Transcriptome analysis reveals specific changes in osteoarthritis synovial fibroblasts

Transcriptome analysis reveals specific changes in osteoarthritis synovial fibroblasts
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DOI:
10.1136/annrheumdis-2011-200281
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发表时间:
2012-02-01
影响因子:
27.4
通讯作者:
Pablos, Jose L.
Pablos, Jose L.
中科院分区:
医学1区
文献类型:
--
作者:
Del Rey, Manuel J.;Usategui, Alicia;Pablos, Jose L.

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Objective Changes in rheumatoid arthritis synovial fibroblast (RASF) gene expression are usually defined by a comparison to osteoarthritis synovial fibroblasts (OASFs). This study was undertaken to analyse the transcriptome of OASFs as compared to RASFs and healthy synovial fibroblasts (HSFs).Methods The authors used microarray messenger RNA expression profiling of synovial fibroblasts cultured from osteoarthritis (OA), rheumatoid arthritis and normal synovial tissues. Quantitative real-time PCR of selected genes was performed to validate microarray data. Analysis of variance, Student t test and the Benjamini-Hochberg multiple testing correction method for multiple testing correction were used to determine the statistical significance of the changes between the three groups.Results Larger numbers of transcripts showed a differential expression in OASFs versus the other groups, rather than in RASFs versus HSFs. Cluster analysis confirmed that the differences between the three groups were mostly due to the differences between OA and the other groups. Functional classification identified a significant number of genes related to growth factor activities, cell adhesion, neurotransmission and Ras signalling that are differentially expressed in OASFs. Classical proinflammatory factors or proteases involved in cartilage degradation were not found to be overexpressed in OASFs.Conclusion Cultured OASFs display a more homogeneous transcriptomic profile than RASFs when compared to HSFs. This supports the participation of synovial fibroblasts in the pathogenesis of OA and may reflect global defects in the mesenchyma-derived lineages of the different tissues in OA joints. These data support individual heterogeneity among RASFs and advise against the use of OASFs as controls.