Exome-Wide Analysis of the DiscovEHR Cohort Reveals Novel Candidate Pharmacogenomic Variants for Clinical Pharmacogenomics

Mining local exome and HLA data to characterize pharmacogenetic variants in Saudi Arabia

Pharmacogenomics (PGx) is a promising field of precision medicine where efficacy of drugs is maximized while side effects are minimized for individual patients. Knowledge of the frequency of PGx-relevant variants (pharmacovariants) in the local population is a pre-requisite to informed policy making. Unfortunately, such knowledge is largely lacking from the Middle East. Here, we describe the use of a large clinical exome database (n = 13,473) and HLA haplotypes (n = 64,737) from Saudi Arabia, one of the largest countries in the Middle East, along with previously published data from the local population to ascertain allele frequencies of known pharmacovariants. In addition, we queried another exome database (n = 816) of well-phenotyped research subjects from Saudi Arabia to discover novel candidate variants in known PGx genes (pharmacogenes). Although our results show that only 26% (63/242) of class 1A/1B PharmGKB variants were identified, we estimate that 99.57% of the local population have at least one such variant. This translates to a minimum estimated impact of 9% of medications dispensed by our medical center annually. We also highlight the contribution of rare variants where 71% of the pharmacogenes devoid of common pharmacovariants had at least one potentially deleterious rare variant. Thus, we show that approaches that go beyond the use of commercial PGx kits that have been optimized for other populations should be implemented to ensure universal and equitable access of all members of the local population to personalized prescription practices.

The need to shift pharmacogenetic research from candidate gene to genome-wide association studies

The primary research approach in pharmacogenetics has been candidate gene association studies (CGAS), but pharmacogenomic genome-wide association studies (GWAS) are becoming more common. We are now at a critical juncture when the results of those two research approaches, CGAS and GWAS, can be compared in pharmacogenetics. We analyzed publicly available databases of pharmacogenetic CGAS and GWAS (i.e., the Pharmacogenomics Knowledgebase [PharmGKB^®] and the NHGRI-EBI GWAS catalog) and the vast majority of variants (98%) and genes (94%) discovered in pharmacogenomic GWAS were novel (i.e., not previously studied CGAS). Therefore, pharmacogenetic researchers are not selecting the right candidate genes in the vast majority of CGAS, highlighting a need to shift pharmacogenetic research efforts from CGAS to GWAS.

PharmaKU: A Web-Based Tool Aimed at Improving Outreach and Clinical Utility of Pharmacogenomics

With the tremendous advancements in genome sequencing technology in the field of pharmacogenomics, data have to be made accessible to be more efficiently utilized by broader clinical disciplines. Physicians who require the drug–genome interactome information, have been challenged by the complicated pharmacogenomic star-based classification system. We present here an end-to-end web-based pharmacogenomics tool, PharmaKU, which has a comprehensive easy-to-use interface. PharmaKU can help to overcome several hurdles posed by previous pharmacogenomics tools, including input in hg38 format only, while hg19/GRCh37 is now the most popular reference genome assembly among clinicians and geneticists, as well as the lack of clinical recommendations and other pertinent dosage-related information. This tool extracts genetic variants from nine well-annotated pharmacogenes (for which diplotype to phenotype information is available) from whole genome variant files and uses Stargazer software to assign diplotypes and apply prescribing recommendations from pharmacogenomic resources. The tool is wrapped with a user-friendly web interface, which allows for choosing hg19 or hg38 as the reference genome version and reports results as a comprehensive PDF document. PharmaKU is anticipated to enable bench to bedside implementation of pharmacogenomics knowledge by bringing precision medicine closer to a clinical reality.

Potential of whole-genome sequencing-based pharmacogenetic profiling

Pharmacogenetics represents a major driver of precision medicine, promising individualized drug selection and dosing. Traditionally, pharmacogenetic profiling has been performed using targeted genotyping that focuses on common/known variants. Recently, whole-genome sequencing (WGS) is emerging as a more comprehensive short-read next-generation sequencing approach, enabling both gene diagnostics and pharmacogenetic profiling, including rare/novel variants, in a single assay. Using the example of the pharmacogene CYP2D6, we demonstrate the potential of WGS-based pharmacogenetic profiling as well as emphasize the limitations of short-read next-generation sequencing. In the near future, we envision a shift toward long-read sequencing as the predominant method for gene diagnostics and pharmacogenetic profiling, providing unprecedented data quality and improving patient care.