FREE SHIPPING over $40
OVER 9000 FIVE-STAR REVIEWS
5% OFF ALL SUBSCRIPTIONS
100% HAPPINESS GUARANTEE
Analyze Diet
0
Home / Equine Research Bank / J Equine Sci / Identification of metabolomic changes in horse plasma after ...
Journal of equine science2019; 30(3); 55-61; doi: 10.1294/jes.30.55

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

Abstract: 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.
©2019 The Japanese Society of Equine Science.
Get Full Text
Publication Date: 2019-10-02 PubMed ID: 31592223PubMed Central: PMC6773618DOI: 10.1294/jes.30.55Google Scholar: Lookup
The Equine Research Bank provides access to a large database of publicly available scientific literature. Inclusion in the Research Bank does not imply endorsement of study methods or findings by Mad Barn.
LinkedInCopy
  • Journal Article

Summary

This research summary has been generated with artificial intelligence and may contain errors and omissions. Refer to the original study to confirm details provided. Submit correction.

The research article explores the metabolomic differences in horse plasma between resting and post-racing states, with the aim of identifying new biomarkers that could be used for anti-doping testing in the horseracing industry.

Objective of the Study

  • The main purpose of this research is to identify potential metabolic markers for anti-doping testing in horses. This is done by comparing the metabolic differences in horse plasma in different physiological states: resting and post-race.
  • The researchers are attempting to address the increasing concerns in the horseracing industry about the illegal application of gene and cell therapies that may not be detected by conventional testing methods.

Methodology

  • The researchers collected plasma samples from two different stages: the resting stage and the sample collection stage after racing (SAD). For each stage, 30 samples were collected.
  • The plasma from these two stages was then compared using liquid chromatography-high resolution mass spectrometry. This process identified numerous peaks, around 25% of which were annotated through a subsequent KEGG analysis.
  • The researchers then used principal component analysis to differentiate the metabolite compositions at these two stages.

Findings

  • The research identified a total of 1,256 annotated peaks, showing that the resting and post-race states had distinctly different metabolite profiles.
  • The level of inosine, xanthosine, uric acid, and allantoin – all induced by extensive exercise – were significantly higher in the post-race samples.
  • The study also found metabolites that were unaffected by extensive exercise, suggesting these could be potential biomarkers for anti-doping testing.

Implications and Conclusions

  • The study’s findings contribute significantly to the search for biomarkers for detecting doping substances that cannot be detected through conventional methods.
  • By identifying the specific metabolic changes that occur after racing, doping control in horse racing can potentially be improved.
  • The research provides valuable information for further exploration of anti-doping methods in the horseracing industry and could stimulate further developments in the implementation of metabolomics approaches to anti-doping testing.

Cite This Article

APA
Ueda T, Tozaki T, Nozawa S, Kinoshita K, Gawahara H. (2019). Identification of metabolomic changes in horse plasma after racing by liquid chromatography-high resolution mass spectrometry as a strategy for doping testing. J Equine Sci, 30(3), 55-61. https://doi.org/10.1294/jes.30.55

Publication

Journal of equine science
ISSN: 1340-3516
NlmUniqueID: 9503751
Country: Japan
Language: English
Volume: 30
Issue: 3
Pages: 55-61

Researcher Affiliations

Ueda, Toshiki
  • Drug Analysis Department, Laboratory of Racing Chemistry, Tochigi 320-0851, Japan.
Tozaki, Teruaki
  • Genetic Analysis Department, Laboratory of Racing Chemistry, Tochigi 320-0851, Japan.
Nozawa, Satoshi
  • Drug Analysis Department, Laboratory of Racing Chemistry, Tochigi 320-0851, Japan.
Kinoshita, Kenji
  • Drug Analysis Department, Laboratory of Racing Chemistry, Tochigi 320-0851, Japan.
Gawahara, Hitoshi
  • Drug Analysis Department, Laboratory of Racing Chemistry, Tochigi 320-0851, Japan.

References

This article includes 23 references
  1. Berthemy A, Newton J, Wu D, Buhrman D. Quantitative determination of an extremely polar compound allantoin in human urine by LC-MS/MS based on the separation on a polymeric amino column.. J Pharm Biomed Anal 1999 Mar;19(3-4):429-34.
    pubmed: 10704108doi: 10.1016/s0731-7085(98)00200-3google scholar: lookup
  2. Dunn WB, Broadhurst D, Begley P, Zelena E, Francis-McIntyre S, Anderson N, Brown M, Knowles JD, Halsall A, Haselden JN, Nicholls AW, Wilson ID, Kell DB, Goodacre R. Procedures for large-scale metabolic profiling of serum and plasma using gas chromatography and liquid chromatography coupled to mass spectrometry.. Nat Protoc 2011 Jun 30;6(7):1060-83.
    pubmed: 21720319doi: 10.1038/nprot.2011.335google scholar: lookup
  3. González-Domínguez R, García-Barrera T, Gómez-Ariza JL. Combination of metabolomic and phospholipid-profiling approaches for the study of Alzheimer's disease.. J Proteomics 2014 Jun 2;104:37-47.
    pubmed: 24473279doi: 10.1016/j.jprot.2014.01.014google scholar: lookup
  4. Guan F, Robinson MA. Comprehensive solid-phase extraction of multitudinous bioactive peptides from equine plasma and urine for doping detection.. Anal Chim Acta 2017 Sep 8;985:79-90.
    pubmed: 28864198doi: 10.1016/j.aca.2017.07.005google scholar: lookup
  5. Guddat S, Solymos E, Orlovius A, Thomas A, Sigmund G, Geyer H, Thevis M, Schänzer W. High-throughput screening for various classes of doping agents using a new 'dilute-and-shoot' liquid chromatography-tandem mass spectrometry multi-target approach.. Drug Test Anal 2011 Nov-Dec;3(11-12):836-50.
    pubmed: 22135086doi: 10.1002/dta.372google scholar: lookup
  6. Ho EN, Chan GH, Wan TS, Curl P, Riggs CM, Hurley MJ, Sykes D. Controlling the misuse of cobalt in horses.. Drug Test Anal 2015 Jan;7(1):21-30.
    pubmed: 25256240doi: 10.1002/dta.1719google scholar: lookup
  7. Ho EN, Kwok WH, Lau MY, Wong AS, Lam KK, Stewart BD, Wan TS. Doping control analysis of filgrastim in equine plasma and its application to a co-administration study of filgrastim and recombinant human erythropoietin in the horse.. J Chromatogr A 2014 Apr 18;1338:92-101.
    pubmed: 24636755doi: 10.1016/j.chroma.2014.02.064google scholar: lookup
  8. Jandrić Z, Roberts D, Rathor MN, Abrahim A, Islam M, Cannavan A. Assessment of fruit juice authenticity using UPLC-QToF MS: a metabolomics approach.. Food Chem 2014 Apr 1;148:7-17.
    pubmed: 24262519doi: 10.1016/j.foodchem.2013.10.014google scholar: lookup
  9. Jobard E, Pontoizeau C, Blaise BJ, Bachelot T, Elena-Herrmann B, Trédan O. A serum nuclear magnetic resonance-based metabolomic signature of advanced metastatic human breast cancer.. Cancer Lett 2014 Feb 1;343(1):33-41.
    pubmed: 24041867doi: 10.1016/j.canlet.2013.09.011google scholar: lookup
  10. Joré C, Loup B, Garcia P, Paris AC, Popot MA, Audran M, Bonnaire Y, Varlet-Marie E, Bailly-Chouriberry L. Liquid chromatography - high resolution mass spectrometry-based metabolomic approach for the detection of Continuous Erythropoiesis Receptor Activator effects in horse doping control.. J Chromatogr A 2017 Oct 27;1521:90-99.
    pubmed: 28941809doi: 10.1016/j.chroma.2017.09.029google scholar: lookup
  11. Lee JE, Lee BJ, Chung JO, Kim HN, Kim EH, Jung S, Lee H, Lee SJ, Hong YS. Metabolomic unveiling of a diverse range of green tea (Camellia sinensis) metabolites dependent on geography.. Food Chem 2015 May 1;174:452-9.
    pubmed: 25529705doi: 10.1016/j.foodchem.2014.11.086google scholar: lookup
  12. Lopez-Sanchez P, de Vos RC, Jonker HH, Mumm R, Hall RD, Bialek L, Leenman R, Strassburg K, Vreeken R, Hankemeier T, Schumm S, van Duynhoven J. Comprehensive metabolomics to evaluate the impact of industrial processing on the phytochemical composition of vegetable purees.. Food Chem 2015 Feb 1;168:348-55.
    pubmed: 25172720doi: 10.1016/j.foodchem.2014.07.076google scholar: lookup
  13. Mahieu NG, Patti GJ. Systems-Level Annotation of a Metabolomics Data Set Reduces 25 000 Features to Fewer than 1000 Unique Metabolites.. Anal Chem 2017 Oct 3;89(19):10397-10406.
    pmc: PMC6427824pubmed: 28914531doi: 10.1021/acs.analchem.7b02380google scholar: lookup
  14. Mahieu NG, Spalding JL, Gelman SJ, Patti GJ. Defining and Detecting Complex Peak Relationships in Mass Spectral Data: The Mz.unity Algorithm.. Anal Chem 2016 Sep 20;88(18):9037-46.
    pmc: PMC6427821pubmed: 27513885doi: 10.1021/acs.analchem.6b01702google scholar: lookup
  15. Moulard Y, Bailly-Chouriberry L, Boyer S, Garcia P, Popot MA, Bonnaire Y. Use of benchtop exactive high resolution and high mass accuracy orbitrap mass spectrometer for screening in horse doping control.. Anal Chim Acta 2011 Aug 26;700(1-2):126-36.
    pubmed: 21742125doi: 10.1016/j.aca.2011.01.006google scholar: lookup
  16. Raro M, Ibáñez M, Gil R, Fabregat A, Tudela E, Deventer K, Ventura R, Segura J, Marcos J, Kotronoulas A, Joglar J, Farré M, Yang S, Xing Y, Van Eenoo P, Pitarch E, Hernández F, Sancho JV, Pozo ÓJ. Untargeted metabolomics in doping control: detection of new markers of testosterone misuse by ultrahigh performance liquid chromatography coupled to high-resolution mass spectrometry.. Anal Chem 2015 Aug 18;87(16):8373-80.
    pubmed: 26200763doi: 10.1021/acs.analchem.5b02254google scholar: lookup
  17. Shima N, Miyawaki I, Bando K, Horie H, Zaitsu K, Katagi M, Bamba T, Tsuchihashi H, Fukusaki E. Influences of methamphetamine-induced acute intoxication on urinary and plasma metabolic profiles in the rat.. Toxicology 2011 Sep 5;287(1-3):29-37.
    pubmed: 21645582doi: 10.1016/j.tox.2011.05.012google scholar: lookup
  18. Stathis CG, Zhao S, Carey MF, Snow RJ. Purine loss after repeated sprint bouts in humans.. J Appl Physiol (1985) 1999 Dec;87(6):2037-42.
    pubmed: 10601147doi: 10.1152/jappl.1999.87.6.2037google scholar: lookup
  19. Stefano B, Franco T, Oberosler R. Plasma lactate and purine derivatives accumulation after exercise of increasing intensity in standardbred horses. J. Equine Vet. Sci. 1999;19:463–468.
  20. Tozaki T, Gamo S, Takasu M, Kikuchi M, Kakoi H, Hirota KI, Kusano K, Nagata SI. Digital PCR detection of plasmid DNA administered to the skeletal muscle of a microminipig: a model case study for gene doping detection.. BMC Res Notes 2018 Oct 10;11(1):708.
    pmc: PMC6180624pubmed: 30309394doi: 10.1186/s13104-018-3815-6google scholar: lookup
  21. Tozaki T, Ohnuma A, Takasu M, Kikuchi M, Kakoi H, Hirota KI, Kusano K, Nagata SI. Droplet Digital PCR Detection of the Erythropoietin Transgene from Horse Plasma and Urine for Gene-Doping Control.. Genes (Basel) 2019 Mar 21;10(3).
    pmc: PMC6471249pubmed: 30901981doi: 10.3390/genes10030243google scholar: lookup
  22. Wang Y, Caldwell R, Cowan DA, Legido-Quigley C. LC-MS-Based Metabolomics Discovers Purine Endogenous Associations with Low-Dose Salbutamol in Urine Collected for Antidoping Tests.. Anal Chem 2016 Feb 16;88(4):2243-9.
    pubmed: 26760048doi: 10.1021/acs.analchem.5b03927google scholar: lookup
  23. Wong KS, Chan GHM, Ho ENM, Wan TSM. Simultaneous detection of recombinant growth hormones in equine plasma by liquid chromatography/high-resolution tandem mass spectrometry for doping control.. J Chromatogr A 2016 Dec 23;1478:35-42.
    pubmed: 27914605doi: 10.1016/j.chroma.2016.11.032google scholar: lookup

Citations

This article has been cited 4 times.
  1. Ishii H, Shibuya M, Kusano K, Sone Y, Kamiya T, Wakuno A, Ito H, Miyata K, Sato F, Kuroda T, Yamada M, Leung GN. Generic approach for the discovery of drug metabolites in horses based on data-dependent acquisition by liquid chromatography high-resolution mass spectrometry and its applications to pharmacokinetic study of daprodustat. Anal Bioanal Chem 2022 Nov;414(28):8125-8142.
    doi: 10.1007/s00216-022-04347-2pubmed: 36181513google scholar: lookup
  2. Halama A, Oliveira JM, Filho SA, Qasim M, Achkar IW, Johnson S, Suhre K, Vinardell T. Metabolic Predictors of Equine Performance in Endurance Racing. Metabolites 2021 Jan 31;11(2).
    doi: 10.3390/metabo11020082pubmed: 33572513google scholar: lookup
  3. Ishii H, Shigematsu R, Takemoto S, Ishikawa Y, Mizobe F, Nomura M, Arima D, Kunii H, Yuasa R, Yamanaka T, Tanabe S, Nagata SI, Yamada M, Leung GN. Quantification of osilodrostat in horse urine using LC/ESI-HRMS to establish an elimination profile for doping control. Bioanalysis 2024;16(17-18):947-958.
    doi: 10.1080/17576180.2024.2385848pubmed: 39235065google scholar: lookup
  4. Laus F, Bazzano M, Spaterna A, Laghi L, Marchegiani A. Nuclear Magnetic Resonance (NMR) Metabolomics: Current Applications in Equine Health Assessment. Metabolites 2024 May 7;14(5).
    doi: 10.3390/metabo14050269pubmed: 38786746google scholar: lookup
Subscribe to our newsletter
Join 99,001 horse owners like you who receive our email updates on horse health and nutrition.