Utilizing Polygenic Risk to Understand and Improve Outcomes: A Model For Overturning Health Disparities Through Minority-Enriched Genomics Healthcare

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ABSTRACT This eMERGE-4 program is focused on generating and validating polygenic risk scores (PRS) for multiple phenotypes using multiple available datasets across the eMERGE network, followed by a site-specific implementation of PRS in 2,500 prospectively recruited patients we perform at The Children’s Hospital of Philadelphia and University of Pennsylvania. To address health disparities and underrepresentation of African Americans in genomic research, 75% (1,875) of participants will be of African ancestry. With capacity to pursue many others, we propose five principal phenotypes: asthma, diabetes (T1D/T2D); autoimmune disease, Crohn’s disease (CD); and hyperlipidemia with focus on coronary artery disease. Sensitivity, specificity, and clinical efficacy/impact with respect to improved healthcare delivery will be measured. We will work with eMERGE partners to develop a customized array that address inequities in traditional approaches, in particular, lack of PRS data in minorities. We will establish an enriched recruitment, engagement, and retention protocol that will include targeted recruitment, enhanced communication with participants and health care professionals, boosted analysis and EHR integration, and a dynamic education program focusing on AAs with an aim to decrease disparities in health by recruitment of minorities and improved health outcomes. The education program will be informed by an empirical collaboration with Boston Children’s Hospital, where we will examine ethical, legal, and social implications (ELSI) of return of genomic risk estimates, specifically differences in risk perception and willingness to participate in risk reduction recommendations based on how risk is framed, disease severity, age of onset, and actionability. Results will inform return of genomic risk estimates to all 2,500 participants, and assess healthcare outcomes across the key disease areas proposed. We will work with the consortium to delineate best practices for returning genomic risk estimates and create an innovative return of results protocol. Finally, we will integrate PRS and genomic risk estimates with patients’ electronic health records by leveraging Care Assistant, an innovative clinical decision support (CDS) framework developed at CHOP. We will create CDS integrated with the CHOP EHR and provider education in MyResults. In a cluster-randomized design using our primary-care research network, we will test the hypothesis that implementation of CDS will increase the uptake of risk reduction recommendations by both patients and providers compared to current EHR integration (EHRI).