Orlando M Gutiérrez1, Michael G Shlipak2, Ronit Katz3, Sushrut S Waikar4, Jason H Greenberg5, Sarah J Schrauben6, Steven Coca7, Chirag R Parikh8, Ramachandran S Vasan9, Harold I Feldman6, Paul L Kimmel10, Mary Cushman11, Joseph V Bonventre12, Mark J Sarnak13, Joachim H Ix14. 1. Departments of Medicine and Epidemiology, University of Alabama at Birmingham, Birmingham, Alabama. Electronic address: ogutierrez@uabmc.edu. 2. Kidney Health Research Collaborative, Department of Medicine, San Francisco VA Healthcare System and University of California, San Francisco, San Francisco, California. 3. Department of Obstetrics and Gynecology, University of Washington, Seattle, Washington. 4. Section of Nephrology, Department of Medicine, Boston University School of Medicine and Boston Medical Center, Boston, Massachusetts. 5. Section of Nephrology, Department of Pediatrics, Program of Applied Translational Research, Yale University School of Medicine, New Haven, Connecticut. 6. Departments of Medicine and Biostatistics, Epidemiology and Informatics and Center for Clinical Epidemiology and Biostatistics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania. 7. Division of Nephrology, Department of Internal Medicine, Icahn School of Medicine at Mount Sinai, New York, New York. 8. Section of Nephrology, Department of Internal Medicine, Johns Hopkins School of Medicine, Baltimore, Maryland. 9. Departments of Medicine and Epidemiology, Boston University Schools of Medicine and Public Health, Boston, Massachusetts. 10. National Institute of Diabetes and Digestive and Kidney Diseases, Bethesda, Maryland. 11. Departments of Medicine and Pathology and Laboratory Medicine, Larner College of Medicine at the University of Vermont, Burlington, Vermont. 12. Division of Renal Medicine, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts. 13. Division of Nephrology, Department of Medicine, Tufts Medical Center, Boston, Massachusetts. 14. Division of Nephrology-Hypertension, Department of Medicine, University of California, San Diego, School of Medicine, La Jolla, California.
Abstract
RATIONALE & OBJECTIVE: Most circulating biomarkers of chronic kidney disease (CKD) progression focus on factors reflecting glomerular filtration. Few biomarkers capture nonglomerular pathways of kidney injury or damage, which may be particularly informative in populations at high risk for CKD progression such as individuals with diabetes. STUDY DESIGN: Cohort study. SETTING & PARTICIPANTS: 594 participants (mean age, 70 years; 53% women) of the Reasons for Geographic and Racial Differences in Stroke (REGARDS) study who had diabetes and an estimated glomerular filtration rate (eGFR)<60mL/min/1.73m2 at baseline. EXPOSURES: Plasma biomarkers of inflammation/fibrosis (TNFR1 and TNFR2, suPAR, MCP-1, YKL-40) and tubular injury (KIM-1) measured at the baseline visit. OUTCOMES: Incident kidney failure with replacement therapy (KFRT). ANALYTICAL APPROACH: Cox proportional hazards regression and least absolute shrinkage and selection operator regression adjusted for established risk factors for kidney function decline, baseline eGFR, and urinary albumin-creatinine ratio (UACR). RESULTS: A total of 98 KFRT events were observed over a mean of 6.2±3.5 (standard deviation) years of follow-up. Plasma biomarkers were modestly associated with baseline eGFR (correlation coefficients ranging from-0.08 to-0.65) and UACR (0.14 to 0.56). In individual biomarker models adjusted for eGFR, UACR, and established risk factors, hazard ratios for incident KFRT per 2-fold higher biomarker concentrations were 1.52 (95% CI, 1.25-1.84) for plasma KIM-1, 1.54 (95% CI, 1.08-2.21) for TNFR1, 1.91 (95% CI, 1.16-3.14) for TNFR2, and 1.39 (95% CI, 1.05-1.84) for YKL-40. In least absolute shrinkage and selection operator regression models accounting for biomarkers in parallel, plasma KIM-1 and TNFR1 remained associated with incident KFRT. LIMITATIONS: Single biomarker measurement, lack of follow-up eGFR assessments. CONCLUSIONS: Individual plasma markers of inflammation/fibrosis (TNFR1, TNFR2, YKL-40) and tubular injury (KIM-1) were associated with risk of incident KFRT in adults with diabetes and an eGFR<60mL/min/1.73m2 after adjustment for established risk factors.
RATIONALE & OBJECTIVE: Most circulating biomarkers of chronic kidney disease (CKD) progression focus on factors reflecting glomerular filtration. Few biomarkers capture nonglomerular pathways of kidney injury or damage, which may be particularly informative in populations at high risk for CKD progression such as individuals with diabetes. STUDY DESIGN: Cohort study. SETTING & PARTICIPANTS: 594 participants (mean age, 70 years; 53% women) of the Reasons for Geographic and Racial Differences in Stroke (REGARDS) study who had diabetes and an estimated glomerular filtration rate (eGFR)<60mL/min/1.73m2 at baseline. EXPOSURES: Plasma biomarkers of inflammation/fibrosis (TNFR1 and TNFR2, suPAR, MCP-1, YKL-40) and tubular injury (KIM-1) measured at the baseline visit. OUTCOMES: Incident kidney failure with replacement therapy (KFRT). ANALYTICAL APPROACH: Cox proportional hazards regression and least absolute shrinkage and selection operator regression adjusted for established risk factors for kidney function decline, baseline eGFR, and urinary albumin-creatinine ratio (UACR). RESULTS: A total of 98 KFRT events were observed over a mean of 6.2±3.5 (standard deviation) years of follow-up. Plasma biomarkers were modestly associated with baseline eGFR (correlation coefficients ranging from-0.08 to-0.65) and UACR (0.14 to 0.56). In individual biomarker models adjusted for eGFR, UACR, and established risk factors, hazard ratios for incident KFRT per 2-fold higher biomarker concentrations were 1.52 (95% CI, 1.25-1.84) for plasma KIM-1, 1.54 (95% CI, 1.08-2.21) for TNFR1, 1.91 (95% CI, 1.16-3.14) for TNFR2, and 1.39 (95% CI, 1.05-1.84) for YKL-40. In least absolute shrinkage and selection operator regression models accounting for biomarkers in parallel, plasma KIM-1 and TNFR1 remained associated with incident KFRT. LIMITATIONS: Single biomarker measurement, lack of follow-up eGFR assessments. CONCLUSIONS: Individual plasma markers of inflammation/fibrosis (TNFR1, TNFR2, YKL-40) and tubular injury (KIM-1) were associated with risk of incident KFRT in adults with diabetes and an eGFR<60mL/min/1.73m2 after adjustment for established risk factors.
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