Abstract
Introduction
Serum phenotyping of elite cyclists regarding cortisol, IGF1 and testosterone is a way to detect endocrine disruptions possibly explained by exercise overload, non-balanced diet or by doping. This latter disruption-driven approach is supported by fundamental physiology although without any evidence of any metabolic markers.
Objectives
Serum samples were distributed through Low, High or Normal endocrine classes according to hormone concentration. A 1H NMR metabolomic study of 655 serum obtained in the context of the longitudinal medical follow-up of 253 subjects was performed to discriminate the three classes for every endocrine phenotype.
Methods
An original processing algorithm was built which combined a partial-least squares-based orthogonal correction of metabolomic signals and a shrinkage discriminant analysis (SDA) to get satisfying classifications. An extended validation procedure was used to plan in larger size cohorts a minimal size to get a global prediction rate (GPR), i.e. the product of the three class prediction rates, higher than 99.9%.
Results
Considering the 200 most SDA-informative variables, a sigmoidal fitting of the GPR gave estimates of a minimal sample size to 929, 2346 and 1408 for cortisol, IGF1 and testosterone, respectively. Analysis of outliers from cortisol and testosterone Normal classes outside the 97.5%-confidence limit of score prediction revealed possibly (i) an inadequate protein intake for outliers or (ii) an intake of dietary ergogenics, glycine or glutamine, which might explain the significant presence of heterogeneous metabolic profiles in a supposedly normal cyclists subgroup.
Conclusion
In a next validation metabolomics study of a so-sized cohort, anthropological, clinical and dietary metadata should be recorded in priority at the blood collection time to confirm these functional hypotheses.
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Data availability
Data available at www.ebi.ac.uk/metabolights/MTBLS2799.
Abbreviations
- AAS:
-
Androgenic anabolic steroids
- ABP:
-
Athletics Biological Passport
- AFLD:
-
Agence Française de Lutte contre le Dopage— French Anti-doping Agency
- ANOVA:
-
ANalysis Of VAriance
- BATMAN:
-
Bayesian AuTomated Metabolite Analyser for NMR spectra
- cat scores:
-
Correlation-adjusted t-scores
- CPMG:
-
Carr–Purcell–Meiboom–Gill NMR sequence
- E:
-
Epitestosterone
- FFC:
-
French Federation of Cycling
- GH:
-
Growth hormone
- GPR:
-
Global prediction rate
- IC:
-
Independent component
- ICDA:
-
Independent Component—Discriminant Analysis
- IGF1:
-
Insulin-like growth factor 1
- LS:
-
Learning size (number of samples selected in the dataset)
- MAGIC:
-
Markov Affinity-based Graph Imputation of Cells
- MANOVA:
-
Multivariate ANalysis Of VAriance
- MDS:
-
MultiDimensional Scaling
- NV:
-
Number of selected ordered variables
- nls:
-
Non-linear squares fitting
- OSC:
-
Orthogonal signal correction
- PCA:
-
Principal component analysis
- PHATE:
-
Mapping using potential of heat-diffusion affinity-based transition embedding
- PLS-DA:
-
Partial least squares-discriminant analysis
- PLSR:
-
Partial least squares regression
- PR:
-
Prediction rate
- SDA:
-
Shrinkage discriminant analysis
- T:
-
Testosterone
- UCI:
-
Union Cycliste Internationale—International Cycling Union
- WADA:
-
Word Anti Doping Agency
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Acknowledgements
Authors thank sportsmen enrolled in the cohort of the French Federation of Cycling for having accepted to be anonymously involved in this exploratory phenotyping study. The French Federation of Cycling is acknowledged for his involvement in the study and providing samples. This study was supported by the French Agency for Doping Control (AFLD, contract Inserm n° R09223DD) and the World Anti-Doping Agency (WADA, contract n° 006D1442 – Inserm n° R07157DD). B Labrador was supported by AFLD and WADA and FX Lejeune by the French Agency of Research.
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AP, MG, JCT and YLB supervised this work. JCT, YLB, MR, MG and AP contributed to design the experiment. AM and MG contributed to sample handling and collection and sample biobanking. MG achieved endocrine phenotyping and curation. CC and JM performed metabolomic analyses. FXL, BL and AP performed statistical analyses. CC did an expert-based assignment of putative biomarkers. AP performed the data interpretation and wrote the manuscript. JCT, YLB, MG, MR, CC, FXL and BL revised the manuscript. All authors have read and approved the manuscript.
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The samples concerning metabolomic research were carried out during the mandatory medical and biological monitoring of the French Federation of Cycling (FFC) according to French legislation (article L 3621 of the French Public Health Code concerning protection of the health of sportsmen and women). The aliquots of blood samples reserved for this project were anonymized with a specific consent signed by those who gave their consent (WADA research grant and project submitted by WADA to an independent ethic review, reference number 06D14YL).
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Informed consent was obtained from all participants included in the study.
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This paper is dedicated to the memory of Dr Armand Mégret who died in September 2019. He was pioneering at the very end of nineties in systematic serum biobanking to help to fight doping practices in sport, particularly in cycling.
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Paris, A., Labrador, B., Lejeune, FX. et al. Metabolomic signatures in elite cyclists: differential characterization of a seeming normal endocrine status regarding three serum hormones. Metabolomics 17, 67 (2021). https://doi.org/10.1007/s11306-021-01812-4
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DOI: https://doi.org/10.1007/s11306-021-01812-4