A Mobasheri1. 1. Musculoskeletal Research Group, School of Veterinary Medicine and Science, Faculty of Medicine and Health Sciences, The University of Nottingham, Sutton Bonington Campus, Sutton Bonington, UK. ali.mobasheri@nottingham.ac.uk
Abstract
PURPOSE: Biomarkers provide useful diagnostic information by detecting cartilage degradation in osteoarthritis (OA), reflecting disease-relevant biological activity and predicting the course of disease progression. They also serve as surrogate endpoints in the drug discovery process. The aim of this narrative review was to focus on OA biomarker-related papers published between the osteoarthritis research society international (OARSI) 2011 meeting in San Diego and the OARSI 2012 meeting in Barcelona. METHODS: The PubMed/MEDLINE and SciVerse Scopus bibliographic databases were searched using the keywords: 'biomarker' and 'osteoarthritis' and/or 'biomarker' and 'proteomics'. RESULTS: Ninety-eight papers were found with the keywords 'biomarker' and 'osteoarthritis'. Fifteen papers were found with the keywords 'biomarker' and 'proteomics'. Review articles were also included. The most relevant published studies focused on extracellular matrix (ECM) molecules in body fluids. Enrichment of the deamidated epitope of cartilage oligomeric matrix protein (D-COMP) suggests that OA disease progression is associated with post-translational modifications that may show specificity for particular joint sites. Fibulin-3 peptides (Fib3-1 and Fib3-2) have been proposed as potential biomarkers of OA along with follistatin-like protein 1 (FSTL1), a new serum biomarker with the capacity to reflect the severity of joint damage. The 'membrane attack complex' (MAC) component of complement has also been implicated in OA. CONCLUSION: Novel OA biomarkers are needed for sub-clinical disease diagnosis. Proteomic techniques are beginning to yield useful data and deliver new OA biomarkers in serum and urine. Combining biochemical markers with tissue and cell imaging techniques and bioinformatics (i.e., machine learning, clustering, data visualization) may facilitate the development of biomarker combinations enabling earlier detection of OA.
PURPOSE: Biomarkers provide useful diagnostic information by detecting cartilage degradation in osteoarthritis (OA), reflecting disease-relevant biological activity and predicting the course of disease progression. They also serve as surrogate endpoints in the drug discovery process. The aim of this narrative review was to focus on OA biomarker-related papers published between the osteoarthritis research society international (OARSI) 2011 meeting in San Diego and the OARSI 2012 meeting in Barcelona. METHODS: The PubMed/MEDLINE and SciVerse Scopus bibliographic databases were searched using the keywords: 'biomarker' and 'osteoarthritis' and/or 'biomarker' and 'proteomics'. RESULTS: Ninety-eight papers were found with the keywords 'biomarker' and 'osteoarthritis'. Fifteen papers were found with the keywords 'biomarker' and 'proteomics'. Review articles were also included. The most relevant published studies focused on extracellular matrix (ECM) molecules in body fluids. Enrichment of the deamidated epitope of cartilage oligomeric matrix protein (D-COMP) suggests that OA disease progression is associated with post-translational modifications that may show specificity for particular joint sites. Fibulin-3 peptides (Fib3-1 and Fib3-2) have been proposed as potential biomarkers of OA along with follistatin-like protein 1 (FSTL1), a new serum biomarker with the capacity to reflect the severity of joint damage. The 'membrane attack complex' (MAC) component of complement has also been implicated in OA. CONCLUSION: Novel OA biomarkers are needed for sub-clinical disease diagnosis. Proteomic techniques are beginning to yield useful data and deliver new OA biomarkers in serum and urine. Combining biochemical markers with tissue and cell imaging techniques and bioinformatics (i.e., machine learning, clustering, data visualization) may facilitate the development of biomarker combinations enabling earlier detection of OA.