Research Article
Genetic polymorphisms of cytochrome P450 enzymes influence metabolism of the antidepressant escitalopram and treatment response
Published Online:29 Mar 2010https://doi.org/10.2217/pgs.09.168
Abstract
Aims: The antidepressant escitalopram (S-CIT) is metabolized by the cytochrome-P450 (CYP) enzymes CYP 2D6, 2C19 and 3A4. This study evaluated the impact of CYP2D6, 2C19 and 3A4 genetic polymorphisms on plasma concentrations of S-CIT and patient treatment response. Materials & methods: A total of 100 patients diagnosed with major depressive disorder were recruited to the study and their depression symptoms were assessed using the Hamilton Depression Rating Scale. The genetic polymorphisms *4, *5 and *10 on CYP2D6, *2, *3 and *17 on CYP2C19, and *18 on CYP3A4 were selected based on their function and respective allele frequencies in Asian populations. Polymorphisms were analyzed using the SNPstream® genotyping system, PCR and direct sequencing methods. The steady-state serum concentrations of S-CIT and its metabolites S-desmethylcitalopram and S-didesmethylcitalopram were analyzed by HPLC. According to semiquantitative gene dose (SGD) and gene dose (GD) models for allele combinations of these polymorphisms, CYP2D6 was clustered into intermediate (0.5, 1 and 1.5 SGD) and extensive (2 SGD) metabolizers, while CYP2C19 was clustered into poor (0 GD) and extensive (1 and 2 GDs) metabolizers. Results: The group of patients with intermediate CYP2D6 metabolism (0.5 SGD) had a significantly higher frequency of remitters from major depressive disorder during the 8-week treatment (p = 0.0001). Furthermore, CYP2C19 poor metabolizers had significantly higher S-CIT serum levels than did extensive metabolizers at weeks 2, 4 and 8 (p < 0.05). The allele frequencies in CYP3A4*18 and CYP2C19*17 were too low to permit further subgroup analyses. Conclusion: Our results suggest that the genetic polymorphisms in CYP2C19 may be influencing S-CIT serum concentrations, and that specific CYP2D6 polymorphisms may be predicting patient treatment outcomes based on gene dosage analyses.
Papers of special note have been highlighted as: ▪ of interest
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