Polygenic Risk Score Diversity Consortium Coordinating Center

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PROJECT SUMMARY Polygenic Risk Scores (PRS) developed from analysis of large-scale genomic data in epidemiological studies hold promise as a precision medicine tool that will help identify individuals at higher disease risk. However, a critical challenge now facing PRS research and clinical translation is that most PRS have been developed using data from predominantly European-descent individuals, resulting in poorer predictive performance in non-European populations and reflecting the lack of diversity in genomic and biomedical research more broadly. NHGRI is establishing a new Polygenic Risk Score Diversity Consortium to address this challenge by (1) leveraging existing diverse cohorts to improve PRS prediction across diverse, non-European populations and for a range of conditions and (2) optimizing the integration of large-scale genomic and phenotype datasets in support of collaborative analysis, reporting, and creation of methods and resources for the broader scientific community. As Coordinating Center, we will support the Consortium's goals by achieving four main aims: (1) leading harmonization of genotype and phenotype data across Consortium Study Sites and Affiliate Members, including variant and sample level quality control, genotype imputation, and use of standard phenotype ontologies. (2) Organizing cross-Consortium analysis and collaborative methods development, featuring standardized evaluation of PRS methods to identify consensus approaches, development of a local-ancestry informed PRS method, and integration of ELSI considerations into analytic best-practices. (3) Facilitating data sharing within and beyond the Consortium through community resources and repositories such as the NHGRI Genomic Data Science Analysis, Visualization, and Informatics Lab-space (AnVIL), NCBI database of Genotypes and Phenotypes (dbGaP), and the Polygenic Score Catalog. (4) Coordinating program logistics and outreach including through a Consortium website, in-person meetings, mentorship and training, and regular engagement with precision medicine partner programs. We propose innovative approaches to achieve these four main aims, including leveraging emerging cloud-based platforms for harmonization, analysis, and sharing of large-scale genomic data; investigating scalable data science approaches to phenotype harmonization; leading a Consortium-wide “bake-off” to establish consensus approaches to PRS generation and evaluation; and incorporating Ethical, Legal, and Social Implications into analytic best practices. Furthermore, our application rests on 13 successful years of experience and expertise serving as Coordinating Centers for five large-scale genetic and biomedical projects. Through scientific and administrative leadership of this Consortium, we will help realize the public health benefit of developing PRS that predict and help prevent or mitigate a range of diseases in genetically diverse populations.