Recommendations on the use and reporting of race, ethnicity, and ancestry in genetic research: experiences from the NHLBI Trans-Omics for Precision Medicine (TOPMed) program
Alyna T. Khan, Stephanie M. Gogarten, Caitlin P. McHugh, Adrienne M., Stilp, Tamar Sofer, Michael Bowers, Quenna Wong, L. Adrienne Cupples, Bertha, Hidalgo, Andrew D. Johnson, Merry-Lynn McDonald, Stephen T. McGarvey, Matthew, R. G. Taylor, Stephanie M. Fullerton

TL;DR
This paper provides recommendations for the use and reporting of race, ethnicity, and ancestry in human genomics research to promote equity, accuracy, and social responsibility, based on experiences from the TOPMed program.
Contribution
It offers concrete guidelines for terminology, data harmonization, analysis, and reporting to improve diversity and reduce racial biases in genetic research.
Findings
Recommendations applicable across diverse genomic research contexts.
Highlighting the importance of structural changes in research practices.
Emphasizing ongoing reflection to address racism in genetics.
Abstract
The ways in which race, ethnicity, and ancestry are used and reported in human genomics research has wide-ranging implications for how research is translated into clinical care, incorporated into public understanding, and implemented in public policy. Genetics researchers play an essential role in proactively dismantling genetic conceptions of race and in recognizing the social and structural factors that drive health disparities. Here, we offer commentary and concrete recommendations on the use and reporting of race, ethnicity, and ancestry across the arc of genetic research, including terminology, data harmonization, analysis, and reporting. While informed by our experiences as researchers in the NHLBI Trans-Omics for Precision Medicine (TOPMed) program, the recommendations are broadly applicable to basic and translational genomic research in diverse populations. To fully realize the…
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Taxonomy
TopicsRace, Genetics, and Society · BRCA gene mutations in cancer · Genetic Associations and Epidemiology
