1. ¹Robert S Boas Center for Genomics and Human Genetics, North Shore-Long Island Jewish Research Institute, Manhasset, NY, USA
2. ²Department of Medicine, NSUH, Manhasset, NY, USA
3. ³Department of Medicine, University of Minnesota, Minneapolis, MN, USA
4. ⁴SurroMed Inc., Menlo Park, CA, USA

Correspondence: Professor PK Gregersen, Robert S Boas Center for Genomics and Human Genetics, North Shore-Long Island Jewish Research Institute, 350 Community Drive, Manhasset, NY 11030, USA. E-mail: peterg@nshs.edu

Received 3 January 2005; Revised 15 February 2005; Accepted 16 February 2005; Published online 23 June 2005.

Abstract

We carried out gene expression profiling of peripheral blood mononuclear cells (PBMCs) in 29 patients with active rheumatoid arthritis (RA) and 21 control subjects using Affymetrix U95Av2 arrays. Using cluster analysis, we observed a significant alteration in the expression pattern of 81 genes (P<0.001) in the PBMCs of RA patients compared with controls. Many of these genes correlated with differences in monocyte counts between the two study populations, and we show that a large fraction of these genes are specifically expressed at high levels in monocytes. In addition, a logistic regression analysis was performed to identify genes that performed best in the categorization of RA and control samples. Glutaminyl cyclase, IL1RA, S100A12 (also known as calgranulin or EN-RAGE) and Grb2-associated binding protein (GAB2) were among the top discriminators. Along with previous data, the overexpression of S100A12 in RA patients emphasizes the likely importance of RAGE pathways in disease pathogenesis. The altered expression of GAB2, an intracellular adaptor molecule involved in regulating phosphatase function, is of particular interest given the recent identification of the intracellular phosphatase PTPN22 as a risk gene for RA. These data suggest that a detailed study of gene expression patterns in peripheral blood can provide insight into disease pathogenesis. However, it is also clear that substantially larger sample sizes will be required in order to evaluate fully gene expression profiling as a means of identifying disease subsets, or defining biomarkers of outcome and response to therapy in RA.