Value of biomarkers in osteoarthritis: current status and perspectives

Abstract

Osteoarthritis affects the whole joint structure with progressive changes in cartilage, menisci, ligaments and subchondral bone, and synovial inflammation. Biomarkers are being developed to quantify joint remodelling and disease progression. This article was prepared following a working meeting of the European Society for Clinical and Economic Aspects of Osteoporosis and Osteoarthritis convened to discuss the value of biochemical markers of matrix metabolism in drug development in osteoarthritis. The best candidates are generally molecules or molecular fragments present in cartilage, bone or synovium and may be specific to one type of joint tissue or common to them all. Many currently investigated biomarkers are associated with collagen metabolism in cartilage or bone, or aggrecan metabolism in cartilage. Other biomarkers are related to non-collagenous proteins, inflammation and/or fibrosis. Biomarkers in osteoarthritis can be categorised using the burden of disease, investigative, prognostic, efficacy of intervention, diagnostic and safety classification. There are a number of promising candidates, notably urinary C-terminal telopeptide of collagen type II and serum cartilage oligomeric protein, although none is sufficiently discriminating to differentiate between individual patients and controls (diagnostic) or between patients with different disease severities (burden of disease), predict prognosis in individuals with or without osteoarthritis (prognostic) or perform so consistently that it could function as a surrogate outcome in clinical trials (efficacy of intervention). Future avenues for research include exploration of underlying mechanisms of disease and development of new biomarkers; technological development; the ‘omics’ (genomics, metabolomics, proteomics and lipidomics); design of aggregate scores combining a panel of biomarkers and/or imaging markers into single diagnostic algorithms; and investigation into the relationship between biomarkers and prognosis.

Chemical Isotope Labeling LC-MS for Monitoring Disease Progression and Treatment in Animal Models: Plasma Metabolomics Study of Osteoarthritis Rat Model

“…Current treatment is limited to symptom control, pain management and (rarely) surgical intervention. In order to develop specific pharmacological treatment options, finding biomarkers of OA and using them to evaluate the efficacy of a potential therapeutics would be of highly significant17. These biomarkers may also provide helpful information for understanding the pathogenic process of the disease at the molecular level17.…”

Evaluation of biomarkers following autologous osteochondral transplantation in the equine stifle joint — An experimental study

“…This study investigated only three biomarkers, which was due to the limited budget available to us. Investigating more biomarkers could have highlighted further processes occurring in the joint after AOT (Lotz et al, 2013). Horses were turned out into paddocks but did not have controlled exercise, which would have been beneficial for testing the results of this transplantation method.…”

“…The best candidates for biomarkers in osteoarthritis are most likely to be structural molecules or fragments linked to cartilage, bone or synovium and may be specific to one type of joint tissue or common to them all. They may represent tissue degradation or tissue synthesis and may be measured in synovial fluid, blood or urine (Lotz et al, 2013).…”

Extending the Paradigm of Osteoarthritis: Comment on the Editorial by McAlindon

“…For stratification, the starting point is to take advantage of new analytical, proteomic, deep sequencing, and imaging modalities that are now available. These techniques may also be crucial in enhancing identification of early markers of disease mechanisms (17,18). These are essential techniques to enable patient intervention before irreparable damage has occurred and also to focus trials of new treatments in subsets of patients who are likely to respond and thereby to reduce the failure rate of candidate drugs (10,11).…”