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Atorvastatin (ATV) is a blood cholesterol-lowering drug used to prevent cardiovascular events, the leading cause of death worldwide. As pharmacokinetics, metabolism and response vary among individuals, we wanted to determine the most reliable metabolic ATV phenotypes and identify novel and preponderant genetic markers that affect ATV plasma levels. A controlled, randomized, crossover, single-blind, three-treatment, three-period, and six-sequence clinical study of ATV (single 80-mg oral dose) was conducted among 60 healthy Mexican men. ATV plasma levels were measured using high-performance liquid chromatography mass spectrometry. Genotyping was performed by real-time PCR with TaqMan probes. Four ATV metabolizer phenotypes were found: slow, intermediate, normal and fast. Six gene polymorphisms, SLCO1B1-rs4149056, ABCB1-rs1045642, CYP2D6-rs1135840, CYP2B6-rs3745274, NAT2-rs1208, and COMT- rs4680, had a significant effect on ATV pharmacokinetics (P < 0.05). The polymorphisms in SLCO1B1 and ABCB1 seemed to have a greater effect and were especially important for the shift from an intermediate to a normal metabolizer. This is the first study that demonstrates how the interaction of genetic variants affect metabolic phenotyping and improves understanding of how SLCO1B1 and ABCB1 variants that affect statin metabolism may partially explain the variability in drug response. Notwithstanding, the influence of other genetic and non-genetic factors is not ruled out.

Aim: To use variants found by next-generation sequencing to predict atorvastatin plasmatic concentration profiles (AUC) in healthy volunteers., Subjects & Methods: A total of 60 healthy Mexican volunteers were enrolled in this study. We used variants with a predicted functional effect across 20 genes involved in atorvastatin metabolism to construct a regression model using a support vector approach with a radial basis function kernel to predict AUC refining it afterwards in order to explain a greater extent of the variance., Results: The final support vector regression model using 60 variants (including six novel variants) explained 94.52% of the variance in atorvastatin AUC., Conclusion: An integrated analysis of several genes known to intervene in the different steps of metabolism is required to predict atorvastatin's AUC.

Discrepancies in the response to drugs are partially due to polymorphisms in genes involved in drug metabolism and transport. The frequency, pattern and impact of these polymorphisms vary among populations. In the present study, the pharmacokinetics and pharmacogenetics of atorvastatin (ATV) in a Mexican population were investigated. The study cohort exhibited differing ATV metabolizing phenotypes, and in subsequent allelic discrimination assays, single nucleotide polymorphisms in the angiotensinogen, angiotensin II type 1 receptor (AGTR1) and bradykinin B2 receptor (BDKRB2) genes were genotyped and their effects on the pharmacokinetic parameters of ATV were assessed. Additionally, association studies were performed to test for a correlation between metabolizing phenotypes and genetic variants. It was observed that carriers of the genotypes A/C and C/T in AGTR1 and BDKRB2 had higher area under the plasma concentration-time curve values from time 0 to the time of the last measurement and from time 0 extrapolated to infinity, and lower values of clearance of the fraction dose absorbed compared with homozygous carriers (P<0.05). Only the C/C genotype of BDKRB2 was associated with the fast metabolizer phenotype. These data suggest that AGTR1 and BDKRB2 are involved in ATV pharmacokinetics; a novel finding that requires confirmation in further studies. [ABSTRACT FROM AUTHOR]