Purpose: Advances in genomic research have facilitated rare disease diagnosis for thousands of individuals. Unfortunately, the benefits of advanced genetic diagnostic technology are not distributed equitably among the population, as has been seen in many other health care contexts. Quantifying and describing inequities in genetic diagnostic yield is inherently challenging due to barriers to both clinical and research genetic testing. We therefore present an implementation protocol developed to expand access to our rare disease genomic research study and to further understand existing inequities.
Methods and findings: The Rare Genomes Project (RGP) at the Broad Institute of MIT and Harvard offers research genome sequencing to individuals with rare disease who remain genetically undiagnosed through direct interaction with the individual or family. This presents an opportunity for diagnosis beyond the clinical context, thus eliminating many barriers to access. An initial goal of RGP was to equalize access to genomic sequencing by decoupling testing access from proximity to a major medical center and physician referral. However, study participants over the initial 3 years of this project were predominantly white and well resourced. To further understand and address the lack of diversity within RGP, we developed a novel protocol embedded within the larger RGP study, in an approach informed by an implementation science framework. The aims of this protocol were: (1) to diversify recruitment and enrollment within RGP; (2) understand the process and context of implementing genomic medicine for rare disease diagnosis; and (3) investigate the value of a diagnosis for underserved populations.
Implications: Improved understanding of existing inequities and potential strategies to address them are needed to advance equity in rare disease genetic diagnosis and research. In addition to the moral imperative of equity in genomic medicine, this approach is critical in order to fully understand the genomic underpinnings of rare disease.
Keywords: Disparities; Genetics; Genomics; Implementation; Inequities; Rare disease.
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