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Soluble biochemical markers of osteoarthritis: Are we close to using them in clinical practice?

Mobasheri, Ali; Bay-Jensen, Anne-Christine; Gualillo, O. et al.

2017 • In Best Practice and Research. Clinical Rheumatology, 31, p. 705-720

Peer Reviewed verified by ORBi

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https://hdl.handle.net/2268/247193

DOI
10.1016/j.berh.2018.07.002

PubMed
30509415

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Keywords :

Biomarker; Clinical phenotype; Clinical practice; Drug development tool; Molecular endotype; Osteoarthritis (OA); Patient stratification

Abstract :

[en] Osteoarthritis (OA) is the most common form of arthritis and a major cause of pain and disability. Recent work suggests that the global burden of OA is increasing, and costs associated with treatment are expected to increase dramatically as the aging human population expands. OA is currently diagnosed using radiography, but this technique is an indirect and insensitive measure of alterations in articular cartilage and fails to measure dynamic inflammatory processes in the joint. Radiographic changes detected overtime are small and occur in only a subset (progressors) of patients with OA. Therefore, we diagnose patients with OA on the basis of a diagnostic classification that is outdated. We also use the same tools and approaches for assessing the efficacy of new pharmacological and nonpharmacological interventions. In this review, we discuss the utility of soluble biochemical markers as biomarkers of OA and discuss whether we are close to using them in clinical practice. Combining patient information, functional imaging and carefully selected panels of biomarkers can help in achieving enhanced patient stratification and lead to better designed clinical trials. Biomarkers can be used for molecular endotyping and for developing more effective and more personalized treatments that will enhance clinical care for patients with OA. © 2018

Disciplines :

Rheumatology

Author, co-author :

Mobasheri, Ali; The D-BOARD FP7 Consortium, United Kingdom, The APPROACH IMI Consortium, United Kingdom, Faculty of Health and Medical Sciences, University of Surrey, Guildford, Surrey, United Kingdom, Arthritis Research UK Centre for Sport, Exercise and Osteoarthritis, Queen's Medical Centre, Nottingham, United Kingdom, Department of Regenerative Medicine, State Research Institute Centre for Innovative Medicine, Vilnius, Lithuania

Bay-Jensen, Anne-Christine; The D-BOARD FP7 Consortium, United Kingdom, The APPROACH IMI Consortium, United Kingdom, Rheumatology, Biomarkers and Research, Nordic Bioscience A/S, Herlev, Denmark

Gualillo, O.; SERGAS (Servizo Galego de Saude) and IDIS (Instituto de Investigación Sanitaria de Santiago), Research Laboratory 9, The NEIRID Lab (Neuroendocrine Interactions in Rheumatology and Inflammatory Diseases), Santiago University Clinical Hospital, Santiago de Compostela, 15706, Spain

Larkin, J.; The APPROACH IMI Consortium, United Kingdom, C3 DPU, Immunoinflammation Therapeutic Area, GlaxoSmithKline, King of Prussia, PA 19406, United States

Levesque, Marc C.; The APPROACH IMI Consortium, United Kingdom, AbbVie Bioresearch Center, 100 Research Drive, Worcester, MA 01605, United States

Henrotin, Yves ; Université de Liège - ULiège > Département des sciences de la motricité > Unité de recherche sur l'os et le cartilage (U.R.O.C.)

Language :

English

Title :

Soluble biochemical markers of osteoarthritis: Are we close to using them in clinical practice?

Publication date :

2017

Journal title :

Best Practice and Research. Clinical Rheumatology

ISSN :

1521-6942

eISSN :

1532-1770

Publisher :

Bailliere Tindall Ltd

Volume :

31

Pages :

705-720

Peer reviewed :

Peer Reviewed verified by ORBi

European Projects :

FP7 - 305815 - D-BOARD - Novel Diagnostics and Biomarkers for Early Identification of Chronic Inflammatory Joint Diseases
H2020 - 734899 - Olive-Net - Bioactive compounds from Olea europaea: investigation and application in food, cosmetic and pharmaceutical industry

Funders :

UE - Union Européenne [BE]
FSE - Fonds Social Européen [BE]
ISCIII - Instituto de Salud Carlos III [ES]
FEDER - Fonds Européen de Développement Régional [BE]
CE - Commission Européenne [BE]

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Bibliography

Loeser, R.F., The role of aging in the development of osteoarthritis. Trans Am Clin Climatol Assoc 128 (2017), 44–54.
Neogi, T., Structural correlates of pain in osteoarthritis. Clin Exp Rheumatol 35:Suppl 107 (2017), 75–78.
Martin, J.A., Buckwalter, J.A., Aging, articular cartilage chondrocyte senescence and osteoarthritis. Biogerontology 3 (2002), 257–264.
Altman, R.D., Hochberg, M., Murphy, W.A., Wolfe, F., Lequesne, M., Atlas of individual radiographic features in osteoarthritis. Osteoarthr Cartil 3:Suppl A (1995), 3–70.
Ackerman, I.N., Kemp, J.L., Crossley, K.M., Culvenor, A.G., Hinman, R.S., Hip and knee osteoarthritis affects younger people, too. J Orthop Sports Phys Ther 47 (2017), 67–79, 10.2519/jospt.2017.7286.
Kloppenburg, M., Hand osteoarthritis-nonpharmacological and pharmacological treatments. Nat Rev Rheumatol 10 (2014), 242–251, 10.1038/nrrheum.2013.214.
Hiligsmann, M., Cooper, C., Arden, N., Boers, M., Branco, J.C., Luisa Brandi, M., et al. Health economics in the field of osteoarthritis: an expert's consensus paper from the European society for clinical and Economic aspects of osteoporosis and osteoarthritis (ESCEO). Semin Arthritis Rheum 43 (2013), 303–313, 10.1016/j.semarthrit.2013.07.003.
Berenbaum, F., Osteoarthritis as an inflammatory disease (osteoarthritis is not osteoarthrosis!). Osteoarthr Cartil 21 (2013), 16–21, 10.1016/j.joca.2012.11.012.
Magnini, D., Montemurro, G., Iovene, B., Tagliaboschi, L., Gerardi, R.E., Lo Greco, E., et al. Idiopathic pulmonary fibrosis: molecular endotypes of fibrosis stratifying existing and emerging therapies. Respiration 93 (2017), 379–395, 10.1159/000475780.
Goodwin, A.T., Jenkins, G., Molecular endotyping of pulmonary fibrosis. Chest 149 (2016), 228–237, 10.1378/chest.15-1511.
Biomarkers Definitions Working Group. Biomarkers and surrogate endpoints: preferred definitions and conceptual framework. Clin Pharmacol Ther 69 (2001), 89–95, 10.1067/mcp.2001.113989.
Henrotin, Y., Sanchez, C., Bay-Jensen, A.C., Mobasheri, A., Osteoarthritis biomarkers derived from cartilage extracellular matrix: current status and future perspectives. Ann Phys Rehabil Med 59 (2016), 145–148, 10.1016/j.rehab.2016.03.004.
Luo, Y., Sinkeviciute, D., He, Y., Karsdal, M., Henrotin, Y., Mobasheri, A., et al. The minor collagens in articular cartilage. Protein Cell 8 (2017), 560–572, 10.1007/s13238-017-0377-7.
Ioan-Facsinay, A., Kloppenburg, M., Bioactive lipids in osteoarthritis: risk or benefit?. Curr Opin Rheumatol 30 (2018), 108–113, 10.1097/BOR.0000000000000463.
Loeser, R.F., Pathmasiri, W., Sumner, S.J., McRitchie, S., Beavers, D., Saxena, P., et al. Association of urinary metabolites with radiographic progression of knee osteoarthritis in overweight and obese adults: an exploratory study. Osteoarthr Cartil 24 (2016), 1479–1486, 10.1016/j.joca.2016.03.011.
Budd, E., Nalesso, G., Mobasheri, A., Extracellular genomic biomarkers of osteoarthritis. Expert Rev Mol Diagn 18 (2018), 55–74, 10.1080/14737159.2018.1415757.
Kraus, V.B., Blanco, F.J., Englund, M., Karsdal, M.A., Lohmander, L.S., Call for standardized definitions of osteoarthritis and risk stratification for clinical trials and clinical use. Osteoarthr Cartil 23 (2015), 1233–1241, 10.1016/j.joca.2015.03.036.
Englund, M., The role of biomechanics in the initiation and progression of OA of the knee. Best Pract Res Clin Rheumatol 24 (2010), 39–46, 10.1016/j.berh.2009.08.008.
Mobasheri, A., Rayman, M.P., Gualillo, O., Sellam, J., van der Kraan, P., Fearon, U., The role of metabolism in the pathogenesis of osteoarthritis. Nat Rev Rheumatol 13 (2017), 302–311, 10.1038/nrrheum.2017.50.
Courties, A., Gualillo, O., Berenbaum, F., Sellam, J., Metabolic stress-induced joint inflammation and osteoarthritis. Osteoarthr Cartil 23 (2015), 1955–1965, 10.1016/j.joca.2015.05.016.
Loeser, R.F., Aging and osteoarthritis. Curr Opin Rheumatol 23 (2011), 492–496, 10.1097/BOR.0b013e3283494005.
Siebuhr, A.S., Bay-Jensen, A.C., Jordan, J.M., Kjelgaard-Petersen, C.F., Christiansen, C., Abramson, S.B., et al. Inflammation (or synovitis)-driven osteoarthritis: an opportunity for personalizing prognosis and treatment?. Scand J Rheumatol 45 (2016), 87–98, 10.3109/03009742.2015.1060259.
Rahmati, M., Mobasheri, A., Mozafari, M., Inflammatory mediators in osteoarthritis: a critical review of the state-of-the-art, current prospects, and future challenges. Bone 85 (2016), 81–90, 10.1016/j.bone.2016.01.019.
Mahjoub, M., Berenbaum, F., Houard, X., Why subchondral bone in osteoarthritis? The importance of the cartilage bone interface in osteoarthritis. Osteoporos Int 23:Suppl 8 (2012), S841–S846, 10.1007/s00198-012-2161-0.
Goldring, M.B., Goldring, S.R., Osteoarthritis. J Cell Physiol 213 (2007), 626–634, 10.1002/jcp.21258.
Liu-Bryan, R., Synovium and the innate inflammatory network in osteoarthritis progression. Curr Rheumatol Rep, 15, 2013, 323, 10.1007/s11926-013-0323-5.
Scanzello, C.R., Goldring, S.R., The role of synovitis in osteoarthritis pathogenesis. Bone 51 (2012), 249–257, 10.1016/j.bone.2012.02.012.
Sutton, S., Clutterbuck, A., Harris, P., Gent, T., Freeman, S., Foster, N., et al. The contribution of the synovium, synovial derived inflammatory cytokines and neuropeptides to the pathogenesis of osteoarthritis. Vet J 179 (2009), 10–24, 10.1016/j.tvjl.2007.08.013.
de Lange-Brokaar, B.J.E., Ioan-Facsinay, A., van Osch, G.J.V.M., Zuurmond, A.M., Schoones, J., Toes, R.E.M., et al. Synovial inflammation, immune cells and their cytokines in osteoarthritis: a review. Osteoarthr Cartil 20 (2012), 1484–1499, 10.1016/j.joca.2012.08.027.
Sellam, J., Berenbaum, F., The role of synovitis in pathophysiology and clinical symptoms of osteoarthritis. Nat Rev Rheumatol 6 (2010), 625–635, 10.1038/nrrheum.2010.159.
Poulet, B., Beier, F., Targeting oxidative stress to reduce osteoarthritis. Arthritis Res Ther, 18, 2016, 32, 10.1186/s13075-015-0908-7.
Mobasheri, A., Matta, C., Zákány, R., Musumeci, G., Chondrosenescence: definition, hallmarks and potential role in the pathogenesis of osteoarthritis. Maturitas 80 (2015), 237–244, 10.1016/j.maturitas.2014.12.003.
Bierma-Zeinstra, S.M., van Middelkoop, M., Osteoarthritis: in search of phenotypes. Nat Rev Rheumatol 13 (2017), 705–706, 10.1038/nrrheum.2017.181.
Vandiedonck, C., Genetic association of molecular traits: a help to identify causative variants in complex diseases. Clin Genet 93 (2018), 520–532, 10.1111/cge.13187.
Deveza, L.A., Loeser, R.F., Is osteoarthritis one disease or a collection of many?. Rheumatology (Oxford), 2017, 10.1093/rheumatology/kex417.
Dell'Isola, A., Steultjens, M., Classification of patients with knee osteoarthritis in clinical phenotypes: data from the osteoarthritis initiative. PLoS One, 13, 2018, e0191045, 10.1371/journal.pone.0191045.
Dell'Isola, A., Allan, R., Smith, S.L., Marreiros, S.S.P., Steultjens, M., Identification of clinical phenotypes in knee osteoarthritis: a systematic review of the literature. BMC Musculoskelet Disord, 17, 2016, 425, 10.1186/s12891-016-1286-2.
Bay-Jensen, A.C., Slagboom, E., Chen-An, P., Alexandersen, P., Qvist, P., Christiansen, C., et al. Role of hormones in cartilage and joint metabolism: understanding an unhealthy metabolic phenotype in osteoarthritis. Menopause 20 (2013), 578–586, 10.1097/GME.0b013e3182745993.
Zhuo, Q., Yang, W., Chen, J., Wang, Y., Metabolic syndrome meets osteoarthritis. Nat Rev Rheumatol 8 (2012), 729–737, 10.1038/nrrheum.2012.135.
Arendt-Nielsen, L., Pain sensitisation in osteoarthritis. Clin Exp Rheumatol 35:Suppl 107 (2017), 68–74.
Baudart, P., Louati, K., Marcelli, C., Berenbaum, F., Sellam, J., Association between osteoarthritis and dyslipidaemia: a systematic literature review and meta-analysis. RMD Open, 3, 2017, e000442, 10.1136/rmdopen-2017-000442.
Courties, A., Sellam, J., Berenbaum, F., Metabolic syndrome-associated osteoarthritis. Curr Opin Rheumatol 29 (2017), 214–222, 10.1097/BOR.0000000000000373.
June, R.K., Liu-Bryan, R., Long, F., Griffin, T.M., Emerging role of metabolic signaling in synovial joint remodeling and osteoarthritis. J Orthop Res 34 (2016), 2048–2058, 10.1002/jor.23420.
Deveza, L.A., Melo, L., Yamato, T.P., Mills, K., Ravi, V., Hunter, D.J., Knee osteoarthritis phenotypes and their relevance for outcomes: a systematic review. Osteoarthr Cartil 25 (2017), 1926–1941, 10.1016/j.joca.2017.08.009.
Cotofana, S., Wyman, B.T., Benichou, O., Dreher, D., Nevitt, M., Gardiner, J., et al. Relationship between knee pain and the presence, location, size and phenotype of femorotibial denuded areas of subchondral bone as visualized by MRI. Osteoarthr Cartil 21 (2013), 1214–1222, 10.1016/j.joca.2013.04.001.
van der Esch, M., Knoop, J., van der Leeden, M., Roorda, L.D., Lems, W.F., Knol, D.L., et al. Clinical phenotypes in patients with knee osteoarthritis: a study in the Amsterdam osteoarthritis cohort. Osteoarthr Cartil 23 (2015), 544–549, 10.1016/j.joca.2015.01.006.
Iranpour-Boroujeni, T., Li, J., Lynch, J.A., Nevitt, M., Duryea, J., Investigators, O.A.I., A new method to measure anatomic knee alignment for large studies of OA: data from the osteoarthritis initiative. Osteoarthr Cartil 22 (2014), 1668–1674, 10.1016/j.joca.2014.06.011.
Kittelson, A.J., Stevens-Lapsley, J.E., Schmiege, S.J., Determination of pain phenotypes in knee osteoarthritis: a latent class analysis using data from the osteoarthritis initiative. Arthritis Care Res (Hoboken) 68 (2016), 612–620, 10.1002/acr.22734.
Eckstein, F., Wirth, W., Nevitt, M.C., Recent advances in osteoarthritis imaging–the osteoarthritis initiative. Nat Rev Rheumatol 8 (2012), 622–630, 10.1038/nrrheum.2012.113.
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 133 (2000), 635–646, 10.7326/0003-4819-133-8-200010170-00016.
Mobasheri, A., Batt, M., An update on the pathophysiology of osteoarthritis. Ann Phys Rehabil Med 59 (2016), 333–339, 10.1016/j.rehab.2016.07.004.
Bay-Jensen, A.-C., Henrotin, Y., Karsdal, M., Mobasheri, A., The need for predictive, prognostic, objective and complementary blood-based biomarkers in osteoarthritis (OA). EBioMedicine 7 (2016), 4–6, 10.1016/j.ebiom.2016.05.004.
Bay-Jensen, A.C., Reker, D., Kjelgaard-Petersen, C.F., Mobasheri, A., Karsdal, M.A., Ladel, C., et al. Osteoarthritis year in review 2015: soluble biomarkers and the BIPED criteria. Osteoarthr Cartil 24 (2016), 9–20, 10.1016/j.joca.2015.10.014.
Henrotin, Y., Sanchez, C., Cornet, A., Van de Put, J., Douette, P., Gharbi, M., Soluble biomarkers development in osteoarthritis: from discovery to personalized medicine. Biomarkers 20 (2015), 540–546, 10.3109/1354750X.2015.1123363.
Mobasheri, A., Osteoarthritis year 2012 in review: biomarkers. Osteoarthr Cartil 20 (2012), 1451–1464, 10.1016/j.joca.2012.07.009.
Mobasheri, A., Bay-Jensen, A.C., van Spil, W.E., Larkin, J., Levesque, M.C., Osteoarthritis Year in Review 2016: biomarkers (biochemical markers). Osteoarthr Cartil 25 (2017), 199–208, 10.1016/j.joca.2016.12.016.
van Spil, W.E., DeGroot, J., Lems, W.F., Oostveen, J.C.M., Lafeber, F.P.J.G., Serum and urinary biochemical markers for knee and hip-osteoarthritis: a systematic review applying the consensus BIPED criteria. Osteoarthr Cartil 18 (2010), 605–612, 10.1016/j.joca.2010.01.012.
Cohen-Solal, M., Funck-Brentano, T., Hay, E., Animal models of osteoarthritis for the understanding of the bone contribution. BoneKEy Rep, 2, 2013, 422, 10.1038/bonekey.2013.156.
Lotz, M., Martel-Pelletier, J., Christiansen, C., Brandi, M.L., Bruyère, O., Chapurlat, R., et al. Value of biomarkers in osteoarthritis: current status and perspectives. Ann Rheum Dis 72 (2013), 1756–1763, 10.1136/annrheumdis-2013-203726.
Bauer, D.C., Hunter, D.J., Abramson, S.B., Attur, M., Corr, M., Felson, D., et al. Classification of osteoarthritis biomarkers: a proposed approach. Osteoarthr Cartil 14 (2006), 723–727, 10.1016/j.joca.2006.04.001.
Kraus, V.B., Burnett, B., Coindreau, J., Cottrell, S., Eyre, D., Gendreau, M., et al. Application of biomarkers in the development of drugs intended for the treatment of osteoarthritis. Osteoarthr Cartil 19 (2011), 515–542, 10.1016/j.joca.2010.08.019.
Kraus, V.B., Collins, J.E., Hargrove, D., Losina, E., Nevitt, M., Katz, J.N., et al. Predictive validity of biochemical biomarkers in knee osteoarthritis: data from the FNIH OA Biomarkers Consortium. Ann Rheum Dis 76 (2017), 186–195, 10.1136/annrheumdis-2016-209252.
Azuaje, F., What does systems biology mean for biomarker discovery?. Expert Opin Med Diagn 4 (2010), 1–10, 10.1517/17530050903468709.
Oresic, M., Clish, C.B., Davidov, E.J., Verheij, E., Vogels, J., Havekes, L.M., et al. Phenotype characterisation using integrated gene transcript, protein and metabolite profiling. Appl Bioinf 3 (2004), 205–217.
Jónasdóttir, H.S., Brouwers, H., Kwekkeboom, J.C., van der Linden, H.M.J., Huizinga, T., Kloppenburg, M., et al. Targeted lipidomics reveals activation of resolution pathways in knee osteoarthritis in humans. Osteoarthr Cartil 25 (2017), 1150–1160, 10.1016/j.joca.2017.01.018.
Kosinska, M.K., Mastbergen, S.C., Liebisch, G., Wilhelm, J., Dettmeyer, R.B., Ishaque, B., et al. Comparative lipidomic analysis of synovial fluid in human and canine osteoarthritis. Osteoarthr Cartil 24 (2016), 1470–1478, 10.1016/j.joca.2016.03.017.
Barter, M.J., Young, D.A., Epigenetic mechanisms and non-coding RNAs in osteoarthritis. Curr Rheumatol Rep, 15, 2013, 353, 10.1007/s11926-013-0353-z.
Wang, X., Ning, Y., Zhou, B., Yang, L., Wang, Y., Guo, X., Integrated bioinformatics analysis of the osteoarthritis-associated microRNA expression signature. Mol Med Rep 17 (2018), 1833–1838, 10.3892/mmr.2017.8057.
Ntoumou, E., Tzetis, M., Braoudaki, M., Lambrou, G., Poulou, M., Malizos, K., et al. Serum microRNA array analysis identifies miR-140-3p, miR-33b-3p and miR-671-3p as potential osteoarthritis biomarkers involved in metabolic processes. Clin Epigenet, 9, 2017, 127, 10.1186/s13148-017-0428-1.
Sanchez, C., Bay-Jensen, A.C., Pap, T., Dvir-Ginzberg, M., Quasnichka, H., Barrett-Jolley, R., et al. Chondrocyte secretome: a source of novel insights and exploratory biomarkers of osteoarthritis. Osteoarthr Cartil 25 (2017), 1199–1209, 10.1016/j.joca.2017.02.797.
Clutterbuck, A.L., Smith, J.R., Allaway, D., Harris, P., Liddell, S., Mobasheri, A., High throughput proteomic analysis of the secretome in an explant model of articular cartilage inflammation. J Proteomics 74 (2011), 704–715, 10.1016/j.jprot.2011.02.017.
Williams, A., Smith, J.R., Allaway, D., Harris, P., Liddell, S., Mobasheri, A., Carprofen inhibits the release of matrix metalloproteinases 1, 3, and 13 in the secretome of an explant model of articular cartilage stimulated with interleukin 1β. Arthritis Res Ther, 15, 2013, R223, 10.1186/ar4424.
Stoddart, M.J., Bara, J., Alini, M., Cells and secretome–towards endogenous cell re-activation for cartilage repair. Adv Drug Deliv Rev 84 (2015), 135–145, 10.1016/j.addr.2014.08.007.
Dvir-Ginzberg, M., Reich, E., Chopping off the chondrocyte proteome. Biomarkers 20 (2015), 526–532, 10.3109/1354750X.2014.955884.
Liao, W., Li, Z., Li, T., Zhang, Q., Zhang, H., Wang, X., Proteomic analysis of synovial fluid in osteoarthritis using SWATH-mass spectrometry. Mol Med Rep 17 (2018), 2827–2836, 10.3892/mmr.2017.8250.
Gharbi, M., Deberg, M., Henrotin, Y., Application for proteomic techniques in studying osteoarthritis: a review. Front Physiol, 2, 2011, 90, 10.3389/fphys.2011.00090.
Ruiz-Romero, C., Rego-Perez, I., Blanco, F.J., What did we learn from “omics” studies in osteoarthritis. Curr Opin Rheumatol 30 (2018), 114–120, 10.1097/BOR.0000000000000460.
Ourradi, K., Sharif, M., Opportunities and challenges for the discovery and validation of proteomic biomarkers for common arthritic diseases. Biomarkers Med 11 (2017), 877–892, 10.2217/bmm-2016-0374.
Lourido, L., Ayoglu, B., Fernández-Tajes, J., Oreiro, N., Henjes, F., Hellström, C., et al. Discovery of circulating proteins associated to knee radiographic osteoarthritis. Sci Rep, 7, 2017, 137, 10.1038/s41598-017-00195-8.
Sierra-Sánchez, Á., Garrido-Martín, D., Lourido, L., González-González, M., Díez, P., Ruiz-Romero, C., et al. Screening and validation of novel biomarkers in osteoarticular pathologies by comprehensive combination of protein array technologies. J Proteome Res 16 (2017), 1890–1899, 10.1021/acs.jproteome.6b00980.
Siebert, S., Porter, D., Paterson, C., Hampson, R., Gaya, D., Latosinska, A., et al. Urinary proteomics can define distinct diagnostic inflammatory arthritis subgroups. Sci Rep, 7, 2017, 40473, 10.1038/srep40473.
Miyaki, S., Lotz, M.K., Extracellular vesicles in cartilage homeostasis and osteoarthritis. Curr Opin Rheumatol 30 (2018), 129–135, 10.1097/BOR.0000000000000454.
Rocha, B., Ruiz-Romero, C., Blanco, F.J., Mass spectrometry imaging: a novel technology in rheumatology. Nat Rev Rheumatol 13 (2017), 52–63, 10.1038/nrrheum.2016.184.
Zhai, G., Wang-Sattler, R., Hart, D.J., Arden, N.K., Hakim, A.J., Illig, T., et al. Serum branched-chain amino acid to histidine ratio: a novel metabolomic biomarker of knee osteoarthritis. Ann Rheum Dis 69 (2010), 1227–1231, 10.1136/ard.2009.120857.
Zhang, W., Sun, G., Aitken, D., Likhodii, S., Liu, M., Martin, G., et al. Lysophosphatidylcholines to phosphatidylcholines ratio predicts advanced knee osteoarthritis. Rheumatology (Oxford) 55 (2016), 1566–1574, 10.1093/rheumatology/kew207.
Francisco, V., Pino, J., Gonzalez-Gay, M.A., Mera, A., Lago, F., Gómez, R., et al. Adipokines and inflammation: is it a question of weight?. Br J Pharmacol, 2018, 10.1111/bph.14181.
Abella, V., Scotece, M., Conde, J., Gómez, R., Lois, A., Pino, J., et al. The potential of lipocalin-2/NGAL as biomarker for inflammatory and metabolic diseases. Biomarkers 20 (2015), 565–571, 10.3109/1354750X.2015.1123354.
Abella, V., Pino, J., Scotece, M., Conde, J., Lago, F., Gonzalez-Gay, M.A., et al. Progranulin as a biomarker and potential therapeutic agent. Drug Discov Today 22 (2017), 1557–1564, 10.1016/j.drudis.2017.06.006.
Francisco, V., Pérez, T., Pino, J., López, V., Franco, E., Alonso, A., et al. Biomechanics, obesity, and osteoarthritis. The role of adipokines: when the levee breaks. J Orthop Res 36 (2018), 594–604, 10.1002/jor.23788.
Abella, V., Scotece, M., Conde, J., Pino, J., Gonzalez-Gay, M.A., Gómez-Reino, J.J., et al. Leptin in the interplay of inflammation, metabolism and immune system disorders. Nat Rev Rheumatol 13 (2017), 100–109, 10.1038/nrrheum.2016.209.
Siebelt, M., Agricola, R., Weinans, H., Kim, Y.J., The role of imaging in early hip OA. Osteoarthr Cartil 22 (2014), 1470–1480, 10.1016/j.joca.2014.04.030.
Ding, C., Zhang, Y., Hunter, D., Use of imaging techniques to predict progression in osteoarthritis. Curr Opin Rheumatol 25 (2013), 127–135, 10.1097/BOR.0b013e32835a0fe1.

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