Pharmacogenetics and pharmacogenomics (PGx) investigate the genetic influence on drug response (gene-drug and genome-drug interactions, respectively). Clinical implementation of PGx has been made possible — given extensive expert-led reviews and curations of PGx discoveries [e.g., by the Pharmacogenomics Knowledgebase (PharmGKB), the Pharmacogene Variation Consortium (PharmVar), the Clinical Pharmacogenetics Implementation Consortium (CPIC), and the Dutch Pharmacogenetics Working Group (DPWG)]. Awareness of the clinical use of PGx is also evident in the increasing coverage of clinical PGx testing in hospitals and clinics, including PGx panel testing by medical insurance programs, such as Medicare and Medicaid. Moreover, studies have also suggested the wide prevalence of PGx variants (>90% of studied individuals possessing PGx variants) and consequential clinical recommended treatments in various cohorts.
If PGx becomes actively implemented in routine clinical care on a global scale, it would be increasingly important to ensure the sharing of worldwide data for diverse PGx haplotypes and diplotypes for robust clinical decision support. Various studies have estimated the frequencies of PGx alleles, diplotypes, and phenotypes in different ethnic populations. Due to scarcity of resources, however — some studies have suffered from limited sample size, some focused on a finite subset of PGx alleles, some restricted themselves to a specific subpopulation, and some investigated only PGx variants rather than the PGx haplotypes/diplotypes which translate to guideline-based drug-prescribing recommendations. Meanwhile, the rise of genetic biobanks across the globe provides the opportunity to understand PGx frequencies in a variety of global populations.
PGx should be considered as an integral part of precision medicine — contributing to the maximization of drug efficacy and plans to reduce adverse drug event risk. Accurate information on PGx allele frequencies would therefore improve the implementation of PGx. Nonetheless, curating such information from published allele data is both time- and resource-intensive; the limited number of allelic variants in most studies leads to an underestimation of certain alleles.
Authors [see attached pdf file] applied the Pharmacogenomics Clinical Annotation Tool (PharmCAT) on an integrated 200,044 UK Biobank genetic dataset. Based on PharmCAT results, authors estimated PGx frequencies (alleles, diplotypes, phenotypes, and activity scores) for 17 pharmacogenes in five biogeographic groups: European, Central/South Asian, East Asian, Afro-Caribbean, and Sub-Saharan African. PGx frequencies were distinct for each biogeographic group. Even biogeographic groups with similar proportions of phenotypes were driven by different sets of dominant PGx alleles. PharmCAT also identified ‘‘no-function’’ alleles that were rare or seldom tested in certain groups by previous studies [e.g., SLCO1B1*31 in the Afro-Caribbean (3.0%) and Sub-Saharan African (3.9%) groups].
Estimated PGx frequencies are disseminated via the PharmGKB (The Pharmacogenomics KnowledgeBase: www.pharmgkb.org). Authors showed that genetic biobanks such as the UK Biobank are a robust resource for estimating PGx frequencies. Improving our understanding of PGx allele and phenotype frequencies should provide guidance for future PGx studies and clinical genetic test panel design — to better serve individuals from wider biogeographic backgrounds. 😊
Am J Hum Genet 5 Oct 2023; 110: 1628–1647