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Using HapMap tools in pharmacogenomic discovery: the thiopurine methyltransferase polymorphism.

Jones TS, Yang W, Evans WE, Relling MV

Department of Pharmaceutical Sciences, St Jude Children's Research Hospital, and College of Pharmacy, University of Tennessee, Memphis, TN, USA.

One purpose of the International HapMap Project is to provide a genome-wide resource to discover pharmacogenetic determinants of drug response. The thiopurine methyltransferase (TPMT) 719A>G single-nucleotide polymorphism (SNP) causes decreased TPMT activity, increased intracellular thiopurines, and drug toxicities. Using HapMap cell lines and 3.3 million SNPs, we tested whether the TPMT 719A>G SNP could be identified as predicting TPMT phenotype. Assuming TPMT was a candidate gene, five SNPs and four haplotypes predicted TPMT phenotype, two of which were in complete linkage disequilibrium with the functional 719A>G SNP. We also used a genome-wide approach to rank all 17,542 genes as predictors of TPMT activity. A TPMT haplotype, HAP1, significantly predicted TPMT phenotype; however, haplotypes of 96 genes ranked higher than TPMT. Our findings show that HapMap resources are useful for pharmacogenetic discovery when the candidate gene is known, but challenges remain for definitive gene identification when a genome-wide agnostic approach is employed.

Published 17 April 2007 in Clin Pharmacol Ther, 81(5): 729-34.
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Pharmacogenomics Research Today Archive:

Volume 1 (2005)
  Issue 1 (October)
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  Issue 3 (December)

Volume 2 (2006)
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Volume 3 (2007)
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Volume 4 (2008)
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Pharmacogenomics Books

Statistical and Computational Pharmacogenomics (Interdisciplinary Statistics)

Statistical and Computational Pharmacogenomics (Interdisciplinary Statistics)