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代谢组学和网络药理学揭示了阿魏酸在血脂异常小鼠模型中的降血脂机制的部分见解。

Metabolomics and network pharmacology reveal partial insights into the hypolipidemic mechanisms of ferulic acid in a dyslipidemia mouse model.

作者信息

Zeng Zhihao, Xiao Guanlin, Liu Yanchang, Wu Minshan, Wei Xingqin, Xie Canhui, Wu Guangying, Jia Dezheng, Li Yangxue, Li Sumei, Bi Xiaoli

机构信息

School of the Fifth Clinical Medicine, Guangzhou University of Chinese Medicine, Guangzhou, China.

Guangdong Provincial Engineering Technology Research Institute of Traditional Chinese Medicine/Guangdong Provincial Key Laboratory of Research and Development in Traditional Chinese Medicine, Guangzhou, China.

出版信息

Front Pharmacol. 2024 Sep 20;15:1466114. doi: 10.3389/fphar.2024.1466114. eCollection 2024.

Abstract

INTRODUCTION

Hyperlipidemia is a condition characterized by abnormal levels of lipids and lipoproteins in the plasma, posing significant health risks. Ferulic acid (FA) is an organic acid with therapeutic properties for diabetes and hyperlipidemia.

METHODS

To explore biomarkers for FA treatment of hyperlipidemia and elucidate the mechanisms of lipid-lowering-related changes in metabolic pathways by metabolomics and network pharmacology. Initially, a hyperlipidemic mouse model induced by triton WR-1339 was established to evaluate the therapeutic effects of FA. Subsequently, serum metabolomics was utilized to identify differential metabolites, and metabolic pathway analysis was performed using MetaboAnalyst 6.0. Thirdly, network pharmacology was employed to identify potential targets of FA for hyperlipidemia. Finally, the compound-target-metabolite (C-T-M) network obtained core targets and validated them with molecular docking.

RESULTS

Biochemical analysis and histological examination showed that FA had lipid-lowering effects on hyperlipidemic mice. It identified 31 potential biomarkers for FA against hyperlipidemia by metabolomics involving lipid and amino acid metabolism. Lipid and atherosclerosis signaling pathways were identified as the key signaling pathways of FA against hyperlipidemia by KEGG analysis. Conjoint analysis showed that FA against hyperlipidemia was associated with 18 core targets and six biomarkers. Molecular docking results showed that FA has a high binding affinity to these core targets.

DISCUSSION

Through the synergy of network pharmacology and metabolomics, this study provides insights into how FA regulates endogenous metabolites, underscoring its promise as a treatment for hyperlipidemia.

摘要

引言

高脂血症是一种以血浆中脂质和脂蛋白水平异常为特征的病症,会带来重大健康风险。阿魏酸(FA)是一种对糖尿病和高脂血症具有治疗特性的有机酸。

方法

通过代谢组学和网络药理学探索阿魏酸治疗高脂血症的生物标志物,并阐明代谢途径中与降脂相关变化的机制。首先,建立由曲拉通WR - 1339诱导的高脂血症小鼠模型以评估阿魏酸的治疗效果。随后,利用血清代谢组学鉴定差异代谢物,并使用MetaboAnalyst 6.0进行代谢途径分析。第三,采用网络药理学确定阿魏酸治疗高脂血症的潜在靶点。最后,化合物 - 靶点 - 代谢物(C - T - M)网络获得核心靶点并用分子对接进行验证。

结果

生化分析和组织学检查表明阿魏酸对高脂血症小鼠具有降脂作用。通过代谢组学确定了31种阿魏酸抗高脂血症的潜在生物标志物,涉及脂质和氨基酸代谢。KEGG分析确定脂质和动脉粥样硬化信号通路是阿魏酸抗高脂血症的关键信号通路。联合分析表明阿魏酸抗高脂血症与18个核心靶点和6个生物标志物相关。分子对接结果表明阿魏酸与这些核心靶点具有高结合亲和力。

讨论

通过网络药理学和代谢组学的协同作用,本研究为阿魏酸如何调节内源性代谢物提供了见解,突出了其作为高脂血症治疗方法的前景。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4365/11453126/ab591a1f1766/fphar-15-1466114-g001.jpg

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