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Metabolite profiling of CKD progression in the chronic renal insufficiency cohort study

Authors :
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
Source :
JCI Insight, Vol 7, Iss 20 (2022)
Publication Year :
2022
Publisher :
American Society for Clinical investigation, 2022.

Abstract

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).

Subjects

Subjects :
Nephrology
Medicine

Details

Language :
English
ISSN :
23793708
Volume :
7
Issue :
20
Database :
Directory of Open Access Journals
Journal :
JCI Insight
Publication Type :
Academic Journal
Accession number :
edsdoj.0a978b3ac5694b419b959298ed540858
Document Type :
article
Full Text :
https://doi.org/10.1172/jci.insight.161696