Improvements in Algorithms for Phenotype Inference: The NAT2 Example
Silvia Selinski, Meinolf Blaszkewicz, Katja Ickstadt, Jan G. Hengstler and Klaus Golka
Affiliation: Leibniz Research Centre for Working Environment and Human Factors (IfADo), Ardeystrasse 67, 44139 Dortmund, Germany.
Keywords: Anti-tuberculosis drug-induced hepatoxicity, bladder cancer, ethnic differences, haplotype phasing, haplotype reconstruction,
individualized medicine, NAT2 activity, ultra-slow acetylators.
Numerous studies have analyzed the impact of N-acetyltransferase 2 (NAT2) polymorphisms on drug efficacy, side effects as
well as cancer risk. Here, we present the state of the art of deriving haplotypes from polymorphisms and discuss the available software.
PHASE v2.1 is currently considered a gold standard for NAT2 haplotype assignment. In vitro studies have shown that some slow acetylation
genotypes confer reduced protein stability. This has been observed particularly for G191A, T341C and G590A. Substantial ethnic
variations of the acetylation status have been described. Probably, upcoming agriculture and the resulting change in diet caused a selection
pressure for slow acetylation. In recent years much research has been done to reduce the complexity of NAT2 genotyping. Deriving
the haplotype from seven SNPs is still considered a gold standard. However, meanwhile several studies have shown that a two-SNP combination,
C282T and T341C, results in a similarly good distinction in Caucasians. However, attempts to further reduce complexity to only
one 'tagging SNP' (rs1495741) may lead to wrong predictions where phenotypically slow acetylators were genotyped as intermediate or
rapid. Numerous studies have shown that slow NAT2 haplotypes are associated with increased urinary bladder cancer risk and increased
risk of anti-tuberculosis drug-induced hepatotoxicity. A drawback of the current practice of solely discriminating slow, intermediate and
rapid genotypes for phenotype inference is limited resolution of differences between slow acetylators. Future developments to differentiate
between slow and ultra-slow genotypes may further improve individualized drug dosing and epidemiological studies of cancer risk.
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