A pilot study comparing the metabolic profiles of elite-level athletes from different sporting disciplines

Abstract

Background: The outstanding performance of an elite athlete might be associated with changes in their blood metabolic profile. The aims of this study were to compare the blood metabolic profiles between moderate- and high-power and endurance elite athletes and to identify the potential metabolic pathways underlying these differences.

Methods: Metabolic profiling of serum samples from 191 elite athletes from different sports disciplines (121 high- and 70 moderate-endurance athletes, including 44 high- and 144 moderate-power athletes), who participated in national or international sports events and tested negative for doping abuse at anti-doping laboratories, was performed using non-targeted metabolomics-based mass spectroscopy combined with ultrahigh-performance liquid chromatography. Multivariate analysis was conducted using orthogonal partial least squares discriminant analysis. Differences in metabolic levels between high- and moderate-power and endurance sports were assessed by univariate linear models.

Results: Out of 743 analyzed metabolites, gamma-glutamyl amino acids were significantly reduced in both high-power and high-endurance athletes compared to moderate counterparts, indicating active glutathione cycle. High-endurance athletes exhibited significant increases in the levels of several sex hormone steroids involved in testosterone and progesterone synthesis, but decreases in diacylglycerols and ecosanoids. High-power athletes had increased levels of phospholipids and xanthine metabolites compared to moderate-power counterparts.

Conclusions: This pilot data provides evidence that high-power and high-endurance athletes exhibit a distinct metabolic profile that reflects steroid biosynthesis, fatty acid metabolism, oxidative stress, and energy-related metabolites. Replication studies are warranted to confirm differences in the metabolic profiles associated with athletes' elite performance in independent data sets, aiming ultimately for deeper understanding of the underlying biochemical processes that could be utilized as biomarkers with potential therapeutic implications.

Keywords: Elite athletes; Endurance; Energy substrates; Metabolomics; Oxidative stress; Power; Steroids biosynthesis.

Fig. 1

PCA analysis of athlete metabolomics data. a A score plot of PC1 and PC2 indicating clustering of samples into two groups according to PC1. Neither PCs is explained by sport type or class. b, c Loading plots offering clues on what the two PCs may represent: The heme/hemoglobin metabolites suggests a hemolysis signature for PC1 (b) while the TCA energy metabolite highlighted by PC2 indicates an energy generating process which may be associated with exercise (c)

Fig. 2

OPLS-DA model comparing moderate- versus high-endurance classes of elite athletes. a A score plot showing the class-discriminatory component (x-axis) versus orthogonal component (y-axis). b The corresponding loading plot showing a clustering of steroids and monohydroxy-fatty acids at the high end of endurance opposed by a clustering of diacyl-glycerols and gamma-glutamyl amino acids at the negative end

Fig. 3

OPLS-DA model of moderate- versus high-power classes of elite athletes. a A score plot showing the class-discriminatory component on the x-axis versus the first orthogonal component on the y-axis. b The corresponding loading plot showing a clustering of sterols, lipids, and xanthine metabolites at the high end of power as opposed to enrichment of gamma-glutamyl amino acids at the low end of power

Fig. 4

A schematic diagram summarizing the biochemical relationships between steroid metabolites found significantly associated with high endurance (shaded boxes). This is based on the steroid hormone biosynthesis reference pathway (map00140) from the Kyoto Encyclopedia of Genes and Genomes (KEGG)

Fig. 5

Heatmap of metabolites significantly associated with high endurance from the linear model association analysis (y-axis). Samples on x-axis were ordered by sports type and group. The color code denotes z-scaled values of metabolites after correction of confounders

Fig. 6

Heatmap of metabolites significantly associated with high power from the linear model association analysis (y-axis). Samples on x-axis were ordered by sports type and group. The color code denotes z-scaled values of metabolites after correction of confounders