Polygenic Risk Score Diversity Consortium Coordinating Center

项目总结 流行病学研究中大规模基因组数据分析的多基因风险评分(PR) 作为一种精准医学工具，将有助于识别疾病风险较高的个人。然而，a 目前PR研究和临床翻译面临的关键挑战是，大多数PR已经开发出来 使用主要来自欧洲裔个人的数据，导致预测性能较差 非欧洲人群，反映出基因组和生物医学研究缺乏多样性 大体上说。NHGRI正在建立一个新的多基因风险评分多样性联盟，以通过以下方式应对这一挑战 (1)利用现有的不同队列来改进对不同的非欧洲人群的预测 以及(2)优化大规模基因组和表型数据集的集成 支持协作分析、报告以及为更广泛的科学领域创建方法和资源 社区。作为协调中心，我们将通过实现四个主要目标来支持财团的目标：(1) 领导协调联盟研究站点和附属成员的基因型和表型数据， 包括变异和样本水平的质量控制、基因分配和标准表型的使用 本体论。(2)组织跨联盟分析和协同方法开发，以 标准化评价方法以确定协商一致的方法，发展当地血统 知情的PRS方法，并将ELSI考虑因素纳入分析最佳实践。(3)数据便利化 通过社区资源和存储库(如NHGRI)在联盟内部和外部共享 基因组数据科学分析、可视化和信息学实验室空间(ANVIL)，NCBI数据库 基因类型和表型(DBGaP)和多基因SCORE目录。(4)协调项目物流和 外联活动，包括通过联合会网站、面对面会议、指导和培训以及定期 参与精准医疗合作伙伴计划。我们提出了创新的方法来实现这些目标 四个主要目标，包括利用新兴的基于云的平台进行协调、分析和共享 大规模基因组数据；研究表型协调的可扩展数据科学方法； 领导一场全联盟范围内的“烘焙活动”，以建立共识的方法来生成和评估方案； 并将伦理、法律和社会影响纳入分析最佳实践。此外，我们的 申请基于13年的成功经验和专业知识，作为五年的协调中心 大规模的遗传和生物医学项目。通过科学的和行政的领导 我们将帮助实现发展可预测和帮助预防疾病的方案的公共卫生益处 减轻遗传多样性人群中的一系列疾病。

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.