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植物性饮食与慢性肾脏病发病的血清代谢组学特征。

Serum metabolomic signatures of plant-based diets and incident chronic kidney disease.

机构信息

Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA.

Welch Center for Prevention, Epidemiology, and Clinical Research, Johns Hopkins University, Baltimore, MD, USA.

出版信息

Am J Clin Nutr. 2022 Jul 6;116(1):151-164. doi: 10.1093/ajcn/nqac054.

Abstract

BACKGROUND

Greater adherence to plant-based diets is associated with a lower risk of incident chronic kidney disease (CKD). Metabolomics can help identify blood biomarkers of plant-based diets and enhance understanding of underlying mechanisms.

OBJECTIVES

Using untargeted metabolomics, we aimed to identify metabolites associated with 4 plant-based diet indices (PDIs) (overall PDI, provegetarian diet, healthful PDI, and unhealthful PDI) and incident CKD in 2 subgroups within the Atherosclerosis Risk in Communities study.

METHODS

We calculated 4 PDIs based on participants' responses on an FFQ. We used multivariable linear regression to examine the association between 4 PDIs and 374 individual metabolites, adjusting for confounders. We used Cox proportional hazards regression to evaluate associations between PDI-related metabolites and incident CKD. Estimates were meta-analyzed across 2 subgroups (n1 = 1762; n2 = 1960). We calculated C-statistics to assess whether metabolites improved the prediction of those in the highest quintile compared to the lower 4 quintiles of PDIs, and whether PDI- and CKD-related metabolites predicted incident CKD beyond the CKD prediction model.

RESULTS

We identified 82 significant PDI-metabolite associations (overall PDI = 27; provegetarian = 17; healthful PDI = 20; unhealthful PDI = 18); 11 metabolites overlapped across the overall PDI, provegetarian diet, and healthful PDI. The addition of metabolites improved prediction of those in the highest quintile as opposed to the lower 4 quintiles of PDIs compared with participant characteristics alone (range of differences in C-statistics = 0.026-0.104; P value ≤ 0.001 for all tests). Six PDI-related metabolites (glycerate, 1,5-anhydroglucitol, γ-glutamylalanine, γ-glutamylglutamate, γ-glutamylleucine, γ-glutamylvaline), involved in glycolysis, gluconeogenesis, pyruvate metabolism, and γ-glutamyl peptide metabolism, were significantly associated with incident CKD and improved prediction of incident CKD beyond the CKD prediction model (difference in C-statistics for 6 metabolites = 0.005; P value = 0.006).

CONCLUSIONS

In a community-based study of US adults, we identified metabolites that were related to plant-based diets and predicted incident CKD. These metabolites highlight pathways through which plant-based diets are associated with incident CKD.

摘要

背景

更多地遵循植物性饮食与较低的慢性肾脏病(CKD)发病风险相关。代谢组学可以帮助确定植物性饮食的血液生物标志物,并增强对潜在机制的理解。

目的

在社区动脉粥样硬化风险研究(Atherosclerosis Risk in Communities study)的 2 个亚组中,我们使用非靶向代谢组学方法,旨在确定与 4 种植物性饮食指数(PDI)(整体 PDI、植物性饮食、健康 PDI 和不健康 PDI)以及 CKD 发病相关的代谢物。

方法

我们根据参与者在 FFQ 上的回答计算了 4 个 PDI。我们使用多变量线性回归来检查 4 个 PDI 与 374 种个体代谢物之间的关联,同时调整了混杂因素。我们使用 Cox 比例风险回归来评估 PDI 相关代谢物与 CKD 发病之间的关联。在 2 个亚组(n1=1762;n2=1960)中进行了估计的荟萃分析。我们计算了 C 统计量,以评估与 PDI 相关的代谢物是否能提高对最高五分位数的预测能力,而不是对 PDI 的较低 4 个五分位数的预测能力,以及 PDI 和 CKD 相关的代谢物是否能在 CKD 预测模型之外预测 CKD 发病。

结果

我们确定了 82 个具有统计学意义的 PDI-代谢物关联(整体 PDI=27;植物性饮食=17;健康 PDI=20;不健康 PDI=18);有 11 种代谢物在整体 PDI、植物性饮食和健康 PDI 中重叠。与参与者特征单独相比,代谢物的加入提高了对 PDI 最高五分位数的预测能力,而不是对 PDI 的较低 4 个五分位数的预测能力(C 统计量的差异范围为 0.026-0.104;所有检验的 P 值均≤0.001)。6 种与 PDI 相关的代谢物(甘油酸、1,5-脱水葡萄糖醇、γ-谷氨酰丙氨酸、γ-谷氨酰谷氨酸、γ-谷氨酰亮氨酸、γ-谷氨酰缬氨酸)与糖酵解、糖异生、丙酮酸代谢和γ-谷氨酰肽代谢有关,与 CKD 发病显著相关,并提高了 CKD 预测模型之外的 CKD 发病预测能力(6 种代谢物的 C 统计量差异=0.005;P 值=0.006)。

结论

在一项基于美国成年人的社区研究中,我们确定了与植物性饮食相关的代谢物,这些代谢物与 CKD 发病相关。这些代谢物突出了植物性饮食与 CKD 发病相关的途径。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/be31/9257476/3161b30e49ab/nqac054fig1.jpg

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