The global spectrum of protein-coding pharmacogenomic diversity

• Published in: The pharmacogenomics journal Vol. 18; no. 1; pp. 187 - 195
• Main Authors: Wright, G E B, Carleton, B, Hayden, M R, Ross, C J D
• Format: Journal Article
• Language: English
• Published: London Nature Publishing Group UK 01.01.2018; Nature Publishing Group
• Subjects: 631/114/2413; Alleles; Annotations; Biomedical and Life Sciences; Biomedicine; Ethnicity - genetics; Gene Expression; Gene frequency; Gene Frequency - genetics; Genetic diversity; Genetic variance; Genetic variation; Genetic Variation - genetics; Genetics, Population - methods; Genomes; Genomics; Human Genetics; Humans; Oncology; Original; original-article; Pharmaceutical sciences; Pharmacogenetics - methods; Pharmacogenomics; Pharmacotherapy; Physiological aspects; Population; Principal components analysis; Proteins; Proteins - genetics; Psychopharmacology; Support vector machines; Canada
• ISSN: 1470-269X; 1473-1150
• DOI: 10.1038/tpj.2016.77

Differences in response to medications have a strong genetic component. By leveraging publically available data, the spectrum of such genomic variation can be investigated extensively. Pharmacogenomic variation was extracted from the 1000 Genomes Project Phase 3 data (2504 individuals, 26 global populations). A total of 12 084 genetic variants were found in 120 pharmacogenes, with the majority (90.0%) classified as rare variants (global minor allele frequency <0.5%), with 52.9% being singletons. Common variation clustered individuals into continental super-populations and 23 pharmacogenes contained highly differentiated variants ( F ST >0.5) for one or more super-population comparison. A median of three clinical variants (PharmGKB level 1A/B) was found per individual, and 55.4% of individuals carried loss-of-function variants, varying by super-population (East Asian 60.9%>African 60.1%>South Asian 60.3%>European 49.3%>Admixed 39.2%). Genome sequencing can therefore identify clinical pharmacogenomic variation, and future studies need to consider rare variation to understand the spectrum of genetic diversity contributing to drug response.