Towards an untargeted mass spectrometric approach for improved screening in equine antidoping

Abstract

The emergence of novel doping agents is a continuous issue for analysts who aim to maintain the integrity of horseracing together with the well-being and safety of the animals and riders involved. Untargeted mass spectrometric analysis presents a potential improvement for antidoping as it enables the detection of compounds being indirectly affected by an administered drug. In this study, liquid chromatographyhigh-resolution mass spectrometry was used to investigate a 12-horse administration study of the synthetic opioid, butorphanol. A mass spectrometric workflow capable of detecting metabolic differences for an extended period of time was successfully developed. This proof-of-concept study demonstrates the potential of untargeted workflows to provide a list of biomarkers of exposure and effect that are indicative of drug administration which may be implemented into routine testing for improved doping control.

Establishment of a post‐race biomarkers database and application of pathway analysis to identify potential biomarkers in post‐race equine plasma

“…Omics approaches such as proteomics, 7,10,12,[22][23][24][25] genomics, [7][8][9]11,12,[22][23][24][26][27][28] and metabolomics 1,7,10,12,22,24,25,29,30 have often been used to identify suitable biomarkers. It might be difficult to apply proteomics approaches to horses because comprehensive protein databases for horses do not yet exist, and expressed proteins differ between humans and horses.…”

Developments in high-resolution mass spectrometric analyses of new psychoactive substances

“…Following on from the work conducted by Steuer et al, Keen et al ( 2021 ) investigated butorphanol administration in equine athletes using a non-targeted mass spectrometric approach employing an LC-HRMS instrument. The developed workflow enabled an extended window of detection for metabolic variation within the horse through a list of biomarkers of exposure, allowing for the effects of the doping to be identified long after the parent drug was below the limit of detection of the employed screening method.…”

“…The developed workflow enabled an extended window of detection for metabolic variation within the horse through a list of biomarkers of exposure, allowing for the effects of the doping to be identified long after the parent drug was below the limit of detection of the employed screening method. The implementation of these biomarkers in routine drug testing would, therefore, allow for improved doping control, especially when a significant delay between sample collection and the doping event occurs (Keen et al 2021 ).…”

Non‐targeted screening of drugs

“…8 The detection of synthetic opioids in equine plasma continues with machine learning approaches to produce a classification model capable of predicting opioid subclasses and a regression model to predict experimental retention times. 9 The potential of broader non-targeted screening workflows using LC-QToF-MS for equine anti-doping is then explored in the short communication by Keen et al 10 Continuing the application for equine anti-doping, the Racing Laboratory of the Hong Kong Jockey Club demonstrated the required diversity for non-targeted screening workflows. Leung et al 11 present a variable Data Independent Acquisition (vDIA) workflow using LC-HRMS that can theoretically accommodate an unlimited number of analytes.…”