Metabolomic Markers of Ultra-Processed Food and Incident CKD

Author:

Su Donghan12,Chen Jingsha12,Du Shutong12,Kim Hyunju12,Yu Bing3,Wong Kari E.4,Boerwinkle Eric3,Rebholz Casey M.12

Affiliation:

1. Welch Center for Prevention, Epidemiology, and Clinical Research, Johns Hopkins University, Baltimore, Maryland

2. Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland

3. Department of Epidemiology, Human Genetics, and Environmental Sciences, The University of Texas Health Science Center at Houston, Houston, Texas

4. Metabolon, Morrisville, North Carolina

Abstract

Background High ultra-processed food consumption is associated with higher risk of CKD. However, there is no biomarker for ultra-processed food, and the mechanism through which ultra-processed food is associated with CKD is not clear. Metabolomics can provide objective biomarkers of ultra-processed food and provide important insights into the mechanisms by which ultra-processed food is associated with risk of incident CKD. Our objective was to identify serum metabolites associated with ultra-processed food consumption and investigate whether ultra-processed food–associated metabolites are prospectively associated with incident CKD. Methods We used data from 3751 Black and White men and women (aged 45–64 years) in the Atherosclerosis Risk in Communities study. Dietary intake was assessed using a semiquantitative 66-item food frequency questionnaire, and ultra-processed food was classified using the NOVA classification system. Multivariable linear regression models were used to identify the association between 359 metabolites and ultra-processed food consumption. Cox proportional hazards models were used to investigate the prospective association of ultra-processed food–associated metabolites with incident CKD. Results Twelve metabolites (saccharine, homostachydrine, stachydrine, N2, N2-dimethylguanosine, catechol sulfate, caffeine, 3-methyl-2-oxovalerate, theobromine, docosahexaenoate, glucose, mannose, and bradykinin) were significantly associated with ultra-processed food consumption after controlling for false discovery rate <0.05 and adjusting for sociodemographic factors, health behaviors, eGFR, and total energy intake. The 12 ultra-processed food–related metabolites significantly improved the prediction of ultra-processed food consumption (difference in C statistics: 0.069, P<1×10−16). Higher levels of mannose, glucose, and N2, N2-dimethylguanosine were associated with higher risk of incident CKD after a median follow-up of 23 years. Conclusions We identified 12 serum metabolites associated with ultra-processed food consumption and three of them were positively associated with incident CKD. Mannose and N2, N2-dimethylguanosine are novel markers of CKD that may explain observed associations between ultra-processed food and CKD. Podcast This article contains a podcast at https://dts.podtrac.com/redirect.mp3/www.asn-online.org/media/podcast/CJASN/2023_03_08_CJN0000000000000062.mp3

Publisher

Ovid Technologies (Wolters Kluwer Health)

Subject

Transplantation,Nephrology,Critical Care and Intensive Care Medicine,Epidemiology

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3