The Pitfalls of Genomic Data Diversity.

Abstract

Biomedical research recruitment today focuses on including participants representative of global genetic variation-rightfully so. But ethnographic attention to practices of inclusion highlights how this agenda often transforms into "predatory inclusion," simplistic pushes to get Black and brown people into genomic databases. As anthropologists of medicine, we argue that the question of how to get from diverse data to concrete benefit for people who are marginalized cannot be presumed to work itself out as a byproduct of diverse datasets. To actualize the equitable translation of genomics, practitioners need to place the impacts of ancestral genetic difference in the scope of much more impactful social determinants. For this to happen, multidisciplinary expertise needs to be leveraged, and current, structurally unequal health care systems ultimately need to transform. As modest steps toward this goal, new models for benefit-sharing must be developed and implemented to mitigate existing inequality between data donors and the entities profiting from that data.