Which can Predict the Outcome of Antidepressants: Metabolic Genes or Pharmacodynamic Genes?

Drug therapy is the primary modality for depression; however, its outcome is often unpredictable, ranging from beneficial effects to serious adverse effects. Genetic variations in drug metabolizing enzymes and pharmacodynamic molecules are responsible for a considerable proportion of interindividual differences in the effectiveness and toxicity of antidepressants. For the improvement in the use of antidepressants, the focus is mainly on personalized treatment emphasizing interindividual differences in genes. This study provides a comprehensive review of the literature on the clinical applications of pharmacogenomics for antidepressant therapy. The polymorphisms of metabolizing enzymes (CYP2D6, CYP2C19,and others) governing the pharmacokinetic behavior of drugs are potential predictors of side effects or treatment failure with medications and there are good pharmacogenetic clinical recommendations for a wide selection of psychopharmacological agents based on functional diplotypes of CYP2C19 and CYP2D6. The relationship between pharmacodynamic genes, including FKBP5, SLC6A4, BDNF, ABCB1, HTR1A, and HTR2A, and clinical outcomes varies in different races. Receptors that are currently used as drug targets for antidepressant drugs are evolutionarily conserved to a higher extent than genes encoding drug metabolism, and the actionability of pharmacodynamic-related genotyping is currently still questionable. The limited availability of large-scale, long-term clinical studies on different races and medications currently impedes the implementation of pharmacogenomics in antidepressant treatment. The use of pharmacokinetic and pharmacodynamic modeling, and therapeutic drug monitoring combined with genetic, somatic, dietary, and environmental factors represents a promising avenue for improving the precision and effectiveness of antidepressant therapy.

Automated summary

Drug therapy for depression varies greatly in its outcomes, ranging from beneficial effects to adverse effects. Genetic variations in drug metabolism enzymes and pharmacodynamic molecules contribute to interindividual differences in response to antidepressants. Personalized treatment focusing on interindividual gene differences has been the main approach for improving the use of antidepressants. This study comprehensively reviews the literature on the clinical applications of pharmacogenomics in antidepressant therapy. Polymorphisms in drug metabolism enzymes such as CYP2D6 and CYP2C19 are potential predictors of side effects or treatment failure, and clinical recommendations based on functional diplotypes of these enzymes have been made for a wide selection of psychopharmacological agents. The relationship between pharmacodynamic genes and clinical outcomes varies across different races.