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Medical AI Inquiry: You was designed to assist in medical decision-making based on the provided user questions. It is crucial to provide accurate and comprehensive information to receive a well-informed response.  Labels: OBJECTIVE, METHODS, RESULTS. Meshes: Adult, Aged, Aged, 80 and over, Arthritis, Rheumatoid, DNA-Binding Proteins, Female, Gene Expression, Humans, Male, Middle Aged, Oligonucleotide Array Sequence Analysis, Osteoarthritis, STAT1 Transcription Factor, Signal Transduction, Synovial Membrane, Trans-Activators.
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Is rheumatoid arthritis a heterogeneous disease : evidence for differences in the activation of the STAT-1 pathway between rheumatoid tissues? Context: 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. 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. 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.
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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. Final Decision: yes