Incident heart failure in chronic kidney disease: proteomics informs biology and risk stratification

Ruth F Dubin; Rajat Deo; Yue Ren; Jianqiao Wang; Alexander R Pico; Josyf C Mychaleckyj; Julia Kozlitina; Victoria Arthur; Hongzhe Lee; Amil Shah; Harold Feldman; Nisha Bansal; Leila Zelnick; Panduranga Rao; Nidhi Sukul; Dominic S Raj; Rupal Mehta; Sylvia E Rosas; Zeenat Bhat; Matthew R Weir; Jiang He; Jing Chen; Mayank Kansal; Paul L Kimmel; Vasan S Ramachandran; Sushrut S Waikar; Mark R Segal; Peter Ganz; CRIC Study Investigators

doi:10.1093/eurheartj/ehae288

Incident heart failure in chronic kidney disease: proteomics informs biology and risk stratification

Eur Heart J. 2024 May 17:ehae288. doi: 10.1093/eurheartj/ehae288. Online ahead of print.

Authors

Ruth F Dubin¹, Rajat Deo², Yue Ren³, Jianqiao Wang⁴, Alexander R Pico⁵, Josyf C Mychaleckyj⁶, Julia Kozlitina⁷, Victoria Arthur⁸, Hongzhe Lee³, Amil Shah⁸, Harold Feldman⁹, Nisha Bansal¹⁰, Leila Zelnick¹⁰, Panduranga Rao¹¹, Nidhi Sukul¹¹, Dominic S Raj¹², Rupal Mehta¹³, Sylvia E Rosas¹⁴, Zeenat Bhat¹¹, Matthew R Weir¹⁵, Jiang He¹⁶, Jing Chen¹⁶, Mayank Kansal¹⁷, Paul L Kimmel¹⁸, Vasan S Ramachandran¹⁹, Sushrut S Waikar²⁰, Mark R Segal²¹, Peter Ganz²²; CRIC Study Investigators

Collaborators

CRIC Study Investigators:
Lawrence J Appel, Debbie L Cohen, James P Lash, Robert G Nelson, Vallabh O Shah, Mark L Unruh

Affiliations

¹ Division of Nephrology, University of Texas Southwestern Medical Center, 5323 Harry Hines Blvd, H5.122E, Dallas, TX 75390, USA.
² Division of Cardiovascular Medicine, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA.
³ Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
⁴ Harvard T.H. Chan School of Public Health, Boston, MA, USA.
⁵ Institute of Data Science and Biotechnology, Gladstone Institutes, San Francisco, CA, USA.
⁶ Center for Public Health Genomics, University of Virginia School of Medicine, Charlottesville, VA, USA.
⁷ McDermott Center for Human Growth and Development, University of Texas Southwestern Medical Center, Dallas, TX, USA.
⁸ Division of Cardiology, University of Texas Southwestern Medical Center, Dallas, TX, USA.
⁹ Patient-Centered Outcomes Research Institute, Washington, DC, USA.
¹⁰ Division of Nephrology, University of Washington Medical Center, Seattle, WA, USA.
¹¹ Division of Nephrology, University of Michigan, Ann Arbor, MI, USA.
¹² Division of Kidney Diseases and Hypertension, George Washington University School of Medicine, Washington, DC, USA.
¹³ Division of Nephrology and Hypertension, Northwestern University Feinberg School of Medicine, USA.
¹⁴ Joslin Diabetes Center, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, USA.
¹⁵ Division of Nephrology, Department of Medicine, University of Maryland School of Medicine, Baltimore, MD, USA.
¹⁶ Department of Epidemiology, Tulane University, New Orleans, LA, USA.
¹⁷ Division of Cardiology, University of Illinois College of Medicine, Chicago, IL, USA.
¹⁸ Division of Kidney, Urologic, and Hematologic Diseases, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Bethesda, MD, USA.
¹⁹ University of Texas School of Public Health San Antonio and the University of Texas Health Sciences Center in San Antonio, Section of Preventive Medicine and Epidemiology, Department of Medicine, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, USA.
²⁰ Section of Nephrology, Department of Medicine, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, USA.
²¹ Department of Epidemiology and Biostatistics, University of California San Francisco, San Francisco, CA, USA.
²² Division of Cardiology, University of California San Francisco, San Francisco, CA, USA.

PMID: 38757788
DOI: 10.1093/eurheartj/ehae288

Abstract

Background and aims: Incident heart failure (HF) among individuals with chronic kidney disease (CKD) incurs hospitalizations that burden patients and health care systems. There are few preventative therapies, and the Pooled Cohort equations to Prevent Heart Failure (PCP-HF) perform poorly in the setting of CKD. New drug targets and better risk stratification are urgently needed.

Methods: In this analysis of incident HF, SomaScan V4.0 (4638 proteins) was analysed in 2906 participants of the Chronic Renal Insufficiency Cohort (CRIC) with validation in the Atherosclerosis Risk in Communities (ARIC) study. The primary outcome was 14-year incident HF (390 events); secondary outcomes included 4-year HF (183 events), HF with reduced ejection fraction (137 events), and HF with preserved ejection fraction (165 events). Mendelian randomization and Gene Ontology were applied to examine causality and pathways. The performance of novel multi-protein risk models was compared to the PCP-HF risk score.

Results: Over 200 proteins were associated with incident HF after adjustment for estimated glomerular filtration rate at P < 1 × 10-5. After adjustment for covariates including N-terminal pro-B-type natriuretic peptide, 17 proteins remained associated at P < 1 × 10-5. Mendelian randomization associations were found for six proteins, of which four are druggable targets: FCG2B, IGFBP3, CAH6, and ASGR1. For the primary outcome, the C-statistic (95% confidence interval [CI]) for the 48-protein model in CRIC was 0.790 (0.735, 0.844) vs. 0.703 (0.644, 0.762) for the PCP-HF model (P = .001). C-statistic (95% CI) for the protein model in ARIC was 0.747 (0.707, 0.787).

Conclusions: Large-scale proteomics reveal novel circulating protein biomarkers and potential mediators of HF in CKD. Proteomic risk models improve upon the PCP-HF risk score in this population.

Keywords: Chronic kidney disease; Heart failure; Mendelian randomization; Risk model.

Abstract

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