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