@article{c4071141bb6241328e1ad70beee7153c,
title = "Plasma metabolomic signatures of healthy dietary patterns in the chronic renal insufficiency cohort (CRIC) study",
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.",
keywords = "Chronic kidney disease, Food components, Healthy dietary patterns, Lipids, Metabolomics",
author = "{the CRIC Study Investigators and for the CKD Biomarkers Consortium} and Hyunju Kim and Anderson, {Cheryl A.M.} and Hu, {Emily A.} and Zihe Zheng and Appel, {Lawrence J.} and Jiang He and Feldman, {Harold I.} and Anderson, {Amanda H.} and Ricardo, {Ana C.} and Zeenat Bhat and Kelly, {Tanika N.} and Jing Chen and Vasan, {Ramachandran S.} and Kimmel, {Paul L.} and Grams, {Morgan E.} and Josef Coresh and Clish, {Clary B.} and Rhee, {Eugene P.} and Rebholz, {Casey M.} and Go, {Alan S.} and Lash, {James P.} and Nelson, {Robert G.} and Mahboob Rahman and Rao, {Panduranga S.} and Shah, {Vallabh O.} and Townsend, {Raymond R.} and Unruh, {Mark L.}",
note = "Funding Information: Funding for the CRIC Study was obtained under a cooperative agreement from National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK) (U01DK060990, U01DK060984, U01DK061022, U01DK061021, U01DK061028, U01DK060980, U01DK060963, U01DK060902, and U24DK060990). In addition, this work was supported in part by: the Perelman School of Medicine at the University of Pennsylvania Clinical and Translational Science Award NIH/National Center for Advancing Translational Sciences UL1TR000003, Johns Hopkins University UL1 TR-000424, University of Maryland General Cilnical Research Center M01 RR-16500, Clinical and Translational Science Collaborative of Cleveland, UL1TR000439 from the NCATS component of the NIH and NIH roadmap for Medical Research, Michigan Institute for Clinical and Health Research (MICHR) UL1TR000433, University of Illinois at Chicago Clinical and Translational Science Award UL1RR029879, Tulane Center of Biomedical Research Excellencefor Clinical and Translational Research in Cardiometabolic Diseases P20 GM109036, Kaiser Permanente NIH/National Center for Research Resources University of California, San Francisco-Clinical and Translational Science Institute UL1 RR-024131, Department of Internal Medicine, University of New Mexico School of Medicine Albuquerque, NM R01DK119199, and a grant from the Mid-Atlantic Nutrition Obesity Research Center (NORC) under NIH award number P30DK072488. This work was partially supported by the Chronic Kidney Disease Biomarker Consortium funded by NIDDKU01 DK106981 (PI: EPR) and U01 DK085689 (PI: JC). CMR is supported by grants from the NIDDK (K01 DK107782, R03 DK128386) and grants from the National Heart, Lung, and Blood Institute (NHLBI; R21 HL143089, R56 HL153178). ZZ is supported by the Ruth L. Kirschstein Predoctoral Individual National Research Service Award (F31 DK-122683) from the National Institute of Diabetes and Digestive and Kidney Diseases. The findings do not necessarily reflect the opinions of the National Institute of Diabetes and Digestive and Kidney Diseases, the NIH, the Department of Health and Human Services, or the government of the USA. Publisher Copyright: {\textcopyright} The Author(s) 2021. Published by Oxford University Press on behalf of the American Society for Nutrition. All rights reserved.",
year = "2021",
month = oct,
day = "1",
doi = "10.1093/jn/nxab203",
language = "English (US)",
volume = "151",
pages = "2894--2907",
journal = "Journal of Nutrition",
issn = "0022-3166",
publisher = "American Society for Nutrition",
number = "10",
}