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Home / Equine Research Bank / Equine Vet J / Metabolomic analysis of synovial fluid from Thoroughbred rac...
Equine veterinary journal2019; 52(3); 384-390; doi: 10.1111/evj.13199

Metabolomic analysis of synovial fluid from Thoroughbred racehorses diagnosed with palmar osteochondral disease using magnetic resonance imaging.

Abstract: Palmar osteochondral disease (POD) is a common cause of lameness in competition horses. Magnetic resonance imaging (MRI) is the most sensitive diagnostic modality currently available, however it may not be financially or logistically practical for routine screening of POD. There is increasing interest in the use of metabolomics for diagnosis prior to progression to irreversible damage. Objective: To determine metabolite levels in synovial fluid (SF) of horses with a clinical diagnosis of POD based on diagnostic analgesia and MRI, with the hypothesis that metabolomic profiles differ between diseased and healthy joints. Methods: Prospective clinical study. Methods: Synovial fluid was collected from metacarpo/tarsophalangeal joints (MC/TPJ) of 29 horses (n = 51 joints), including 14 controls (n = 26) and 15 cases (n = 25), the latter with lameness localised to the MC/TPJ and MR changes consistent with POD (n = 23). Spectra were produced using 1 H-nuclear magnetic resonance (NMR) spectroscopy and analysed. Results: Twenty-five metabolites were recognised associated with various biosynthetic and degradation pathways. The metabolite abundances within the controls demonstrated increased variability compared with the clinical group. The low level of variance between the spectra of the two groups was explained by five principal components. Cross-validation of the cohort demonstrated modest separation of predictive power (R2  = 0.67; Q2  = 0.34). Although statistical significance was not achieved, the most influential metabolites were glucose and lactate. Conclusions: The modest sample size and variation in signalment, background and presenting condition of the controls may have impacted the discriminative power of the constructed models. The lack of matched controls, differences in time of fluid collection and freezing times may have also reduced accuracy when representing metabolite profiles. Conclusions: This study identified and quantified metabolites present in MC/TPJ SF of clinical cases with POD.
© 2019 EVJ Ltd.
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Publication Date: 2019-11-28 PubMed ID: 31657070DOI: 10.1111/evj.13199Google Scholar: Lookup
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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.

This study aimed to explore the potential of using metabolomic analysis in determining the presence of a common lameness-causing disease called Palmar Osteochondral Disease in racehorses. Using magnetic resonance imaging for diagnosis, the researchers then compared metabolite levels in the synovial fluid of healthy horses with those diagnosed with the disease.

Objective and Methodology

  • The objective of this research was to identify differences between the metabolomic profiles of healthy horse joints and those suffering from Palmar Osteochondral Disease (POD). The study hypothesized that there would be significant differences between these profiles.
  • The researchers carried out a clinical study in which the synovial fluid (fluid that reduces friction in the cavities of synovial joints) was collected from a particular joint of 29 Thoroughbred racehorses, with 15 cases identified as having POD based on MRI and diagnostic analgesia.
  • The researchers then used H-nuclear magnetic resonance (NMR) spectroscopy to produce spectra (a representation of the composition of the sample) and analyzed the results.

Results and Findings

  • The study recognized twenty-five metabolites (substances formed in or necessary for metabolism) associated with various biosynthetic and degradation pathways. The metabolites’ abundances were more variable in the healthy joints compared to the diseased ones.
  • Five principal components explained the low level of variance between the spectra of the two groups. This suggests that despite being from different groups, the metabolic profiles were similar.
  • Statistical significance was not achieved, but glucose and lactate were identified as the most influential metabolites. Their levels could be an important predictor for the disease.

Conclusion and Limitations

  • The study successfully identified and quantified metabolites present in a specific joint’s synovial fluid in clinical cases with POD.
  • The moderate sample size alongside varying backgrounds and conditions of the controls may have affected the discriminative power of the constructed models, which could lead to less robust predictions and conclusions.
  • The absence of matched controls (both in terms of disease profile and other factors such as time of fluid collection and freezing times) could have also caused inaccuracies in representing metabolite profiles.

This research contributes to the ongoing investigation and discussion around using metabolomics as a diagnostic tool which can eventually expedite diagnosis and treatment for Palmar Osteochondral Disease in horses.

Cite This Article

APA
Graham RJTY, Anderson JR, Phelan MM, Cillan-Garcia E, Bladon BM, Taylor SE. (2019). Metabolomic analysis of synovial fluid from Thoroughbred racehorses diagnosed with palmar osteochondral disease using magnetic resonance imaging. Equine Vet J, 52(3), 384-390. https://doi.org/10.1111/evj.13199

Publication

Equine veterinary journal
ISSN: 2042-3306
NlmUniqueID: 0173320
Country: United States
Language: English
Volume: 52
Issue: 3
Pages: 384-390

Researcher Affiliations

Graham, R J T Y
  • Equine Hospital, Royal (Dick) School of Veterinary Studies, University of Edinburgh, Midlothian, UK.
Anderson, J R
  • Institute of Ageing and Chronic Disease, University of Liverpool, Liverpool, UK.
Phelan, M M
  • Institute of Integrative Biology, University of Liverpool, Liverpool, UK.
  • HLS Technology Directorate, University of Liverpool, Liverpool, UK.
Cillan-Garcia, E
  • Equine Hospital, Royal (Dick) School of Veterinary Studies, University of Edinburgh, Midlothian, UK.
Bladon, B M
  • Donnington Grove Veterinary Group, Newbury, Berkshire, UK.
Taylor, S E
  • Equine Hospital, Royal (Dick) School of Veterinary Studies, University of Edinburgh, Midlothian, UK.

MeSH Terms

  • Animals
  • Horse Diseases
  • Horses
  • Magnetic Resonance Imaging
  • Metabolomics
  • Prospective Studies
  • Synovial Fluid

Grant Funding

  • MR/M009114/1 / Medical Research Council
  • J. Anderson was generously funded through a Horse Trust PhD studentship.
  • CS024 / Horserace Betting Levy Board

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Citations

This article has been cited 5 times.
  1. 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
  2. Laus F, Gialletti R, Bazzano M, Laghi L, Dini F, Marchegiani A. Synovial Fluid Metabolome Can Differentiate between Healthy Joints and Joints Affected by Osteoarthritis in Horses. Metabolites 2023 Aug 4;13(8).
    doi: 10.3390/metabo13080913pubmed: 37623857google scholar: lookup
  3. Noordwijk KJ, Qin R, Diaz-Rubio ME, Zhang S, Su J, Mahal LK, Reesink HL. Metabolism and global protein glycosylation are differentially expressed in healthy and osteoarthritic equine carpal synovial fluid. Equine Vet J 2022 Mar;54(2):323-333.
    doi: 10.1111/evj.13440pubmed: 33587757google scholar: lookup
  4. Anderson JR, Phelan MM, Foddy L, Clegg PD, Peffers MJ. Ex Vivo Equine Cartilage Explant Osteoarthritis Model: A Metabolomics and Proteomics Study. J Proteome Res 2020 Sep 4;19(9):3652-3667.
    doi: 10.1021/acs.jproteome.0c00143pubmed: 32701294google scholar: lookup
  5. Anderson JR, Phelan MM, Rubio-Martinez LM, Fitzgerald MM, Jones SW, Clegg PD, Peffers MJ. Optimization of Synovial Fluid Collection and Processing for NMR Metabolomics and LC-MS/MS Proteomics. J Proteome Res 2020 Jul 2;19(7):2585-2597.
    doi: 10.1021/acs.jproteome.0c00035pubmed: 32227958google scholar: lookup
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