| 引用本文: | 李远志,黄江海,李志文,迟敬轩,方志远.中医非药物疗法治疗坐骨神[]经痛作用机制[J].生物信息学,2026,24(1):57-69. |
| LI Yuanzhi,HUANG Jianghai,LI Zhiwen,CHI Jingxuan,FANG Zhiyuan.Mechanism of non-pharmacological therapy of traditional chinese medicine in treating sciatica[J].Chinese Journal of Bioinformatics,2026,24(1):57-69. |
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| 中医非药物疗法治疗坐骨神[]经痛作用机制 |
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李远志1 ,黄江海2 ,李志文1 , 迟敬轩1,方志远2
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(1.北京中医药大学 第二临床医学院,北京 100078;2.北京中医药大学东方医院,北京 100078)[HJ1.55mm]
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| 摘要: |
| 基于生物信息学研究中医非药物疗法治疗坐骨神经痛的物质基础与潜在作用机制,构建相关miRNA-mRNA。通过高通量基因表达数据库(Gene expression omnibus,GEO)检索坐骨神经痛相关芯片,分析得到差异表达基因。通过支持向量机特征消除算法(Support vector machine based recursive feature elimination,SVM-RFE)和随机森林模型算法(Random forest,RF)结合受试者工作特征(Receiver operating characteristic curve,ROC)曲线及箱式图筛选出具有较高诊断效能的坐骨神经痛核心基因。利用Mfuzz时序分析识别中医非药物疗法治疗坐骨神经痛过程中具有相同变化特征的基因群。利用蛋白质互作网络分析数据平台(String)进行蛋白质交互作用(Protein-protein interaction,PPI)分析,将PPI分析结果导入到Cytoscape3.10.2软件中,并通过cytoHubba插件挖掘核心基因。对中医非药物疗法治疗坐骨神经痛的核心基因进行基因本体论(Gene ontology,GO)分析、京都基因与基因组百科全书(Kyoto encyclopedia of genes and genomes,KEGG)及疾病富集分析(Disease ontology enrichment analysis,DO)通路富集分析。利用8个miRNA在线数据库检索坐骨神经痛核心基因及中医非药物疗法治疗坐骨神经痛核心基因上游miRNA,构建miRNA-mRNA调控网络。结果发现癌胚抗原细胞粘附分子4(CEA cell adhesion molecule 4,CEACAM4)、kelch 样家族成员 14(kelch like family member 14 Gene,KLHL14)、盘状蛋白(Discoidin CUB And LCCL domain containing 1,DCBLD1)、双特异性磷酸酶2(Dual specificity phosphatase 2,DUSP2)、IKAROS家族锌指2(IKAROS family zinc finger 2,IKZF2)及神经元细胞粘附分子(Neuronal cell adhesion molecule gene,NRCAM)有可能成为坐骨神经痛核心基因。中医非药物疗法可能通过成纤维细胞生长因子6(Fibroblast growth factor 6,FGF6)、过氧化物酶体增殖物激活受体γ(Peroxisome proliferator-activated receptor gamma,PPARG)、胰岛素样生长因子 1(Insulin like growth factor 1,IGF1)、载脂蛋白E(Apolipoprotein E,APOE)介导丝氨酸/苏氨酸激酶(Phosphatidylinositide 3-kinases/protein kinase B,PI3K/AKT)信号通路与腺苷酸激活蛋白激酶(Adenosine 5'-monophosphate-activated protein kinase,AMPK)信号通路治疗坐骨神经痛。坐骨神经痛核心基因与中医非药物疗法治疗坐骨神经痛核心基因经筛选后共募集到hsa-miR-27a-3p、hsa-miR-27b-3p等21个miRNA。本研究通过生物信息学方法发现了坐骨神经痛核心基因以及中医非药物疗法治疗坐骨神经痛的核心基因与作用机制,为坐骨神经痛的治疗提供了新的思路。本研究还构建了相关miRNA-mRNA调控网络,该调控网络可能在坐骨神经痛的发病及中医非药物疗法治疗中扮演重要角色。 |
| 关键词: 生物信息学 坐骨神经痛 中医非药物疗法 机器学习 |
| DOI：10.12113/202409005 |
| 分类号:R274.9 |
| 文献标识码:A |
| 基金项目:北京中医药大学高层次人才科研创业项目(No.2021-XJKYQD- 001). |
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| Mechanism of non-pharmacological therapy of traditional chinese medicine in treating sciatica |
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LI Yuanzhi1, HUANG Jianghai2, LI Zhiwen1, CHI Jingxuan1, FANG Zhiyuan2
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(1. Second Clinical College, Beijing University of Chinese Medicine ,Beijing 100078,China;2. Dongfang Hospital, Beijing University of Chinese Medicine,Beijing 100078,China)
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| Abstract: |
| Based on bioinformatics, this study aimed to explore potential molecular mechanism of non-pharmacological therapy of traditional Chinese medicine in treating sciatica, as well as the the miRNA-mRNA regulatory network related to sciatica and the material basis. This study retrieved sciatica-related microarray data from the Gene Expression Omnibus (GEO) database and analyzed differentially expressed genes. Support Vector Machine based Recursive Feature Elimination (SVM-RFE) and Random Forest (RF) algorithms were applied to screen out core genes with high diagnostic performance by combining Receiver Operating Characteristic (ROC) curve and boxplot. Mfuzz was utilized to identify gene clusters with similar change characteristics under non-pharmacotherapy of traditional Chinese medicine in treating sciatica. The Protein-Protein Interaction (PPI) analysis was conducted on the String platform, and the results of PPI data were imported into Cytoscape 3.10.2 software. Core genes were then identified using the cytoHubba plugin. Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and Disease Ontology enrichment analyses were performed to obtain the mechanism of non-pharmacological therapy of traditional Chinese medicine in treating sciatica. Using 8 miRNA online databases, this study retrieved the core genes related to sciatica and the core genes in non-pharmacological therapy of traditional Chinese medicine in treating sciatica, and then constructed a critical miRNA-mRNA regulatory network. CEA Cell Adhesion Molecule 4(CEACAM4), kelch like family member 14 Gene(KLHL14),Discoidin CUB And LCCL Domain Containing 1(DCBLD1),Dual Specificity Phosphatase 2(DUSP2), IKAROS Family Zinc Finger 2(IKZF2), and Neuronal Cell Adhesion Molecule Gene (NRCAM) may be biomarkers for the diagnosis of sciatica. Non-pharmacological therapy of traditional Chinese medicine in treating sciatica may be based on fibroblast growth factor 6(FGF6), Peroxisome Proliferator-Activated Receptor Gamma (PPARG), Insulin like growth factor 1(IGF1), Apolipoprotein E(APOE) mediates the Phosphatidylinositide 3-kinases/protein kinase B (PI3K/AKT) signaling pathway and Adenosine 5-monophosphate-activated protein kinase(AMPK) signaling pathway in treating sciatica. A total of 21 miRNAs, including hsa-mi-27a-3p and hsa-miR-27b-3p, were recruited from the sciatica core gene and the core gene of non-pharmacological therapy of traditional Chinese medicine in treating sciatica.In this study, bioinformatics were used to successfully screen a number of core genes that may be associated with sciatica. At the same time, we also discovered the core genes and mechanism of action of non-pharmacological therapy of traditional Chinese medicine in treating sciatica, which provides a new idea for the treatment of sciatica. Finally, we constructed a miRNA-mRNA regulatory network, which may play an important role in the pathogenesis of sciatica and the therapeutic mechanism of non-pharmacological therapy of traditional Chinese medicine in treating sciatica. |
| Key words: Bioinformatics Sciatica Non-pharmacological therapy of traditional chinese medicine Machine learning |
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