This study was designed to test the utility of a blood-based approach to identify mild osteoarthritis (OA) of the knee.
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.
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.
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.