Challenges and Considerations of Using Race, Ethnicity, and Ancestry (REA) Labels in Genomics Research

Oregon Convention Center 

Rapid advances in genetic technology have led to increased accessibility of large genomic databases. This information is often combined with electronic health records and participant survey data, which are then analyzed together to improve our understanding of disease etiology. These databases consist of thousands of participants from large biobanks or cohorts where individuals are categorized using race and/or ethnicity labels. Race and ethnicity are socially constructed population labels that can be paired with inferred genetic ancestry for analyses; however, the misuse of these population descriptors can be problematic in understanding the role of human genetics in disease. Moreover, the significant lack of diversity in genomic studies is concerning, as populations that are underrepresented are often the same ones currently underserved in the U.S. Therefore, it is important to carefully consider the use of race, ethnicity, and ancestry labels and how they impact the accuracy of genomics analyses - our goal is to emphasize the challenges and ethical considerations of using these labels in genomics research.