A Polygenic Score for Reduced Kidney Function and Adverse Outcomes in a Chronic Kidney Disease Cohort

We studied whether a polygenic score for reduced kidney function developed from population-based studies was associated with adverse outcomes among persons with chronic kidney disease. The polygenic score was significantly associated with incident kidney failure, major adverse cardiovascular outcomes and overall mortality while adjusting for age, sex, and baseline eGFR: the hazard ratio for kidney failure over 6.5 years was 1.83 (95% CI 1.40-2.39) comparing those in the highest and lowest quartiles of the polygenic score. However, the significant associations of the polygenic score did not translate to improved outcome prediction in comparison to established risk equations.

[1]  Judy H. Cho,et al.  Genome-wide polygenic score to predict chronic kidney disease across ancestries , 2022, Nature Medicine.

[2]  Matthew S. Lebo,et al.  Development of a clinical polygenic risk score assay and reporting workflow , 2022, Nature Medicine.

[3]  D. Schaid,et al.  Genome-wide polygenic score with APOL1 risk genotypes predicts chronic kidney disease across major continental ancestries , 2021, medRxiv.

[4]  N. Chatterjee,et al.  Polygenic Risk Scores for Kidney Function and Their Associations with Circulating Proteome, and Incident Kidney Diseases , 2021, Journal of the American Society of Nephrology : JASN.

[5]  A. Köttgen,et al.  The CKDGen Consortium: ten years of insights into the genetic basis of kidney function. , 2020, Kidney international.

[6]  Sangsoo Kim,et al.  Genetic risk score raises the risk of incidence of chronic kidney disease in Korean general population-based cohort , 2019, Clinical and Experimental Nephrology.

[7]  N. Wald,et al.  The illusion of polygenic disease risk prediction , 2019, Genetics in Medicine.

[8]  K. Kiryluk,et al.  Genome-wide polygenic risk predictors for kidney disease , 2018, Nature Reviews Nephrology.

[9]  P. Donnelly,et al.  The UK Biobank resource with deep phenotyping and genomic data , 2018, Nature.

[10]  E. Topol,et al.  The personal and clinical utility of polygenic risk scores , 2018, Nature Reviews Genetics.

[11]  M. Schemper,et al.  Statistical controversies in clinical research: the importance of importance. , 2016, Annals of oncology : official journal of the European Society for Medical Oncology.

[12]  P. Visscher,et al.  Modeling Linkage Disequilibrium Increases Accuracy of Polygenic Risk Scores , 2015, bioRxiv.

[13]  V. Jha,et al.  Chronic kidney disease: global dimension and perspectives , 2013, The Lancet.

[14]  Kai-Uwe Eckardt,et al.  Evolving importance of kidney disease: from subspecialty to global health burden , 2013, The Lancet.

[15]  Thomas A Gerds,et al.  Estimating a time‐dependent concordance index for survival prediction models with covariate dependent censoring , 2013, Statistics in medicine.

[16]  Brenda R. Hemmelgarn,et al.  Notice , 2012, Kidney International Supplements.

[17]  Hans-Ulrich Prokosch,et al.  The German Chronic Kidney Disease (GCKD) study: design and methods. , 2012, Nephrology, dialysis, transplantation : official publication of the European Dialysis and Transplant Association - European Renal Association.

[18]  N. Tangri,et al.  A predictive model for progression of chronic kidney disease to kidney failure. , 2011, JAMA.

[19]  Harald Binder,et al.  Adapting Prediction Error Estimates for Biased Complexity Selection in High-Dimensional Bootstrap Samples , 2008, Statistical applications in genetics and molecular biology.