Genetic polymorphisms of cytochrome P450 enzymes influence metabolism of the antidepressant escitalopram and treatment response

Ming Hsien Tsai, Keh Ming Lin, Mei Chun Hsiao, Winston W. Shen, Mong Liang Lu, Hwa Sheng Tang, Chun Kai Fang, Chi Shin Wu, Shao Chun Lu, Shu Chih Liu, Chun Yu Chen, Yu Li Liu

Research output: Contribution to journalArticle

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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 ß4, ß5 and ß10 on CYP2D6, ß2, ß3 and ß17 on CYP2C19, and ß18 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 CYP3A4ß18 and CYP2C19ß17 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.

Original languageEnglish
Pages (from-to)537-546
Number of pages10
JournalPharmacogenomics
Volume11
Issue number4
DOIs
Publication statusPublished - Apr 2010

Fingerprint

Cytochrome P-450 CYP2D6
Citalopram
Genetic Polymorphisms
Cytochrome P-450 Enzyme System
Antidepressive Agents
Genes
Cytochrome P-450 CYP3A
Major Depressive Disorder
Gene Frequency
Therapeutics
Serum
Depression
Gene Dosage
Alleles
High Pressure Liquid Chromatography
Polymerase Chain Reaction
Cytochrome P-450 CYP2C19
Population

Keywords

  • CYP2C19
  • CYP2D6
  • CYP3A4
  • Escitalopram
  • Major depression
  • Therapeutic drug monitoring

ASJC Scopus subject areas

  • Pharmacology
  • Genetics
  • Molecular Medicine

Cite this

Genetic polymorphisms of cytochrome P450 enzymes influence metabolism of the antidepressant escitalopram and treatment response. / Tsai, Ming Hsien; Lin, Keh Ming; Hsiao, Mei Chun; Shen, Winston W.; Lu, Mong Liang; Tang, Hwa Sheng; Fang, Chun Kai; Wu, Chi Shin; Lu, Shao Chun; Liu, Shu Chih; Chen, Chun Yu; Liu, Yu Li.

In: Pharmacogenomics, Vol. 11, No. 4, 04.2010, p. 537-546.

Research output: Contribution to journalArticle

Tsai, MH, Lin, KM, Hsiao, MC, Shen, WW, Lu, ML, Tang, HS, Fang, CK, Wu, CS, Lu, SC, Liu, SC, Chen, CY & Liu, YL 2010, 'Genetic polymorphisms of cytochrome P450 enzymes influence metabolism of the antidepressant escitalopram and treatment response', Pharmacogenomics, vol. 11, no. 4, pp. 537-546. https://doi.org/10.2217/pgs.09.168
Tsai, Ming Hsien ; Lin, Keh Ming ; Hsiao, Mei Chun ; Shen, Winston W. ; Lu, Mong Liang ; Tang, Hwa Sheng ; Fang, Chun Kai ; Wu, Chi Shin ; Lu, Shao Chun ; Liu, Shu Chih ; Chen, Chun Yu ; Liu, Yu Li. / Genetic polymorphisms of cytochrome P450 enzymes influence metabolism of the antidepressant escitalopram and treatment response. In: Pharmacogenomics. 2010 ; Vol. 11, No. 4. pp. 537-546.
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AU - Lin, Keh Ming

AU - Hsiao, Mei Chun

AU - Shen, Winston W.

AU - Lu, Mong Liang

AU - Tang, Hwa Sheng

AU - Fang, Chun Kai

AU - Wu, Chi Shin

AU - Lu, Shao Chun

AU - Liu, Shu Chih

AU - Chen, Chun Yu

AU - Liu, Yu Li

PY - 2010/4

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N2 - 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 ß4, ß5 and ß10 on CYP2D6, ß2, ß3 and ß17 on CYP2C19, and ß18 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 CYP3A4ß18 and CYP2C19ß17 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.

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