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

摘要 该Emerge-4计划专注于生成和验证多基因风险评分(PR) 使用Emerge网络中的多个可用数据集的表型，然后是特定于站点的 我们在儿童医院进行的2500名前瞻性招募患者中实施了PRS 费城和宾夕法尼亚大学。解决健康差距和非洲人代表性不足的问题 在基因组研究方面，75%(1875)的参与者将是非洲血统。有能力追求 我们提出了五种主要的表型：哮喘、糖尿病(T1D/T2D)、自身免疫性疾病、克罗恩病 疾病(CD)；和高脂血症，重点是冠状动脉疾病。敏感性、特异性和临床 将衡量与改善医疗保健提供有关的效力/影响。我们将与Emerge合作 合作伙伴开发定制的阵列，以解决传统方法中的不平等问题，特别是缺乏 少数民族的社区卫生服务数据。我们将建立一个丰富的招聘、参与和保留协议，以 包括有针对性招聘，加强与参与者和保健专业人员的沟通， 分析和EHR整合，以及侧重于AA的动态教育方案，目的是减少 由于招募少数群体而造成的健康差距和健康结果的改善。教育计划将是 由与波士顿儿童医院的经验合作提供信息，在那里我们将检查伦理、法律和 基因组风险估计结果的社会影响(ELSI)，特别是风险感知和风险估计的差异 是否愿意参与基于风险构成、疾病严重程度、年龄等因素的风险降低建议 起诉性和可操作性。结果将向所有2,500名参与者通报基因组风险估计的回报，以及 评估建议的关键疾病领域的医疗保健结果。我们将与财团合作， 描述返回基因组风险估计的最佳实践，并创建创新的结果返回协议。 最后，我们将通过杠杆将PR和基因组风险估计与患者的电子健康记录相结合 CARE Assistant是CHOP开发的一个创新的临床决策支持(CDS)框架。我们将创造 CDS集成了CHOP EHR和MyResults中的提供者培训。在集群随机化设计中，使用 我们的初级保健研究网络，我们将检验CDS的实施将增加 与当前的EHR集成相比，患者和提供者对降低风险建议的接受程度 (Ehri)。

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).