Improving reporting standards for polygenic scores in risk prediction studies

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 VlessisKim 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 L. Wojcik

Research output: Contribution to journalReview articlepeer-review

Abstract

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, we present the Polygenic Risk Score Reporting Standards (PRS-RS), in which we 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. Items span detailed descriptions of study populations, statistical methods for the development and validation of PRSs and considerations for the potential limitations of these scores. In addition, we emphasize the need for data availability and transparency, and we 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.

Original languageEnglish (US)
Pages (from-to)211-219
Number of pages9
JournalNature
Volume591
Issue number7849
DOIs
StatePublished - Mar 11 2021

ASJC Scopus subject areas

  • General

Fingerprint

Dive into the research topics of 'Improving reporting standards for polygenic scores in risk prediction studies'. Together they form a unique fingerprint.

Cite this