Power and predictive accuracy of polygenic risk scores. The genetic interpretation of area under the ROC curve in genomic profiling. Developing and evaluating polygenic risk prediction models for stratified disease prevention. Clinical use of current polygenic risk scores may exacerbate health disparities. References 7 and 8 are useful reviews outlining the potential benefits and clinical uses of polygenic risk scores. The personal and clinical utility of polygenic risk scores. Towards clinical utility of polygenic risk scores.
Dissecting the genetics of complex traits using summary association statistics. 10 years of GWAS discovery: biology, function, and translation. A brief history of human disease genetics. The new NHGRI-EBI Catalog of published genome-wide association studies (GWAS Catalog). A standardized framework for representation of ancestry data in genomics studies, with application to the NHGRI-EBI GWAS Catalog. 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. 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. 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. 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.
#MARTIN KULLO UPDATE#
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. However, there is notable heterogeneity in the application and reporting of these risk scores, which hinders the translation of PRSs into clinical care. 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. Nature volume 591, pages 211–219 ( 2021) Cite this article Improving reporting standards for polygenic scores in risk prediction studies
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