In:
Current Drug Metabolism, Bentham Science Publishers Ltd., Vol. 24 ( 2023-09-07)
Abstract:
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.
Type of Medium:
Online Resource
ISSN:
1389-2002
DOI:
10.2174/1389200224666230907093349
Language:
English
Publisher:
Bentham Science Publishers Ltd.
Publication Date:
2023
SSG:
15,3
