An analysis of 14 molecular markers for monitoring osteoarthritis: segregation of the markers into clusters and distinguishing osteoarthritis at baseline

Objective: To investigate the relationships between serum and urinary molec ular markers (MM) used to monitor osteoarthritis. Design: Forty osteoarthritis patients had blood and urine collected at base line and 1, 3, 6 and 12 months later. Specimens from 20 controls were obtai ned twice at a one month interval. The concentration of 14 different marker s was determined at each time point and the data were analyzed by statistic al methodology. Results: The markers could be divided by the method of principal components analysis into five clusters of related markers: inflammation markers (C-re active protein. tumor necrosis receptor type I and tumor necrosis receptor type II, interleukin 6, eosinophilic cationic protein), bone markers (bone sialoprotein, hydroxylysyl pyridinoline, lysyl pyridinoline), putative mark ers of cartilage anabolism (carboxypropeptide of type Il procollagen, hyalu ronan, epitope 846) and catabolism (keratan sulfate, cartilage oligomeric m atrix protein), and transforming growth factor beta. Three markers (tumor n ecrosis factor receptor ii, cartilage oligomeric matrix protein and epitope 846) from independent clusters discriminated osteoarthritis patients from controls. inflammation was not a confounding factor in measurement, but a r ecognizable distinguishing factor in osteoarthritis. Conclusions: The markers separated into rational groups on the basis of the ir covariance, a finding with independent biochemical support. The covarian ce of markers from the same cluster suggests the use of a representative ma rker from the cluster to reflect changes in osteoarthritis. If multiple mar kers are being measured within a single cluster, then the use of a weighted cluster 'factor' may be preferable to the separate use of individual marke rs. (C) 2000 OsteoArthritis Research Society International.