Quantitative Proteomic Profiling of Human Articular Cartilage Degradation in Osteoarthritis

Osteoarthritis (OA) is the most common rheumatic pathology and is characterized primarily by articular cartilage degradation. Despite its high prevalence, there is no effective therapy to slow disease progression or regenerate the damaged tissue. Therefore, new diagnostic and monitoring tests for OA are urgently needed, which would also promote the development of alternative therapeutic strategies. In the present study, we have performed an iTRAQ-based quantitative proteomic analysis of secretomes from healthy human articular cartilage explants, comparing their protein profile to those from unwounded (early disease) and wounded (advanced disease) zones of osteoarthritic tissue. This strategy allowed us to identify a panel of 76 proteins that are distinctively released by the diseased tissue. Clustering analysis allowed the classification of proteins according to their different profile of release from cartilage. Among these proteins, the altered release of osteoprotegerin (decreased in OA) and periostin (increased in OA), both involved in bone remodelling processes, was verified in further analyses. Moreover, periostin was also increased in the synovial fluid of OA patients. Altogether, the present work provides a novel insight into the mechanisms of human cartilage degradation and a number of new cartilage-characteristic proteins with possible biomarker value for early diagnosis and prognosis of OA

Analysis of Autoantibody Profiles in Osteoarthritis Using Comprehensive Protein Array Concepts

Osteoarthritis (OA) is the most common rheumatic disease and one of the most disabling pathologies worldwide. To date, the diagnostic methods of OA are very limited, and there are no available medications capable of halting its characteristic cartilage degeneration. Therefore, there is a significant interest in new biomarkers useful for the early diagnosis, prognosis, and therapeutic monitoring. In the recent years, protein microarrays have emerged as a powerful proteomic tool to search for new biomarkers. In this study, we have used two concepts for generating protein arrays, antigen microarrays, and NAPPA (nucleic acid programmable protein arrays), to characterize differential autoantibody profiles in a set of 62 samples from OA, rheumatoid arthritis (RA), and healthy controls. An untargeted screen was performed on 3840 protein fragments spotted on planar antigen arrays, and 373 antigens were selected for validation on bead-based arrays. In the NAPPA approach, a targeted screening was performed on 80 preselected proteins. The autoantibody targeting CHST14 was validated by ELISA in the same set of patients. Altogether, nine and seven disease related autoantibody target candidates were identified, and this work demonstrates a combination of these two array concepts for biomarker discovery and their usefulness for characterizing disease-specific autoantibody profiles