Improving reporting standards for polygenic scores in risk prediction studies
Publication: Nature
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, et al
10 March 2021
Summary
This research is a perspective piece that provides a framework to promote the validity, transparency, and reproducibility of polygenic risk scores (PRS) by encouraging authors to detail the study population, statistical methods, and potential clinical utility of a published score.
Polygenic risk scores (PRSs), which often aggregate results from genome-wide association studies, can bridge the gap between initial discovery efforts and clinical applications for the estimation of disease risk using genetics.
However, there is notable heterogeneity in the application and reporting of these risk scores, which hinders the translation of PRSs into clinical care. Here, in a collaboration between the Clinical Genome Resource (ClinGen) Complex Disease Working Group and the Polygenic Score (PGS) Catalog, the researchers present the Polygenic Risk Score Reporting Standards (PRS-RS), in which they update the Genetic Risk Prediction Studies (GRIPS) Statement to reflect the present state of the field.
Drawing on the input of experts in epidemiology, statistics, disease-specific applications, implementation and policy, this comprehensive reporting framework defines the minimal information that is needed to interpret and evaluate PRSs, especially with respect to downstream clinical applications.
The researchers encourage researchers to deposit and share PRSs through the PGS Catalog to facilitate reproducibility and comparative benchmarking. By providing these criteria in a structured format that builds on existing standards and ontologies, the use of this framework in publishing PRSs will facilitate translation into clinical care and progress towards defining best practice.