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Improving reporting standards for polygenic scores in risk prediction studies


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.

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Fig. 1: Prototype of PRS development and validation process.


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We acknowledge the input of the ClinGen Complex Disease Working Group members, including C. D. Bustamante, M. Meyer, F. Harrell, D. Kent, P. Visscher, T. Assimes, S. Plon and J. Berg. We also thank D. Durham for her editorial support and A. Paolucci for her administrative support in the preparation and submission of this manuscript. ClinGen is primarily funded by the National Human Genome Research Institute (NHGRI), through the following three grants: U41HG006834, U41HG009649 and U41HG009650. ClinGen also receives support for content curation from the Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD), through the following three grants: U24HD093483, U24HD093486 and U24HD093487. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health (NIH). In addition, the views expressed in this article are those of the author(s) and not necessarily those of the National Health Service (NHS), the National Institute for Health Research (NIHR) or the Department of Health. Research reported in this publication was supported by the NHGRI under award number U41HG007823 (EBI-NHGRI GWAS Catalog, PGS Catalog). We also acknowledge funding from the European Molecular Biology Laboratory (EMBL). Individuals were funded from the following sources: M.I.M. was a Wellcome Investigator and an NIHR Senior Investigator with funding from the National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK; U01-DK105535) and Wellcome (090532, 098381, 106130, 203141 and 212259); M.I. is supported by the Munz Chair of Cardiovascular Prediction and Prevention at the Baker Heart and Diabetes Institute; M.I., S.A.L. and J.N.D. were supported by core funding from: the UK Medical Research Council (MR/L003120/1), the British Heart Foundation (RG/13/13/30194 and RG/18/13/33946) and the NIHR (Cambridge Biomedical Research Centre at the Cambridge University Hospitals NHS Foundation Trust); S.A.L. is supported by a Canadian Institutes of Health Research postdoctoral fellowship (MFE-171279); and J.N.D. holds a British Heart Foundation Personal Chair and a NIH Research Senior Investigator Award. This work was also supported by Health Data Research UK, which is funded by the UK Medical Research Council, Engineering and Physical Sciences Research Council, Economic and Social Research Council, Department of Health and Social Care (England), Chief Scientist Office of the Scottish Government Health and Social Care Directorates, Health and Social Care Research and Development Division (Welsh Government), Public Health Agency (Northern Ireland), British Heart Foundation and Wellcome.

Author information




H.W., C.T., M.A.I., J.S.D., I.J.K., C.S., R.R., K.V., K.K., K.A.B.G., P.K. and G.L.W. conducted the literature review of reporting practices. H.W., S.A.L., C.T., M.A.I., J.W.O., I.J.K., R.R., D.B., E.V., M.I.M., A.C.A., D.F.E., R.A.H., A.V.K., N.C., C.K., K.E., E.M.R., M.C.R., K.E.O., M.J.K., A.C.J.W.J., K.A.B.G., P.K., J.A.L.M., M.I. and G.L.W. provided feedback on the reporting framework. H.W., S.A.L., C.T., M.A.I., J.W.O., J.S.D., I.J.K., A.V.K., J.N.D., H.P., E.M.R., M.C.R., A.C.J.W.J., K.A.B.G., P.K., J.A.L.M., M.I. and G.L.W. wrote and edited the manuscript text and items.

Corresponding author

Correspondence to Genevieve L. Wojcik.

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Competing interests

M.I.M. is on the advisory panels for Pfizer, Novo Nordisk and Zoe Global; honoraria: Merck, Pfizer, Novo Nordisk and Eli Lilly; research funding: Abbvie, Astra Zeneca, Boehringer Ingelheim, Eli Lilly, Janssen, Merck, Novo Nordisk, Pfizer, Roche, Sanofi Aventis, Servier and Takeda. As of June 2019, he is an employee of Genentech with stock and stock options in Roche. No other authors have competing interests to declare.

Additional information

Peer review information Nature thanks Guillaume Lettre, Paul O’Reilly and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

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Supplementary information

Supplementary Information

This file contains Supplementary Notes, including additional Supplementary Methods detailing the development and revisions of the Polygenic Risk Score Reporting Statement (PRS-RS), as well as additional considerations for each of the reporting items.

Supplementary Table 1

Considerations for clinical translation. This table outlines considerations to inform downstream stakeholder perspectives regarding the translational spectrum of lab test development.

Supplementary Table 2

Mappings between the PGS Catalog and PRS-RS fields. As the PGS Catalog and PRS-RS do not completely align in their fields, we have provided a mapping between the two frameworks to assist in reporting of published PRS.

Supplementary Table 3

Example curations of 10 manuscripts using PRSRS. We have detailed information from ten PRS manuscripts using the fields outlined in PRS-RS as an example for the research community.

Supplementary Table 4

Introduction, Methods, Results and Discussion (IMRAD) Mappings for PRS-RS. Additionally, we have provided mappings between PRS-RS reporting items and a traditional IMRAD structure to aid authors in the reporting of items in manuscript preparation.

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Wand, H., Lambert, S.A., Tamburro, C. et al. Improving reporting standards for polygenic scores in risk prediction studies. Nature 591, 211–219 (2021).

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