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Kidney Week

Abstract: TH-PO931

Plasma Biomarkers and Diabetic Kidney Disease (DKD) Progression: Findings from the Chronic Renal Insufficiency Cohort (CRIC) Study

Session Information

Category: Diabetic Kidney Disease

  • 602 Diabetic Kidney Disease: Clinical

Authors

  • Schrauben, Sarah J., Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania, United States
  • Shou, Haochang, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania, United States
  • Anderson, Amanda Hyre, Tulane University, New Orleans, Louisiana, United States
  • Bonventre, Joseph V., Brigham and Women's Hospital, Boston, Massachusetts, United States
  • Chen, Jing, Tulane School of Medicine, New Orleans, Louisiana, United States
  • Coca, Steven G., Icahn School of Medicine at Mount Sinai, New York, New York, United States
  • Furth, Susan L., The Children's Hospital of Philadelphia, Philadelphia, Pennsylvania, United States
  • Greenberg, Jason Henry, Yale University, Woodbridge, Connecticut, United States
  • Gutierrez, Orlando M., UAB School of Medicine, Birmingham, Alabama, United States
  • Ix, Joachim H., UCSD, San Diego, California, United States
  • Lash, James P., University of Illinois at Chicago, Chicago, Illinois, United States
  • Parikh, Chirag R., Johns Hopkins University, Baltimore, Maryland, United States
  • Rebholz, Casey, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, United States
  • Sarnak, Mark J., Tufts Medical Center, Boston, Massachusetts, United States
  • Shlipak, Michael, San Francisco VA Medical Center, San Francisco, California, United States
  • Kimmel, Paul L., National Institute of Diabetes and Digestive Kidney Diseases (NIDDK), Bethesda, Maryland, United States
  • Ramachandran, Vasan S., Boston University School of Medicine, Framingham, Massachusetts, United States
  • Feldman, Harold I., Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania, United States
  • Schelling, Jeffrey R., Case Western Reserve University, Cleveland, Ohio, United States
Background

DKD is the leading cause of end-stage kidney disease (ESKD) in the US. There is an unmet need for biomarkers to identify patients at high risk for DKD progression.

Methods

CRIC participants with diabetes, estimated glomerular filtration rate (eGFR) <60 ml/min/1.73m2, and plasma collected at baseline (N=1315) were eligible for this case-cohort study. Eligible participants were randomly selected for the subcohort (N=597); cases were all participants who developed DKD progression, defined as ESKD or 40% eGFR decline (N=538, 240 in the subcohort). Plasma biomarkers (KIM-1, TNFR-1, TNFR-2, MCP-1, suPAR, & YLK-40) were measured using a novel multiplex platform. Spearman correlations estimated relationships between markers, eGFR, and proteinuria. Weighted Cox regression models adjusted for age, sex, race, education, blood pressure, hsCRP, body mass index, smoking, eGFR, and proteinuria estimated the relation of markers with DKD progression. Mixed effects models estimated the relationship of markers with change in yearly eGFR.

Results

The median follow-up was 8.7 (6.4-9.3) years. The mean change in eGFR was -0.6 and -4.1 ml/min/1.73m2 among non-cases and cases, respectively. TNFR-1 and TNFR-2 were the most correlated markers (ρ=0.85). All markers inversely correlated with eGFR. Higher marker levels associated with greater risk of DKD progression (Table). Four markers associated with eGFR decline.

Conclusion

Higher plasma levels of KIM-1, TNFR-1, TNFR-2, MCP-1, suPAR, and YKL-40 were independently associated with increased risk of DKD progression. These biomarkers may yield prognostic and mechanistic value for future DKD research.

Adjusted associations of Plasma Biomarkers with DKD progression.
 ESRD or 40% decline in eGFR (HR, 95% CI)Change in yearly eGFR
ml/min/1.73m2 (β, 95% CI)
KIM-11.5 (1.2, 1.9)-0.5 (-0.8, -0.2)
TNFR-12.1 (1.6, 2.8)-0.4 (-0.7, -0.1)
TNFR-22.1 (1.5, 2.7)-0.5 (-0.8, -0.2)
MCP-11.4 (1.2, 1.7)-0.01 (-0.2, 0.2)
suPAR1.7 (1.3, 2.2)-0.3 (-0.6, 0.0)
YKL-401.4 (1.2, 1.6)-0.4 (-0.6, -0.2)

HR = hazard ratio associated with SD in (natural log) biomarker

Funding

  • NIDDK Support