Elsevier

Osteoarthritis and Cartilage

Volume 20, Issue 12, December 2012, Pages 1451-1464
Osteoarthritis and Cartilage

Review
Osteoarthritis year 2012 in review: biomarkers

https://doi.org/10.1016/j.joca.2012.07.009Get rights and content
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Summary

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.

Keywords

Osteoarthritis
Articular cartilage
Synovium
Inflammation
Biomarker
Biochemical marker
Proteomics
Complement
Chemotactic proteins
Adipokines

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