Pharmacogenomics strategies to optimize treatments for multiple sclerosis: Insights from clinical research

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Abstract

Multiple sclerosis (MS) is a chronic, progressive, disabling disorder characterized by immune-mediated demyelination, inflammation, and neurodegenerative tissue damage in the central nervous system (CNS), associated with frequent exacerbations and remissions of neurologic symptoms and eventual permanent neurologic disability. While there are several MS therapies that are successful in reducing MS relapses, none have been effective in treating all patients. The specific response of an individual patient to any one of the MS therapies remains largely unpredictable, and physicians and patients are forced to use a trial and error approach when deciding on treatment regimens. A priori markers to predict the optimal benefit-to-risk profile of an individual MS patient would greatly facilitate the decision-making process, thereby helping the patient receive the most optimal treatment early on in the disease process. Pharmacogenomic methods evaluate how a person's genetic and genomic makeup affects their response to therapeutics. This review focuses on how pharmacogenomics studies are being used to identify biologically relevant differences in MS treatments and provide characterization of the predictive clinical response patterns. As pharmacogenomics research is dependent on the availability of longitudinal clinical research, studies concerning glatiramer acetate and the interferon beta products which have the majority of published long term data to date are described in detail. These studies have provided considerable insight in the prognostic markers associated with MS disease and potential predictive markers of safety and beneficial response.

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