Plasma Biomarkers as Risk Factors for Incident CKD

Mark J Sarnak; Ronit Katz; Joachim H Ix; Paul L Kimmel; Joseph V Bonventre; Jeffrey Schelling; Mary Cushman; Ramachandran S Vasan; Sushrut S Waikar; Jason H Greenberg; Chirag R Parikh; Steven G Coca; Venkata Sabbisetti; Manasi P Jogalekar; Casey Rebholz; Zihe Zheng; Orlando M Gutierrez; Michael G Shlipak

doi:10.1016/j.ekir.2022.03.018

Plasma Biomarkers as Risk Factors for Incident CKD

Kidney Int Rep. 2022 Mar 25;7(7):1493-1501. doi: 10.1016/j.ekir.2022.03.018. eCollection 2022 Jul.

Authors

Mark J Sarnak¹, Ronit Katz², Joachim H Ix³, Paul L Kimmel⁴, Joseph V Bonventre⁵, Jeffrey Schelling⁶, Mary Cushman^{7

8}, Ramachandran S Vasan^{9

10}, Sushrut S Waikar¹¹, Jason H Greenberg¹², Chirag R Parikh¹³, Steven G Coca¹⁴, Venkata Sabbisetti⁵, Manasi P Jogalekar⁵, Casey Rebholz¹⁵, Zihe Zheng¹⁶, Orlando M Gutierrez^{17

18}, Michael G Shlipak¹⁹

Affiliations

¹ Division of Nephrology, Department of Medicine, Tufts Medical Center, Boston, Massachusetts, USA.
² Department of Obstetrics and Gynecology, University of Washington, Seattle, Washington, USA.
³ Division of Nephrology-Hypertension, Department of Medicine, University of California San Diego School of Medicine, San Diego, California, USA.
⁴ National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Bethesda, Maryland, USA.
⁵ Division of Renal Medicine, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, USA.
⁶ Division of Nephrology, Case Western Reserve, Cleveland, Ohio, USA.
⁷ Department of Medicine, Larner College of Medicine at the University of Vermont, Burlington, USA.
⁸ Department of Pathology and Laboratory Medicine, Larner College of Medicine at the University of Vermont, Burlington, USA.
⁹ Department of Medicine, Boston University Schools of Medicine and Public Health, Boston, Massachusetts, USA.
¹⁰ Department of Epidemiology, Boston University Schools of Medicine and Public Health, Boston, Massachusetts, USA.
¹¹ Section of Nephrology, Department of Medicine, Boston University School of Medicine and Boston Medical Center, Boston, Massachusetts, USA.
¹² Section of Nephrology, Department of Pediatrics, Program of Applied Translational Research, Yale University School of Medicine, New Haven, Connecticut, USA.
¹³ Section of Nephrology, Department of Internal Medicine, Johns Hopkins School of Medicine, Baltimore, Maryland, USA.
¹⁴ Division of Nephrology, Department of Internal Medicine, Icahn School of Medicine at Mount Sinai, New York, New York, USA.
¹⁵ Department of Epidemiology and Statistics, Johns Hopkins School of Medicine, Baltimore, Maryland, USA.
¹⁶ Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania, USA.
¹⁷ Department of Medicine, University of Alabama at Birmingham, Birmingham, Alabama, USA.
¹⁸ Department of Epidemiology, University of Alabama at Birmingham, Birmingham, Alabama, USA.
¹⁹ Kidney Health Research Collaborative, Department of Medicine, San Francisco Veterans Affairs Healthcare System, University of California, San Francisco, San Francisco, California, USA.

Abstract

Introduction: Earlier identification of individuals at high risk of chronic kidney disease (CKD) may facilitate improved risk factor mitigation.

Methods: We evaluated the association of novel plasma biomarkers with incident CKD using a case-cohort design in participants without diabetes and with baseline estimated glomerular filtration rate (eGFR) ≥ 60 ml/min per 1.73 m² in the Multi-Ethnic Study of Atherosclerosis (MESA) and Reasons for Geographic and Racial Differences in Stroke (REGARDS) cohorts. Incident CKD was defined as development of eGFR < 60 ml/min per 1.73 m² and ≥40% decline in eGFR from baseline. We measured plasma markers of inflammation/fibrosis-soluble tumor necrosis factor receptors (TNFRs) 1 and 2 (TNFR-1 and TNFR-2), monocyte chemotactic protein-1 (MCP-1), chitinase 3-like protein 1 (YKL-40), and soluble urokinase-type plasminogen activator receptor (suPAR)-and tubular injury (kidney injury molecule 1 [KIM-1]). Cox regression models weighted for the case-cohort design were used to estimate hazard ratios (HRs) of incident CKD after adjustment for CKD risk factors, eGFR, and albuminuria.

Results: In MESA (median follow-up of 9.2 years), there were 497 individuals in the random subcohort and 163 incident CKD cases. In REGARDS (median follow-up of 9.4 years), there were 497 individuals in the random subcohort and 497 incident CKD cases. Each 2-fold higher plasma KIM-1 (adjusted HR 1.38 [95% CI 1.05-1.81]), suPAR (1.96 [1.10-3.49]), TNFR-1 (1.65 [1.04-2.62]), TNFR-2 (2.02 [1.21-3.38]), and YKL-40 (1.38 [1.09-1.75]) concentrations were associated with incident CKD in MESA. In REGARDS, TNFR-1 (1.99 [1.43-2.76]) and TNFR-2 (1.76 [1.22-2.54]) were associated with incident CKD.

Conclusion: Plasma concentrations of soluble TNFR-1 and TNFR-2 are consistently associated with incident CKD in nondiabetic community-living individuals in MESA and REGARDS.

Keywords: chronic kidney disease; plasma biomarkers; risk factors for chronic kidney disease.

Abstract

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