BACKGROUND Metabolomic profiling in individuals with chronic kidney disease (CKD) has the potential to identify novel biomarkers and provide insight into disease pathogenesis.METHODS We examined the association between blood metabolites and CKD progression, defined as the subsequent development of end-stage renal disease (ESRD) or estimated glomerular filtrate rate (eGFR) halving, in 1,773 participants of the Chronic Renal Insufficiency Cohort (CRIC) study, 962 participants of the African-American Study of Kidney Disease and Hypertension (AASK), and 5,305 participants of the Atherosclerosis Risk in Communities (ARIC) study.RESULTS In CRIC, more than half of the measured metabolites were associated with CKD progression in minimally adjusted Cox proportional hazards models, but the number and strength of associations were markedly attenuated by serial adjustment for covariates, particularly eGFR. Ten metabolites were significantly associated with CKD progression in fully adjusted models in CRIC; 3 of these metabolites were also significant in fully adjusted models in AASK and ARIC, highlighting potential markers of glomerular filtration (pseudouridine), histamine metabolism (methylimidazoleacetate), and azotemia (homocitrulline). Our findings also highlight N-acetylserine as a potential marker of kidney tubular function, with significant associations with CKD progression observed in CRIC and ARIC.CONCLUSION Our findings demonstrate the application of metabolomics to identify potential biomarkers and causal pathways in CKD progression.FUNDING This study was supported by the NIH (U01 DK106981, U01 DK106982, U01 DK085689, R01 DK108803, and R01 DK124399).
Donghai Wen, Zihe Zheng, Aditya Surapaneni, Bing Yu, Linda Zhou, Wen Zhou, Dawei Xie, Haochang Shou, Julian Avila-Pacheco, Sahir Kalim, Jiang He, Chi-Yuan Hsu, Afshin Parsa, Panduranga Rao, James Sondheimer, Raymond Townsend, Sushrut S. Waikar, Casey M. Rebholz, Michelle R. Denburg, Paul L. Kimmel, Ramachandran S. Vasan, Clary B. Clish, Josef Coresh, Harold I. Feldman, Morgan E. Grams, Eugene P. Rhee, the CKD Biomarkers Consortium and CRIC Study Investigators
Baseline characteristics of the study sample