Quantitative Modeling Analysis Demonstrates the Impact of CYP2C19 and CYP2D6 Genetic Polymorphisms on the Pharmacokinetics of Amitriptyline and Its Metabolite, Nortriptyline.

Abstract

Amitriptyline is a tricyclic antidepressant that is metabolized mainly by CYP2C19 and CYP2D6 enzymes. Higher plasma levels of amitriptyline and its active metabolite, nortriptyline, are associated with an increased risk of adverse events including anticholinergic effects. The aim of this study was to evaluate the effects of CYP2C19 and CYP2D6 genetic polymorphisms on amitriptyline and nortriptyline pharmacokinetics. Twenty-four Korean healthy adult male volunteers were enrolled in the study after stratification by their CYP2C19 and CYP2D6 genotypes. Serial blood draws for pharmacokinetic analysis were made after a single oral 25-mg dose of amitriptyline was administered. Plasma amitriptyline and nortriptyline concentrations were measured by a validated liquid chromatography with tandem mass spectrometry. Population pharmacokinetic modeling analysis was conducted using NONMEM, which evaluated the effects of CYP2C19 and CYP2D6 genotypes on amitriptyline and nortriptyline pharmacokinetics. The biotransformation of amitriptyline into nortriptyline was significantly different between subjects with the CYP2C19*2/*2, *2/*3, and *3/*3 genotypes and those with the other genotypes, with an estimated metabolic clearance of 17 and 61.5 L/h, respectively. Clearance of amitriptyline through pathways other than biotransformation into nortriptyline was estimated as 18.8 and 30.6 L/h for subjects with the CYP2D6*10/*10 and *10/*5 genotypes and those with the other genotypes, respectively. This study demonstrated a quantitative effect of the CYP2C19 and CYP2D6 genotypes on amitriptyline and nortriptyline pharmacokinetics. Production of nortriptyline from amitriptyline was associated with CYP2C19 genotypes, and clearance of amitriptyline through pathways other than biotransformation into nortriptyline was associated with CYP2D6 genotypes. These observations may be useful in developing individualized, optimal therapy with amitriptyline.