Addressing Ancestry Disparities in Genomic Medicine: A Geographic-aware Algorithm

Kavli Affiliate: Carlos Bustamante

| First 5 Authors: Daniel Mas Montserrat, Arvind Kumar, Carlos Bustamante, Alexander Ioannidis,

| Summary:

With declining sequencing costs a promising and affordable tool is emerging
in cancer diagnostics: genomics. By using association studies, genomic variants
that predispose patients to specific cancers can be identified, while by using
tumor genomics cancer types can be characterized for targeted treatment.
However, a severe disparity is rapidly emerging in this new area of precision
cancer diagnosis and treatment planning, one which separates a few genetically
well-characterized populations (predominantly European) from all other global
populations. Here we discuss the problem of population-specific genetic
associations, which is driving this disparity, and present a novel
solution–coordinate-based local ancestry–for helping to address it. We
demonstrate our boosting-based method on whole genome data from divergent
groups across Africa and in the process observe signals that may stem from the
transcontinental Bantu-expansion.

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