New AMP testing recommendations for alleles in CYP3A4 and CYP3A5

The Association for Molecular Pathology, Clinical Pharmacogenetics Implementation Consortium, College of American Pathologists, Dutch Pharmacogenetics Working Group of the Royal Dutch Pharmacists Association, European Society for Pharmacogenomics and Personalized Therapy, and Pharmacogenomics Knowledgebase have jointly published recommendations on what constitutes the minimum panel of variant alleles (tier 1) and an extended panel of variant alleles (tier 2) for CYP3A4 and CYP3A5 [PMID:337419245].

Tier 1 CYP3A4*22, CYP3A5*3, CYP3A5*6, CYP3A5*7

Tier 2 CYP3A4*20

PharmGKB maintains the lists for these alleles and the tier 1 and tier 2 alleles previously published for CYP2C19, CYP2C9, VKORC1, TPMT. NUDT15 at https://www.pharmgkb.org/ampAllelesToTest

When on an allele page there is a tag to show if this allele is part of the recommended test set:

When on a gene page there is a tag to show the gene has an AMP set of test alleles plus there is a link to the AMP page from the VIP summary. 

Insights on CYP2C19 and phenoconversion

Phenoconversion in the PGx context is a drug-drug interaction that impacts a drug metabolizing phenotype such that it mimics the effects of a metabolizer genotype (see blog from October 2022). Historically much of the discussion on phenoconversion has focused on CYP2D6.

A new paper in Frontiers in Pharmacology investigates the phenoconversion effects of different CYP2C19 inhibitors [PMID:37361233]. 

Forty donor liver samples were genotyped for CYP2C19 *2, *3 and *17 and the metabolizer phenotypes predicted. Microsomes were assayed with the probe drug s-mephenytoin and then in the presence of strong CYP2C19 inhibitor fluvoxamine, moderate inhibitors omeprazole and voriconazole and weak inhibitor pantoprazole to look at changes in metabolizer status. 

Excerpts from paper:

“Our results demonstrate that the outcome of a DDI is dictated by both inhibitor strength and CYP2C19 activity, which is in turn dependent on genotype and non-genetic factors including comorbidities. … 

Fluvoxamine, a strong inhibitor of CYP2C19, caused 86% of *1/*17 donors to become phenotypically IM, whereas most of genetically-predicted IMs were converted to a PM phenotype (57%). In accordance with unaltered CYP2C19 activity in patients with gastroesophageal reflux disease taking pantoprazole, weak inhibition by pantoprazole did not induce phenoconversion…

However, the outcomes of DDIs with moderate inhibitors (omeprazole/voriconazole) matched less well to the proposed phenoconversion model by Mostafa et al, which predicted that NMs/IMs convert to a PM phenotype upon moderate inhibition of CYP2C19. In our study, voriconazole, which acts as a moderate CYP2C19 inhibitor, significantly reduced the drug metabolizing capabilities of CYP2C19 by approximately one level (i.e., from a phenotypic NM to a IM). As a result, 40% of the donors (12/30) were converted into IM or PM phenotypes by voriconazole. Though, none of the NMs were converted into PMs, except for one donor who already exhibited impaired CYP2C19 activity in the absence of voriconazole treatment (basal phenoconversion). For omeprazole, phenoconversion into IM or PM phenotypes was even less frequently seen, in only 10% of the donors …

Altogether, our data suggest that CYP2C19 inhibition by moderate inhibitors can result in phenoconversion, but it seems unlikely to result into a PM phenotype for wild-type *1/*1 genotypes.”

There are a number of interesting results and discussion points:

• There is phenoconversion from disease phenotype - namely diabetes. 
• The initial concordance for genotype to phenotype with s-mephenytoin was only 40% and the two CYP2C19*17/*17 did not have ultra-rapid UM phenotype (with Vmax in the low normal NM range). The discussion mentions “other (rare) genetic variants within CYP2C19 could also have influenced the mismatch between predicted and observed activities in our study” but it would have been useful to have ruled out *4. The *17/*17 did produce functional mRNA but the *4 is in the start codon and its impact is on translation not transcription [PMID: 9435198]. 
• There were two *1/*1 outliers with very high UM phenotype that would be interesting to see further genetic analysis of especially given the escitalopram UM CYP2C-haplotype defined by rs2860840T and rs11188059G in [PMID: 33759177]. 

Overall, this paper shows that while phenoconversion exists for CYP2C19 based on disease status and DDIs, the impact is not a simple downgrading of phenotype (e.g. from IM to PM) that can be applied in a consistent manner across subjects. The authors show that even for strong inhibitors, phenoconversion happens in 40%-86% of subjects with no clear way to predict which subjects would experience phenoconversion and which wouldn’t. More research on how DDIs alter patient-predicted genotype to phenotype  is needed to enable better prediction of patient phenotype for PGx drug dosing recommendations.