Extremely low-coverage whole genome sequencing (XLC-WGS) as a cost-effective tool for pharmacogenomic profiling: Advantages and Challenges

Despite more than 10 years have passed since the first FDA labeling for pharmacogenomics (PGx), factors like the continuous updates on PGx related SNVs and the high cost for PGx testing have challenged its clinical implementation. However, next generation sequencing technologies like extremely low coverage whole genome sequencing (XLC-WGS) could overcome these difficulties. Our purpose is to explore the potential use of XLC-WGS as a cost-effective way for generate reliable PGx profiles that can be applied in preemptive and clinical scenarios. We sequenced 195 patients enrolled to the Utah Diabetes and Diabetic Complications Study using XLC-WGS, for further PGx Profiles generation. Additionally, we sequenced a subset of 190 individuals using Illumina CoreExome-24 v1.3 microarray and 50 individuals using Deep Coverage Whole Genome Sequencing (DC-WGS) for cross-platform comparisons. We built the Pharmacogenomic profiles extracting the genetic information from XLC-WGS in accordance to the extended manifest of the commercially available PGx microarray PharmacoScan. Once the PGx profiles were generated we perform a preemptive analysis using the Clinical Pharmacogenetics Implementation Consortium (CPIC®) Gene-Drugs interaction with “A” level. The cross-platform comparison revealed that genetic concordance between XLC-WGS, DC-WGS and Microarray platforms ranged from 98.25% to 99.7%. The preemptive PGx profiles identified patients at risk of potential adverse effects for intake of commonly prescribed medications, including 4 homozygote carriers of rs4149056 (in SLCO1B1) which has previously been associated with statin-related myopathy. As well as 25 homozygote carriers of rs9923231 (in VKORC1) that increased risk of Hemorrhage when starting Warfarin intake without dose adjustment/reduction.