Using Population Descriptors in Genetics and Genomics Research

Genetic and genomic information has become far more accessible, and research using human genetic data has grown exponentially over the past decade. The use of genetic information is now widespread across biomedical research. Genetics and genomics research is conducted by a wide range of investigators across disciplines, who often use population descriptors inconsistently and/or inappropriately to capture the complex patterns of continuous human genetic variation. Because there is a misconception that humans can be grouped into discrete, innate categories, researchers can inappropriately rely on descent-associated population descriptors such as race to describe population genetic differences. Therefore, there is a need to create clear guidance about the use of population descriptors as well as an opportunity to implement substantive changes to the ways they are used.

There is a long history of prior attempts to address population descriptors, and this may create some skepticism about the usefulness of another report aiming to create best practices for this complex area, however, there are several reasons that this is a particularly opportune and important moment to offer concrete guidance to the research community.

• The growth in research using human genetic data has occurred in part by major investments in large-scale studies, many of which have genomic sequence data of a more diverse set of populations, raising more questions about how best to represent their diversity in the study data. Clear guidance about the use of population descriptors is therefore urgently needed before the mistakes of the past are baked into this new era of genetics research.
• There has been development of more advanced methods of understanding and describing population structure and variation. These advances have not been accompanied, however, by new approaches to the use of population descriptors in genetics and genomics research with an implementation and accountability plan.

The report aims to emphasize that scientists must get the descent-associated concepts right—that is, have a clear understanding of what these descriptors represent and a rigorous rationale for using them—before selecting the appropriate group categories and labels to work with.

Since 2020, the U.S. scientific community has become more attentive to the urgency of addressing racism and the lack of diversity in science as well as the admission that little progress has been made in making science accessible and relevant to a more diverse citizenry (Yudell et al., 2020). Research universities embarked on efforts to address diversity, equity, and inclusion in their scientific and educational programs. The social construct of race, the role of intersectionality, and the fundamental effect of racism on all aspects of science and medicine have become parts of faculty trainings at many institutions (Dupree and Boykin, 2021; Holdren et al., 2022; Kossek et al., 2022). Journal editors recognized the problems of using racial labels in research studies, with growing calls for eliminating the use of high-risk proxy measures (Flanagin et al., 2021; Nature Human Behavior, 2022). The call to remove race from clinical prediction models spread rapidly because of the attention to the danger of false assumptions about innate racial differences and resulting harms to patients (Vyas et al., 2020). Recognition by the U.S. biomedical research community of the need to address the complex and important issue of population descriptors in genetics research has never been greater.

In response to the timeliness of the study and the statement of task, the committee developed a framework to explore the use of population descriptors in genetics and genomics research (see Guiding Principles). Learn more about the report.