Research Article

Pharmacogenomics: accessing important alleles by imputation from commercial genome-wide SNP arrays

Published: July 25, 2014
Genet. Mol. Res. 13 (3) : 5713-5721 DOI: https://doi.org/10.4238/2014.July.25.27
Cite this Article:
R. Liboredo, S.D.J. Pena (2014). Pharmacogenomics: accessing important alleles by imputation from commercial genome-wide SNP arrays. Genet. Mol. Res. 13(3): 5713-5721. https://doi.org/10.4238/2014.July.25.27
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Abstract

Personalized medicine is becoming a medical reality, as important genotype-phenotype relationships are being unraveled. The availability of pharmacogenomic data is a key element of individualized care. In this study, we explored genotype imputation as a means to infer important pharmacogenomic alleles from a regular commercially available genome-wide SNP array. Using these arrays as a starting point can reduce testing costs, increasing access to these pharmacogenomic data and still retain a larger amount of genome-wide information. IMPUTE2 and MaCH-Admix were used to perform genotype imputation with a dense reference panel from 1000 Genomes data. We were able to correctly infer genotypes for the warfarin-related loci VKORC1 and CYP2C9 alleles *2, *3, *5, and *11 and also clopidogrel-related CYP2C19 alleles *2 and *17 for a small sample of Brazilian individuals, as well as for HapMap samples. The success of an imputation approach in admixed samples using publicly available reference panels can encourage further imputation initiatives in those populations.

Personalized medicine is becoming a medical reality, as important genotype-phenotype relationships are being unraveled. The availability of pharmacogenomic data is a key element of individualized care. In this study, we explored genotype imputation as a means to infer important pharmacogenomic alleles from a regular commercially available genome-wide SNP array. Using these arrays as a starting point can reduce testing costs, increasing access to these pharmacogenomic data and still retain a larger amount of genome-wide information. IMPUTE2 and MaCH-Admix were used to perform genotype imputation with a dense reference panel from 1000 Genomes data. We were able to correctly infer genotypes for the warfarin-related loci VKORC1 and CYP2C9 alleles *2, *3, *5, and *11 and also clopidogrel-related CYP2C19 alleles *2 and *17 for a small sample of Brazilian individuals, as well as for HapMap samples. The success of an imputation approach in admixed samples using publicly available reference panels can encourage further imputation initiatives in those populations.

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