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The genomics and genetics of ankylosing spondylitis
- Publication Year :
- 2011
-
Abstract
- Tony J Kenna, Stuart I Davidson, Gethin P ThomasUniversity of Queensland Diamantina Institute, Brisbane, AustraliaAbstract: The spondyloarthropathies are a group of arthritides which specifically target the spine and pelvis with ankylosing spondylitis (AS) being the most prevalent and debilitating of these conditions. Unique to AS is the progression to excessive uncontrolled bone formation following an initial inflammatory phase that can result in joint fusion and significant disability. Spondyloarthritis is estimated to affect 1%–2% of the population, twice as many as rheumatoid arthritis and thus constitutes a significant health problem. Currently AS pathogenesis is very poorly understood but recent large-scale genetics and gene expression profiling studies have identified some of the underlying mechanisms and pathways contributing to the disease. Genome-wide association studies have identified a number of candidate genes associated with AS sharing the same pathways which are now being targeted for therapeutic intervention. However, although such approaches can identify genes contributing to the disease process and are very informative as to disease aetiopathogenesis, they cannot profile the actual changes in gene/cell activity at any point in the disease process or possibly more importantly at specific sites. Such information is generated using expression profiling. A number of expression profiling studies have been undertaken in AS, looking at both circulating cells and tissues from affected joints. Although some common genes/pathways have been identified, overall the results to date have been somewhat disappointing due to differences in experimental design and tissue source as well as the low power of the studies. More recent better powered studies have shown some potential in developing gene expression profiling as a diagnostic tool in AS. True future success will rely on larger genetic and genomic studies and the combination of these datasets in eQT
Details
- Database :
- OAIster
- Notes :
- text/html, English
- Publication Type :
- Electronic Resource
- Accession number :
- edsoai.on1365539194
- Document Type :
- Electronic Resource