Hyunju Kim1,2, Cheryl Am Anderson3, Emily A Hu4, Zihe Zheng5, Lawrence J Appel1,2, Jiang He6,7, Harold I Feldman5, Amanda H Anderson6, Ana C Ricardo8, Zeenat Bhat9, Tanika N Kelly6,7, Jing Chen6,7, Ramachandran S Vasan10, Paul L Kimmel11, Morgan E Grams1,2, Josef Coresh1,2, Clary B Clish12, Eugene P Rhee13, Casey M Rebholz1,2. 1. Welch Center for Prevention, Epidemiology, and Clinical Research, Johns Hopkins University, Baltimore, MD, USA. 2. Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA. 3. Herbert Wertheim School of Public Health and Human Longevity Science, University of California San Diego, San Diego, CA, USA. 4. Foodsmart, San Francisco, CA, USA. 5. Department of Biostatistics, Epidemiology, and Informatics, University of Pennsylvania, Philadelphia, PA, USA. 6. Department of Epidemiology, Tulane University School of Public Health and Tropical Medicine, New Orleans, LA, USA. 7. Department of Medicine, Tulane University, New Orleans, LA, USA. 8. Department of Medicine, University of Illinois, Chicago, IL, USA. 9. Department of Medicine, Wayne State University, Detroit, MI, USA. 10. Department of Medicine, Boston University, Boston, MA, USA. 11. Division of Kidney, Urologic, and Hematologic Diseases, National Institute of Diabetes and Digestive and Kidney Diseases, NIH, Bethesda, MD, USA. 12. The Broad Institute of Harvard and Massachusetts Institute of Technology , Boston, MA, USA. 13. Nephrology Division and Endocrine Unit, Massachusetts General Hospital, Boston, MA, USA.
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.
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.
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