BACKGROUND: Arylamine N-acetyltransferase 2 (CoASAc; NAT2, EC 2.3.1.5) is a drug-metabolizing enzyme that displays common polymorphisms leading to impaired drug metabolism and adverse drug effects. Determination of the N-acetyltransferase 2 (arylamine N-acetyltransferase) (NAT2) genotype in clinical practice is hampered by the occurrence of ambiguous haplotype combinations that may lead to patient misclassification. We determined the frequencies for ambiguous NAT2 haplotypes and diplotypes in a white population and investigated the use of PHASE v2.1.1, a statistical program for haplotype reconstruction, to clarify this ambiguity and classify individuals according to their acetylation status. METHODS: By means of allele-specific haplotype mapping and sequencing, we determined the haplotypes for 7 common single-nucleotide polymorphisms in the NAT2 gene (n = 2624 haplotypes). To test the performance of PHASE, actual genotypes were deconstructed and then reconstructed by haplotype prediction. RESULTS: We identified 21 NAT2 allelic variants, including a new variant allele that combines the single-nucleotide polymorphisms rs1801279, rs1799929, and rs1208. In contrast, the previously described variant alleles *5G, *5J, *6E, *7A, *11A, *11B, and *14B were not identified in the study population. Ambiguous haplotypes were observed in 98 alleles (3.7%), and ambiguous diplotypes were observed in 64 individuals (4.9%). Eleven individuals (0.8%) were misclassified by the use of haplotype prediction. CONCLUSIONS: Ambiguous NAT2 genotyping data are common. Actual NAT2 genotypes cannot be fully determined by haplotype prediction techniques. This study provides real haplotype data that can be used as a guide to convert NAT2 haplotypes and diplotypes into actual genotypes in white individuals.
BACKGROUND:Arylamine N-acetyltransferase 2 (CoASAc; NAT2, EC 2.3.1.5) is a drug-metabolizing enzyme that displays common polymorphisms leading to impaired drug metabolism and adverse drug effects. Determination of the N-acetyltransferase 2 (arylamine N-acetyltransferase) (NAT2) genotype in clinical practice is hampered by the occurrence of ambiguous haplotype combinations that may lead to patient misclassification. We determined the frequencies for ambiguous NAT2 haplotypes and diplotypes in a white population and investigated the use of PHASE v2.1.1, a statistical program for haplotype reconstruction, to clarify this ambiguity and classify individuals according to their acetylation status. METHODS: By means of allele-specific haplotype mapping and sequencing, we determined the haplotypes for 7 common single-nucleotide polymorphisms in the NAT2 gene (n = 2624 haplotypes). To test the performance of PHASE, actual genotypes were deconstructed and then reconstructed by haplotype prediction. RESULTS: We identified 21 NAT2 allelic variants, including a new variant allele that combines the single-nucleotide polymorphisms rs1801279, rs1799929, and rs1208. In contrast, the previously described variant alleles *5G, *5J, *6E, *7A, *11A, *11B, and *14B were not identified in the study population. Ambiguous haplotypes were observed in 98 alleles (3.7%), and ambiguous diplotypes were observed in 64 individuals (4.9%). Eleven individuals (0.8%) were misclassified by the use of haplotype prediction. CONCLUSIONS: Ambiguous NAT2 genotyping data are common. Actual NAT2 genotypes cannot be fully determined by haplotype prediction techniques. This study provides real haplotype data that can be used as a guide to convert NAT2 haplotypes and diplotypes into actual genotypes in white individuals.
Authors: J P Clancy; S G Johnson; S W Yee; E M McDonagh; K E Caudle; T E Klein; M Cannavo; K M Giacomini Journal: Clin Pharmacol Ther Date: 2014-03-05 Impact factor: 6.875
Authors: Jhon D Ruiz; Carmen Martínez; Kristin Anderson; Myron Gross; Nicholas P Lang; Elena García-Martín; José A G Agúndez Journal: PLoS One Date: 2012-09-06 Impact factor: 3.240
Authors: José A G Agúndez; Francisco Abad-Santos; Ana Aldea; Hortensia Alonso-Navarro; María L Bernal; Alberto M Borobia; Emma Borrás; Miguel Carballo; Alfonso Carvajal; José D García-Muñiz; Guillermo Gervasini; Félix J Jiménez-Jiménez; María I Lucena; Carmen Martínez; José A Sacristán; Inés Salado; Blanca Sinués; Jorge Vicente; Elena García-Martín Journal: Front Genet Date: 2012-11-26 Impact factor: 4.599
Authors: Elena García-Martín; José A G Agúndez; Carmen Martínez; Julián Benito-León; Jorge Millán-Pascual; Patricia Calleja; María Díaz-Sánchez; Diana Pisa; Laura Turpín-Fenoll; Hortensia Alonso-Navarro; Lucía Ayuso-Peralta; Dolores Torrecillas; José Francisco Plaza-Nieto; Félix Javier Jiménez-Jiménez Journal: PLoS One Date: 2013-06-20 Impact factor: 3.240
Authors: Elena García-Martín; Oswaldo Lorenzo-Betancor; Carmen Martínez; Pau Pastor; Julián Benito-León; Jorge Millán-Pascual; Patricia Calleja; María Díaz-Sánchez; Diana Pisa; Laura Turpín-Fenoll; Hortensia Alonso-Navarro; Lucía Ayuso-Peralta; Dolores Torrecillas; Elena Lorenzo; José Francisco Plaza-Nieto; José A G Agúndez; Félix Javier Jiménez-Jiménez Journal: BMC Neurol Date: 2013-04-10 Impact factor: 2.474