Autor: |
E Pieterman, D Botstein, Ash A. Alizadeh, T.W.J. Huizinga, Patrick O. Brown, Pia V Kasperkovitz, CL Verweij, Mike Fero, Nicolette L. Verbeet, Louis M. Staudt, Ferdinand C. Breedveld, F. van Gaalen, Tctm van der Pouw Kraan |
Rok vydání: |
2002 |
Předmět: |
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Zdroj: |
Arthritis Research. 4:28 |
ISSN: |
1465-9905 |
DOI: |
10.1186/ar468 |
Popis: |
A potentially powerful way to gain insight in the complex pathogenesis of rheumatoid arthritis (RA) and to classify arthritides has arisen from cDNA microarray technology, which provides the opportunity to determine differences in gene expression of a large portion of the genome in search of genes that are differently expressed between clinically diagnosed arthritides. Therefore, we studied the gene expression profile of synovial tissues from affected joints of patients with diagnosed RA (n = 21) in comparison to those of patients with osteoarthritis (OA) (n = 9), a degenerative joint disease. Cy-5 labeled mRNAs from these samples were hybridized together with a Cy-3 labeled common reference mRNA preparation to arrays containing 18,000 genes of importance in immunology. The results revealed 1066 genes with a twofold difference in expression in at least 4 samples, relative to the median Cy-5 to Cy-3 ratio. Hierarchical cluster analysis revealed a remarkably ordered variation in gene expression profiles in the affected joint tissues of patients with RA and OA. These data revealed biological pathways and novel genes involved in disease. Based on the molecular signatures at least two distinct subsets of RA tissues could be identified. One class revealed abundant expression of gene clusters indicative of the presence and activation of the adaptive immune response, and the other group resembled the expression pattern of the OA tissues, which is characterized by a low inflammatory gene expression signature and increased tissue remodeling. The differences in the gene expression profiles reflect important aspects of biological variation within the clinically diagnosed arthritides that may help to understand the molecular pathology of and (sub-)classify rheumatic diseases. |
Databáze: |
OpenAIRE |
Externí odkaz: |
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