Monday, November 27, 2023

New Fluoropyrimidine Toxicity Variants Reported in DPYS and PPARD

A recent paper highlights new variants and genes associated with severe fluoropyrimidine-related toxicity in patients who were genotyped as negative for the four DPYD variants the European Medicines Agency recommends testing for.

Online ahead of print in the Human Genomics journal is De Mattia et al "The burden of rare variants in DPYS gene is a novel predictor of the risk of developing severe fluoropyrimidine-related toxicity" [PMID: 37946254].

The study sequenced 120 patients with fluoropyrimidine induced grade 3-5 toxicity confirming they lacked DPYD*2A, DPYD*13, c.2846A > T, c.1236G > A-HapB3. The paper reports rare and common variants including DPYS rs143004875-T and PPARD rs2016520-T which were associated with increased risk of severe toxicity.

Thursday, November 9, 2023

Save the Date: ClinPGx 2024 Meeting

In collaboration with CPIC, PharmGKB, PharmCAT and PharmVar,  the University of Pennsylvania, Penn Center for Precision Medicine will be hosting the ClinPGx 2024: Knowledge, Implementation, Education meeting June 20th and 21st, 2024 in Philadelphia, PA. The meeting will provide educational content to cover all aspects of PGx implementation including knowledgebases, implementation strategies, informatics, use of AI in precision medicine, clinical laboratory insights, and more. Additional details to soon.

Tuesday, September 26, 2023

Frequencies of Pharmacogenomic Alleles across UK Biobank Biogeographic Groups Published

We are happy to announce the publication of our latest research article in the American Journal of Human Genetics (AJHG), titled “Frequencies of Pharmacogenomic Alleles across Biogeographic Groups in a Large-Scale Biobank.” The paper is now available online on the AJHG website.

Genetic biobanks provide rich data sets to investigate population-specific pharmacogenomic (PGx) allele frequencies and the implications of equitable and inclusive implementation. Using an integrated UK Biobank 200K genetic dataset (N = 200,044), we estimated the pharmacogenomic (PGx) allele frequencies for seventeen (17) pharmacogenes in five (5) biogeographic groups. 
  • Pharmacogenes included ABCG2, CACNA1S, CYP2B6, CYP2C19, CYP2C9, CYP3A5, CYP4F2, DPYD, G6PD, IFNL3, NUDT15, RYR1, SLCO1B1, TPMT, UGT1A1, and VKORC1. CFTR and the CYP2C cluster variant (rs12777823) were also investigated. CYP2D6 alleles that could be determined from VCF, and therefore not including structural variants, were also predicted.
  • The five (5) biogeographic groups are Europeans (n = 187,660), Central/South Asians (n = 3,460), East Asians (n = 637), African Americans/Afro-Caribbeans (n = 1,926), and Sub-Saharan Africans (n = 1,235)
  • Frequencies of PGx alleles, diplotypes, phenotypes, and/or activity scores, if applicable, were reported for each gene in each biogeographic group.

We found that 100% of the UK Biobank participants harbored at least one genetic variant found in known PGx haplotypes. 

The main takeaways messages are:

1. UK Biobank PGx frequencies complemented the CPIC frequency tables.

2. This study reported frequencies for a nontrivial number of PGx alleles that are rare or seldom tested, especially in the non-European group.

3. There are uncataloged PGx alleles.

PGx frequencies estimated from this study will be disseminated via PharmGKB. Biobank-derived allele frequencies can provide guidance for future PGx studies and clinical genetic test panel design, and better serve individuals from wider biogeographic backgrounds.

Monday, September 25, 2023

Disulfiram Pathway published in Pharmacogenetics and Genomics

Substance abuse disorders are a significant public health cost [PMID: 34453125]. Prescribers have limited choices for pharmaceutical therapies with only three FDA-approved choices for alcohol use disorder and zero for cocaine use disorder. Disulfiram is an FDA-approved treatment for alcohol use disorder which is also used for cocaine use disorder. There are some preliminary studies on the PGx of disulfiram but little replication.

PharmGKB together with Dr Aneysis De Las Mercedes Gonzalez (Stanford University School of Medicine), have published PharmGKB summary: disulfiram pathway in Pharmacogenetics and Genomics, 2023 Sep 21. doi: 10.1097/FPC.0000000000000509. Online ahead of print. PMID: 37728645. It summarizes the candidate genes involved in disulfiram PGx in pharmacokinetics and action in dopaminergic, seratonergic and noradrenergic neurons and highlights the knowledge gaps.

As always interactive versions of the diagrams with underlying linked evidence, are available on PharmGKB:

Disulfiram Pathway, Pharmacokinetics,

Disulfiram Pathway, Pharmacodynamics (Cocaine and Ethanol PK)

Disulfiram Pathway, Pharmacodynamics (Dopaminergic neuron)

Disulfiram Pathway, Pharmacodynamics (Serotonergic neuron)

Sympathetic Nerve Pathway (Neuroeffector Junction)

Friday, August 18, 2023

Please Take This Survey If Your Site Conducts DPYD Genetic Testing Prior to Fluoropyrimidine Chemotherapy

Dan Hertz ( and the DPYD Implementation Team are collecting information from sites and clinicians in the USA that conduct DPYD genetic testing prior to fluoropyrimidine chemotherapy treatment. If this applies to you, please complete this brief (<5 minutes) survey on behalf of your site before mid-September. This information will be used to develop best practice guidelines for pre-treatment DPYD testing.


Thanks for your participation!

Thursday, July 13, 2023

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

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

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. 

Wednesday, July 12, 2023

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.