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An update on pharmacogenomics in rheumatoid arthritis with a focus on TNF-blocking agents
1Washington University School of Medicine, Department of Medicine, Division of Rheumatology, St Louis, MO 63110, USA. prangana@im.wustl.edu
Abstract:
TNFalpha is a proinflammatory cytokine, which is crucial in the pathogenesis of rheumatoid arthritis (RA). In recent years, biological therapies which block the damaging effects of TNFalpha on synovium and cartilage have been developed. TNF antagonists, such as etanercept, infliximab and adalimumab, although highly effective in RA, are expensive, totaling several thousand US dollars in yearly costs. In addition, only approximately 60% of patients respond to these agents. This has led to the need to prospectively identify patients most likely to respond to these agents, which can be achieved by pharmacogenomics approaches. Polymorphisms in genes encoding for TNFalpha, the MHC region, and the Fcgamma receptor IIIA, as well as their ability to predict disease progression in RA and response to anti-TNF therapies, have been the focus of a number of studies, which are discussed in this review. There is no consensus at present as to whether pharmacogenomics will allow prediction of anti-TNF therapy efficacy in RA. Large, prospective, multicenter studies are needed to replicate and validate the results of the studies outlined in this review.
Insights
Identifying genetic markers for rheumatoid arthritis (RA) treatment response is crucial. Pharmacogenomics may predict efficacy of anti-tumor necrosis factor (TNF) therapies, but more research is needed.
Area of Science:
- Immunology
- Rheumatology
- Genetics
Background:
- Tumor necrosis factor-alpha (TNFalpha) is key in rheumatoid arthritis (RA) pathogenesis.
- Anti-TNF biologic therapies are effective but costly, with variable patient response rates.
- Predicting response to anti-TNF agents is essential for personalized RA treatment.
Purpose of the Study:
- To review the role of pharmacogenomics in predicting response to anti-TNF therapies in RA.
- To evaluate the predictive potential of genetic polymorphisms in RA patients undergoing anti-TNF treatment.
Main Methods:
- Review of studies investigating genetic polymorphisms related to TNFalpha, MHC region, and Fcgamma receptor IIIA.
- Analysis of the association between these polymorphisms and RA disease progression and anti-TNF therapy response.
Main Results:
- Several genetic polymorphisms have been studied for their potential to predict RA disease progression and response to anti-TNF therapies.
- Current evidence does not establish a consensus on the utility of pharmacogenomics for predicting anti-TNF therapy efficacy in RA.
Conclusions:
- Pharmacogenomic approaches show promise for personalizing anti-TNF therapy in RA.
- Large, prospective, multicenter studies are required to validate existing findings and establish clinical utility.
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