Biomarkers and proteomic analysis of osteoarthritis

Our friend and colleague, Dr. Dick Heinegard, contributed greatly to the understanding of joint tissue biochemistry, the discovery and validation of arthritis-related biomarkers and the establishment of methodology for proteomic studies in osteoarthritis (OA). To date, discovery of OA-related biomarkers has focused on cartilage, synovial fluid and serum. Methods, such as affinity depletion and hyaluronidase treatment have facilitated proteomics discovery research from these sources. Osteoarthritis usually involves multiple joints; this characteristic makes it easier to detect OA with a systemic biomarker but makes it hard to delineate abnormalities of individual affected joints. Although the abundance of cartilage proteins in urine may generally be lower than other tissue/sample sources, the protein composition of urine is much less complex and its collection is non-invasive thereby facilitating the development of patient friendly biomarkers. To date however, relatively few proteomics studies have been conducted in OA urine. Proteomics strategies have identified many proteins that may relate to pathological mechanisms of OA. Further targeted approaches to validate the role of these proteins in OA are needed. Herein we summarize recent proteomic studies related to joint tissues and the cohorts used; a clear understanding of the cohorts is important for this work as we expect that the decisive discoveries of OA-related biomarkers rely on comprehensive phenotyping of healthy non-OA and OA subjects. Besides the common phenotyping criteria that include, gender, age, and body mass index (BMI), it is essential to collect data on symptoms and signs of OA outside the index joints and to bolster this with objective imaging data whenever possible to gain the most precise appreciation of the total burden of disease. Proteomic studies on systemic biospecimens, such as serum and urine, rely on comprehensive phenotyping data to unravel the true meaning of the proteomic results. (C) 2014 Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/3.0/).