Dataset Information

E-GEOD-55235

ABSTRACT: Identification of rheumatoid arthritis and osteoarthritis patients by transcriptome-based rule set generation

DISEASE(S): Rheumatoid Arthritis,Normal,Osteoarthritis

PROVIDER: E-GEOD-55235 | ExpressionAtlas | 2019-03-20

REPOSITORIES: ExpressionAtlas

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			Action	DRS
	E-GEOD-55235-analysis-methods.tsv	Tabular
	E-GEOD-55235-atlasExperimentSummary.Rdata	Rdata
	E-GEOD-55235-configuration.xml	Xml
	E-GEOD-55235-percentile-ranks.tsv	Tabular
	E-GEOD-55235.condensed-sdrf.tsv	Tabular

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Project description:Rheumatoid arthritis (RA) is an inflammatory joint disorder that results in progressive joint damage when insufficiently treated. In order to prevent joint destruction and functional disability in RA, early diagnosis and initiation of appropriate treatment with Disease-Modifying Antirheumatic Drugs (DMARDs) is needed. However, in daily clinical practice, patients may initially display symptoms of arthritis that do not fulfil the classification criteria for a definite diagnosis of RA, or any other joint disease, a situation called “Undifferentiated Arthritis” (UA). Out of the patients with UA, 30 to 50% usually develop RA, and early identification of these remains a challenge. At the present time, although several risk factors associated with the development of RA have been identified (6-9), a model that reliably predicts the probability of evolution of UA into RA in individual patients is lacking. In order to better identify early RA patients, an American College of Rheumatology (ACR)/European League Against Rheumatism (EULAR) collaboration recently developed new classification criteria. Although these criteria are more sensitive, the risk of over-diagnosis is an important issue to consider, especially in very early disease. In this context, the present study explores the feasibility of a molecular diagnosis of arthritis, based on the identification of disease-specific transcriptomic profiles in synovial biopsies from patients with arthritis according to the underlying condition. In a previous study, we performed global analyses of gene expression in synovial biopsies from patients with RA, Systemic Lupus Erythematosus (SLE) and Osteoarthritis (OA), using high-density oligonucleotide spotted microarrays. We found that the gene expression profiles are strikingly different according to the underlying condition. Thus, the majority of the genes up-regulated in SLE are type I Interferon-inducible genes, as compared with the up-regulation genes involved in T cell and B cell activation in RA, and in extracellular matrix homeostasis in OA. Based on these results, similar analyses were performed in synovial biopsies from patients with seronegative arthritis (SA) and microcrystalline arthritis (MIC), in order to identify disease-specific molecular signatures.

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E-GEOD-55235

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