Jason H Greenberg1,2, Alison G Abraham3, Yunwen Xu3, Jeffrey R Schelling4, Harold I Feldman5, Venkata S Sabbisetti6, Joachim H Ix7,8, Manasi P Jogalekar6, Steven Coca9, Sushrut S Waikar10, Michael G Shlipak11, Bradley A Warady12, Ramachandran S Vasan13, Paul L Kimmel14, Joseph V Bonventre6, Michelle Denburg15, Chirag R Parikh16, Susan Furth14. 1. Department of Pediatrics, Yale University School of Medicine, New Haven, Connecticut jason.greenberg@yale.edu. 2. Department of Medicine Clinical and Translational Research Accelerator, Yale University School of Medicine, New Haven, Connecticut. 3. Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland. 4. Department of Internal Medicine, Case Western Reserve University School of Medicine, Cleveland, Ohio. 5. Department of Medicine, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania. 6. Division of Renal Medicine, Brigham and Women's Hospital, Boston, Massachusetts. 7. Division of Nephrology-Hypertension, University of California San Diego, San Diego, California. 8. Nephrology Section, Veterans Affairs San Diego Healthcare System, La Jolla, California. 9. Department of Internal Medicine, Icahn School of Medicine at Mount Sinai, New York, New York. 10. Section of Nephrology, Boston University School of Medicine and Boston Medical Center, Boston, Massachusetts. 11. UCSF Division of General Internal Medicine at the VA, Kidney Health Research Collaborative, San Francisco Veterans Affairs Health Care System and University of California, San Francisco, California. 12. Department of Pediatrics, Children's Mercy Kansas City, Kansas City, Missouri. 13. Departments of Medicine and Epidemiology, Boston University Schools of Medicine and Public Health, Boston, Massachusetts. 14. National Institute of Diabetes and Digestive and Kidney Diseases, Bethesda, Maryland. 15. Department of Pediatrics, The Children's Hospital of Philadelphia, Philadelphia, Pennsylvania. 16. Department of Internal Medicine, Johns Hopkins School of Medicine, Baltimore, New York.
Abstract
BACKGROUND: Novel urine biomarkers may improve identification of children at greater risk of rapid kidney function decline, and elucidate the pathophysiology of CKD progression. METHODS: We investigated the relationship between urine biomarkers of kidney tubular health (EGF and α-1 microglobulin), tubular injury (kidney injury molecule-1; KIM-1), and inflammation (monocyte chemoattractant protein-1 [MCP-1] and YKL-40) and CKD progression. The prospective CKD in Children Study enrolled children aged 6 months to 16 years with an eGFR of 30-90ml/min per 1.73m2. Urine biomarkers were assayed a median of 5 months [IQR: 4-7] after study enrollment. We indexed the biomarker to urine creatinine by dividing the urine biomarker concentration by the urine creatinine concentration to account for the concentration of the urine. The primary outcome was CKD progression (a composite of a 50% decline in eGFR or kidney failure) during the follow-up period. RESULTS: Overall, 252 of 665 children (38%) reached the composite outcome over a median follow-up of 6.5 years. After adjustment for covariates, children with urine EGF concentrations in the lowest quartile were at a seven-fold higher risk of CKD progression versus those with concentrations in the highest quartile (fully adjusted hazard ratio [aHR], 7.1; 95% confidence interval [95% CI], 3.9 to 20.0). Children with urine KIM-1, MCP-1, and α-1 microglobulin concentrations in the highest quartile were also at significantly higher risk of CKD progression versus those with biomarker concentrations in the lowest quartile. Addition of the five biomarkers to a clinical model increased the discrimination and reclassification for CKD progression. CONCLUSIONS: After multivariable adjustment, a lower urine EGF concentration and higher urine KIM-1, MCP-1, and α-1 microglobulin concentrations were each associated with CKD progression in children.
BACKGROUND: Novel urine biomarkers may improve identification of children at greater risk of rapid kidney function decline, and elucidate the pathophysiology of CKD progression. METHODS: We investigated the relationship between urine biomarkers of kidney tubular health (EGF and α-1 microglobulin), tubular injury (kidney injury molecule-1; KIM-1), and inflammation (monocyte chemoattractant protein-1 [MCP-1] and YKL-40) and CKD progression. The prospective CKD in Children Study enrolled children aged 6 months to 16 years with an eGFR of 30-90ml/min per 1.73m2. Urine biomarkers were assayed a median of 5 months [IQR: 4-7] after study enrollment. We indexed the biomarker to urine creatinine by dividing the urine biomarker concentration by the urine creatinine concentration to account for the concentration of the urine. The primary outcome was CKD progression (a composite of a 50% decline in eGFR or kidney failure) during the follow-up period. RESULTS: Overall, 252 of 665 children (38%) reached the composite outcome over a median follow-up of 6.5 years. After adjustment for covariates, children with urine EGF concentrations in the lowest quartile were at a seven-fold higher risk of CKD progression versus those with concentrations in the highest quartile (fully adjusted hazard ratio [aHR], 7.1; 95% confidence interval [95% CI], 3.9 to 20.0). Children with urine KIM-1, MCP-1, and α-1 microglobulin concentrations in the highest quartile were also at significantly higher risk of CKD progression versus those with biomarker concentrations in the lowest quartile. Addition of the five biomarkers to a clinical model increased the discrimination and reclassification for CKD progression. CONCLUSIONS: After multivariable adjustment, a lower urine EGF concentration and higher urine KIM-1, MCP-1, and α-1 microglobulin concentrations were each associated with CKD progression in children.
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