%0 Journal Article
%T Prediction of Disease Severity in Patients with Early Rheumatoid Arthritis by Gene Expression Profiling
%A Zheng Liu
%A Tuulikki Sokka
%A Kevin Maas
%A Nancy J. Olsen
%J Human Genomics and Proteomics
%D 2009
%I 
%R 10.4061/2009/484351
%X In order to test the ability of peripheral blood gene expression profiles to predict future disease severity in patients with early rheumatoid arthritis (RA), a group of 17 patients (1”Ą0.2 years disease duration) was evaluated at baseline for gene expression profiles. Disease status was evaluated after a mean of 5 years using an index combining pain, global and recoded MHAQ scores. Unsupervised and supervised algorithms identified ”°predictor genes”± whose combined expression levels correlated with follow-up disease severity scores. Unsupervised clustering algorithms separated patients into two branches. The only significant difference between these two groups was the disease severity score; demographic variables and medication usage were not different. Supervised T-Test analysis identified 19 ”°predictor genes”± of future disease severity. Results were validated in an independent cohort of subjects of established RA with using Support Vector Machines and K-Nearest-Neighbor Classification. Our study demonstrates that peripheral blood gene expression profiles may be a useful tool to predict future disease severity in patients with early and established RA.
%U http://dx.doi.org/10.4061/2009/484351