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循环代谢物与中国成年人 2 型糖尿病的发生。

Circulating Metabolites and the Development of Type 2 Diabetes in Chinese Adults.

机构信息

Clinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, U.K.

Medical Research Council Population Health Research Unit, Nuffield Department of Population Health, University of Oxford, Oxford, U.K.

出版信息

Diabetes Care. 2022 Feb 1;45(2):477-480. doi: 10.2337/dc21-1415.

Abstract

OBJECTIVE

To assess prospective associations of circulating metabolites with the risk of type 2 diabetes (T2D) among Chinese adults.

RESEARCH DESIGN AND METHODS

A case-cohort study within the 8-year prospective China Kadoorie Biobank comprised 882 participants with incident T2D and 789 subcohort participants. Nuclear magnetic resonance metabolomic profiling quantified 225 metabolites in stored baseline plasma samples. Cox regression related individual metabolites with T2D risk, adjusting for potential confounders and fasting time.

RESULTS

After correction for multiple testing, 163 metabolites were significantly associated with the risk of T2D (P < 0.05). There were strong positive associations of VLDL particle size, the ratio of apolipoprotein B to apolipoprotein A-1, branched-chain amino acids, glucose, and triglycerides with T2D, and inverse associations of HDL-cholesterol, HDL particle size, and relative n-3 and saturated fatty acid concentrations.

CONCLUSIONS

In Chinese adults, metabolites across diverse pathways were independently associated with T2D risk, providing valuable etiological insights and potential to improve T2D risk prediction.

摘要

目的

评估循环代谢物与中国成年人 2 型糖尿病(T2D)风险之间的前瞻性关联。

研究设计和方法

在中国 8 年前瞻性的中国科克瑞生物样本库中,进行了一项病例-队列研究,该研究纳入了 882 名新发 T2D 患者和 789 名亚队列参与者。通过储存的基线血浆样本中的核磁共振代谢组学分析,定量了 225 种代谢物。Cox 回归分析了个体代谢物与 T2D 风险之间的关系,同时调整了潜在的混杂因素和空腹时间。

结果

经过多次检验校正后,有 163 种代谢物与 T2D 风险显著相关(P<0.05)。VLDL 颗粒大小、载脂蛋白 B 与载脂蛋白 A-1 的比值、支链氨基酸、葡萄糖和甘油三酯与 T2D 呈正相关,而高密度脂蛋白胆固醇、高密度脂蛋白颗粒大小以及 n-3 和饱和脂肪酸浓度的相对比值与 T2D 呈负相关。

结论

在中国成年人中,不同途径的代谢物与 T2D 风险独立相关,为 T2D 的病因学提供了有价值的见解,并有可能改善 T2D 的风险预测。

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