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Rheumatoid arthritis is a heterogeneous disease: Evidence for differences in the activation of the STAT‐1 pathway between rheumatoid tissues

类风湿性关节炎 STAT蛋白 基因表达 发病机制 基因 斯达 基因表达谱 微阵列分析技术 微阵列 免疫系统 生物 免疫学 医学 车站3 遗传学
作者
Tineke C. T. M. van der Pouw Kraan,F. van Gaalen,Pia V. Kasperkovitz,Nicolette L. Verbeet,Tom Smeets,Maarten C. Kraan,Mike Fero,Paul‐Peter Tak,T. Huizinga,Elsbet J. Pieterman,Ferdinand C. Breedveld,Ash A. Alizadeh,Cornelis L. Verweij
出处
期刊:Arthritis & Rheumatism [Wiley]
卷期号:48 (8): 2132-2145 被引量:259
标识
DOI:10.1002/art.11096
摘要

Abstract Objective To generate a molecular description of synovial tissue from rheumatoid arthritis (RA) patients that would allow us to unravel novel aspects of pathogenesis and to identify different forms of disease. Methods We applied complementary DNA microarray analysis to profile gene expression, with a focus on immune‐related genes, in affected joint tissues from RA patients and in tissues from osteoarthritis (OA) patients as a control. To validate microarray data, real‐time polymerase chain reaction was performed on genes of interest. Results The gene expression signatures of synovial tissues from RA patients showed considerable variability, resulting in the identification of at least two molecularly distinct forms of RA tissues. One class of tissues revealed abundant expression of clusters of genes indicative of an involvement of the adaptive immune response. Detailed analysis of the expression profile provided evidence for a prominent role of an activated signal transducer and activator of transcription 1 pathway in these tissues. The expression profiles of another group of RA tissues revealed an increased tissue remodeling activity and a low inflammatory gene expression signature. The gene expression pattern in the latter tissues was reminiscent of that observed in the majority of OA tissues. Conclusion The differences in the gene expression profiles provide a unique perspective for distinguishing different pathogenetic RA subsets based on molecular criteria. These data reflect important aspects of molecular variation that are relevant for understanding the biologic dysregulation underlying these subsets of RA. This approach may also help to define homogeneous groups for clinical studies and evaluation of targeted therapies.
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