Proteomic cardiovascular risk assessment in chronic kidney disease

Author:

Deo Rajat1ORCID,Dubin Ruth F2,Ren Yue3,Murthy Ashwin C1,Wang Jianqiao3,Zheng Haotian3,Zheng Zihe3,Feldman Harold3,Shou Haochang3,Coresh Josef45,Grams Morgan45,Surapaneni Aditya L4,Bhat Zeenat6,Cohen Jordana B37ORCID,Rahman Mahboob8,He Jiang9ORCID,Saraf Santosh L10,Go Alan S1112,Kimmel Paul L13,Vasan Ramachandran S141516,Segal Mark R17,Li Hongzhe3,Ganz Peter18ORCID

Affiliation:

1. Division of Cardiovascular Medicine, Electrophysiology Section, Perelman School of Medicine at the University of Pennsylvania , One Convention Avenue, Level 2 / City Side, Philadelphia, PA 19104 , USA

2. Division of Nephrology, University of Texas Southwestern Medical Center , 5323 Harry Hines Blvd, Dallas, TX 75390 , USA

3. Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine, University of Pennsylvania , 215 Blockley Hall, 423 Guardian Drive, Philadelphia, PA 19104 , USA

4. Department of Epidemiology; Welch Center for Prevention, Epidemiology, and Clinical Research, Johns Hopkins University Bloomberg School of Public Health , 615 N Wolfe St, Baltimore, MD 21205 , USA

5. Department of Medicine, Johns Hopkins University , 2024 E. Monument Street, Room 2-635, Suite 2-600, Baltimore, MD 21287 , USA

6. Division of Nephrology, University of Michigan , 5100 Brehm Tower, 1000 Wall Street, Ann Arbor, MI 48105 , USA

7. Renal, Electrolyte and Hypertension Division, Perelman School of Medicine, University of Pennsylvania , 831 Blockley Hall, 423 Guardian Drive, Philadelphia, PA 19104 , USA

8. Department of Medicine, Case Western Reserve University School of Medicine , 11100 Euclid Avenue, Wearn Bldg. 3rd Floor. Rm 352, Cleveland, OH 44106 , USA

9. Department of Epidemiology, Tulane University School of Public Health and Tropical Medicine , 1440 Canal Street, SL 18, New Orleans, LA 70112 , USA

10. Division of Hematology and Oncology, University of Illinois at Chicago , 1740 West Taylor Street, Chicago, IL 60612 , USA

11. Division of Research, Kaiser Permanente Northern California , 2000 Broadway, Oakland, CA 94612 , USA

12. Departments of Epidemiology, Biostatistics and Medicine, University of California at San Francisco , San Francisco, CA , USA

13. Division of Kidney, Urologic, and Hematologic Diseases, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health , 9000 Rockville Pike, Bethesda, MD 20892 , USA

14. Section of Preventive Medicine and Epidemiology, Department of Medicine, Boston University School of Medicine , Boston, MA , USA

15. Section of Cardiology, Department of Medicine, Boston University School of Medicine , Boston, MA , USA

16. Department of Epidemiology, Boston University School of Public Health , Boston, MA , USA

17. Department of Epidemiology and Biostatistics, University of California , 550 16th Street, 2nd Floor, Box #0560, San Francisco, CA 94143 , USA

18. Division of Cardiology, Zuckerberg San Francisco General Hospital and Department of Medicine, University of California , San Francisco, 1001 Potrero Avenue, 5G1, San Francisco, CA 94110 , USA

Abstract

Abstract Aims Chronic kidney disease (CKD) is widely prevalent and independently increases cardiovascular risk. Cardiovascular risk prediction tools derived in the general population perform poorly in CKD. Through large-scale proteomics discovery, this study aimed to create more accurate cardiovascular risk models. Methods and results Elastic net regression was used to derive a proteomic risk model for incident cardiovascular risk in 2182 participants from the Chronic Renal Insufficiency Cohort. The model was then validated in 485 participants from the Atherosclerosis Risk in Communities cohort. All participants had CKD and no history of cardiovascular disease at study baseline when ∼5000 proteins were measured. The proteomic risk model, which consisted of 32 proteins, was superior to both the 2013 ACC/AHA Pooled Cohort Equation and a modified Pooled Cohort Equation that included estimated glomerular filtrate rate. The Chronic Renal Insufficiency Cohort internal validation set demonstrated annualized receiver operating characteristic area under the curve values from 1 to 10 years ranging between 0.84 and 0.89 for the protein and 0.70 and 0.73 for the clinical models. Similar findings were observed in the Atherosclerosis Risk in Communities validation cohort. For nearly half of the individual proteins independently associated with cardiovascular risk, Mendelian randomization suggested a causal link to cardiovascular events or risk factors. Pathway analyses revealed enrichment of proteins involved in immunologic function, vascular and neuronal development, and hepatic fibrosis. Conclusion In two sizeable populations with CKD, a proteomic risk model for incident cardiovascular disease surpassed clinical risk models recommended in clinical practice, even after including estimated glomerular filtration rate. New biological insights may prioritize the development of therapeutic strategies for cardiovascular risk reduction in the CKD population.

Funder

National Institutes of Health

National Institute of Diabetes

Perelman School of Medicine

University of Pennsylvania Clinical

Translational Science

Johns Hopkins University

University of Maryland

Clinical and Translational Science

National Center for Advancing Translational Sciences

Medical Research, Michigan Institute for Clinical and Health Research

University of Illinois at Chicago

Clinical and Translational Research

Department of Internal Medicine

University of New Mexico School of Medicine

Winkelman Family

Department of Health and Human

Publisher

Oxford University Press (OUP)

Subject

Cardiology and Cardiovascular Medicine

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