Division of Clinical Pharmacology, Department of Medicine, Indiana University School of Medicine, Indianapolis, Indiana; Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, Indiana.
Division of Clinical Pharmacology, Department of Medicine, Indiana University School of Medicine, Indianapolis, Indiana.
J Mol Diagn. 2022 Jun;24(6):576-585. doi: 10.1016/j.jmoldx.2022.03.008. Epub 2022 Apr 20.
Germline whole exome sequencing from molecular tumor boards has the potential to be repurposed to support clinical pharmacogenomics. However, accurately calling pharmacogenomics-relevant genotypes from exome sequencing data remains challenging. Accordingly, this study assessed the analytical validity of the computational tool, Aldy, in calling pharmacogenomics-relevant genotypes from exome sequencing data for 13 major pharmacogenes. Germline DNA from whole blood was obtained for 164 subjects seen at an institutional molecular solid tumor board. All subjects had whole exome sequencing from Ashion Analytics and panel-based genotyping from an institutional pharmacogenomics laboratory. Aldy version 3.3 was operationalized on the LifeOmic Precision Health Cloud with copy number fixed to two copies per gene. Aldy results were compared with those from genotyping for 56 star allele-defining variants within CYP2B6, CYP2C8, CYP2C9, CYP2C19, CYP2D6, CYP3A4, CYP3A5, CYP4F2, DPYD, G6PD, NUDT15, SLCO1B1, and TPMT. Read depth was >100× for all variants except CYP3A4∗22. For 75 subjects in the validation cohort, all 3393 Aldy variant calls were concordant with genotyping. Aldy calls for 736 diplotypes containing alleles assessed by both platforms were also concordant. Aldy identified additional star alleles not covered by targeted genotyping for 139 diplotypes. Aldy accurately called variants and diplotypes for 13 major pharmacogenes, except for CYP2D6 variants involving copy number variations, thus allowing repurposing of whole exome sequencing to support clinical pharmacogenomics.
从分子肿瘤委员会获取种系全外显子组测序有可能被重新用于支持临床药物基因组学。然而，从外显子组测序数据中准确地识别与药物基因组学相关的基因型仍然具有挑战性。因此，本研究评估了计算工具 Aldy 在从 13 个主要药物基因组学基因的外显子组测序数据中识别与药物基因组学相关的基因型的分析有效性。从机构分子实体肿瘤委员会就诊的 164 名患者的全血中获得种系 DNA。所有患者均进行了 Ashion Analytics 的全外显子组测序和机构药物基因组学实验室的基于面板的基因分型。Aldy 版本 3.3 在 LifeOmic Precision Health Cloud 上运行，基因拷贝数固定为每个基因两份。将 Aldy 结果与 CYP2B6、CYP2C8、CYP2C9、CYP2C19、CYP2D6、CYP3A4、CYP3A5、CYP4F2、DPYD、G6PD、NUDT15、SLCO1B1 和 TPMT 中 56 个星等位基因定义变体的基因分型结果进行比较。除 CYP3A4∗22 外，所有变体的读取深度均>100×。在验证队列的 75 名受试者中，所有 3393 个 Aldy 变体均与基因分型一致。Aldy 还对包含两种平台评估的等位基因的 736 个二倍体型进行了一致的调用。对于 139 个二倍体型，Aldy 鉴定了其他未被靶向基因分型覆盖的星等位基因。Aldy 准确地识别了 13 个主要药物基因组学基因的变体和二倍体型，除了涉及拷贝数变异的 CYP2D6 变体外，从而允许重新使用全外显子组测序来支持临床药物基因组学。
