Casey M Rebholz1,2, Zihe Zheng1,2, Morgan E Grams2,3, Lawrence J Appel2,4, Mark J Sarnak5, Lesley A Inker5, Andrew S Levey5, Josef Coresh1,2,4. 1. Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health. 2. Welch Center for Prevention, Epidemiology, and Clinical Research, Johns Hopkins University. 3. Division of Nephrology, Baltimore, MD. 4. Division of General Internal Medicine, Department of Medicine, Johns Hopkins School of Medicine, Baltimore, MD. 5. Division of Nephrology, Tufts Medical Center, Boston, MA.
Abstract
BACKGROUND: Accurate assessment of dietary intake is essential, but self-report of dietary intake is prone to measurement error and bias. Discovering metabolic consequences of diets with lower compared with higher protein intake could elucidate new, objective biomarkers of protein intake. OBJECTIVES: The goal of this study was to identify serum metabolites associated with dietary protein intake. METHODS: Metabolites were measured with the use of untargeted, reverse-phase ultra-performance liquid chromatography-tandem mass spectrometry quantification in serum specimens collected at the 12-mo follow-up visit in the Modification of Diet in Renal Disease (MDRD) Study from 482 participants in study A (glomerular filtration rate: 25-55 mL · min-1 · 1.73 m-2) and 192 participants in study B (glomerular filtration rate: 13-24 mL · min-1 · 1.73 m-2). We used multivariable linear regression to test for differences in log-transformed metabolites (outcome) according to randomly assigned dietary protein intervention groups (exposure). Statistical significance was assessed at the Bonferroni-corrected threshold: 0.05/1193 = 4.2 × 10-5. RESULTS: In study A, 130 metabolites (83 known from 28 distinct pathways, including 7 amino acid pathways; 47 unknown) were significantly different between participants randomly assigned to the low-protein diet compared with the moderate-protein diet. In study B, 32 metabolites (22 known from 8 distinct pathways, including 4 amino acid pathways; 10 unknown) were significantly different between participants randomly assigned to the very-low-protein diet compared with the low-protein diet. A total of 11 known metabolites were significantly associated with protein intake in the same direction in both studies A and B: 3-methylhistidine, N-acetyl-3-methylhistidine, xanthurenate, isovalerylcarnitine, creatine, kynurenate, 1-(1-enyl-palmitoyl)-2-arachidonoyl-GPE (P-16:0/20:4), 1-(1-enyl-stearoyl)-2-arachidonoyl-GPE (P-18:0/20:4), 1-(1-enyl-palmitoyl)-2-arachidonoyl-GPC (P-16:0/20:4), sulfate, and γ-glutamylalanine. CONCLUSIONS: Among patients with chronic kidney disease, an untargeted serum metabolomics platform identified multiple pathways and metabolites associated with dietary protein intake. Further research is necessary to characterize unknown compounds and to examine these metabolites in association with dietary protein intake among individuals without kidney disease.This trial was registered at clinicaltrials.gov as NCT03202914.
RCT Entities:
BACKGROUND: Accurate assessment of dietary intake is essential, but self-report of dietary intake is prone to measurement error and bias. Discovering metabolic consequences of diets with lower compared with higher protein intake could elucidate new, objective biomarkers of protein intake. OBJECTIVES: The goal of this study was to identify serum metabolites associated with dietary protein intake. METHODS: Metabolites were measured with the use of untargeted, reverse-phase ultra-performance liquid chromatography-tandem mass spectrometry quantification in serum specimens collected at the 12-mo follow-up visit in the Modification of Diet in Renal Disease (MDRD) Study from 482 participants in study A (glomerular filtration rate: 25-55 mL · min-1 · 1.73 m-2) and 192 participants in study B (glomerular filtration rate: 13-24 mL · min-1 · 1.73 m-2). We used multivariable linear regression to test for differences in log-transformed metabolites (outcome) according to randomly assigned dietary protein intervention groups (exposure). Statistical significance was assessed at the Bonferroni-corrected threshold: 0.05/1193 = 4.2 × 10-5. RESULTS: In study A, 130 metabolites (83 known from 28 distinct pathways, including 7 amino acid pathways; 47 unknown) were significantly different between participants randomly assigned to the low-protein diet compared with the moderate-protein diet. In study B, 32 metabolites (22 known from 8 distinct pathways, including 4 amino acid pathways; 10 unknown) were significantly different between participants randomly assigned to the very-low-protein diet compared with the low-protein diet. A total of 11 known metabolites were significantly associated with protein intake in the same direction in both studies A and B: 3-methylhistidine, N-acetyl-3-methylhistidine, xanthurenate, isovalerylcarnitine, creatine, kynurenate, 1-(1-enyl-palmitoyl)-2-arachidonoyl-GPE (P-16:0/20:4), 1-(1-enyl-stearoyl)-2-arachidonoyl-GPE (P-18:0/20:4), 1-(1-enyl-palmitoyl)-2-arachidonoyl-GPC (P-16:0/20:4), sulfate, and γ-glutamylalanine. CONCLUSIONS: Among patients with chronic kidney disease, an untargeted serum metabolomics platform identified multiple pathways and metabolites associated with dietary protein intake. Further research is necessary to characterize unknown compounds and to examine these metabolites in association with dietary protein intake among individuals without kidney disease.This trial was registered at clinicaltrials.gov as NCT03202914.
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