Laure Elens1,2, Vincent Haufroid2,3. 1. Department of Integrated PharmacoMetrics, PharmacoGenomics & PharmacoKinetics, Louvain Drug Research Institute, Université Catholique de Louvain, 1200 Brussels, Belgium. 2. Louvain Centre for Toxicology & Applied Pharmacology, Institut de Recherche Expérimentale et Clinique, Université Catholique de Louvain, 1200 Brussels, Belgium. 3. Department of Clinical Chemistry, Cliniques Universitaires St Luc, Université Catholique de Louvain, 1200 Brussels, Belgium.
Abstract
AIM: To test the relevance of revisiting the genotype classification based on CYP3A5*3 solely by incorporating CYP3A4*22 information. METHODS: Discriminant analysis of principal component was performed to evaluate the relevance of either the CYP3A (CYP3A5 + CYP3A4 genotypes) or CYP3A5*3 classification variables. This analysis was based on a linear combination of noncompartmental pharmacokinetics parameters. RESULTS: Discriminant analysis of principal component gave better results with CYP3A compared with CYP3A5*3 clustering. The centroid means of the pharmacokinetics variables were significantly different with CYP3A genotype clustering (p = 0.04) but not with CYP3A5*3 solely (p = 0.06). Canonical plots reveal a better delimitation of clusters with CYP3A genotype compared with CYP3A5*3 and the reciever operating characteristic curves confirm this better discriminative power. CONCLUSION: We provide strong arguments of incorporating CYP3A4*22 genotype in practice to fine-tune the existing Clinical Phamacogenetics Implementation Consortium guidelines in the Caucasian population.
AIM: To test the relevance of revisiting the genotype classification based on CYP3A5*3 solely by incorporating CYP3A4*22 information. METHODS: Discriminant analysis of principal component was performed to evaluate the relevance of either the CYP3A (CYP3A5 + CYP3A4 genotypes) or CYP3A5*3 classification variables. This analysis was based on a linear combination of noncompartmental pharmacokinetics parameters. RESULTS: Discriminant analysis of principal component gave better results with CYP3A compared with CYP3A5*3 clustering. The centroid means of the pharmacokinetics variables were significantly different with CYP3A genotype clustering (p = 0.04) but not with CYP3A5*3 solely (p = 0.06). Canonical plots reveal a better delimitation of clusters with CYP3A genotype compared with CYP3A5*3 and the reciever operating characteristic curves confirm this better discriminative power. CONCLUSION: We provide strong arguments of incorporating CYP3A4*22 genotype in practice to fine-tune the existing Clinical Phamacogenetics Implementation Consortium guidelines in the Caucasian population.
Entities:
Keywords:
CYP3A4*22; CYP3A5*3; discriminant analysis of principal component; dosage guidelines; genotype; kidney transplantation; tacrolimus
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