Prof. Dr. Matthias Schmid
Institute of medical Biometry, Computer Science and Epidemiology
sekretariat@imbie.uni-bonn.de View member: Prof. Dr. Matthias Schmid
American journal of kidney diseases : the official journal of the National Kidney Foundation
RATIONALE & OBJECTIVE: Mechanisms underlying the variable course of disease progression in patients with chronic kidney disease (CKD) are incompletely understood. The aim of this study was to identify novel biomarkers of adverse kidney outcomes and overall mortality, which may offer insights into pathophysiologic mechanisms.
STUDY DESIGN: Metabolome-wide association study.
SETTING & PARTICIPANTS: 5,087 patients with CKD enrolled in the observational German Chronic Kidney Disease Study.
EXPOSURES: Measurements of 1,487 metabolites in urine.
OUTCOMES: End points of interest were time to kidney failure (KF), a combined end point of KF and acute kidney injury (KF+AKI), and overall mortality.
ANALYTICAL APPROACH: Statistical analysis was based on a discovery-replication design (ratio 2:1) and multivariable-adjusted Cox regression models.
RESULTS: After a median follow-up of 4 years, 362 patients died, 241 experienced KF, and 382 experienced KF+AKI. Overall, we identified 55 urine metabolites whose levels were significantly associated with adverse kidney outcomes and/or mortality. Higher levels of C-glycosyltryptophan were consistently associated with all 3 main end points (hazard ratios of 1.43 [95% CI, 1.27-1.61] for KF, 1.40 [95% CI, 1.27-1.55] for KF+AKI, and 1.47 [95% CI, 1.33-1.63] for death). Metabolites belonging to the phosphatidylcholine pathway showed significant enrichment. Members of this pathway contributed to the improvement of the prediction performance for KF observed when multiple metabolites were added to the well-established Kidney Failure Risk Equation.
LIMITATIONS: Findings among patients of European ancestry with CKD may not be generalizable to the general population.
CONCLUSIONS: Our comprehensive screen of the association between urine metabolite levels and adverse kidney outcomes and mortality identifies metabolites that predict KF and represents a valuable resource for future studies of biomarkers of CKD progression.
Copyright © 2021 National Kidney Foundation, Inc. Published by Elsevier Inc. All rights reserved.
PMID: 33839201