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

Performance assessment of an equine metabolomics model for screening a range of anabolic agents

INTRODUCTION

Despite their ban, Anabolic Androgenic Steroids (AAS) are considered as the most important threat for equine doping purposes. In the context of controlling such practices in horse racing, metabolomics has emerged as a promising alternative strategy to study the effect of a substance on metabolism and to discover new relevant biomarkers of effect. Based on the monitoring of 4 metabolomics derived candidate biomarkers in urine, a prediction model to screen for testosterone esters abuse was previously developed. The present work focuses on assessing the robustness of the associated method and define its scope of application.

MATERIALS AND METHODS

Several hundred urine samples were selected from 14 different horses of ethically approved administration studies involving various doping agents' (AAS, SARMS, β-agonists, SAID, NSAID) (328 urine samples). In addition, 553 urine samples from untreated horses of doping control population were included in the study. Samples were characterized with the previously described LC-HRMS/MS method, with the objective of assessing both its biological and analytical robustness.

RESULTS

The study concluded that the measurement of the 4 biomarkers involved in the model was fit for purpose. Further, the classification model confirmed its effectiveness in screening for testosterone esters use; and it demonstrated its ability to screen for the misuse of other anabolic agents, allowing the development of a global screening tool dedicated to this class of substances. Finally, the results were compared to a direct screening method targeting anabolic agents demonstrating complementary performances of traditional and omics approaches in the screening of anabolic agents in horses.

Factors affecting untargeted detection of doping agents in biological samples

Doping control is essential for sports, and untargeted detection of doping agents (UDDA) is the holy grail for anti-doping strategies. The present study examined major factors impacting UDDA with metabolomic data processing, including the use of blank samples, signal-to-noise ratio thresholds, and the minimum chromatographic peak intensity. Contrary to data processing in metabolomics studies, both blank sample use (either blank solvent or plasma) and marking of background compounds were found to be unnecessary for UDDA in biological samples, the first such report to the authors' knowledge. The minimum peak intensity required to detect chromatographic peaks affected the limit of detection (LOD) and data processing time for untargeted detection of 57 drugs spiked into equine plasma. The ratio of the mean (ROM) of the extracted ion chromatographic peak area of a compound in the sample group (SG) to that in the control group (CG) impacted its LOD, and a small ROM value such as 2 is recommended for UDDA. Mathematical modeling of the required signal-to-noise ratio (S/N) for UDDA provided insights into the effect of the number of samples in the SG, the number of positive samples, and the ROM on the required S/N, highlighting the power of mathematics in addressing issues in analytical chemistry. The UDDA method was validated by its successful identification of untargeted doping agents in real-world post-competition equine plasma samples. This advancement in UDDA methodology will be a useful addition to the arsenal of approaches used to combat doping in sports.

Metabolomics in clinical and forensic toxicology, sports anti-doping and veterinary residues

Metabolomics is a multidisciplinary field providing workflows for complementary approaches to conventional analytical determinations. It allows for the study of metabolically related groups of compounds or even the study of novel pathways within the biological system. The procedural stages of metabolomics; experimental design, sample preparation, analytical determinations, data processing and statistical analysis, compound identification and validation strategies are explored in this review. The selected approach will depend on the type of study being conducted. Experimental design influences the whole metabolomics workflow and thus needs to be properly assessed to ensure sufficient sample size, minimal introduced and biological variation and appropriate statistical power. Sample preparation needs to be simple, yet potentially global in order to detect as many compounds as possible. Analytical determinations need to be optimised either for the list of targeted compounds or a universal approach. Data processing and statistical analysis approaches vary widely and need to be better harmonised for review and interpretation. This includes validation strategies that are currently deficient in many presented workflows. Common compound identification approaches have been explored in this review. Metabolomics applications are discussed for clinical and forensic toxicology, human and equine sports anti-doping and veterinary residues.

FROM A NON-TARGETED METABOLOMICS APPROACH TO A TARGETED BIOMARKERS STRATEGY TO HIGHLIGHT TESTOSTERONE ABUSE IN EQUINE. ILLUSTRATION OF A METHODOLOGICAL TRANSFER BETWEEN PLATFORMS AND LABORATORIES

In order to overcome the challenge associated with the screening of Anabolic-Androgenic Steroids (AAS) abuses in animal competitions, a non-targeted LC-HRMS based metabolomics approach was implemented on equine urine samples to highlight potential biomarkers associated with the administration of such compounds, using testosterone esters as model steroids. A statistical model relying on 4 potential biomarkers intensity could be defined to predict the status of the samples. With a routine application perspective, the monitoring of the highlighted potential biomarkers was first transferred into high-throughput LC-SRM. The model's performances and robustness of the approach were preserved and providing a first demonstration of metabolomics-based biomarkers integration within a targeted workflow using common benchtop MS instrumentation. In addition, with a view to the widespread implementation of such biomarker-based tools, we have transferred the method to a second laboratory with similar instrumentation. This proof of concept allows the development and application of biomarker-based strategies to meet current doping control needs.

Novel Algorithms for Comprehensive Untargeted Detection of Doping Agents in Biological Samples

To address the limitations of current targeted analytical methods that can only detect known doping agents, a novel methodology that permits untargeted drug detection (UDD) has been developed to help in the fight against doping in sports. Fifty-seven drugs were spiked into blank equine plasma and were treated as unknowns since their exact masses and chromatographic retention times were not utilized for detection. The spiked drugs were extracted from the plasma samples and were analyzed using liquid chromatography coupled to high-resolution mass spectrometry (LC-HRMS). The acquired LC-HRMS raw data files were processed using metabolomic software for compound detection and identification. For UDD with the resultant data, a mathematical model was created, and two algorithms were generated to calculate the ratio of the mean (ROM) and outlier index (OLI). Using ROM and OLI, the majority of the 57 drugs were accurately detected by name (52 of 57) or chemical formula (1 of 57). The limit of detection for the drugs was from tens of picograms to nanograms per milliliter. Xenobiotics and endogenous substances relevant to doping control were also identified using this untargeted approach following their extraction from real-world race samples, thus validating the UDD methodology. To the authors' knowledge, this is the first completely UDD methodological approach and represents significant advance toward using artificial intelligence for the detection of both known and emerging doping agents in sports.

miRNAs detection in equine plasma by quantitative polymerase chain reaction for doping control: Assessment of blood sampling and study of eca-miR-144 as potential erythropoiesis stimulating agent biomarker

Short half-life doping substances are, quickly eliminated and therefore difficult to control with traditional analytical chemistry methods. Indirect methods targeting biomarkers constitute an alternative to extend detection time frames in doping control analyses. Gene expression analysis (i.e., transcriptomics) has already shown interesting results in both humans and equines for erythropoietin (EPO), growth hormone (GH), and anabolic androgenic steroid (AAS) misuses. In humans, circulating cell-free microRNAs in plasma were described as new potential biomarkers for control of major doping agent (MDA) abuses. The development of a quantitative polymerase chain reaction (qPCR) method allowing the detection of circulating miRNAs was carried out on equine plasma collected on different type of tubes (EDTA, lithium-heparin [LiHep]). Although analyzing plasma collected in EDTA tubes is a standard method in molecular biology, analyzing plasma collected in LiHep tubes is challenging, as heparin is a reverse transcription (RT) and a PCR inhibitor. Different strategies were considered, and attention was paid on both miRNAs extraction quality and detection sensitivity. The detection of endogenous circulating miRNAs was performed and compared between the different types of tubes. In parallel, homologs of human miRNAs characterized as potential biomarkers of doping were sought in equine databases. The miRNA eca-miR-144, described as potential erythropoiesis stimulating agents (ESAs) administration candidate biomarker was retained and assessed in equine post-administration samples. The results about the qPCR method development and optimization are exposed as well as the equine miRNAs detection. To our knowledge, this work is the first study and the proof of concept of circulating miRNAs detection in plasma dedicated to equine doping control.

Doping detection in animals: A review of analytical methodologies published from 1990 to 2019

Despite the impressive innate physical abilities of horses, camels, greyhounds, or pigeons, doping agents might be administered to these animals to improve their performance. To control these illegal practices, anti-doping analytical methodologies have been developed. This review compiles the analytical methods that have been published for the detection of prohibited substances administered to animals involved in sports over 30 years. Relevant papers meeting the search criteria that discussed analytical methods aiming to detect and/or quantify doping substances in animal biological matrices published from 1990 to 2019 were considered. A total of 317 studies were included, of which 298 were related to horses, demonstrating significant advances toward the development of doping detection methods for equine sports. However, analytical methods for the detection of doping agents in sports involving other species are lacking. Due to enhanced accuracy and specificity, chromatographic analysis coupled to mass spectrometry detection is preferred over immunoassays. Regarding biological matrices, blood and urine remain the first choice, although alternative biological matrices, such as hair and feces, have been considered. With the increasing number and type of drugs used as doping agents, the analytes addressed in the published papers are diverse. It is very important to continue to detect and quantify these drugs, recognizing those that are most frequently used, in order to punish the abusers, protect animals' health, and ensure a healthier and genuine competition.

Label-free proteomics for discovering biomarker candidates of RAD140 administration to castrated horses

Selective androgen receptor (AR) modulators (SARMs) are potent anabolic agents with a high potential of misuse in horseracing and equestrian sports. In this study, we applied label-free proteomics to discover plasma protein biomarkers in geldings (castrated horses) after administration with a popular SARM named RAD140. Tryptic peptides were prepared from plasma samples and analyzed by nano-flow ultrahigh-performance liquid chromatography-high-resolution tandem mass spectrometry (nano-UHPLC-HRMS/MS) using data-independent acquisition (DIA) method. Orthogonal projection on latent structure-discriminant analysis (OPLS-DA) has led to the development of a predictive model that could discriminate RAD140-administered samples from control samples and could also correctly classify 18 out of 19 in-training horses as control samples. The model comprises 75 proteins with variable importance in projection (VIP) score above 1. Gene Ontology (GO) enrichment analysis and literature review have identified upregulation of AR-regulated clusterin, and proteins associated with inflammation (haptoglobin, cluster of differentiation 14 [CD14], and inter-alpha-trypsin inhibitor heavy chain 4 [ITIH4]) and erythropoiesis (glycosylphosphatidylinositol-specific phospholipase D1 [GPLD1]) after RAD140 administration. Their changes were confirmed by selected reaction monitoring (SRM) experiments. Similar effects have been reported by the use of androgens and other SARMs. This is the first reported study that describes the use of a proteomic biomarker approach to detect horses that have been administered with RAD140 by applying label-free proteomic profiling of plasma samples. These results support the concept of a biomarker-driven approach to enhance the doping control of RAD140 and potentially other SARMs in the future.

Analytical techniques for metabolomic studies: a review

Metabolomics is the comprehensive study of small-molecule metabolites. Obtaining a wide coverage of the metabolome is challenging because of the broad range of physicochemical properties of the small molecules. To study the compounds of interest spectroscopic (NMR), spectrometric (MS) and separation techniques (LC, GC, supercritical fluid chromatography, CE) are used. The choice for a given technique is influenced by the sample matrix, the concentration and properties of the metabolites, and the amount of sample. This review discusses the most commonly used analytical techniques for metabolomic studies, including their advantages, drawbacks and some applications.

Identification of metabolomic changes in horse plasma after racing by liquid chromatography-high resolution mass spectrometry as a strategy for doping testing

Recently, the illegal use of novel technologies, such as gene and cell therapies, has become a great concern for the horseracing industry. As a potential way to control this, metabolomics approaches that comprehensively analyze metabolites in biological samples have been gaining attention. However, it may be difficult to identify metabolic biomarkers for doping because physiological conditions generally differ between resting and exercise states in horses. To understand the metabolic differences in horse plasma between the resting state at training centres and the sample collection stage after racing for doping test (SAD), we took plasma samples from these two stages (n=30 for each stage) and compared the metabolites present in these samples by liquid chromatography-high resolution mass spectrometry. This analysis identified 5,010 peaks, of which 1,256 peaks (approximately 25%) were annotated using KEGG analysis. Principal component analysis showed that the resting state and SAD groups had entirely different metabolite compositions. In particular, the levels of inosine, xanthosine, uric acid, and allantoin, which are induced by extensive exercise, were significantly increased in the SAD group. In addition, many metabolites not affected by extensive exercise were also identified. These results will contribute to the discovery of biomarkers for detecting doping substances that cannot be detected by conventional methods.

Characterization of trotter horses urine metabolome by means of proton nuclear magnetic resonance spectroscopy

BACKGROUND

Metabolomics has been recognized as a powerful approach for disease screening. In order to highlight potential health issues in subjects, a key factor is the possibility to compare quantitatively the metabolome of their biofluids with reference values from healthy individuals. Such efforts towards the systematic characterization of the metabolome of biofluids in perfect health conditions, far from concluded for humans, have barely begun on horses.

OBJECTIVES

The present work attempts, for the first time, to give reference quantitative values for the molecules mostly represented in the urine metabolome of horses at rest and under light training, as observable by ¹H-NMR.

METHODS

The metabolome of ten trotter horses, four male and six female, ranging from 3 to 8 years of age, has been observed by ¹H-NMR spectroscopy before and after three training sessions.

RESULTS

We could characterize and quantify 54 molecules in trotter horse urine, originated from diet, protein digestion, energy generation or gut-microbial co-metabolism.

CONCLUSION

We were able to describe how gender, age and exercise affected their concentration, by means of a two steps protocol based on univariate and robust principal component analysis.