A generic screening methodology for horse doping control by LC-TOF-MS, GC-HRMS and GC-MS.

The study presents a comprehensive screening methodology for detecting prohibited substances used in horse doping cases, utilizing various mass spectrometry techniques. The developed method can identify more than 350 target substances in horse urine and can easily accommodate new substances without major changes in the testing process – a breakthrough in equine sports doping control.

Research Methodology

The researchers implemented a unified sample preparation protocol entailing two parallel procedures:

• Enzymatic hydrolysis of sulfate and glucuronide conjugates: This process breaks down these compounds, which are often used by the body to make substances more water-soluble and easily expelled.
• Methanolysis of 17β-sulfate steroid conjugates: Methanolysis is a process of splitting a compound through reaction with methanol – in this case to break apart specific steroid compounds that may be used in doping.

They then turned to a combined process of liquid and gas chromatographic Mass Spectrometry (MS) analysis using LC-TOF-MS, GC-HRMS, and GC-MS assays.

Data Analysis

Most of the illegal substances were recognized through a high mass accuracy technique, known as LC-TOF-MS, without a need for prior manipulation of compounds (derivatization). The preparation process did, however, involve introducing methylated and trimethylsilylated derivatives, common in toxicological Gas Chromatography-Mass Spectrometry (GC-MS) libraries.
The researchers enhanced the screening process by using automated mass spectral deconvolution and identification system (AMDIS) in combination with deconvolution reporting software (DRS). This allows for automated and more efficient detection and identification of substances.

Validation and Versatility of the Method

The researchers further tested and validated the method for sixty representative compounds, addressing factors like detection limit, specificity, recovery, precision, mass accuracy, matrix effect, and risk of contamination. This proposition can detect more than 350 target substances with the potential for identifying many more. The methodology allows for retrospective identification of prohibited substances in stored urine samples by reprocessing the acquired data. Additionally, the researchers further evidenced its usability by accurately identifying prohibited substances in previously declared positive horse urine samples.