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Kidney Week

Abstract: PO0741

Urine Biomarkers and ESKD Risk in Persons with Diabetes and CKD

Session Information

Category: Diabetic Kidney Disease

  • 602 Diabetic Kidney Disease: Clinical

Authors

  • Amatruda, Jonathan G., University of California San Francisco, San Francisco, California, United States
  • Katz, Ronit, University of Washington, Seattle, Washington, United States
  • Sarnak, Mark J., Tufts Medical Center, Boston, Massachusetts, United States
  • Gutierrez, Orlando M., Departments of Medicine and Epidemiology, University of Alabama at Birmingham, Birmingham, Alabama, United States
  • Greenberg, Jason Henry, Section of Nephrology, Department of Pediatrics, Clinical and Translational Research Accelerator, Yale University School of Medicine, New Haven, Connecticut, United States
  • Cushman, Mary, University of Vermont College of Medicine, Burlington, Vermont, United States
  • Waikar, Sushrut S., Section of Nephrology, Department of Medicine, Boston Medical Center, Boston, Massachusetts, United States
  • Parikh, Chirag R., Johns Hopkins Medicine, Baltimore, Maryland, United States
  • Schelling, Jeffrey R., Case Western Reserve University Department of Medicine, Cleveland, Ohio, United States
  • Bonventre, Joseph V., Brigham and Women's Hospital Department of Medicine, Boston, Massachusetts, United States
  • Ramachandran, Vasan S., Departments of Medicine and Epidemiology, Boston University School of Medicine and School of Public Health, Boston, Massachusetts, United States
  • Kimmel, Paul L., National Institute of Diabetes and Digestive and Kidney Diseases, Bethesda, Maryland, United States
  • Shlipak, Michael, Department of Medicine, San Francisco VA Health Care System, San Francisco, California, United States
  • Ix, Joachim H., Division of Nephrology and Hypertension, Department of Medicine, University of California San Diego, San Diego, California, United States
Background

Tubulointerstitial damage is a feature of diabetic CKD, but correlates poorly with eGFR and albuminuria. Urine biomarkers of kidney tubule health may be independently associated with risk of ESKD in diabetic CKD.

Methods

We identified 1,145 participants from the REGARDS study with baseline eGFR≤60 mL/min/1.73m2 and diabetes. Per case-cohort design, we randomly selected a subcohort of 560. Within the subcohort there were 93 ESKD cases; we further sampled all remaining ESKD cases not included in the subcohort (N=68). These 161 ESKD cases were identified by USRDS linkage over mean follow-up of 4.3±2.7 years. In baseline urine samples, we measured biomarkers of kidney tubule injury (kidney injury molecule-1 [KIM-1]), inflammation and fibrosis (monocyte chemoattractant protein-1 [MCP-1]; chitinase-3-like protein [YKL-40]), function (alpha-1-microglobulin [α1m]; uromodulin [UMOD]), and cell repair (epidermal growth factor [EGF]). Using weighted Cox models, we calculated hazard ratios (HR) of ESKD by baseline biomarkers. LASSO regression identified a subset of biomarkers most strongly associated with ESKD.

Results

Subcohort participants had mean age 70±9 years, 47% male, 53% Black, mean eGFR=40±13 mL/min/1.73m2 and median UACR 33 (IQR 10-213) mg/g. Adjusting for baseline eGFR and albuminuria, higher KIM-1, α1m, and MCP-1 were each associated with higher ESKD risk. Strengths of association were of comparable magnitude to urine albumin (Table). LASSO regression retained KIM-1 (HR per doubling=1.31 [1.06-1.62]) and α1m (HR per doubling=1.36 [1.08-1.70]) as most strongly associated with ESKD.

Conclusion

Among persons with eGFR≤60 mL/min/1.73m2 and diabetes, urine KIM-1 and α1m captured the influence of kidney tubule health on longitudinal risk of ESKD. These biomarkers may facilitate identification of persons with kidney disease and diabetes at greatest risk of ESKD.

Adjusted HR per doubling of individually-modeled urine biomarkers with ESKD

Funding

  • NIDDK Support