Additional file 2: Table S1. of A pilot study comparing the metabolic profiles of elite-level athletes from different sporting disciplines

Comparison of previously published metabolite changes in plasma at 60 min after completion of exercise [1] and their corresponding PC2 loading values obtained in this study. Table S2. Metabolites differentiating between moderate- and high-endurance athletes (p ≤ 0.05). Table S3. Metabolites differentiating between moderate- and high-endurance athletes (p ≤ 0.05) in males only. Table S4. Pearson’s Correlations between various sex steroid metabolites. Significant p values are highlighted (* < 0.05, ** < 0.01, *** < 0.001). Table S5. Metabolites differentiating between moderate- and high-power athletes (p ≤ 0.05). Table S6. Metabolites differentiating between moderate- and high-power athletes (p ≤ 0.05) in males only. Table S7. Gender-endurance interaction metabolites. Columns A–F show the effect of endurance on gender-interaction metabolites in males only. Columns H to L show the different effect in females. Table S8. Gender-power interaction metabolites. Columns A–F show the effect of power on gender-interaction metabolites in males only. Columns H to L show the different effect in females. (XLSX 1377 kb

Additional file 3: Figure S1. of A pilot study comparing the metabolic profiles of elite-level athletes from different sporting disciplines

Heatmap (left) and hierarchical clustering (right) of steroid metabolites featured in this study. The significant metabolites from the linear model associated with endurance are highlighted in red (right). (PPTX 73 kb

Additional file 1: of A pilot study comparing the metabolic profiles of elite-level athletes from different sporting disciplines

Materials and Methods. (DOCX 16 kb

Metabolic GWAS of elite athletes reveals novel genetically-influenced metabolites associated with athletic performance

Genetic research of elite athletic performance has been hindered by the complex phenotype and the relatively small effect size of the identified genetic variants. The aims of this study were to identify genetic predisposition to elite athletic performance by investigating genetically-influenced metabolites that discriminate elite athletes from non-elite athletes and to identify those associated with endurance sports. By conducting a genome wide association study with high-resolution metabolomics profiling in 490 elite athletes, common variant metabolic quantitative trait loci (mQTLs) were identified and compared with previously identified mQTLs in non-elite athletes. Among the identified mQTLs, those associated with endurance metabolites were determined. Two novel genetic loci in FOLH1 and VNN1 are reported in association with N-acetyl-aspartyl-glutamate and Linoleoyl ethanolamide, respectively. When focusing on endurance metabolites, one novel mQTL linking androstenediol (3alpha, 17alpha) monosulfate and SULT2A1 was identified. Potential interactions between the novel identified mQTLs and exercise are highlighted. This is the first report of common variant mQTLs linked to elite athletic performance and endurance sports with potential applications in biomarker discovery in elite athletic candidates, non-conventional anti-doping analytical approaches and therapeutic strategies.Other Information Published in: Scientific Reports License: https://creativecommons.org/licenses/by/4.0See article on publisher's website: http://dx.doi.org/10.1038/s41598-019-56496-7</p