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Improving reporting standards for polygenic scores in risk prediction studies
medRxiv - Genetic and Genomic Medicine Pub Date : 2020-11-24 , DOI: 10.1101/2020.04.23.20077099
Hannah Wand , Samuel A. Lambert , Cecelia Tamburro , Michael A. Iacocca , Jack W. O’Sullivan , Catherine Sillari , Iftikhar J. Kullo , Robb Rowley , Jacqueline S. Dron , Deanna Brockman , Eric Venner , Mark I. McCarthy , Antonis C. Antoniou , Douglas F. Easton , Robert A. Hegele , Amit V. Khera , Nilanjan Chatterjee , Charles Kooperberg , Karen Edwards , Katherine Vlessis , Kim Kinnear , John N. Danesh , Helen Parkinson , Erin M. Ramos , Megan C. Roberts , Kelly E. Ormond , Muin J. Khoury , A. Cecile J.W. Janssens , Katrina A.B. Goddard , Peter Kraft , Jaqueline A. L. MacArthur , Michael Inouye , Genevieve Wojcik

Polygenic risk scores (PRS), often aggregating the results from genome-wide association studies, can bridge the gap between the initial discovery efforts and clinical applications for disease risk estimation. However, there is remarkable heterogeneity in the reporting of these risk scores. This lack of adherence to reporting standards hinders the translation of PRS into clinical care. The ClinGen Complex Disease Working Group, in a collaboration with the Polygenic Score (PGS) Catalog, have updated the Genetic Risk Prediction (GRIPS) Reporting Statement to the current state of the field and to enable downstream utility. Drawing upon experts in epidemiology, statistics, disease-specific applications, implementation, and policy, this 22-item reporting framework defines the minimal information needed to interpret and evaluate a PRS, especially with respect to any downstream clinical applications. Items span detailed descriptions of the study population (recruitment method, key demographic and clinical characteristics, inclusion/exclusion criteria, and outcome definition), statistical methods for both PRS development and validation, and considerations for potential limitations of the published risk score and downstream clinical utility. Additionally, emphasis has been placed on data availability and transparency to facilitate reproducibility and benchmarking against other PRS, such as deposition in the publicly available PGS Catalog. By providing these criteria in a structured format that builds upon existing standards and ontologies, the use of this framework in publishing PRS will facilitate translation of PRS into clinical care and progress towards defining best practices.

中文翻译:

改进风险预测研究中多基因评分的报告标准

多基因风险评分(PRS)通常会汇总全基因组关联研究的结果,可以弥合最初发现工作与疾病风险估计的临床应用之间的差距。但是,这些风险评分的报告存在明显的异质性。缺乏对报告标准的遵守阻碍了PRS转变为临床护理。ClinGen复杂疾病工作组与多基因评分(PGS)目录合作,已将遗传风险预测(GRIPS)报告声明更新为该领域的当前状态,以实现下游效用。该22个项目的报告框架利用流行病学,统计学,特定疾病的应用,实施和政策方面的专家,定义了解释和评估PRS所需的最少信息,特别是在任何下游临床应用方面。项目涵盖了研究人群的详细说明(招募方法,主要人口统计学和临床​​特征,纳入/排除标准和结果定义),PRS开发和验证的统计方法,以及对已发表风险评分和下游临床研究的潜在限制的考虑效用。此外,重点已放在数据的可用性和透明度上,以促进可重复性和与其他PRS的比较,例如存放在可公开获得的PGS目录中。通过以现有标准和本体为基础以结构化格式提供这些标准,在发布PRS时使用此框架将有助于将PRS转换为临床护理,并朝着定义最佳实践的方向发展。
更新日期:2020-11-25
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