Analytical Validation of a Computational Method for Pharmacogenetic Genotyping from Clinical Whole Exome Sequencing

dc.contributor.authorLy, Reynold C.
dc.contributor.authorShugg, Tyler
dc.contributor.authorRatcliff, Ryan
dc.contributor.authorOsei, Wilberforce
dc.contributor.authorLynnes, Ty C.
dc.contributor.authorPratt, Victoria M.
dc.contributor.authorSchneider, Bryan P.
dc.contributor.authorRadovich, Milan
dc.contributor.authorBray, Steven M.
dc.contributor.authorSalisbury, Benjamin A.
dc.contributor.authorParikh, Baiju
dc.contributor.authorSahinalp, S. Cenk
dc.contributor.authorNumanagić, Ibrahim
dc.contributor.authorSkaar, Todd C.
dc.contributor.departmentMedicine, School of Medicine
dc.date.accessioned2024-01-17T14:03:17Z
dc.date.available2024-01-17T14:03:17Z
dc.date.issued2022
dc.description.abstractGermline 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.
dc.eprint.versionFinal published version
dc.identifier.citationLy RC, Shugg T, Ratcliff R, et al. Analytical Validation of a Computational Method for Pharmacogenetic Genotyping from Clinical Whole Exome Sequencing. J Mol Diagn. 2022;24(6):576-585. doi:10.1016/j.jmoldx.2022.03.008
dc.identifier.urihttps://hdl.handle.net/1805/38044
dc.language.isoen_US
dc.publisherElsevier
dc.relation.isversionof10.1016/j.jmoldx.2022.03.008
dc.relation.journalThe Journal of Molecular Diagnostics
dc.rightsPublisher Policy
dc.sourcePMC
dc.subjectCytochrome P-450 CYP2D6
dc.subjectDNA Copy Number Variations
dc.subjectHigh-Throughput Nucleotide Sequencing
dc.subjectLiver-Specific Organic Anion Transporter 1
dc.titleAnalytical Validation of a Computational Method for Pharmacogenetic Genotyping from Clinical Whole Exome Sequencing
dc.typeArticle
ul.alternative.fulltexthttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC9227988/
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