Tracking main environmental factors masking a minor steroidal doping effect using metabolomic analysis of horse urine by liquid chromatography–high-resolution mass spectrometry. Issue 3 (June 2019)

• Record Type: Journal Article
• Authors: Stojiljkovic, Natali; Leroux, Fanny; Bubanj, Saša; Popot, Marie-Agnès; Paris, Alain; Tabet, Jean-Claude; Junot, Christophe
• Is Part Of: European journal of mass spectrometry. Volume 25:Issue 3(2019)
• Page Start: 339
• Page End: 353
• Publication Date: 2019-06
• Subjects: Metabolomics -- high-resolution mass spectrometry -- doping -- urine -- horses -- confounding factors; Mass spectrometry -- Periodicals; Mass Spectrometry; Mass spectrometry; Periodicals; Periodicals; 543.6505
• DOI: 10.1177/1469066719839034
• Languages: English
• ISSNs: 1469-0667

Abstract

There is an urgent need to implement holistic and untargeted doping control protocols with improved discriminatory power, compared to conventional methods that only target doping agents. Metabolomics, which aims to characterize all metabolites present in biological matrices, could fulfill this need. In this context, the aim of this study was to evaluate the impact of environmental factors on the ability to obtain a metabolic signature of stanozolol administration in horse doping situation. Urine samples from 16 horses breeded in two different places were collected over a one-year period, before, during and seven months after the administration of stanozolol, a horse doping agent. Metabolomic analysis was performed using ultra-high pressure reverse phase liquid chromatography coupled to quadrupole-time-of-flight mass spectrometry (MS). Results showed a major impact of the nutritional regimen, drug administration (for de-worming purpose) and breeding place on the metabolite profiles of horse urines, which hampered the detection of metabolic perturbations induced by stanozolol administration. After having used MS/MS experiments to characterize some MS features related to these environmental factors, we showed that highlighting and then removing the features impacted by these confounding factors before performing supervised multivariate statistical analyses could address this issue. In conclusion, adequate consideration should be given to environmental and physiological factors; otherwise, they can emerge as confounding factors and conceal doping administration.