Multiple measures for self-identification improve matching donors with patients in unrelated hematopoietic stem cell transplant

Background: Questions persist around whether and how to use race or geographic ancestry in biomedical research and medicine, but these forms of self-identification serve as a critical tool to inform matching algorithms for human leukocyte antigen (HLA) of varying levels of resolution for unrelated hematopoietic stem cell transplant in large donor registries. Methods: Here, we examined multiple self-reported measures of race and ancestry from a survey of a cohort of over 100,000 U.S. volunteer bone marrow donors alongside their high-resolution HLA genotype data. Results: We find that these self-report measures are often non-overlapping, and that no single self-reported measure alone provides a better fit to HLA genetic ancestry than a combination including both race and geographic ancestry. We also found that patterns of reporting for race and ancestry appear to be influenced by participation in direct-to-consumer genetic ancestry testing. Conclusions: While these data are not used directly in matching for transplant, our results demonstrate that there is a place for the language of both race and geographic ancestry in the critical process of facilitating accurate prediction of HLA in the donor registry context.