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Gene expression profiling in rheumatoid arthritis; current concepts and future directions
  1. Erik JM Toonen (e.toonen{at}antrg.umcn.nl)
  1. Radboud University Nijmegen Medical Centre, Netherlands
    1. Pilar Barrera (p.barrera{at}reuma.umcn.nl)
    1. Radboud University Nijmegen Medical Centre, Netherlands
      1. Timothy RDJ Radstake (t.radstake{at}reuma.umcn.nl)
      1. Radboud University Nijmegen Medical Centre, Netherlands
        1. Piet LCM van Riel (p.vanriel{at}reuma.umcn.nl)
        1. Radboud University Nijmegen Medical Centre, Netherlands
          1. Hans Scheffer (h.scheffer{at}antrg.umcn.nl)
          1. Radboud University Nijmegen Medical Centre, Netherlands
            1. Barbara Franke (b.franke{at}antrg.umcn.nl)
            1. Radboud University Nijmegen Medical Centre, Netherlands
              1. Marieke JH Coenen (m.coenen{at}antrg.umcn.nl)
              1. Radboud University Nijmegen Medical Centre, Netherlands

                Abstract

                Over the last years microarray technologies have generated new perspectives for high-throughput analysis of biological systems. Nowadays, it is possible to monitor thousands of genes in a single experiment. This molecular profiling technology combined with standardized and validated clinical measurements can allow a more precise characterization of a patient’s phenotype, and may lead to the design of therapeutic protocols and procedures better tailored to individual patient’s needs. In this report we provide an overview of expression profiling studies in rheumatoid arthritis (RA). RA is a chronic inflammatory disease in which both genetic and environmental factors are involved. The precise molecular mechanisms underlying RA are not fully understood. A systematic literature search revealed nine array-based expression profiling studies in RA patients. Findings from these studies were compared to those of linkage and genome-wide association (GWA) studies. Although we observed many differences in study design, analysis and interpretation of results between the different studies, we extracted two sets of genes: 1) those differentially expressed in more than one study and 2) genes differentially expressed in at least one of the reviewed studies and present in RA linkage or GWA loci. We suggest that both sets of genes include interesting candidate genes for further study in RA.

                • autoimmune diseases
                • expression profiling
                • rheumatoid arthritis

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