Evaluation of horse urine sample preparation methods for metabolomics using LC coupled to HRMS

Background: Horse urine is the medium of choice for the implementation of metabolomic approaches aimed at improving horse doping control. However, drug analysis in this biofluid is a challenging task due to the presence of large amounts of interfering compounds. [br/]Methodology & Results: A comparative study of sample preparation has been conducted to evaluate five sample-preparation methods, namely acetonitrile precipitation, proteinase K hydrolysis, membrane filtration and sample dilution with water by factors of five and 20, for metabolome analysis using liquid chromatography coupled to high resolution mass spectrometry. Assessment was performed at both global and targeted levels, by using a few thousand features obtained from peak detection software, and internal standards and 100 annotated or identified metabolites. [br/]Conclusion: By considering the number of detected signals, their intensity and their detection repeatability, acetonitrile precipitation was selected as the most efficient sample-preparation method for the analysis of horse urine metabolome in liquid chromatography coupled to high resolution mass spectrometry conditions

A validated UHPLC-MS/MS method to quantify low levels of anabolic-androgenic steroids naturally present in urine of untreated horses

Doping control is a main priority for regulatory bodies of both the horse racing industry and the equestrian sports. Urine and blood samples are screened for the presence of hundreds of forbidden substances including anabolic-androgenic steroids (AASs). Based on the suspected endogenous origin of some AASs, with β-boldenone as the most illicit candidate, this study aimed to improve the knowledge of the naturally present AAS in horse urine. To this extent, a novel ultra high-performance liquid chromatography-tandem mass spectrometry (UHPLC-MS/MS) method was developed and validated according to the Association of Official Racing Chemists (AORC) and European Commission (EC) guidelines, proving the power of this new method. Low limits of detection (0.2 ng/mL), good reproducibility (percentage of standard deviation (%RSD)0.99 and lack-of-fit analysis) were obtained for all included AASs. With this method, urine samples of 105 guaranteed untreated horses (47 geldings, 53 mares and 5 stallions serving as a control) were screened for β-boldenone and five related natural steroids: androstadienedione (ADD), androstenedione (AED), alpha-testosterone (αT), beta-testosterone (βT), and progesterone (P). Progesterone, β-testosterone, and α-testosterone were detected in more than half of the horses at low concentrations (<2 ng/mL). Occasionally, not only testosterone and progesterone but also low concentrations of AED, ADD, and boldenone (Bol) were found (0.5–5 ng/mL)

Liquid chromatography – high resolution mass spectrometry-based metabolomic approach for the detection of Continuous Erythropoiesis Receptor Activator effects in horse doping control

International audienceErythropoiesis Stimulating Agents (ESAs) were developed for therapeutic purposes to stimulate red blood cell (RBC) production. Consequently, tissue oxygenation is enhanced as athlete's endurance and ESAs misuse now benefits doping. Our hypothesis is that most of ESAs should have similar mechanisms and thus have the same effects on metabolism. Studying the metabolome variations could allow suspecting the use of any ESAs with a single method by targeting their effects. In this objective, a metabolomic study was carried out on 3 thoroughbred horses with a single administration of 4.2μg/kg of Mircera®, also called Continuous Erythropoiesis Receptor Activator (CERA). Blood and urine samples were collected from D-17to D+74and haematological parameters were followed throughout the study as plasmatic CERA concentration (ELISA). Urine and plasma metabolic fingerprints were recorded by Liquid Chromatography coupled to High Resolution Mass Spectrometry (LC-HRMS) in positive and negative mode. After preprocessing steps, normalized data were analyzed by multivariate statistics to build OPLS models. Hemoglobin concentration and hematocrit showed a significant increase after CERA administration unlike reticulocytes. CERA concentration showed a high intensity peak and then a slow decrease until becoming undetectable after D+31. Models built with multivariate statistics allow a discrimination between pre and post-administration plasma and urine samples until 74days after administration, i.e. 43days longer than ELISA method. By reducing and studying variables (ions), some potential candidate biomarkers were found