Variability in synovial inflammation in rheumatoid arthritis investigated by microarray technology.
In recent years microarray technology has been used increasingly to acquire knowledge about the pathogenic processes involved in rheumatoid arthritis. The present study investigated variations in gene expression in synovial tissues within and between patients with rheumatoid arthritis. This was done by applying microarray technology on multiple synovial biopsies obtained from the same knee joints. In this way the relative levels of intra-patient and inter-patient variation could be assessed. The biopsies were obtained from 13 different patients: 7 by orthopedic surgery and 6 by rheumatic arthroscopy. The data show that levels of heterogeneity varied substantially between the biopsies, because the number of genes found to be differentially expressed between pairs of biopsies from the same knee ranged from 6 to 2,133. Both arthroscopic and orthopedic biopsies were examined, allowing us to compare the two sampling methods. We found that the average number of differentially expressed genes between biopsies from the same patient was about three times larger in orthopedic than in arthroscopic biopsies. Using a parallel analysis of the tissues by immunohistochemistry, we also identified orthopedic biopsies that were unsuitable for gene expression analysis of synovial inflammation due to sampling of non-inflamed parts of the tissue. Removing these biopsies reduced the average number of differentially expressed genes between the orthopedic biopsies from 455 to 171, in comparison with 143 for the arthroscopic biopsies. Hierarchical clustering analysis showed that the remaining orthopedic and arthroscopic biopsies had gene expression signatures that were unique for each patient, apparently reflecting patient variation rather than tissue heterogeneity. Subsets of genes found to vary between biopsies were investigated for overrepresentation of biological processes by using gene ontology. This revealed representative 'themes' likely to vary between synovial biopsies affected by inflammatory disease.
Lindberg
Johan
J
Department of Biotechnology, AlbaNova University Center, Royal Institute of Technology, S-106 91 Stockholm, Sweden.
af Klint
Erik
E
Ulfgren
Ann-Kristin
AK
Stark
André
A
Andersson
Tove
T
Nilsson
Peter
P
Klareskog
Lars
L
Lundeberg
Joakim
J
D000368:Aged; D001172:Arthritis, Rheumatoid / Q000150:complications*; D001182:Arthroscopy; D001706:Biopsy / Q000379:methods; D016000:Cluster Analysis; D005260:Female; D015870:Gene Expression; D006801:Humans; D007150:Immunohistochemistry; D008297:Male; D008875:Middle Aged; D020411:Oligonucleotide Array Sequence Analysis; D019637:Orthopedic Procedures; D013583:Synovial Membrane / Q000378:metabolism / Q000473:pathology; D013585:Synovitis / Q000209:etiology / Q000235:genetics / Q000378:metabolism* / Q000473:pathology*