Associations of Urine and Plasma Metabolites With Kidney Failure and Death in a Chronic Kidney Disease Cohort

Rationale & objective: Biomarkers that enable better identification of persons with chronic kidney disease (CKD) who are at higher risk for disease progression and adverse events are needed. This study sought to identify urine and plasma metabolites associated with progression of kidney disease.

Study design: Prospective metabolome-wide association study.

Setting & participants: Persons with CKD enrolled in the GCKD (German CKD) study with metabolite measurements, with external validation within the ARIC (Atherosclerosis Risk in Communities) Study.

Exposures: 1,513 urine and 1,416 plasma metabolites (Metabolon Inc) measured at study entry using untargeted mass spectrometry.

Outcomes: Main end points were kidney failure (KF) and a composite kidney end point (CKE) of KF, estimated glomerular filtration rate<15mL/min/1.73m², or a 40% decrease in estimated glomerular filtration rate. Death from any cause was a secondary end point. After a median of 6.5 years of follow-up, 500 persons had experienced KF, 1,083 had experienced the CKE, and 680 had died.

Analytical approach: Time-to-event analyses using multivariable proportional hazard regression models in a discovery-replication design with external validation.

Results: 5,088 GCKD study participants were included in analyses of urine metabolites, and 5,144 were included in analyses of plasma metabolites. Among 182 unique metabolites, 30 were significantly associated with KF, 49 with the CKE, and 163 with death. The strongest association with KF was observed for plasma hydroxyasparagine (HR, 1.95; 95% CI, 1.68-2.25). An unnamed metabolite measured in plasma and urine was significantly associated with KF, the CKE, and death. External validation of the identified associations of metabolites with KF or the CKE revealed directional consistency for 88% of observed associations. Selected associations of 18 metabolites with study outcomes have not been previously reported.

Limitations: Use of observational data and semiquantitative metabolite measurements at a single time point.

Conclusions: The observed associations between metabolites and KF, the CKE, or death in persons with CKD confirmed previously reported findings and also revealed several associations not previously described. These findings warrant confirmatory research in other study cohorts.

Plain-language summary: Incomplete understanding of the variability of chronic kidney disease (CKD) progression motivated the search for new biomarkers that would help identify people at increased risk. We explored metabolites in plasma and urine for their association with unfavorable kidney outcomes or death in persons with CKD. Metabolomic analyses revealed 182 metabolites significantly associated with CKD progression or death. Many of these associations confirmed previously reported findings or were validated by analysis in an external study population. Our comprehensive screen of the metabolome serves as a valuable foundation for future investigations into biomarkers associated with CKD progression.