Characterization of Reference Materials with an Association for Molecular Pathology Pharmacogenetics Working Group Tier 2 Status: CYP2C9, CYP2C19, VKORC1, CYP2C Cluster Variant, and GGCX: A GeT-RM Collaborative Project

Characterization of Reference Materials for DPYD: A GeT-RM Collaborative Project

The DPYD gene encodes dihydropyrimidine dehydrogenase (DPD), which is involved in the catalysis of uracil and thymine, as well as 5-fluorouracil (5-FU), which is used to treat solid tumors. Patients with decreased DPD activity are at risk of serious, sometimes fatal, adverse drug reactions to this important cancer drug. Pharmacogenetic testing for DPYD is increasingly provided by clinical and research laboratories; however, only a limited number of quality control and reference materials are currently available for clinical DPYD testing. To address this need, the Division of Laboratory Systems, Centers for Disease Control and Prevention-based Genetic Testing Reference Materials Coordination Program, in collaboration with members of the pharmacogenetic testing and research communities and the Coriell Institute for Medical Research, has characterized 33 DNA samples derived from Coriell cell lines for DPYD. Samples were distributed to four volunteer laboratories for genetic testing using a variety of commercially available and laboratory-developed tests. Sanger sequencing was used by one laboratory and publicly available whole-genome sequence data from the 1000 Genomes Project were used by another to inform genotype. Thirty-three distinct DPYD variants were identified among the 33 samples characterized. These publicly available and well-characterized materials can be used to support the quality assurance and quality control programs of clinical laboratories performing clinical pharmacogenetic testing.

Frequencies of pharmacogenomic alleles across biogeographic groups in a large-scale biobank

Pharmacogenomics (PGx) is an integral part of precision medicine and contributes to the maximization of drug efficacy and reduction of adverse drug event risk. Accurate information on PGx allele frequencies improves the implementation of PGx. Nonetheless, curating such information from published allele data is time and resource intensive. The limited number of allelic variants in most studies leads to an underestimation of certain alleles. We applied the Pharmacogenomics Clinical Annotation Tool (PharmCAT) on an integrated 200K UK Biobank genetic dataset (N = 200,044). Based on PharmCAT results, we estimated PGx frequencies (alleles, diplotypes, phenotypes, and activity scores) for 17 pharmacogenes in five biogeographic groups: European, Central/South Asian, East Asian, Afro-Caribbean, and Sub-Saharan African. PGx frequencies were distinct for each biogeographic group. Even biogeographic groups with similar proportions of phenotypes were driven by different sets of dominant PGx alleles. PharmCAT also identified "no-function" alleles that were rare or seldom tested in certain groups by previous studies, e.g., SLCO1B1∗31 in the Afro-Caribbean (3.0%) and Sub-Saharan African (3.9%) groups. Estimated PGx frequencies are disseminated via the PharmGKB (The Pharmacogenomics Knowledgebase: www.pharmgkb.org). We demonstrate that genetic biobanks such as the UK Biobank are a robust resource for estimating PGx frequencies. Improving our understanding of PGx allele and phenotype frequencies provides guidance for future PGx studies and clinical genetic test panel design, and better serves individuals from wider biogeographic backgrounds.

Characterization of Reference Materials for CYP3A4 and CYP3A5: A (GeT-RM) Collaborative Project

Pharmacogenetic testing for CYP3A4 is increasingly provided by clinical and research laboratories; however, only a limited number of quality control and reference materials are currently available for many of the CYP3A4 variants included in clinical tests. To address this need, the Division of Laboratory Systems, CDC-based Genetic Testing Reference Material Coordination Program (GeT-RM), in collaboration with members of the pharmacogenetic testing and research communities and the Coriell Institute for Medical Research, has characterized 30 DNA samples derived from Coriell cell lines for CYP3A4. Samples were distributed to five volunteer laboratories for genotyping using a variety of commercially available and laboratory-developed tests. Sanger and next-generation sequencing were also utilized by some of the laboratories. Whole-genome sequencing data from the 1000 Genomes Projects were utilized to inform genotype. Twenty CYP3A4 alleles were identified in the 30 samples characterized for CYP3A4: CYP3A4∗4, ∗5, ∗6, ∗7, ∗8, ∗9, ∗10, ∗11, ∗12, ∗15, ∗16, ∗18, ∗19, ∗20, ∗21, ∗22, ∗23, ∗24, ∗35, and a novel allele, CYP3A4∗38. Nineteen additional samples with preexisting data for CYP3A4 or CYP3A5 were re-analyzed to generate comprehensive reference material panels for these genes. These publicly available and well-characterized materials can be used to support the quality assurance and quality control programs of clinical laboratories performing clinical pharmacogenetic testing.

From gene to dose: Long-read sequencing and *-allele tools to refine phenotype predictions of CYP2C19

Background: Inter-individual differences in drug response based on genetic variations can lead to drug toxicity and treatment inefficacy. A large part of this variability is caused by genetic variants in pharmacogenes. Unfortunately, the Single Nucleotide Variant arrays currently used in clinical pharmacogenomic (PGx) testing are unable to detect all genetic variability in these genes. Long-read sequencing, on the other hand, has been shown to be able to resolve complex (pharmaco) genes. In this study we aimed to assess the value of long-read sequencing for research and clinical PGx focusing on the important and highly polymorphic CYP2C19 gene. Methods and Results: With a capture-based long-read sequencing panel we were able to characterize the entire region and assign variants to their allele of origin (phasing), resulting in the identification of 813 unique variants in 37 samples. To assess the clinical utility of this data we have compared the performance of three different *-allele tools (Aldy, PharmCat and PharmaKU) which are specifically designed to assign haplotypes to pharmacogenes based on all input variants. Conclusion: We conclude that long-read sequencing can improve our ability to characterize the CYP2C19 locus, help to identify novel haplotypes and that *-allele tools are a useful asset in phenotype prediction. Ultimately, this approach could help to better predict an individual's drug response and improve therapy outcomes. However, the added value in clinical PGx might currently be limited.

Characterization of Reference Materials for TPMT and NUDT15: A GeT-RM Collaborative Project

Pharmacogenetic testing is increasingly provided by clinical and research laboratories; however, only a limited number of quality control and reference materials are currently available for many of the TPMT and NUDT15 variants included in clinical tests. To address this need, the Division of Laboratory Systems, Centers for Disease Control and Prevention-based Genetic Testing Reference Material (GeT-RM) coordination program, in collaboration with members of the pharmacogenetic testing and research communities and the Coriell Institute for Medical Research, has characterized 19 DNA samples derived from Coriell cell lines. DNA samples were distributed to four volunteer testing laboratories for genotyping using a variety of commercially available and laboratory developed tests and/or Sanger sequencing. Of the 12 samples characterized for TPMT, newly identified variants include TPMT∗2, ∗6, ∗12, ∗16, ∗21, ∗24, ∗32, ∗33, and ∗40; for the 7 NUDT15 reference material samples, newly identified variants are NUDT15∗2, ∗3, ∗4, ∗5, ∗6, and ∗9. In addition, a novel haplotype, TPMT∗46, was identified in this study. Preexisting data on an additional 11 Coriell samples, as well as some supplemental testing, were used to create comprehensive reference material panels for TPMT and NUDT15. These publicly available and well-characterized materials can be used to support the quality assurance and quality control programs of clinical laboratories performing clinical pharmacogenetic testing.

ClinPharmSeq: A targeted sequencing panel for clinical pharmacogenetics implementation

The accurate identification of genetic variants contributing to therapeutic drug response or adverse effects is the first step in implementation of precision drug therapy. Targeted sequencing has recently become a common methodology for large-scale studies of genetic variation thanks to its favorable balance between low cost, high throughput, and deep coverage. Here, we present ClinPharmSeq, a targeted sequencing panel of 59 genes with associations to pharmacogenetic (PGx) phenotypes, as a platform to explore the relationship between drug response and genetic variation, both common and rare. For validation, we sequenced DNA from 64 ethnically diverse Coriell samples with ClinPharmSeq to call star alleles (haplotype patterns) in 27 genes using the bioinformatics tool PyPGx. These reference samples were extensively characterized by multiple laboratories using PGx testing assays and, more recently, whole genome sequencing. We found that ClinPharmSeq can consistently generate deep-coverage data (mean = 274x) with high uniformity (30x or above = 94.8%). Our genotype analysis identified a total of 185 unique star alleles from sequencing data, and showed that diplotype calls from ClinPharmSeq are highly concordant with that from previous publications (97.6%) and whole genome sequencing (97.9%). Notably, all 19 star alleles with complex structural variation including gene deletions, duplications, and hybrids were recalled with 100% accuracy. Altogether, these results demonstrate that the ClinPharmSeq platform offers a feasible path for broad implementation of PGx testing and optimization of individual drug treatments.

Sertraline dosing trends in children and adolescents stratified by CYP2C19 genotype

Aim: Sertraline is a CYP2C19 substrate commonly prescribed to children with anxiety. Materials & methods: This medical record review examined dosing trends and treatment discontinuation in children prescribed sertraline with documented CYP2C19 genotypes. Variables collected included age, weight, diagnosis, concomitant medications, initial sertraline dose, dose changes and CYP2C19 genotypes. Results: A total of 90 individuals (average age: 10.5 years; 40% female) were included. Nearly 80% were prescribed sertraline for anxiety. Initial weight-adjusted doses were similar, but mean weight-adjusted doses of sertraline were 65% higher in increased metabolizers (1.5 mg/kg/day) compared with normal metabolizers (0.91 mg/kg/day; p = 0.067) at the second dose change. Conclusion: While all children started at a similar sertraline dose, different trends in prescribed doses were observed across CYP2C19 genotypes at subsequent dose changes.