Research to understand human genomic variation and its implications in health has great potential to contribute in the reduction of health disparities. Biological anthropology can play important roles in genomics and health disparities research using a biocultural approach. This paper argues that racial/ethnic categories should not be used as a surrogate for sociocultural factors or global genomic clusters in biomedical research or clinical settings, because of the high genetic heterogeneity that exists within traditional racial/ethnic groups. Genetic ancestry is used to show variation in ancestral genomic contributions to recently admixed populations in the United States, such as African Americans and Hispanic/Latino Americans. Genetic ancestry estimates are also used to examine the relationship between ancestry-related biological and sociocultural factors affecting health disparities. To localize areas of genomes that contribute to health disparities, admixture mapping and genome-wide association studies (GWAS) are often used. Recent GWAS have identified many genetic variants that are highly differentiated among human populations that are associated with disease risk. Some of these are population-specific variants. Many of these variants may impact disease risk and help explain a portion of the difference in disease burden among racial/ethnic groups. Genetic ancestry is also of particular interest in precision medicine and disparities in drug efficacy and outcomes. By using genetic ancestry, we can learn about potential biological differences that may contribute to the heterogeneity observed across self-reported racial groups.genetic ancestry, health disparities, precision medicine | INTRODUCTIONRace is a sociocultural concept, and genetic and biological evidence does not support racial classification for human populations. When race and ethnicity is used in biomedical research, it is often self-reported and used as a proxy for measurable indicators of group differences, such as socioeconomic status, cultural and behavioral lifestyle, and biology. Reducing each of these contributors into a composite called "race" precludes independent analysis of important factors, such as genetics and the physical and social environments, which vary significantly within populations.Human genetic variation is structured by the evolutionary history of our species. The pattern of this population structure, however, is not bounded or discrete, but continuous, resulting from the demographic history of populations which includes such forces as natural and social "mate" selection, genetic drift, gene flow and mutations

Background: Given the scarcity of cell lines from underrepresented populations, it is imperative that genetic ancestry for these cell lines is characterized. Consequences of cell line mischaracterization include squandered resources and publication retractions. Methods: We calculated genetic ancestry proportions for 15 cell lines to assess the accuracy of previous race/ethnicity classification and determine previously unknown estimates. DNA was extracted from cell lines and genotyped for ancestry informative markers representing West African (WA), Native American (NA), and European (EUR) ancestry. Results: Of the cell lines tested, all previously classified as White/Caucasian were accurately described with mean EUR ancestry proportions of 97%. Cell lines previously classified as Black/African American were not always accurately described. For instance, the 22Rv1 prostate cancer cell line was recently found to carry mixed genetic ancestry using a much smaller panel of markers. However, our more comprehensive analysis determined the 22Rv1 cell line carries 99% EUR ancestry. Most notably, the E006AA-hT prostate cancer cell line, classified as African American, was found to carry 92% EUR ancestry. We also determined the MDA-MB-468 breast cancer cell line carries 23% NA ancestry, suggesting possible Afro-Hispanic/ Latina ancestry. Conclusions: Our results suggest predominantly EUR ancestry for the White/Caucasian-designated cell lines, yet high variance in ancestry for the Black/African Americandesignated cell lines. In addition, we revealed an extreme misclassification of the E006AA-hT cell line. Impact: Genetic ancestry estimates offer more sophisticated characterization leading to better contextualization of findings. Ancestry estimates should be provided for all cell lines to avoid erroneous conclusions in disparities literature.