Plasma Metabolomic Signatures of Healthy Dietary Patterns in the Chronic Renal Insufficiency Cohort (CRIC) Study. Issue 10 (30th June 2021)

• Record Type: Journal Article
• Authors: Kim, Hyunju; Anderson, Cheryl Am; Hu, Emily A; Zheng, Zihe; Appel, Lawrence J; He, Jiang; Feldman, Harold I; Anderson, Amanda H; Ricardo, Ana C; Bhat, Zeenat; Kelly, Tanika N; Chen, Jing; Vasan, Ramachandran S; Kimmel, Paul L; Grams, Morgan E; Coresh, Josef; Clish, Clary B; Rhee, Eugene P; Rebholz, Casey M
• Is Part Of: Journal of nutrition. Volume 151:Issue 10(2021)
• Page Start: 2894
• Page End: 2907
• Publication Date: 2021-06-30
• Subjects: metabolomics -- healthy dietary patterns -- lipids -- chronic kidney disease -- food components; Nutrition -- Periodicals; Diet -- Periodicals; 613.205
• DOI: 10.1093/jn/nxab203
• Languages: English
• ISSNs: 0022-3166

Abstract

ABSTRACT: Background: In individuals with chronic kidney disease (CKD), healthy dietary patterns are inversely associated with CKD progression. Metabolomics, an approach that measures many small molecules in biofluids, can identify biomarkers of healthy dietary patterns. Objectives: We aimed to identify known metabolites associated with greater adherence to 4 healthy dietary patterns in CKD patients. Methods: We examined associations between 486 known plasma metabolites and Healthy Eating Index (HEI)-2015, Alternative Healthy Eating Index (AHEI)-2010, the Dietary Approaches to Stop Hypertension (DASH) diet, and alternate Mediterranean diet (aMED) in 1056 participants (aged 21–74 y at baseline) in the Chronic Renal Insufficiency Cohort (CRIC) Study. Usual dietary intake was assessed using a semiquantitative FFQ. We conducted multivariable linear regression models to study associations between healthy dietary patterns and individual plasma metabolites, adjusting for sociodemographic characteristics, health behaviors, and clinical factors. We used principal component analysis to identify groups of metabolites associated with individual food components within healthy dietary patterns. Results: After Bonferroni correction, we identified 266 statistically significant diet-metabolite associations (HEI: n = 60; AHEI: n = 78; DASH: n = 77; aMED: n = 51); 78 metabolites were associated with >1 dietary pattern. Lipids with a longer acyl chain length and double bonds (unsaturated) were positively associated with all 4 dietary patterns. A metabolite pattern low in saturated diacylglycerols and triacylglycerols, and a pattern high in unsaturated triacylglycerols was positively associated with intake of healthy food components. Plasmalogens were negatively associated with the consumption of nuts and legumes and healthy fat, and positively associated with the intake of red and processed meat. Conclusions: We identified many metabolites associated with healthy dietary patterns, indicative of food consumption. If replicated, these metabolites may be considered biomarkers of healthy dietary patterns in patients with CKD.