An update on CYP2C9 polymorphisms and phenytoin metabolism: implications for adverse effects. (2nd August 2020)

• Record Type: Journal Article
• Authors: Chang, Wan-Chun; Hung, Shuen-Iu; Carleton, Bruce C; Chung, Wen-Hung
• Is Part Of: Expert opinion on drug metabolism and toxicology. Volume 16:Number 8(2020)
• Page Start: 723
• Page End: 734
• Publication Date: 2020-08-02
• Subjects: Adverse drug reaction (ADR) -- CYP2C9 -- human leukocyte antigen (HLA) -- pharmacogenomics -- phenytoin -- Stevens-Johnson syndrome (SJS) -- toxic epidermal necrolysis (TEN); Drugs -- Toxicology -- Periodicals; Drugs -- Metabolism -- Periodicals; 615.7
• DOI: 10.1080/17425255.2020.1780209
• Languages: English
• ISSNs: 1742-5255

Abstract

ABSTRACT: Introduction: Phenytoin is a frequently used drug treatment for epilepsy. Genetic polymorphisms in the metabolism of phenytoin, particularly CYP2C9, are strongly associated with increased plasma concentrations and can result in toxicity. Human leukocyte antigen ( HLA ) alleles are well-known genetic predictors of certain antiepileptic drug-associated severe cutaneous adverse reactions (SCAR), including Stevens-Johnson syndrome (SJS) and toxic epidermal necrolysis (TEN). Recent pharmacogenomic studies show genetic polymorphisms in CYP2C9, as well as HLA alleles, are significantly associated with phenytoin-related SCAR. Areas covered: Updated pharmacogenomic information of CYP2C9 variants and HLA alleles involved in phenytoin-associated cutaneous adverse drug reactions (cADRs) are discussed in this article. Expert opinion: CYP2C9*3: has been identified as the most significant genetic variant associated with increased phenytoin concentrations and adverse events. Recent pharmacogenomic findings reveal that CYP2C9*3 and HLA alleles, i.e. HLA-B*15:02, HLA-B*13:01, and HLA-B*51:01, are important genetic variants in the occurrence of phenytoin-induced cADRs or SCAR. A phenotype- and population-specific multigene panel can be used before prescribing to predict phenytoin-induced cADRs and further guide optimal dose selection.