Urinary Metabolite Profile Predicting the Progression of CKD

Background Because CKD is caused by genetic and environmental factors, biomarker development through metabolomic analysis, which reflects gene-derived downstream effects and host adaptation to the environment, is warranted. Methods We measured the metabolites in urine samples collected from 789 patients at the time of kidney biopsy and from urine samples from 147 healthy participants using nuclear magnetic resonance. The composite outcome was defined as a 30% decline in eGFR, doubling of serum creatinine levels, or end-stage kidney disease. Results Among the 28 candidate metabolites, we identified seven metabolites showing (1) good discrimination between healthy controls and patients with stage 1 CKD and (2) a consistent change in pattern from controls to patients with advanced-stage CKD. Among the seven metabolites, betaine, choline, glucose, fumarate, and citrate showed significant associations with the composite outcome after adjustment for age, sex, eGFR, the urine protein-creatinine ratio, and diabetes. Furthermore, adding choline, glucose, or fumarate to traditional biomarkers, including eGFR and proteinuria, significantly improved the ability of the net reclassification improvement (P, 0.05) and integrated discrimination improvement (P, 0.05) to predict the composite outcome. Conclusion Urinary metabolites, including betaine, choline, fumarate, citrate, and glucose, were found to be significant predictors of the progression of CKD. As a signature of kidney injury-related metabolites, it would be warranted to monitor to predict the renal outcome.

Automated summary

Metabolomic analysis can identify urinary metabolites that are significant predictors of CKD progression, with better predictive ability than traditional biomarkers.