Serum Metabolomic Markers of Protein-Rich Foods and Incident CKD: Results From the Atherosclerosis Risk in Communities Study

Abstract

Rationale & ObjectiveWhile urine excretion of nitrogen estimates total protein intake, biomarkers of specific dietary protein sources have been sparsely studied. Using untargeted metabolomics, this study aimed to identify serum metabolomic markers of six protein-rich foods and to examine whether dietary protein-related metabolites are associated with incident chronic kidney disease (CKD). Study DesignProspective cohort study. Setting & Participants3,726 participants from the Atherosclerosis Risk in Communities (ARIC) study without CKD at baseline. ExposureDietary intake of six protein-rich foods (fish, nuts, legumes, red and processed meat, eggs, poultry), serum metabolites. OutcomesIncident CKD [eGFR <60 mL/min/1.73 m2 with ≥25% eGFR decline relative to visit 1, hospitalization or death related to CKD, or end-stage kidney disease. Analytical ApproachMultivariable linear regression models estimated cross-sectional associations between protein-rich foods and serum metabolites. C-statistics assessed the metabolites’ ability to improve discrimination of highest versus lower three quartiles of intake of protein-rich foods beyond covariates (demographics, clinical factors, health behaviors, and intake of nonprotein food groups). Cox regression models identified prospective associations between protein-related metabolites and incident chronic kidney disease (CKD). ResultsThirty significant associations were identified between protein-rich foods and serum metabolites (fish, n=8; nuts, n=5; legumes, n=0; red and processed meat, n=5; eggs, n=3; poultry, n=9). Metabolites collectively significantly improved discrimination of high intake of protein-rich foods compared to covariates alone (difference in C-statistics=0.033, 0.051, 0.003, 0.024, and 0.025 for fish, nuts, red and processed meat, eggs, and poultry-related metabolites, respectively; p<1.00 x 10-16 for all). Dietary intake of fish was positively associated with 1-docosahexaenoylglycerophosphocholine (22:6n3), which was inversely associated with incident CKD (HR 0.82, 95% CI 0.75-0.89, p=7.81×10-6). LimitationsResidual confounding and sample storage duration. ConclusionsWe identified candidate biomarkers of fish, nuts, red and processed meat, eggs, and poultry. A fish-related metabolite, 1-docosahexaenoylglycerophosphocholine (22:6n3), was associated with lower risk of CKD.