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

Abstract

Rationale & objective: While urine excretion of nitrogen estimates the 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 6 protein-rich foods and to examine whether dietary protein-related metabolites are associated with incident chronic kidney disease (CKD).

Study design: Prospective cohort study.

Setting & participants: A total of 3,726 participants from the Atherosclerosis Risk in Communities study without CKD at baseline.

Exposures: Dietary intake of 6 protein-rich foods (fish, nuts, legumes, red and processed meat, eggs, and poultry), serum metabolites.

Outcomes: Incident CKD (estimated glomerular filtration rate < 60 mL/min/1.73 m² with ≥25% estimated glomerular filtration rate decline relative to visit 1, hospitalization or death related to CKD, or end-stage kidney disease).

Analytical approach: Multivariable linear regression models estimated cross-sectional associations between protein-rich foods and serum metabolites. C statistics assessed the ability of the metabolites to improve the discrimination of highest versus lower 3 quartiles of intake of protein-rich foods beyond covariates (demographics, clinical factors, health behaviors, and the intake of nonprotein food groups). Cox regression models identified prospective associations between protein-related metabolites and incident CKD.

Results: Thirty 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; and poultry, n = 9). Metabolites collectively and significantly improved the discrimination of high intake of protein-rich foods compared with 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 × 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).

Limitations: Residual confounding and sample-storage duration.

Conclusions: We identified candidate biomarkers of fish, nuts, red and processed meat, eggs, and poultry. A fish-related metabolite, 1-docosahexaenoylglycerophosphocholine (22:6n3), was associated with a lower risk of CKD.

Keywords: Chronic kidney disease; dietary protein; metabolomics; protein sources.

Figure 1

Meta-analyzed associations between fish-related metabolites and incident chronic kidney disease. Cox regression models are adjusted for age, sex, race (in subgroup 2), study center (in subgroup 2), body mass index, total energy intake, and estimated glomerular filtration rate based on creatinine, smoking status, physical activity, education, alcohol consumption, total vegetable intake, total fruit intake, dairy intake, whole grain intake, refined grain intake, diabetes, hypertension, and coronary heart disease. The red dashed vertical line denotes the null value (hazard ratio = 1.0). The red dashed horizontal line denotes the statistical significance threshold, defined using the Bonferroni method as follows: -ln (0.05/8 fish-related metabolites) = 5.08. ∗Tier 2 metabolites that had no reference standard available but were identified based on physiochemical properties or spectral similarities. CI, confidence interval; HR, hazard ratio.