| Title: | Frequencies of pharmacogenomic alleles across biogeographic groups in a large-scale biobank |
| Journal: | American Journal of Human Genetics |
| Published: | 26 Sep 2023 |
| Pubmed: | https://pubmed.ncbi.nlm.nih.gov/37757824/ |
| DOI: | https://doi.org/10.1016/j.ajhg.2023.09.001 |
Publication 9470
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Abstract
Pharmacogenomics (PGx) is an integral part of precision medicine and contributes to the maximization of drug efficacy and reduction of adverse drug event risk. Accurate information on PGx allele frequencies improves the implementation of PGx. Nonetheless, curating such information from published allele data is time and resource intensive. The limited number of allelic variants in most studies leads to an underestimation of certain alleles. We applied the Pharmacogenomics Clinical Annotation Tool (PharmCAT) on an integrated 200K UK Biobank genetic dataset (N = 200,044). Based on PharmCAT results, we 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). We demonstrate 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 provides guidance for future PGx studies and clinical genetic test panel design, and better serves individuals from wider biogeographic backgrounds.</p>
8 Authors
- Binglan Li
- Katrin Sangkuhl
- Ryan Whaley
- Mark Woon
- Karl Keat
- Michelle Whirl-Carrillo
- Marylyn D Ritchie
- Teri E Klein
1 Application
| Application ID | Title |
|---|---|
| 33722 | Identifying precision drug treatments by linking phenotype and genotype in drug response |
Enabling scientific discoveries that improve human health