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| Status |
Public on Mar 27, 2012 |
| Title |
Gene expression profiles in synovial biopsies from patients with arthritis |
| Organism |
Homo sapiens |
| Experiment type |
Expression profiling by array
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| Summary |
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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| Overall design |
GeneChip® Human Genome U133 Plus 2.0 Arrays (Affymetrix UK Ltd., High Wycombe, UK) were hybridized in monoplicates with 10 μg biotinylated cRNA, using synovial biopsy samples obtained in 4 patients with SA (based on the presence of psoriasis or x-ray evidence of sacro-iliacal joint involvement), 5 patients with MIC, based on the identification of urate or calcium pyrophosphate crystals in the synovial fluid, 7 patients with RA (ACR 1987 criteria), 4 patients with SLE (ACR criteria) and 5 patients with OA (based on x-ray evidence of osteoarthritis)
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| Contributor(s) |
Lauwerys BR |
| Citation(s) |
17469140, 25927832 |
| Submission date |
Mar 22, 2012 |
| Last update date |
Aug 09, 2019 |
| Contact name |
Bernard Robert Lauwerys |
| E-mail(s) |
Bernard.Lauwerys@uclouvain.be
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| Phone |
+3227645391
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| Organization name |
Université catholique de Louvain
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| Department |
Institut de Recherches Expérimentales et Cliniques
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| Lab |
Pôle de pathologies rhumatismales et systémiques
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| Street address |
Avenue Hippocrate 10
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| City |
Brussels |
| ZIP/Postal code |
1200 |
| Country |
Belgium |
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| Platforms (1) |
| GPL570 |
[HG-U133_Plus_2] Affymetrix Human Genome U133 Plus 2.0 Array |
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| Samples (25)
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| Relations |
| BioProject |
PRJNA156753 |
| Supplementary file |
Size |
Download |
File type/resource |
| GSE36700_RAW.tar |
117.2 Mb |
(http)(custom) |
TAR (of CEL, CHP) |
| Processed data included within Sample table |
| Processed data provided as supplementary file |
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