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Inconsistency in race and ethnic classification in pharmacogenetics studies and its potential clinical implications

Authors Zhang F, Finkelstein J

Received 3 March 2019

Accepted for publication 30 May 2019

Published 2 July 2019 Volume 2019:12 Pages 107—123

DOI https://doi.org/10.2147/PGPM.S207449

Checked for plagiarism Yes

Review by Single-blind

Peer reviewers approved by Dr Cristina Weinberg

Peer reviewer comments 2

Editor who approved publication: Dr Martin H. Bluth


Frederick Zhang,1 Joseph Finkelstein2

1Center for Bioinformatics and Data Analytics, Columbia University Irving Medical Center, New York, NY, USA; 2Department of Population Health Science and Policy, Icahn School of Medicine at Mount Sinai, New York, NY, USA

Introduction: Racial and ethnic categories are frequently used in pharmacogenetics literature to stratify patients; however, these categories can be inconsistent across different studies. To address the ongoing debate on the applicability of traditional concepts of race and ethnicity in the context of precision medicine, we aimed to review the application of current racial and ethnic categories in pharmacogenetics and its potential impact on clinical care.
Methods: One hundred and three total pharmacogenetics papers involving the CYP2C9, CYP2C19, and CYP2D6 genes were analyzed for their country of origin, racial, and ethnic categories used, and allele frequency data. Correspondence between the major continental racial categories promulgated by National Institutes of Health (NIH) and those reported by the pharmacogenetics papers was evaluated.
Results: The racial and ethnic categories used in the papers we analyzed were highly heterogeneous. In total, we found 66 different racial and ethnic categories used which fall under the NIH race category “White”, 47 different racial and ethnic categories for “Asian”, and 62 different categories for “Black”. The number of categories used varied widely based on country of origin: Japan used the highest number of different categories for “White” with 17, Malaysia used the highest number for “Asian” with 24, and the US used the highest number for “Black” with 28. Significant variation in allele frequency between different ethnic subgroups was identified within 3 major continental racial categories.
Conclusion: Our analysis showed that racial and ethnic classification is highly inconsistent across different papers as well as between different countries. Evidence-based consensus is necessary for optimal use of self-identified race as well as geographical ancestry in pharmacogenetics. Common taxonomy of geographical ancestry which reflects specifics of particular countries and is accepted by the entire scientific community can facilitate reproducible pharmacogenetic research and clinical implementation of its results.

Keywords: pharmacogenetics, single nucleotide polymorphism, ethnic differences, drug responsiveness

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