Volume 105, Issue 5 p. 1256-1262
Article

Standardized Biogeographic Grouping System for Annotating Populations in Pharmacogenetic Research

Rachel Huddart

Rachel Huddart

Department of Biomedical Data Science, Stanford University, Stanford, California, USA

These authors contributed equally to this work.Search for more papers by this author
Alison E. Fohner

Alison E. Fohner

Department of Biomedical Data Science, Stanford University, Stanford, California, USA

Department of Epidemiology, University of Washington, Seattle, Washington, USA

These authors contributed equally to this work.Search for more papers by this author
Michelle Whirl-Carrillo

Michelle Whirl-Carrillo

Department of Biomedical Data Science, Stanford University, Stanford, California, USA

These authors contributed equally to this work.Search for more papers by this author
Genevieve L. Wojcik

Genevieve L. Wojcik

Department of Biomedical Data Science, Stanford University, Stanford, California, USA

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Christopher R. Gignoux

Christopher R. Gignoux

Department of Biostatistics, Division of Bioinformatics and Personalized Medicine, University of Colorado, Aurora, Colorado, USA

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Alice B. Popejoy

Alice B. Popejoy

Department of Biomedical Data Science, Stanford University, Stanford, California, USA

Stanford Center for Integration of Research on Genetics and Ethics, Stanford, California, USA

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Carlos D. Bustamante

Carlos D. Bustamante

Department of Biomedical Data Science, Stanford University, Stanford, California, USA

Department of Genetics, Stanford University, Stanford, California, USA

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Russ B. Altman

Russ B. Altman

Department of Biomedical Data Science, Stanford University, Stanford, California, USA

Department of Genetics, Stanford University, Stanford, California, USA

Department of Biomedical Engineering, Stanford University, Stanford, California, USA

Department of Medicine, Stanford University, Stanford, California, USA

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Teri E. Klein

Corresponding Author

Teri E. Klein

Department of Biomedical Data Science, Stanford University, Stanford, California, USA

Department of Medicine, Stanford University, Stanford, California, USA

Shriram Center for BioE & ChemE, Stanford, California, USA

Correspondence: Teri E. Klein ([email protected])Search for more papers by this author
First published: 01 December 2018
Citations: 77

Abstract

The varying frequencies of pharmacogenetic alleles among populations have important implications for the impact of these alleles in different populations. Current population grouping methods to communicate these patterns are insufficient as they are inconsistent and fail to reflect the global distribution of genetic variability. To facilitate and standardize the reporting of variability in pharmacogenetic allele frequencies, we present seven geographically defined groups: American, Central/South Asian, East Asian, European, Near Eastern, Oceanian, and Sub-Saharan African, and two admixed groups: African American/Afro-Caribbean and Latino. These nine groups are defined by global autosomal genetic structure and based on data from large-scale sequencing initiatives. We recognize that broadly grouping global populations is an oversimplification of human diversity and does not capture complex social and cultural identity. However, these groups meet a key need in pharmacogenetics research by enabling consistent communication of the scale of variability in global allele frequencies and are now used by Pharmacogenomics Knowledgebase (PharmGKB).

Conflicts of Interest

C.R.G. owns stock in 23andMe and is a founder of and advisor to Encompass Bioscience. C.D.B. is a member of the scientific advisory boards for Liberty Biosecurity, Personalis, 23andMe, Roots into the Future, Ancestry.com, IdentifyGenomics, and Etalon and is a founder of CDB Consulting. R.B.A. is a stockholder in Personalis and 23andMe and a paid advisor for Youscript. The remaining authors have no conflicts of interest.