A new study reports that genome-wide polygenic risk scores can identify individuals at risk of common complex diseases, such as coronary artery disease or type 2 diabetes, with comparable performance to that of monogenic mutation screens. These findings support the potential clinical utility of genome-wide association study (GWAS)-based risk stratification; however, several issues need to be addressed before this approach can be applied to kidney disease.
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Acknowledgements
The authors acknowledge support from the following grants from the National Institutes of Health (NIH): Kidney Precision Medicine Project grant number UG3DK114926 from the National Institute of Diabetes and Digestive Kidney Diseases (NIDDK), the Electronic Medical Records and Genomics (eMERGE) Network grant number U01HG8680 from the National Human Genome Research Institute (NHGRI), and the Columbia Clinical and Translational Science Award grant number UL1TR001873 from the National Center for Advancing Translational Sciences (NCATS). Additional sources of funding include the following grants: R01-DK105124 and RC2-DK116690 (NIDDK) and R01-MD009223 (National Institute on Minority Health and Health Disparities (NIMHD)). The content is solely the responsibility of the authors and does not necessarily represent the official views of the NIH.
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Liu, L., Kiryluk, K. Genome-wide polygenic risk predictors for kidney disease. Nat Rev Nephrol 14, 723–724 (2018). https://doi.org/10.1038/s41581-018-0067-6
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DOI: https://doi.org/10.1038/s41581-018-0067-6
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