基于GEO数据库的阿尔茨海默病差异表达基因分析及治疗中药预测*

刘艳云; 唐晓伟; 汪洋; 曹明刚; 周爱民; 张娟

doi:10.16833/j.cnki.jbmc.2025.04.004

包头医学院学报 >

2025 , Vol. 41 >Issue 4: 16 - 22

DOI: https://doi.org/10.16833/j.cnki.jbmc.2025.04.004

中国医学论著

基于GEO数据库的阿尔茨海默病差异表达基因分析及治疗中药预测^*

刘艳云 ,
唐晓伟 ,
汪洋 ,
曹明刚 ,
周爱民 ,
张娟

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1.安徽中医药高等专科学校,安徽芜湖 241002;
2.安徽中医药大学第一附属医院

张娟

收稿日期: 2024-05-31

网络出版日期: 2025-05-14

基金资助

国家自然科学基金项目(No.82274493);国家自然科学基金项目(No.81774299);安徽省教育厅2022年高等学校省级质量工程项目(No.2022cxtd083);安徽省教育厅2020年高等学校省级质量工程项目(No.2020jxtd151)

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Analysis of differentially expressed genes of Alzheimer's disease based on GEO database and prediction of therapeutic chinese medicine

LIU Yanyun ,
TANG Xiaowei ,
WANG Yang ,
CAO Minggang ,
ZHOU Aimin ,
ZHANG Juan

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1. Anhui College of Chinese Medicine, Wuhu 241002, China;
2. The First Affiliated Hospital of Anhui University of Chinese Medicine

Received date: 2024-05-31

Online published: 2025-05-14

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摘要

目的：通过生物信息学方法获得阿尔茨海默病(AD)的差异基因,预测治疗AD的潜在中药、成分及靶点。方法：从GEO数据库下载AD的基因芯片数据GSE129055,筛选数据集中的差异表达基因并对差异表达的mRNA进行基因本体功能(GO)及京都基因和基因组百科全书(KEGG)富集分析;通过TargetScan数据库预测miRNA的靶基因并构建miRNA-mRNA网络;将miRNA-mRNA网络中Degree值前50%的mRNA导入Coremine Medical平台筛选潜在治疗中药;TCMSP平台筛选潜在中药作用于差异表达mRNA的成分和靶点,二者结合构建中药治疗AD的药物-成分-mRNA-miRNA共表达网络并进行分子对接验证。结果：在GSE129055数据集中共筛选出178个差异表达mRNA,96个差异表达miRNA;通过筛选发现作用于差异表达mRNA的常用中药有人参、丹参、黄芩、冬虫夏草、五味子等,关键活性成分为左旋山槐素和β-谷甾醇,关键靶点为μ阿片受体基因(OPRM1)和5-羟色胺受体亚基3A阳性抑制性神经元(HTR3A),关键miRNA为miR-9-3p和miR-3607-3p;分子对接结果显示,关键活性成分能够分别与关键靶点结合并展现出较好的亲和力。结论：AD大鼠海马组织多种基因差异性表达,同时中药治疗AD具有多成分、多靶点的特点,可以通过影响神经肽、生物胺及减轻神经炎症等发挥神经保护作用。

关键词： 阿尔茨海默病; GEO; 差异基因分析; 中药预测

本文引用格式

刘艳云 , 唐晓伟 , 汪洋 , 曹明刚 , 周爱民 , 张娟 . 基于GEO数据库的阿尔茨海默病差异表达基因分析及治疗中药预测^*[J]. 包头医学院学报, 2025 , 41(4) : 16 -22 . DOI: 10.16833/j.cnki.jbmc.2025.04.004

Abstract

Objective:To obtain the differential genes of Alzheimer's disease (AD) by bioinformatics methods, and to predict the potential traditional Chinese medicines, components and targets for the treatment of AD. Methods: The AD gene chip data GSE129055 was downloaded from the GEO database. The differentially expressed genes in the data set were screened and the differentially expressed mRNAs were analyzed by gene ontology function (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis. The target genes of miRNAs were predicted by TargetScan database and the miRNA-mRNA network was constructed. The top 50% mRNA of Degree value in miRNA-mRNA network was imported into Coremine Medical platform to screen potential therapeutic Chinese medicine. The TCMSP platform was used to screen the components and targets of potential Chinese medicines acting on differentially expressed mRNAs. The two were combined to construct a drug-component-mRNA-miRNA co-expression network for Chinese medicine treatment of AD and molecular docking verification was performed. Results: A total of 178 differentially expressed mRNAs and 96 differentially expressed miRNAs were screened in the GSE129055 data set. Through screening, it was found that the commonly used traditional Chinese medicines acting on differentially expressed mRNAs were ginseng, salvia miltiorrhiza, scutellaria baicalensis, cordyceps sinensis, schisandra chinensis, etc. The key active ingredients were levoshansophorin and β-sitosterol. The key targets were μ-opioid receptor gene (OPRM1) and 5-hydroxytryptamine receptor subunit 3A positive inhibitory neuron (HTR3A), and the key miRNAs were miR-9-3p and miR-3607-3p. The results of molecular docking showed that the key active components could bind to the key targets and showed good affinity. Conclusion: The expression of multiple genes in hippocampus of AD rats is different. At the same time, traditional Chinese medicine has the characteristics of multi-component and multi-target in the treatment of AD. It can play a neuroprotective role by neuropeptides, biogenic amines and reducing neuroinflammation.

Key words： Alzheimer's disease; GEO; Differential gene analysis; Traditional Chinese medicine prediction

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