Objective: This study was designed to test the utility of a blood-based approach to identify mild osteoarthritis (OA) of the knee.
Methods: Blood samples were drawn from 161 subjects, including 85 subjects with arthroscopically diagnosed mild OA of the knee and 76 controls. Following RNA isolation, an in-house custom cDNA microarray was used to screen for differentially expressed genes. A subset of selected genes was then tested using real-time RT-PCR. Logistic regression analysis was used to evaluate linear combinations of the biomarkers and receiver operating characteristic curve analysis was used to assess the discriminatory power of the combinations.
Results: Genes differentially expressed (3543 genes) between mild knee OA and control samples were identified through microarray analysis. Subsequent real-time RT-PCR verification identified six genes significantly down-regulated in mild OA: heat shock 90kDa protein 1, alpha; inhibitor of kappa light polypeptide gene enhancer in B-cells, kinase complex-associated protein; interleukin 13 receptor, alpha 1; laminin, gamma 1; platelet factor 4 (also known as chemokine (C-X-C motif) ligand 4) and tumor necrosis factor, alpha-induced protein 6. Logistic regression analysis identified linear combinations of nine genes--the above six genes, early growth response 1; alpha glucosidase II alpha subunit; and v-maf musculoaponeurotic fibrosarcoma oncogene homolog B (avian)--as discriminatory between subjects with mild OA and controls, with a sensitivity of 86% and specificity of 83% in a training set of 78 samples. The optimal biomarker combinations were then evaluated using a blind test set (67 subjects) which showed 72% sensitivity and 66% specificity.
Conclusions: Linear combinations of blood RNA biomarkers offer a substantial improvement over currently available diagnostic tools for mild OA. Blood-derived RNA biomarkers may be of significant clinical value for the diagnosis of early, asymptomatic OA of the knee.