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Cartilage debris and osteoarthritis risk factors influence gene expression in the synovium in end stage osteoarthritis

  • Margaret M. Roebuck
    Correspondence
    Corresponding author at: Department of Musculoskeletal & Ageing Science, Institute of Life Course & Medical Sciences, University of Liverpool, Liverpool L7 8TX, United Kingdom.
    Affiliations
    Department of Musculoskeletal & Ageing Science, Institute of Life Course & Medical Sciences, University of Liverpool, Liverpool L7 8TX, United Kingdom

    Department of Molecular and Clinical Cancer Medicine, Institute of Translational Medicine, University of Liverpool, Liverpool L3 9TA, United Kingdom
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  • Juliana Jamal
    Affiliations
    Department of Musculoskeletal & Ageing Science, Institute of Life Course & Medical Sciences, University of Liverpool, Liverpool L7 8TX, United Kingdom

    Department of Pharmacology, Faculty of Medicine, University of Malaya, Kuala Lumpur 50603, Malaysia
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  • Brian Lane
    Affiliations
    Department of Musculoskeletal Biology, Institute of Ageing and Chronic Disease, University of Liverpool, Liverpool L69 3BX, United Kingdom
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  • Amanda Wood
    Affiliations
    Department of Musculoskeletal & Ageing Science, Institute of Life Course & Medical Sciences, University of Liverpool, Liverpool L7 8TX, United Kingdom
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  • Alasdair Santini
    Affiliations
    Liverpool University Hospitals NHS Foundation Trust, Prescot Street, Liverpool L7 8XP, United Kingdom

    Faculty of Health and Life Science, The University of Liverpool, University of Liverpool, Liverpool L7 8TX, United Kingdom
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  • Pooi-Fong Wong
    Affiliations
    Department of Pharmacology, Faculty of Medicine, University of Malaya, Kuala Lumpur 50603, Malaysia
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  • George Bou-Gharios
    Affiliations
    Department of Musculoskeletal & Ageing Science, Institute of Life Course & Medical Sciences, University of Liverpool, Liverpool L7 8TX, United Kingdom
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  • Author Footnotes
    † Died February 08, 2020
    Simon P. Frostick
    Footnotes
    † Died February 08, 2020
    Affiliations
    Department of Molecular and Clinical Cancer Medicine, Institute of Translational Medicine, University of Liverpool, Liverpool L3 9TA, United Kingdom
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  • Author Footnotes
    † Died February 08, 2020

      Highlights

      • Detailed clinical, histology and expression data from 33 patients was triangulated.
      • Synovial gene expression profiles from knee OA and two non-OA injuries are reported.
      • OA risk factors BMI and gender, impact the significance of synovial gene expression.
      • UPR is the top up-regulated pathway in OA synovium.
      • ER-associated degradation pathway component SYVN1 may be therapeutic target for OA.

      Abstract

      Background

      Gene expression in healthy synovium remains poorly characterised. Thus, synovial functional activity changes associated with osteoarthritis (OA) are difficult to define. This study sought to identify differentially expressed genes (DEG) of end-stage OA and assess the influence of OA risk factors on these DEG.

      Methods

      Anonymised patient clinical data and x-ray images were analysed. Osteoarthritic and non-osteoarthritic patients with soft tissue or traumatic knee injuries were matched for body mass index (BMI) and sex. Tissue samples were partitioned for immunocytochemistry (IHC) and microarray analysis. Multiple bioinformatics applications were utilised to determine changes in functional and canonical pathway activation.

      Results

      Age, disease-modifying injections and hypertension were confounding factors between patient groups. Inflammation was present in all tissues. Cartilage debris and inflammatory aggregates were noted in many osteoarthritic patient tissues. IHC and expression analyses revealed upregulation of synoviolin 1 (SYVN1) in osteoarthritic synovium. Significant differential expression was noted in 2084 genes. Osteoarthritic synovium displayed a significant upregulation of 95% of DEG coding for proteins, relative to non-osteoarthritic synovium tissues. Unfolded protein response (UPR)-related genes were upregulated in osteoarthritic synovium; gene expression of molecules within many canonical pathways including protein ubiquitination and UPR pathways was modified by BMI and sex.

      Conclusions

      The synovium of all three pathologies exhibited elements of an inflammatory response. Cartilage debris, age, BMI and sex influence DEG of osteoarthritic synovium. UPR pathway is the top deregulated canonical pathway identified in osteoarthritic synovium regardless of BMI and sex, while typical OA-associated inflammatory and matrix gene responses were minimal.

      Keywords

      Abbreviations:

      BM (Base Model), BMI (body mass index), DEG (differentially expressed genes), IHC (immunohistochemistry), IM (Improved Model), IM-OATKR (Improved Model-OA total knee replacement), IPA (Ingenuity pathway analysis), OATKR (OA total knee replacement), PCA (Principal component analysis), SF-12 Ph (The Short Form 12 physical score), SF-12 M (The Short Form 12 mental score), SYVN1 (synoviolin), WOMAC (The Western Ontario and McMaster Universities Osteoarthritis Index)
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      References

        • Loeser R.F.
        • Goldring S.R.
        • Scanzello C.R.
        • Goldring M.B.
        Osteoarthritis: A disease of the joint as an organ.
        Arthritis Rheum. 2012; 64: 1697-1707https://doi.org/10.1002/art.34453
        • Felson D.T.
        • Lawrence R.C.
        • Dieppe P.A.
        • Hirsch R.
        • Helmick C.G.
        • Jordan J.M.
        • et al.
        Osteoarthritis: New Insights. Part 1: The Disease and Its Risk Factors.
        Ann Intern Med. 2000; 133: 635-646https://doi.org/10.7326/0003-4819-133-8-200010170-00016
      1. Powers-Freeling L. Knees - Primary Procedures - Patient Characteristics; 2018. Available from: https://reports.njrcentre.org.uk/knees-primary-procedures-patient-characteristics.

        • Sl M.
        • Kd B.
        • Jw E.
        • Em B.
        • Kd S.
        • Da H.
        • et al.
        Synovial inflammation in patients with early osteoarthritis of the knee.
        J Rheumatol. 1990; 17: 1662-1669
        • Sellam J.
        • Berenbaum F.
        The role of synovitis in pathophysiology and clinical symptoms of osteoarthritis.
        Nat Rev Rheumatol. 2010; 6: 625-635https://doi.org/10.1038/nrrheum.2010.159
      2. TM G, CR S. Innate inflammation and synovial macrophages in osteoarthritis pathophysiology. Clin Exp Rheumatol 2019;37 Suppl 120(5):57–63.

        • Mathiessen A.
        • Conaghan P.G.
        Synovitis in osteoarthritis: current understanding with therapeutic implications.
        Arthritis Res Therapy. 2017; 19: 18https://doi.org/10.1186/s13075-017-1229-9
        • Woetzel D.
        • Huber R.
        • Kupfer P.
        • Pohlers D.
        • Pfaff M.
        • Driesch D.
        • et al.
        Identification of rheumatoid arthritis and osteoarthritis patients by transcriptome-based rule set generation.
        Arthritis Res Therapy. 2014; 16: R84https://doi.org/10.1186/ar4526
        • Zhang X.
        • Bu Y.
        • Zhu B.
        • Zhao Q.
        • Lv Z.
        • Li B.
        • et al.
        Global transcriptome analysis to identify critical genes involved in the pathology of osteoarthritis.
        Bone Joint Res. 2018; 7: 298-307https://doi.org/10.1302/2046-3758.74.BJR-2017-0245.R1
        • Zhu N.
        • Hou J.
        • Wu Y.
        • Li G.
        • Liu J.
        • Ma G.
        • et al.
        Identification of key genes in rheumatoid arthritis and osteoarthritis based on bioinformatics analysis.
        Medicine. 2018; 97: e10997https://doi.org/10.1097/MD.0000000000010997
        • Cai P.
        • Jiang T.
        • Li B.
        • Qin X.
        • Lu Z.
        • Le Y.
        • et al.
        Comparison of rheumatoid arthritis (RA) and osteoarthritis (OA) based on microarray profiles of human joint fibroblast-like synoviocytes.
        Cell Biochem Funct. 2019; 37: 31-41https://doi.org/10.1002/cbf.3370
        • Broeren M.G.A.
        • de Vries M.
        • Bennink M.B.
        • van Lent P.L.E.M.
        • van der Kraan P.M.
        • Koenders M.I.
        • et al.
        Functional Tissue Analysis Reveals Successful Cryopreservation of Human Osteoarthritic Synovium.
        PLoS ONE. 2016; 11: e0167076https://doi.org/10.1371/journal.pone.0167076
        • Huang H.
        • Zheng J.
        • Shen N.
        • Wang G.
        • Zhou G.
        • Fang Y.
        • et al.
        Identification of pathways and genes associated with synovitis in osteoarthritis using bioinformatics analyses.
        Sci Rep. 2018; 8https://doi.org/10.1038/s41598-018-28280-6
        • Li Z.
        • Wang Q.
        • Chen G.
        • Li X.
        • Yang Q.
        • Du Z.
        • et al.
        Integration of Gene Expression Profile Data to Screen and Verify Hub Genes Involved in Osteoarthritis.
        Biomed Res Int. 2018; 2018: 1-10https://doi.org/10.1155/2018/9482726
        • Del Rey M.J.
        • Usategui A.
        • Izquierdo E.
        • Cañete J.D.
        • Blanco F.J.
        • Criado G.
        • et al.
        Transcriptome analysis reveals specific changes in osteoarthritis synovial fibroblasts.
        Ann Rheum Dis. 2012; 71: 275-280https://doi.org/10.1136/annrheumdis-2011-200281
        • Balakrishnan L.
        • Nirujogi R.S.
        • Ahmad S.
        • Bhattacharjee M.
        • Manda S.S.
        • Renuse S.
        • et al.
        Proteomic analysis of human osteoarthritis synovial fluid.
        Clin Proteomics. 2014; 11https://doi.org/10.1186/1559-0275-11-6
        • Hastings S.L.
        Encyclopedia of Research Design.
        Triangulation. 2012; https://doi.org/10.4135/9781412961288
        • Mahler E.A.
        • Zweers M.C.
        • van Lent P.L.
        • Blom A.B.
        • van den Hoogen F.H.
        • van den Berg W.B.
        • et al.
        Association between serum levels of the proinflammatory protein S100A8/A9 and clinical and structural characteristics of patients with established knee, hip, and hand osteoarthritis.
        Scand J Rheumatol. 2015; 44: 56-60https://doi.org/10.3109/03009742.2014.918176
      3. Jamal J. The Role of Knee Synovium in the Pathophysiology of Osteoarthritis Institute of Life Course and Medical Sciences 2021;Dual PhD University of Liverpool, United Kingdom and University of Malaya, Malaysia https://doi.org/10.17638/03118190.

        • Kellgren J.H.
        • Lawrence J.S.
        Radiological Assessment of Osteo-Arthrosis.
        Ann Rheum Dis. 1957; 16: 494-502https://doi.org/10.1136/ard.16.4.494
        • Kohn M.D.
        • Sassoon A.A.
        • Fernando N.D.
        Classifications in Brief: Kellgren-Lawrence Classification of Osteoarthritis.
        Clin Orthopaedics Related Res®. 2016; 474: 1886-1893https://doi.org/10.1007/s11999-016-4732-4
        • McConnell S.
        • Kolopack P.
        • Davis A.M.
        The Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC): a review of its utility and measurement properties.
        Arthritis Care Res. 2001; 45: 453-461https://doi.org/10.1002/1529-0131(200110)45:5<453::AID-ART365>3.0.CO;2-W
        • Ware Jr., J.
        • Kosinski M.
        • Keller S.D.
        A 12-Item Short-Form Health Survey: construction of scales and preliminary tests of reliability and validity.
        Med Care. 1996; 34: 220-233https://doi.org/10.1097/00005650-199603000-00003
      4. Gene N. Entrez, gene ID; 2019. Available from: https://www.ncbi.nlm.nih.gov/gene/.

      5. Uniprot K. Uniprot protein database; 2019. Available from: https://www.uniprot.org/.

        • Lenz M.
        • Müller F.J.
        • Zenke M.
        • Schuppert A.
        Principal components analysis and the reported low intrinsic dimensionality of gene expression microarray data.
        Sci Rep. 2016; 6: 25696https://doi.org/10.1038/srep25696
        • Krenn V.
        • Morawietz L.
        • Burmester G.-R.
        • Kinne R.W.
        • Mueller-Ladner U.
        • Muller B.
        • et al.
        Synovitis score: discrimination between chronic low-grade and high-grade synovitis.
        Histopathology. 2006; 49: 358-364https://doi.org/10.1111/j.1365-2559.2006.02508.x
        • Krenn V.
        • Perino G.
        • Rüther W.
        • Krenn V.T.
        • Huber M.
        • Hügle T.
        • et al.
        15 years of the histopathological synovitis score, further development and review: A diagnostic score for rheumatology and orthopaedics.
        Pathology - Res Practice. 2017; 213: 874-881
        • Hutchinson R.A.
        • Coleman H.G.
        • Gately K.
        • Young V.
        • Nicholson S.
        • Cummins R.
        • et al.
        IHC-based subcellular quantification provides new insights into prognostic relevance of FLIP and procaspase-8 in non-small-cell lung cancer.
        Cell Death Discov. 2017; 3https://doi.org/10.1038/cddiscovery.2017.50
        • Pfaffl M.W.
        A new mathematical model for relative quantification in real-time RT–PCR.
        Nucleic Acids Res. 2001; 29 (e45-e)https://doi.org/10.1093/nar/29.9.e45
        • Fradin D.
        • Boëlle P.-Y.
        • Belot M.-P.
        • Lachaux F.
        • Tost J.
        • Besse C.
        • et al.
        Genome-Wide Methylation Analysis Identifies Specific Epigenetic Marks In Severely Obese Children.
        Sci Rep. 2017; 7https://doi.org/10.1038/srep46311
        • Glastonbury C.
        • Viñuela A.
        • Buil A.
        • Halldorsson G.
        • Thorleifsson G.
        • Helgason H.
        • et al.
        Adiposity-Dependent Regulatory Effects on Multi-tissue Transcriptomes.
        Am J Human Genet. 2016; 99: 567-579
        • Vincenz-Donnelly L.
        • Hipp M.S.
        The endoplasmic reticulum: A hub of protein quality control in health and disease.
        Free Radical Biol Med. 2017; 108: 383-393https://doi.org/10.1016/j.freeradbiomed.2017.03.031
        • Hamdan N.
        • Kritsiligkou P.
        • Grant C.M.
        ER stress causes widespread protein aggregation and prion formation.
        J Cell Biol. 2017; 216: 2295-2304https://doi.org/10.1083/jcb.201612165
        • Karamyshev A.L.
        • Karamysheva Z.N.
        Lost in Translation: Ribosome-Associated mRNA and Protein Quality Controls.
        Front Genet. 2018; 9https://doi.org/10.3389/fgene.2018.00431
        • Higgins R.
        • Gendron J.
        • Rising L.
        • Mak R.
        • Webb K.
        • Kaiser S.
        • et al.
        The Unfolded Protein Response Triggers Site-Specific Regulatory Ubiquitylation of 40S Ribosomal Proteins.
        Mol Cell. 2015; 59: 35-49
        • Iida Y.
        • Fujimori T.
        • Okawa K.
        • Nagata K.
        • Wada I.
        • Hosokawa N.
        SEL1L Protein Critically Determines the Stability of the HRD1-SEL1L Endoplasmic Reticulum-associated Degradation (ERAD) Complex to Optimize the Degradation Kinetics of ERAD Substrates.
        J Biol Chem. 2011; 286: 16929-16939https://doi.org/10.1074/jbc.M110.215871
        • Hwang J.
        • Walczak C.P.
        • Shaler T.A.
        • Olzmann J.A.
        • Zhang L.
        • Elias J.E.
        • et al.
        Characterization of protein complexes of the endoplasmic reticulum-associated degradation E3 ubiquitin ligase Hrd1.
        J Biol Chem. 2017; 292: 9104-9116https://doi.org/10.1074/jbc.M117.785055
        • Yagishita N.
        • Ohneda K.
        • Amano T.
        • Yamasaki S.
        • Sugiura A.
        • Tsuchimochi K.
        • et al.
        Essential Role of Synoviolin in Embryogenesis.
        J Biol Chem. 2005; 280: 7909-7916https://doi.org/10.1074/jbc.M410863200
        • Fujita H.
        • Yagishita N.
        • Aratani S.
        • Saito-Fujita T.
        • Morota S.
        • Yamano Y.
        • et al.
        The E3 ligase synoviolin controls body weight and mitochondrial biogenesis through negative regulation of PGC-1β.
        The EMBO J. 2015; 34: 1042-1055https://doi.org/10.15252/embj.201489897
        • Yamasaki S.
        • Yagishita N.
        • Tsuchimochi K.
        • Nishioka K.
        • Nakajima T.
        Rheumatoid arthritis as a hyper-endoplasmic reticulum-associated degradation disease.
        Arthritis Res Therapy. 2005; 7: 181https://doi.org/10.1186/ar1808
        • López-Otín C.
        • Blasco M.A.
        • Partridge L.
        • Serrano M.
        • Kroemer G.
        The Hallmarks of Aging.
        Cell. 2013; 153: 1194-1217https://doi.org/10.1016/j.cell.2013.05.039
        • Hipp M.S.
        • Kasturi P.
        • Hartl F.U.
        The proteostasis network and its decline in ageing.
        Nat Rev Mol Cell Biol. 2019; 20: 421-435https://doi.org/10.1038/s41580-019-0101-y
        • Shorter J.
        • Iijima K.M.
        The Mammalian Disaggregase Machinery: Hsp110 Synergizes with Hsp70 and Hsp40 to Catalyze Protein Disaggregation and Reactivation in a Cell-Free System.
        PLoS ONE. 2011; 6: e26319https://doi.org/10.1371/journal.pone.0026319
        • van der Merwe C.
        • Jalali Sefid Dashti Z.
        • Christoffels A.
        • Loos B.
        • Bardien S.
        Evidence for a common biological pathway linking three Parkinson's disease-causing genes: parkin, PINK1 and DJ-1.
        Eur J Neurosci. 2015; 41: 1113-1125https://doi.org/10.1111/ejn.12872
        • Ma J.
        • Malladi S.
        • Beck A.H.
        Systematic Analysis of Sex-Linked Molecular Alterations and Therapies in Cancer.
        Sci Rep. 2016; 6: 19119https://doi.org/10.1038/srep19119
        • Park J.M.
        • Kim J.W.
        • Hahm K.B.
        HSPA4, the “Evil Chaperone” of the HSP Family, Delays Gastric Ulcer Healing.
        Dig Dis Sci. 2015; 60: 824-826https://doi.org/10.1007/s10620-015-3597-9
        • Adachi T.
        • Sakurai T.
        • Kashida H.
        • Mine H.
        • Hagiwara S.
        • Matsui S.
        • et al.
        Involvement of Heat Shock Protein A4/Apg-2 in Refractory Inflammatory Bowel Disease.
        Inflamm Bowel Dis. 2015; 21: 31-39
        • Kocaturk N.M.
        • Gozuacik D.
        Crosstalk Between Mammalian Autophagy and the Ubiquitin-Proteasome System.
        Front Cell Dev Biol. 2018; 6https://doi.org/10.3389/fcell.2018.00128
        • Benyair R.
        • Ron E.
        • Lederkremer G.Z.
        Protein quality control, retention, and degradation at the endoplasmic reticulum.
        Int Rev Cell Mol Biol. 2011; 292: 197-280https://doi.org/10.1016/b978-0-12-386033-0.00005-0
        • Noordzij M.
        • Tripepi G.
        • Dekker F.W.
        • Zoccali C.
        • Tanck M.W.
        • Jager K.J.
        Sample size calculations: basic principles and common pitfalls.
        Nephrol Dial Transplant. 2010; 25: 1388-1393https://doi.org/10.1093/ndt/gfp732