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 molecular markers (MM) used to monitor osteoarthritis.
DESIGN: Forty osteoarthritis patients had blood and urine collected at baseline and 1, 3, 6 and 12 months later. Specimens from 20 controls were obtained twice at a one month interval. The concentration of 14 different markers was determined at each time point and the data were analyzed by statistical methodology.
RESULTS: The markers could be divided by the method of principal components analysis into five clusters of related markers: inflammation markers (C-reactive 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 markers of cartilage anabolism (carboxypropeptide of type II procollagen, hyaluronan, epitope 846) and catabolism (keratan sulfate, cartilage oligomeric matrix protein), and transforming growth factor beta. Three markers (tumor necrosis 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 recognizable distinguishing factor in osteoarthritis.
CONCLUSIONS: The markers separated into rational groups on the basis of their covariance, a finding with independent biochemical support. The covariance of markers from the same cluster suggests the use of a representative marker from the cluster to reflect changes in osteoarthritis. If multiple markers are being measured within a single cluster, then the use of a weighted cluster 'factor' may be preferable to the separate use of individual markers.