Clinical proteomics

Abstract

Purpose: The diagnosis methods currently available for Osteoarthritis (OA) are limited and lack sensitivity. Therefore, there is a considerable interest pointed in identifying new specific biological markers for cartilage degradation, both to facilitate early diagnosis of joint destruction and to improve the prognosis and evaluation of disease progression. In the recent years, shotgun proteomics strategies have demonstrated an impressive capacity for the discovery and validation of OA biomarkers, allowing the identification of proteins with putative usefulness for the early diagnosis of the disease, prognosis studies and monitorization of alternative therapies. Methods: We have employed proteomic tools for OA research, that enable the large-scale relative quantification of hundreds of proteins between samples obtained from different conditions. The approaches that have been followed are essentially based in the differential labeling of peptides with isobaric tags (iTRAQ) and the subsequent multidimensional liquid-chromatography separation of the mixture coupled to tandem mass spectrometry (LC-MS/MS) analysis. By these means, both tissue samples (articular cartilage) and biofluids (serum) from OA patients and healthy donors have been analyzed. Results: The proteomic analysis of the serum samples led to the identification of around 345 different proteins. A relative quantification of these proteins was obtained between OA patients at different stages of the disease (K/L grade II or grade IV) and controls. This study led to the identification of 29 proteins that whose abundance was different in the serum of OA patients (17 increased and 12 decreased) when compared to healthy donors (p < 0.05). From these, 12 were altered independently of the degree of the disease, 6 were modified only in early stages (grade II), and 11 exclusively in advanced OA (grade IV). The reported altered proteins, which are novel putative OA biomarker candidates, are involved in a wide range of biological functions, such as immune response, inflammation processes, lipid metabolism, oxidative stress defence, transport or cell adhesion. In full thickness cartilage, the proteomic study allowed the identification of 339 distinct proteins. As expected, those proteins identified with a higher number of peptides are cartilage extracellular matrix molecules, such as type II collagen, prolargin, aggrecan, biglycan or COMP. A quantitative comparison was carried out to identify those proteins with a differential localization according to the tissue layers in healthy cartilage (superficial, intermediate or deep). An increased abundance of type VI collagen, small proteoglycans (mimecan, lumican or PRG4) and proteins involved in cell adhesion processes (gelsolin, vitronectin, tenascins) was detected in the superficial layer. On the other hand, the intermediate layer was characterized by a high presence of type II, V, IX and XXVIII collagens, cartilage intermediate layer proteins (CILPs), COMP, vitrin and decorin. Finally, the deep layer exhibited an increased abundance of type I and XI collagens, aggrecan and bone-related proteins (bone sialoprotein 2, osteomodulin, and bone morphogenetic protein 3). Comparison of this normal cartilage proteome with the osteoarthritic one led to the identification of 23 proteins increased in the pathologic tissue, including aggrecan, COMP, complement factors or thrombospondin 1. We could also identify 36 proteins that were decreased in OA cartilage, such as type I, II and VI collagens, proteoglycans (biglycan, PRG4), tenascins or actin. Conclusions: In summary, proteomics strategies have demonstrated its usefulness both for increasing the knowledge of cartilage biology and OA pathophysiology, and also for unravelling novel proteins with putative biomarker value of cartilage degradation in OA. The information obtained in these studies would be of high relevance in the search of tissue-specific OA biomarkers. Targeted verification of these results on a higher number of samples will be necessary for the design of final panels, which will be particularly useful for OA early diagnosis and therapy studies.