I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. Parts of this study have been conducted using the UKBB Resource under UKBB project ID number 41849. The REGARDS (R01HL136666), HyperGEN (R01HL055673), GenHAT (R01HL123782), and WPC (R01HL092173, K24HL133373) studies were all supported by the National Heart, Lung, and Blood Institute (NHLBI). This work was funded by the National Human Genome Research Institute (NHGRI) Electronic Medical Records and Genomics-IV (eMERGE-IV grants 2U01HG008680-05, 1U01HG011167-01, 1U01HG011176-01). The authors have declared no competing interest. With the upper tail of the GPS distribution associated with disease risk equivalent to a positive family history, this score could be used for clinically meaningful risk stratification. We tested the performance of the score in 15 independent testing cohorts, including 3 cohorts of European ancestry (total 23,364 cases and 117,883 controls), 6 cohorts of African ancestry (4,268 cases and 10,276 controls), 4 cohorts of Asian ancestry (1,030 cases and 9,896 controls), and 2 Hispanic/Latinx cohorts (1,492 cases and 2,984 controls).Ĭonclusions By combining APOL1 risk genotypes with the available GWAS for renal function, we designed, optimized, and validated a GPS predictive of CKD across four major continental ancestries. The polygenic component of the score was developed and optimized using 28,047 cases and 251,772 controls (70% of UK Biobank participants of European ancestry), while the weights for APOL1 effects were derived based on UK Biobank participants of African ancestry (967 cases and 6,191 controls). The score was designed to ensure transferability across major continental ancestries, genotyping platforms, imputation panels, and phenotyping strategies, and was tested following ClinGen guidelines. ( John Wiley and Sons Inc.Methods We developed and validated a genome-wide polygenic score (GPS) for CKD defined by estimated glomerular filtration rate (eGFR) <60 mL/min/1.73m 2 using common variant association statistics from GWAS for eGFR combined with information on APOL1 risk genotypes. Potter, Simon Golledge, Jonathan Eriksson, Per Norman, Paul E. Waltham, Matthew Edkins, Sarah Gwilliam, Rhian Hunt, Sarah E. Wijmenga, Cisca de Graaf, Jacqueline Kiemeney, Lambertus A. Thorleifsson, Gudmar Thorsteinsdottir, Unnur Teijink, Joep A. Futers, Simon Sohrabi, Soroush Smith, Alberto Thompson, Matthew M. Bumpstead, Suzannah Gretarsdottir, Solveig Badger, Stephen A. ![]() Saratzis, Athanasios Slowik, Agnieszka Takahashi, Atsushi Tromp, Gerard Uitterlinden, André G. Pera, Joanna Rasmussen‐Torvik, Laura Ritchie, Marylyn D. ![]() Nakamura, Yusuke Nakaoka, Hirofumi Niemelä, Mika Pacheco, Jennifer Peissig, Peggy L. Low, Siew‐Kee Malinowski, Jennifer McCarty, Catherine A. Laakso, Aki Lai, Dongbing Leal, Suzanne M. Kivisaari, Riku Ko, Nerissa Koskinen, Seppo Kubo, Michiaki Kullo, Iftikhar J. Hernesniemi, Juha Hofman, Albert Inoue, Ituro Jääskeläinen, Juha E. Gottesman, Omri Guo, Dong‐Chuan Harrison, Seamus C. Fornage, Myriam Foroud, Tatiana von und zu Fraunberg, Mikael Friedrich, Christoph M. Broderick, Joseph Bijlenga, Philippe Carrell, David S. Lee, Cue Hyunkyu Ripke, Stephan Anderson, Graig de Andrade, Mariza Baas, Annette F.
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