ABSTRACT
Background: Tramadol is primarily metabolized by the highly polymorphic CYP2D6 enzyme, leading to a large spectrum of adverse events and clinical response. Ample evidence pointed a reduced CYPD26 activity score in individuals harboring the CYP2D6*10/*10 genotype, nevertheless, there is scarce studies on the impact of CYP2D6*10/*10 genetic polymorphism on long-term tramadol's adverse effects. Aim: To test the correlation between CYP2D6*10/*10 expression and the risk for tramadol-associated adverse effects. Method: Using a database of Leumit Healthcare Services in Israel, we retrospectively assessed the occurrence of adverse events in patients who were prescribed tramadol. A binary logistic regression model was applied to model the relationship between CYP2D6*10/*10 genotype and the occurrence of adverse effects. Results: Data from four hundred ninety-three patients were included in this study. Only 25 (5.1%) patients were heterozygous for the CYP2D6*10 variant, while 56 patients (11%) were tested positive to the CYP2D6*10/*10 genotype. Compared to carriers of other variants, patients with the CYP2D6*10/*10 variant exhibited a higher occurrence of adverse events (odds ratio [OR] = 6.14, 95% confidence interval 3.18-11.83); the odds ratio for central nervous system adverse events and gastrointestinal adverse events were 5.13 (95% CI 2.84-9.28), and 3.25 (95% CI 1.78-5.93), respectively. Conclusion: Among the different CYP2D6 genotypes, CYP2D6*10/*10 genotype carries the higher risk of tramadol related adverse events. Appreciating the frequency of this specific allele it seems prudent to pharmacogenetically screen patients considered for long term tramadol treatment for better tolerability and efficacy outcomes.
ABSTRACT
Background-Various antidepressant agents are metabolized by the CYP2C19 enzyme, including Citalopram and Escitalopram. Variation in CYP2C19 expression might give rise to different plasma concentrations of the active metabolites, potentially affecting both drugs' efficacy and tolerability. Aim-The aim of this study was to evaluate differences in the Escitalopram and Citalopram efficacy and tolerability between different CYP2C19 genotype-based metabolizing categories in outpatients suffering from major depressive disorder (MDD). Methods-In a retrospective, longitudinal cohort study of electronic medical-record data, 283 patients with MDD who were prescribed Escitalopram or Citalopram with the available CYP2C19-genotyping test were enrolled. The primary efficacy end point was adverse drug reactions recorded in the medical files. A proportional-odds, multilevel-regression model for longitudinal ordinal data was used to estimate the relation between the CYP2C19 genotype and adverse drug reactions, adjusting for potential confounding variables and other explanatory variables. Latent-class analysis (LCA) was utilized to detect the presence of clinically significant subgroups and their relation to an individual's metabolizing status for CYP2D6/CYP2C19. Results-With poor CYP2C19 metabolizers as a reference, for each unit difference in the activity score of the CYP2C19 phenotype, the odds ratio for drug intolerability was lowered by 0.73 (95% credible intervals: 0.56-0.89), adjusting for significant covariates. In addition, applying LCA, we identified two qualitatively different subgroups: the first group (61.85%) exhibited multiple side effects, low compliance, and frequent treatment changes, whereas the second group (38.15%) demonstrated fewer side effects, good adherence, and fewer treatment changes. The CYP2C19 phenotype was substantially associated with the group membership. Conclusions-We found a positive association between the CYP2C19 activity scores, as inferred from the genotype, and both the efficacy of and tolerability to both Es/Citalopram. LCA enabled valuable insights into the underlying structure of the population; the CYP2C19 phenotype has a predictive value that discriminates between low-adherence, low-drug-tolerance, and low-response patients and high-adherence, high-drug-tolerance, and high-response patients. Personalized medicine based on CYP2C19 genotyping could evolve as a promising new avenue towards mitigating Escitalopram and Citalopram therapy and the associated side effects and enhancing treatment success.