Abstract
The current detection methods for stanozolol are all based on targeted approach. The present study aimed to assess the global biological effect of stanozolol-treatment by means of chemometric models, after generating and comparing horse urine LC-HRMS fingerprints collected from control and stanozolol-treated horses. The animal study was conducted according to an ethically approved protocol at two different places in France: Chamberet and Coye la Foret. The total duration of the animal phase was seven months and only females were selected to partake. The sixteen mares in this study were not actively racing horses, but were in good physical condition. SIMCA-P+ software and R free software environment were used for multivariate data analysis. Principal Component Analysis (PCA) and Orthogonal Projections to Latent Structures-Discriminant Analysis (OPLS-DA) were applied to build some descriptive and predictive models. The analyzed horse urine fingerprints based on the 220 features selected after suppression of confounding factors show changes in metabolic states after chronic stanozolol treatment. This proof of concept study confirms the power of untargeted approach in doping control since the changes are present over seven months after anabolic administration.
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