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

Abstract

Abstract 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.