饮食摄入与葡萄糖耐量在临床和基于代谢组学的代谢型之间的关系。

Amanda Rundblad, Jacob J Christensen, Kristin S Hustad, Nasser E Bastani, Inger Ottestad, Kirsten B Holven, Stine M Ulven
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引用次数: 0

摘要

背景:代谢分型是对代谢相似个体进行分组的新概念。不同的代谢类型可能对饮食干预有不同的反应;因此,代谢分型可能成为未来精确营养策略的重要工具。然而,与仅基于少数临床相关代谢物的代谢分型相比,基于综合组学数据的代谢分型是否能提供更有用的代谢型鉴定尚不清楚。目的:本研究旨在探讨习惯性饮食摄入和葡萄糖耐量之间的关联是否取决于从标准临床变量或综合核磁共振(NMR)代谢组学确定的代谢型。方法:我们使用了通过针对2型糖尿病高危人群的广告招募的参与者的横断面数据(n = 203)。通过2小时口服葡萄糖耐量试验(OGTT)评估葡萄糖耐量,并通过食物频率问卷记录习惯性饮食摄入量。用核磁共振光谱法定量脂蛋白亚类和各种代谢物,用高效液相色谱法定量血浆类胡萝卜素。我们根据既定的HbA1c、空腹和2小时OGTT血糖临界值将参与者分为有利和不利的临床代谢型。利用核磁共振代谢物的k-均值聚类建立了有利和不利的核磁共振代谢型。结果:临床代谢型主要由血糖变量分离,NMR代谢型主要由脂蛋白相关变量分离。在不利的临床代谢型中,高摄入量的蔬菜与更好的葡萄糖耐量相关,但与有利的临床代谢型无关(相互作用,p = 0.01)。这种相互作用通过叶黄素和玉米黄质(蔬菜摄入量的客观生物标志物)的血浆浓度得到证实。糖耐量与纤维摄入量之间的关系取决于临床代谢型,而糖耐量与饱和脂肪酸摄入量和膳食脂肪来源之间的关系取决于核磁共振代谢型。结论:代谢分型可能是一种有用的工具,可以定制饮食干预措施,使特定人群受益。用于创建代谢型的变量将影响饮食摄入与疾病风险之间的关联。
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Associations between dietary intake and glucose tolerance in clinical and metabolomics-based metabotypes.

Background: Metabotyping is a novel concept to group metabolically similar individuals. Different metabotypes may respond differently to dietary interventions; hence, metabotyping may become an important future tool in precision nutrition strategies. However, it is not known if metabotyping based on comprehensive omic data provides more useful identification of metabotypes compared to metabotyping based on only a few clinically relevant metabolites.

Aim: This study aimed to investigate if associations between habitual dietary intake and glucose tolerance depend on metabotypes identified from standard clinical variables or comprehensive nuclear magnetic resonance (NMR) metabolomics.

Methods: We used cross-sectional data from participants recruited through advertisements aimed at people at risk of type 2 diabetes mellitus (n = 203). Glucose tolerance was assessed with a 2-h oral glucose tolerance test (OGTT), and habitual dietary intake was recorded with a food frequency questionnaire. Lipoprotein subclasses and various metabolites were quantified with NMR spectroscopy, and plasma carotenoids were quantified using high-performance liquid chromatography. We divided participants into favorable and unfavorable clinical metabotypes based on established cutoffs for HbA1c and fasting and 2-h OGTT glucose. Favorable and unfavorable NMR metabotypes were created using k-means clustering of NMR metabolites.

Results: While the clinical metabotypes were separated by glycemic variables, the NMR metabotypes were mainly separated by variables related to lipoproteins. A high intake of vegetables was associated with a better glucose tolerance in the unfavorable, but not the favorable clinical metabotype (interaction, p = 0.01). This interaction was confirmed using plasma concentrations of lutein and zeaxanthin, objective biomarkers of vegetable intake. Although non-significantly, the association between glucose tolerance and fiber intake depended on the clinical metabotypes, while the association between glucose tolerance and intake of saturated fatty acids and dietary fat sources depended on the NMR metabotypes.

Conclusion: Metabotyping may be a useful tool to tailor dietary interventions that will benefit specific groups of individuals. The variables that are used to create metabotypes will affect the association between dietary intake and disease risk.

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