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Metabolomic and Proteomic Stratification of Equine Osteoarthritis

View ORCID ProfileJames R Anderson, Marie M Phelan, Eva Caamaño-Gutiérrez, Peter D Clegg, Luis M Rubio-Martinez, Mandy J Peffers
doi: https://doi.org/10.1101/2020.05.04.077305
James R Anderson
1Musculoskeletal and Ageing Science, Institute of Life Course and Medical Sciences, University of Liverpool, Liverpool, UK
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  • For correspondence: janders@liverpool.ac.uk
Marie M Phelan
2NMR Metabolomics Facility, Technology Directorate & Department of Biochemistry & Systems Biology, Institute of Systems, Molecular and Integrative Biology, Liverpool, UK
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Eva Caamaño-Gutiérrez
3Computational Biology Facility, Technology Directorate & Department of Biochemistry and Systems Biology, Institute of Systems, Molecular and Integrative Biology, Liverpool, UK
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Peter D Clegg
1Musculoskeletal and Ageing Science, Institute of Life Course and Medical Sciences, University of Liverpool, Liverpool, UK
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Luis M Rubio-Martinez
1Musculoskeletal and Ageing Science, Institute of Life Course and Medical Sciences, University of Liverpool, Liverpool, UK
4Equine Clinical Science, Institute of Infection, Veterinary and Ecological Sciences, University of Liverpool, Neston, UK
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Mandy J Peffers
1Musculoskeletal and Ageing Science, Institute of Life Course and Medical Sciences, University of Liverpool, Liverpool, UK
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Abstract

Osteoarthritis (OA) is characterised by loss of articular cartilage, synovial membrane dysfunction and subchondral sclerosis. Few studies have used a global approach to stratify equine synovial fluid (SF) molecular profiles according to OA severity. SF was collected from 58 metacarpophalangeal (MCP) and metatarsophalangeal joints of racing Thoroughbred horses (Hong Kong Jockey Club; HKJC) and 83 MCP joints of mixed breed horses from an abattoir and equine hospital (biobank). Joints were histologically and macroscopically assessed for OA severity. For proteomic analysis, native SF and SF loaded onto ProteoMiner™ equalisation columns, to deplete high abundant proteins, were analysed using liquid chromatography-tandem mass spectrometry (LC-MS/MS) and label-free quantification. Validation of selected differentially expressed proteins was undertaken using clinical SF collected during diagnostic investigations. Native SF metabolites were analysed using 1D 1H Nuclear Magnetic Resonance (NMR). 1,834 proteins and 40 metabolites were identified in equine SF. Afamin levels decreased with synovitis severity and four uncharacterised proteins decreased with OA severity. Gelsolin and lipoprotein binding protein decreased with OA severity and apolipoprotein A1 levels increased for mild and moderate OA. Within the biobank, glutamate levels decreased with OA severity and for the HKJC cohort, 2-aminobutyrate, alanine and creatine increased with severity. Proteomic and metabolomic integration was undertaken using linear regression via Lasso penalisation modelling, incorporating 29 variables (R2=0.82) with principal component 2 able to discriminate advanced OA from earlier stages, predominantly driven by H9GZQ9, F6ZR63 and alanine. Combining biobank and HKJC datasets, discriminant analysis of principal components modelling prediction was good for mild OA (90%). This study has stratified equine OA using both metabolomic and proteomic SF profiles and identified a panel of markers of interest which may be applicable to grading OA severity. This is also the first study to undertake computational integration of NMR metabolomic and LC-MS/MS proteomic datasets of any biological system.

Competing Interest Statement

The authors have declared no competing interest.

Footnotes

  • Supplementary material has been added to version 2.

  • https://www.ebi.ac.uk/metabolights/MTBLS1645

  • Abbreviations

    ADAMTS
    A disintegrin and metalloproteinase with thrombospondin motifs
    ApoA1
    Apolipoprotein A1
    ApoA2
    Apolipoprotein A-II
    BLAST
    Basic local alignment search tool
    CPMG
    Carr-Purcell-Meiboom-Gill
    COMP
    Cartilage oligomeric matrix protein
    CD14
    Cluster of differentiation 14
    DAPC
    Discriminant analysis of principal components
    ECM
    Extracellular matrix
    FDR
    False discovery rate
    H & E
    Haematoxylin and eosin
    HDL
    High density lipoprotein
    HKJC
    Hong Kong Jockey Club
    Lasso
    Least absolute shrinkage and selection operator
    LBP
    Lipopolysaccharide binding protein
    MMP
    Matrix metalloproteinase
    MSI
    Metabolomics Standards Initiative
    MCP
    Metacarpophalangeal
    MTP
    Metatarsophalangeal
    OA
    Osteoarthritis
    POD
    Palmar/plantar osteochondral disease
    PFA
    Paraformaldehyde
    PCA
    Principal component analysis
    PQN
    Probabilistic quotient normalisation
    Saf O
    Safranin O
    SF
    Synovial fluid
    TIC
    Total ion current.
  • Copyright 
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    Metabolomic and Proteomic Stratification of Equine Osteoarthritis
    James R Anderson, Marie M Phelan, Eva Caamaño-Gutiérrez, Peter D Clegg, Luis M Rubio-Martinez, Mandy J Peffers
    bioRxiv 2020.05.04.077305; doi: https://doi.org/10.1101/2020.05.04.077305
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    Metabolomic and Proteomic Stratification of Equine Osteoarthritis
    James R Anderson, Marie M Phelan, Eva Caamaño-Gutiérrez, Peter D Clegg, Luis M Rubio-Martinez, Mandy J Peffers
    bioRxiv 2020.05.04.077305; doi: https://doi.org/10.1101/2020.05.04.077305

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