corresponds to a spectrum, colored in blue for 2011 and 2013 samples and in red for 2012 samples. (B) Score plot of the PCA model computed with all spectra from samples taken from young horses after removing the effect of year. Each dot corresponds to a spectrum, colored in blue for 2011 and 2013 samples and in red for 2012 samples.

Mentions: The PCA models obtained with the spectra from all of the young horses (Figure 2A) showed the existence of two distinct clouds, one for the spectra of samples obtained in 2011 and 2013, and another for those obtained in 2012. However, the PCA model could not differentiate the spectra of BE horse plasma from those of AE plasma.


Energetics of endurance exercise in young horses determined by nuclear magnetic resonance metabolomics.

Luck MM, Le Moyec L, Barrey E, Triba MN, Bouchemal N, Savarin P, Robert C - Front Physiol (2015)

(A) Score plot of the PCA model computed with all spectra from samples taken from young horses. Each dot corresponds to a spectrum, colored in blue for 2011 and 2013 samples and in red for 2012 samples. (B) Score plot of the PCA model computed with all spectra from samples taken from young horses after removing the effect of year. Each dot corresponds to a spectrum, colored in blue for 2011 and 2013 samples and in red for 2012 samples.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4544308&req=5

Figure 2: (A) Score plot of the PCA model computed with all spectra from samples taken from young horses. Each dot corresponds to a spectrum, colored in blue for 2011 and 2013 samples and in red for 2012 samples. (B) Score plot of the PCA model computed with all spectra from samples taken from young horses after removing the effect of year. Each dot corresponds to a spectrum, colored in blue for 2011 and 2013 samples and in red for 2012 samples.
Mentions: The PCA models obtained with the spectra from all of the young horses (Figure 2A) showed the existence of two distinct clouds, one for the spectra of samples obtained in 2011 and 2013, and another for those obtained in 2012. However, the PCA model could not differentiate the spectra of BE horse plasma from those of AE plasma.

Bottom Line: The statistical parameters showed the robustness of the model (R2Y = 0.947, Q2Y = 0.856 and cros-validated ANOVA p < 0.001).For confirmation of the predictive value of the model, a test set of 104 sample spectra were projected by the model, which provided perfect predictions as the area under the receiving-operator curve was 1.The metabolomic profile determined with the OPLS model showed that glycemia after the race was lower than glycemia before the race, despite the involvement of lipid and protein catabolism.

View Article: PubMed Central - PubMed

Affiliation: Unité de Biologie Intégrative et Adaptation à l'Exercice EA 7362, Université d'Evry Val D'Essonne Evry, France.

ABSTRACT
Long-term endurance exercise severely affects metabolism in both human and animal athletes resulting in serious risk of metabolic disorders during or after competition. Young horses (up to 6 years old) can compete in races up to 90 km despite limited scientific knowledge of energetic metabolism responses to long distance exercise in these animals. The hypothesis of this study was that there would be a strong effect of endurance exercise on the metabolomic profiles of young horses and that the energetic metabolism response in young horses would be different from that of more experienced horses. Metabolomic profiling is a powerful method that combines Nuclear Magnetic Resonance (NMR) spectrometry with supervised Orthogonal Projection on Latent Structure (OPLS) statistical analysis. (1)H-NMR spectra were obtained from plasma samples drawn from young horses (before and after competition). The spectra obtained before and after the race from the same horse (92 samples) were compared using OPLS. The statistical parameters showed the robustness of the model (R2Y = 0.947, Q2Y = 0.856 and cros-validated ANOVA p < 0.001). For confirmation of the predictive value of the model, a test set of 104 sample spectra were projected by the model, which provided perfect predictions as the area under the receiving-operator curve was 1. The metabolomic profile determined with the OPLS model showed that glycemia after the race was lower than glycemia before the race, despite the involvement of lipid and protein catabolism. An OPLS model was calculated to compare spectra obtained on plasma taken after the race from 6-year-old horses and from experienced horses (cross-validated ANOVA p < 0.001). The comparison of metabolomic profiles in young horses to those from experienced horses showed that experienced horses maintained their glycemia with higher levels of lactate and a decrease of plasma lipids after the race.

No MeSH data available.


Related in: MedlinePlus