多阶段代谢组学和遗传分析确定了代谢综合征的代谢生物标志物及其遗传决定因素。

Multi-stage metabolomics and genetic analyses identified metabolite biomarkers of metabolic syndrome and their genetic determinants.

机构信息

Department of Epidemiology & Biostatistics, School of Public Health, Zhejiang University, Hangzhou 310058, Zhejiang, China.

Institute of Medical Research, Northwestern Polytechnical University, 127 West Youyi Road, Xi'an, Shanxi 710072, China.

出版信息

EBioMedicine. 2021 Dec;74:103707. doi: 10.1016/j.ebiom.2021.103707. Epub 2021 Nov 18.

DOI:10.1016/j.ebiom.2021.103707

PMID:34801968

原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8605407/

Abstract

BACKGROUND

Metabolic syndrome (MetS) is a cluster of multiple cardiometabolic risk factors that increase the risk of type 2 diabetes and cardiovascular diseases. Identifying novel biomarkers of MetS and their genetic associations could provide insights into the mechanisms of cardiometabolic diseases.

METHODS

Potential MetS-associated metabolites were screened and internally validated by untargeted metabolomics analyses among 693 patients with MetS and 705 controls. External validation was conducted using two well-established targeted metabolomic methods among 149 patients with MetS and 253 controls. The genetic associations of metabolites were determined by linear regression using our previous genome-wide SNP data. Causal relationships were assessed using a one-sample Mendelian Randomization (MR) approach.

FINDINGS

Nine metabolites were ultimately found to be associated with MetS or its components. Five metabolites, including LysoPC(14:0), LysoPC(15:0), propionyl carnitine, phenylalanine, and docosapentaenoic acid (DPA) were selected to construct a metabolite risk score (MRS), which was found to have a dose-response relationship with MetS and metabolic abnormalities. Moreover, MRS displayed a good ability to differentiate MetS and metabolic abnormalities. Three SNPs (rs11635491, rs7067822, and rs1952458) were associated with LysoPC(15:0). Two SNPs, rs1952458 and rs11635491 were found to be marginally correlated with several MetS components. MR analyses showed that a higher LysoPC(15:0) level was causally associated with the risk of overweight/obesity, dyslipidaemia, high uric acid, high insulin and high HOMA-IR.

INTERPRETATION

We identified five metabolite biomarkers of MetS and three SNPs associated with LysoPC(15:0). MR analyses revealed that abnormal LysoPC metabolism may be causally linked the metabolic risk.

FUNDING

This work was supported by grants from the National Key Research and Development Program of China (2017YFC0907004).

摘要

背景

代谢综合征（MetS）是一组多种心血管代谢危险因素的聚集，增加了 2 型糖尿病和心血管疾病的风险。识别代谢综合征的新型生物标志物及其遗传关联，可以深入了解心血管代谢疾病的发病机制。

方法

通过对 693 例代谢综合征患者和 705 例对照者进行非靶向代谢组学分析，筛选并内部验证潜在的代谢综合征相关代谢物。采用两种成熟的靶向代谢组学方法对 149 例代谢综合征患者和 253 例对照者进行外部验证。使用我们之前的全基因组 SNP 数据，通过线性回归确定代谢物的遗传相关性。使用单样本孟德尔随机化（MR）方法评估因果关系。

结果

最终发现 9 种代谢物与代谢综合征或其成分相关。包括 LysoPC(14:0)、LysoPC(15:0)、丙酰肉碱、苯丙氨酸和二十二碳五烯酸（DPA）在内的 5 种代谢物被选入构建代谢风险评分（MRS），该评分与代谢综合征和代谢异常呈剂量反应关系。此外，MRS 显示出区分代谢综合征和代谢异常的良好能力。3 个 SNP(rs11635491、rs7067822 和 rs1952458)与 LysoPC(15:0)相关。rs1952458 和 rs11635491 两个 SNP 与多个代谢综合征成分呈边缘相关。MR 分析表明，较高的 LysoPC(15:0)水平与超重/肥胖、血脂异常、高尿酸血症、高胰岛素血症和高 HOMA-IR 风险相关。