Which can Predict the Outcome of Antidepressants: Metabolic Genes or Pharmacodynamic 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.PMID:37691197 | DOI:10.2174/1389200224666230907093349
Source: Current Drug Metabolism - Category: Drugs & Pharmacology Authors: Source Type: research