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Using HapMap Tools in Pharmacogenomic Discovery: The Thiopurine Methyltransferase Polymorphism
Author(s) -
Jones T S,
Yang W,
Evans W E,
Relling M V
Publication year - 2007
Publication title -
clinical pharmacology and therapeutics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.941
H-Index - 188
eISSN - 1532-6535
pISSN - 0009-9236
DOI - 10.1038/sj.clpt.6100135
Subject(s) - international hapmap project , thiopurine methyltransferase , pharmacogenomics , single nucleotide polymorphism , haplotype , pharmacogenetics , linkage disequilibrium , snp , biology , genetics , 1000 genomes project , candidate gene , genotyping , snp genotyping , imputation (statistics) , computational biology , gene , allele , genotype , medicine , computer science , azathioprine , disease , machine learning , missing data
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. Clinical Pharmacology & Therapeutics (2007) 81 , 729–734. doi: 10.1038/sj.clpt.6100135 ; published online 28 February 2007