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

Abstract

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. 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. 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. 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. Self-identification with respect to race and ancestry is an important component in the process of finding a matching unrelated bone marrow donor for a patient in large donor registries. Here, we considered whether terms specific to either race or the geographic ancestry of donors would be more useful in the matching process. We found that rather than using either of these terms alone, collecting responses for both race and geographic ancestry from potential donors is most likely to provide the information necessary to find a genetic match among millions of donors for a patient in need of a transplant. Damotte et al. examine the utility of multiple measures of race and ancestry self-identification in the context of matching HLA for potential unrelated bone marrow donors with patients. They show that combining both race and geographic ancestry provides a better fit to HLA than either measure alone.