Biomarkers for equine joint injury and osteoarthritis

McIlwraith, C. Wayne; Kawcak, Christopher E.; Frisbie, David D.; Little, Christopher B.; Clegg, Peter; Peffers, Mandy J.; Karsdal, Morten A.; Ekman, Stina; Laverty, Sheila; Slayden, Richard A.; Sandell, Linda J.; Lohmander, L.S.; Kraus, Virginia B.

doi:10.1002/jor.23738

Cited by 50 publications

(43 citation statements)

References 84 publications

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“…However, due to the slow onset of the condition, this often leads to substantial pathology of the joint, particularly to articular cartilage prior to diagnosis 10 . There is therefore a need to develop diagnostic tests which are sensitive and specific to the early stages of OA, which are repeatable and reproducible, as well as gaining a greater understanding of the underlying pathogenesis 11,12 . Early detection of OA could enable timely management interventions which could potentially slow the progression of the disease.…”

Section: Introductionmentioning

confidence: 99%

Ex-VivoEquine Cartilage Explant Osteoarthritis Model - A Metabolomics and Proteomics Study

Anderson

Phelan

Foddy

et al. 2020

Preprint

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Osteoarthritis (OA) is an age-related degenerative musculoskeletal disease characterised by loss of articular cartilage, synovitis, abnormal bone proliferation and subchondral bone sclerosis. Underlying OA pathogenesis is yet to be fully elucidated with no OA specific biomarkers in clinical use. Ex-vivo equine cartilage explants (n=5) were incubated in TNFα/IL-1β supplemented culture media for 8 days, with media removed and replaced at 2, 5 and 8 days. Acetonitrile metabolite extractions of 8 day cartilage explants and media samples at all time points underwent 1D 1 H nuclear magnetic resonance metabolomic analysis with media samples also undergoing mass spectrometry proteomic analysis.Within the cartilage, metabolites glucose and lysine were elevated following TNF-α/IL-1β treatment whilst adenosine, alanine, betaine, creatine, myo-inositol and uridine levels decreased. Within the culture media, four, four and six differentially abundant metabolites and 154, 138 and 72 differentially abundant proteins, with > 2 fold change, were identified for 1-2 day, 3-5 day and 6-8 day time points respectively. Nine potential novel OA neopeptides were elevated in treated media. Our innovative study has identified differentially abundant metabolites, proteins and extracellular matrix derived neopeptides, providing insightful information on OA pathogenesis, enabling potential translation for clinical markers and possible new therapeutic targets.

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Section: Introductionmentioning

confidence: 99%

Ex-VivoEquine Cartilage Explant Osteoarthritis Model - A Metabolomics and Proteomics Study

Anderson

Phelan

Foddy

et al. 2020

Preprint

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“…Metabolite phenotypic profiling captures relationships of the cellular processes they represent. It provides multi‐dimensional information on biochemical responses of complex systems to a range of intrinsic and environmental stimuli under specific circumstances , with the ultimate aim of serving as unique ‘fingerprints’ or disease biomarkers in named pathological states. Compared with other biochemical techniques, metabolomics requires minimal pretreatment and processing and has been used successfully in the rapid assessment of numerous systemic disease states in human and veterinary medicine .…”

Section: Introductionmentioning

confidence: 99%

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

Graham

Anderson

Phelan

et al. 2019

Equine Veterinary Journal

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Summary Background 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. Objectives 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. Study design 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 1H‐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. Main limitations 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.

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“…There has been ongoing interest for several decades in developing biochemical biomarker approaches to identify joint disease at an early stage. To date such approaches have identified some promise but have yet to identify biochemical markers which can accurately predict disease for an individual [21]. Two recent studies have investigated specific biomarkers.…”

mentioning

confidence: 99%

Clinical insights: Recent developments in equine articular disease (2016–2018)

Clegg

2018

Equine Veterinary Journal

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Biomarkers for equine joint injury and osteoarthritis

Cited by 50 publications

References 84 publications

Ex-VivoEquine Cartilage Explant Osteoarthritis Model - A Metabolomics and Proteomics Study

Ex-VivoEquine Cartilage Explant Osteoarthritis Model - A Metabolomics and Proteomics Study

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

Clinical insights: Recent developments in equine articular disease (2016–2018)

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