Single-Ancestry versus Multi-Ancestry Polygenic Risk Scores for CKD in Black American Populations

Author:

Jones Alana C.12ORCID,Patki Amit3ORCID,Srinivasasainagendra Vinodh3,Tiwari Hemant K.3,Armstrong Nicole D.2ORCID,Chaudhary Ninad S.2ORCID,Limdi Nita A.4ORCID,Hidalgo Bertha A.2ORCID,Davis Brittney4ORCID,Cimino James J.5ORCID,Khan Atlas6ORCID,Kiryluk Krzysztof6ORCID,Lange Leslie A.7,Lange Ethan M.7ORCID,Arnett Donna K.8ORCID,Young Bessie A.9ORCID,Diamantidis Clarissa J.10ORCID,Franceschini Nora11ORCID,Wassertheil-Smoller Sylvia12ORCID,Rich Stephen S.13ORCID,Rotter Jerome I.14ORCID,Mychaleckyj Josyf C.13ORCID,Kramer Holly J.15ORCID,Chen Yii-Der I.14ORCID,Psaty Bruce M.1617,Brody Jennifer A.17ORCID,de Boer Ian H.1618ORCID,Bansal Nisha18ORCID,Bis Joshua C.17ORCID,Irvin Marguerite R.2

Affiliation:

1. Medical Scientist Training Program, Heersink School of Medicine, University of Alabama at Birmingham, Birmingham, Alabama

2. Department of Epidemiology, School of Public Health, University of Alabama at Birmingham, Birmingham, Alabama

3. Department of Biostatistics, School of Public Health, University of Alabama at Birmingham, Birmingham, Alabama

4. Department of Neurology, Heersink School of Medicine, University of Alabama at Birmingham, Birmingham, Alabama

5. Department of Biomedical Informatics and Data Science, Heersink School of Medicine, University of Alabama at Birmingham, Birmingham, Alabama

6. Division of Nephrology, Department of Medicine, Columbia University Medical Center, New York, New York

7. Department of Biomedical Informatics, University of Colorado-Anschutz, Aurora, Colorado

8. Office of the Provost, University of South Carolina, Columbia, South Carolina

9. Division of Nephrology, University of Washington, Seattle, Washington

10. Department of Medicine, Duke University School of Medicine, Durham, North Carolina

11. Department of Epidemiology, Gillings School of Public Health, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina

12. Department of Epidemiology and Population Health, Albert Einstein College of Medicine, New York, New York

13. Department of Genome Sciences, University of Virginia, Charlottesville, Virginia

14. Department of Pediatrics, The Institute for Translational Genomic and Population Sciences, The Lundquist Institute for Biomedical Innovation at Harbort-UCLA Medical Center, Torrance, California

15. Departments of Public Health Sciences and Medicine, Loyola University Medical Center, Taywood, Illinois

16. Department of Epidemiology, School of Public Health, University of Washington, Seattle, Washington

17. Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, Washington

18. Division of Nephrology, Department of Medicine, University of Washington, Seattle, Washington

Abstract

Key Points The predictive performance of an African ancestry–specific polygenic risk score (PRS) was comparable to a European ancestry–derived PRS for kidney traits.However, multi-ancestry PRSs outperform single-ancestry PRSs in Black American populations.Predictive accuracy of PRSs for CKD was improved with the use of race-free eGFR. Background CKD is a risk factor of cardiovascular disease and early death. Recently, polygenic risk scores (PRSs) have been developed to quantify risk for CKD. However, African ancestry populations are underrepresented in both CKD genetic studies and PRS development overall. Moreover, European ancestry–derived PRSs demonstrate diminished predictive performance in African ancestry populations. Methods This study aimed to develop a PRS for CKD in Black American populations. We obtained score weights from a meta-analysis of genome-wide association studies for eGFR in the Million Veteran Program and Reasons for Geographic and Racial Differences in Stroke Study to develop an eGFR PRS. We optimized the PRS risk model in a cohort of participants from the Hypertension Genetic Epidemiology Network. Validation was performed in subsets of Black participants of the Trans-Omics in Precision Medicine Consortium and Genetics of Hypertension Associated Treatment Study. Results The prevalence of CKD—defined as stage 3 or higher—was associated with the PRS as a continuous predictor (odds ratio [95% confidence interval]: 1.35 [1.08 to 1.68]) and in a threshold-dependent manner. Furthermore, including APOL1 risk status—a putative variant for CKD with higher prevalence among those of sub-Saharan African descent—improved the score's accuracy. PRS associations were robust to sensitivity analyses accounting for traditional CKD risk factors, as well as CKD classification based on prior eGFR equations. Compared with previously published PRS, the predictive performance of our PRS was comparable with a European ancestry–derived PRS for kidney traits. However, single-ancestry PRSs were less predictive than multi-ancestry–derived PRSs. Conclusions In this study, we developed a PRS that was significantly associated with CKD with improved predictive accuracy when including APOL1 risk status. However, PRS generated from multi-ancestry populations outperformed single-ancestry PRS in our study.

Funder

National Heart, Lung, and Blood Institute

National Institute of Diabetes and Digestive and Kidney Diseases

National Human Genome Research Institute

Publisher

Ovid Technologies (Wolters Kluwer Health)

Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Polygenic scores and their applications in kidney disease;Nature Reviews Nephrology;2024-09-13

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