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

Abstract

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.

Targeted haplotyping in pharmacogenomics using Oxford Nanopore Technologies’ adaptive sampling

“…Although tools such as Cyrius also use a WGS .bam file, they are designed for short-read data and are specific to the CYP2D6 locus (Chen et al, 2021). The benchmarking results from Graansma et al and Shugg et al strengthen us in using Aldy as the most informative tool (Graansma et al, 2023;Shugg et al, 2023). We summarized our results for the 24 VIPs that Aldy currently supports in Table 5.…”

A comprehensive Thai pharmacogenomics database (TPGxD‐1): Phenotype prediction and variants identification in 942 whole‐genome sequencing data

“…Star allele nomenclature is a user‐friendly method for identifying gene‐level haplotype patterns, including variants like SNPs, InDels, and CNVs, making it accessible for non‐specialized professionals. 20 PharmVar has systematically converted 14 genes' variants into star nomenclature for approximately 14 genes. 15 The identified novel alleles in this study can be included in the already existing system with new allele numbers.…”