Skip to content

Advertisement

  • Meeting abstract
  • Open Access

Unraveling complexity of rheumatoid synovial gene expression by comparison with purified leukocyte profiles

  • 1,
  • 3,
  • 3,
  • 3,
  • 4,
  • 1,
  • 1,
  • 5,
  • 2,
  • 6,
  • 7,
  • 6,
  • 1 and
  • 3
Arthritis Res Ther20046 (Suppl 1) :73

https://doi.org/10.1186/ar1115

  • Received: 16 January 2004
  • Published:

Keywords

  • Rheumatoid Arthritis
  • Synovitis
  • Synovial Tissue
  • Normal Donor
  • Gene Array

Background

Gene array analyses reflect the molecular complexity in rheumatoid synovitis. Insufficient knowledge about the majority of differentially regulated genes hampers adequate interpretation.

Objective

To unravel this complexity, cell type specific expression profiles were applied as baseline information for comparison.

Methods

Gene expression profiles were determined by Affymetrix HG-U133A array hybridization of synovial tissues, sorted blood monocytes, granulocytes, CD4 and CD8 T cells from up to 10 patients with rheumatoid arthritis (RA) and 10 normal donors (ND). Primary analysis was performed using MAS5.0. Tissues were scored according to histological standards (Krenn, Pathol Res Pract 2002).

Results

Compared with ND synovium, 145 genes were differentially regulated in all, and up to 2681 genes in at least 50% of RA-ND pairwise comparisons. Marker genes of isolated cell populations were defined by absence in more than 70% of other populations and normal synovial tissue, defining 59, 25 or 110 genes for granulocytes, monocytes or T cells, respectively. Of these markers, 1, 6 or 22 were identified in more than 50% of RA-ND comparisons for each cell type, respectively. This reflects the altered cellular composition in synovitis. Excluding all genes present in normal tissue or any of the purified populations revealed immunoglobulins as markers of B-cell infiltration.

Conclusion

This initial analysis of our approach substantially improved the quality of array interpretation and allows identification of tissue associated gene regulation. It helps to identify markers shared between blood and tissue and may provide candidates for disease classification and activity scoring.

Authors’ Affiliations

(1)
Department of Rheumatology, Charité CCM, Berlin, Germany
(2)
Department of Rheumatology, Charité CCBF, Berlin, Germany
(3)
DRFZ, Berlin, Germany
(4)
MPI-MG, Berlin, Germany
(5)
Oligene GmbH, Berlin, Germany
(6)
Institute of Pathology, Charité, Berlin, Germany
(7)
Department of Orthopedics, Helios-Klinik, Berlin-Buch, Germany

Copyright

Advertisement