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Abstract
Osteoarthritis (OA) is one of the most common age-related chronic disorders of articular cartilage, joints and bone tissue. Diagnosis of OA commonly depends on clinical and radiographic findings. However, changes in cartilage associated with the early stage of OA cannot be detected using radiographs, because significant cartilage degeneration must occur before radiographic findings show alterations of the appearance of cartilage. To identify new biomarkers of OA, we analysed gene expression profiles of synovium from 43 patients with OA, ten patients with rheumatoid arthritis (RA), and eight non-OA/non-RA patients using a novel cDNA microarray chip. We identified 21 genes with simultaneous significant differences in expression between OA and non-OA/non-RA groups and between OA and RA groups. Linear discriminant analysis showed that the three groups could be well separated using those 21 genes. Statistical analysis also revealed that several of the 21 genes were associated with disease progression and clinical presentation. The graphical modelling method indicated that some of the 21 genes are significantly associated with a particular clinical presentation, suggesting biological relationships among those genes. This is the first report of the use of cDNA microarray technology to create large-scale gene expression profiles differentially expressed in situ in OA synovium of the knee joint.