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Pharmacogenomics. 2008 May;9(5):639-45. doi: 10.2217/14622416.9.5.639.

Pharmacogenomics of the response to IFN-beta in multiple sclerosis: ramifications from the first genome-wide screen.

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  • 1University of the Basque Country (UPV-EHU), Neurogenomiks Laboratory, Neuroscience Department, 48940 Leioa, Vizcaya, Spain. k.vandenbroeck@ikerbasque.org

Abstract

Evaluation of: Byun E, Caillier SJ, Montalban X et al.: Genome-wide pharmacogenomic analysis of the response to interferon-beta therapy in multiple sclerosis. Arch. Neurol. 65(3) 337-344 (2008). Specifically, IFN-beta is the most widely used disease-modifying therapy for the treatment of multiple sclerosis. The main benefits of the therapy, fewer and less severe relapses as well as delayed disease progression, are seen in only approximately 50% of the patients. Genetic polymorphisms may constitute in-built determinants of individual differences in response to IFN-beta. Prior attempts to identify such 'predictors of response' were hypothesis-driven in that they were based on preselection of candidate genes associated with Type I interferon pathways. In the present study, the authors performed the first ever nonbiased genome-wide association screen in an attempt to identify response-predictive SNPs. Using a robust four-stage completion strategy coupled to advanced SNP ranking/clustering algorithms, 18 significant SNPs were identified, many of which are located in genes that have never before been linked clearly to Type I interferon biology or therapeutic effects. While this study was not designed per se so as to validate earlier findings, genes arising from previous pharmacogenomic studies were generally not confirmed. This is due to major discrepancies between interstudy sets of used SNPs, but may also reflect differential strategies for ascertainment of response to IFN-beta, or simply Type I/II errors. The 100-K SNP screen by Byun et al. hallmarks a new stage of pharmacogenomics research applied to multiple sclerosis treatments. Through the judicious implementation of DNA pooling on SNP microarrays, it vividly demonstrates that informative genome-wide pharmacogenomic screens can be performed at a fraction of the cost of individual microarray genotyping. Although, unquestionably, higher-density SNP screens and further replication studies are needed, this study is instrumental in bringing the concept of personalized medicine a (small) step closer to the multiple sclerosis patient. In addition, it has generated a flurry of novel information of likely importance in furthering our understanding of Type I interferon biology.

PMID:
18466107
[PubMed - indexed for MEDLINE]
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