| 张元斌,朱素燕,徐萍,等.基于数据挖掘和网络药理学的甬派中医治疗糖尿病的用药规律及机制分析[J].浙江中医药大学学报,2022,46(11):1225-1236. |
| 基于数据挖掘和网络药理学的甬派中医治疗糖尿病的用药规律及机制分析 |
| Analysis of Medication Rules and Mechanisms of Chinese Medicine of Ningbo School in Treatment of Diabetes Based on Data Mining and Network Pharmacology |
| DOI：10.16466/j.issn1005-5509.2022.11.007 |
| 中文关键词: 中药 甬派中医 糖尿病 数据挖掘 用药规律 网络药理学 活性成分 晚期糖基化终末产物-晚期糖基化终末产物受体 |
| 英文关键词: Chinese medicine Chinese medicine of Ningbo school diabetes data mining medication rules network pharmacology active components AGE-RAGE |
| 基金项目:宁波市科技创新2025重大专项(2021Z018)；浙江省中医药管理局陈雪琴名老中医专家传承工作室(GZS2021033) |
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| 中文摘要: |
| [目的] 基于数据挖掘分析甬派中医治疗糖尿病的用药规律，同时采用网络药理学分析核心药物治疗糖尿病的潜在活性成分及机制。 [方法] 收集宁波市第一医院2016至2020年中药治疗糖尿病的处方，采用中医传承辅助系统构建处方数据库，分析用药规律并筛选核心药物。采用中医药数据和分析平台(Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform，TCMSP)以及基因组注释数据平台(Genome Annotation Database Platform，GeneCard)等数据库构建“疾病-核心药物-成分-靶点”网络，采用STRING数据库构建蛋白互作(protein protein interaction，PPI)网络，采用R语言对相关靶点进行核心靶点的基因本体(gene ontology，GO)和京都基因和基因组百科全书(Kyoto encyclopedia of genes and genomes，KEGG)富集分析。 [结果] 共纳入处方430首，其中药性以寒、温、平为主，药味以甘类为主。使用频次最高(＞100次)的中药有甘草、茯苓、陈皮、石斛、白术、黄芪、地黄、党参和枸杞子。关联规则表明，使用频率较高的两药组合有:陈皮-甘草、陈皮-茯苓、白术-茯苓、甘草-茯苓；三药组合为陈皮-白术-茯苓。药物组合网络筛选出核心药物组成为白术-茯苓-陈皮-甘草，发挥益气健脾的功效。网络药理学分析结果表明，核心药物中的32个活性成分与糖尿病靶点相关，在活性成分贡献度排名中，白术和茯苓的成分排名普遍靠前，白术主要成分为白术三醇和苍术酮衍生物，茯苓主要成分为甾醇类，陈皮为柚皮素和甾醇类，甘草以黄酮类成分为主。KEGG结果表明核心药物主要影响脂质和动脉粥样硬化、内分泌抵抗、环磷酸腺苷(cyclic adenosine monophosphate，cAMP)信号通路和晚期糖基化终末产物-晚期糖基化终末产物受体(advanced glycation end products-receptor for advanced glycation end products，AGE-RAGE)系统，其中AGE-RAGE系统包含的核心靶点最多，且与糖尿病密切相关。[结论] 甬派中医对糖尿病的治疗以益气健脾为主，同时配合养阴清热，具有多成分、多靶点治疗的特点，其机制可能主要与AGE-RAGE轴密切相关，上述研究为甬派中医治疗糖尿病的方法提供了理论支撑。 |
| 英文摘要: |
| [Objective] To explore the medication rules of Chinese medicine of Ningbo school in treatment of diabetes by data mining and analyze the potential active ingredients and mechanisms of the screened core medicine combinations(CMC). [Methods] The prescriptions of Chinese medicine for diabetes treatment from 2016 to 2020 in Ningbo First Hospital were collected， and input into the Traditional Chinese Medicine Inheritance Support Platform to analyze medication rules and screen CMC. Then， this study constructed the disease-CMC-components-targets network(DCCTN) diagram with Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform(TCMSP)， Genome Annotation Database Platform(GeneCard) and other databases. The STRING database was used to obtain a protein-protein interaction(PPI) network. The related targets were enriched and analyzed by gene ontology(GO) and Kyoto encyclopedia of genes and genomes(KEGG) enrichment analysis in R language package. [Results] A total of 430 prescriptions were obtained by data mining. The most common herb properties were cold， warm and flat， and the main taste was sweet. Glycyrrhizae Radix et Rhizoman， Poria Cocos， Citri Reticulatae Pericarpium， Dendrobii Caulis， Atractylodis Macrocephalae Rhizoma， Astragali Radix， Rehmanniae Radix， Codonopsis Radix and Lycii Fructus as well as therapeutic herbs were at a higher frequency. The association rules indicated that Citri Reticulatae Pericarpium-Glycyrrhizae Radix et Rhizoman， Citri Reticulatae Pericarpium-Poria Cocos， Atractylodis Macrocephalae Rhizoma-Poria Cocos， Glycyrrhizae Radix et Rhizoman-Poria Cocos， and Citri Reticulatae Pericarpium-Atractylodis Macrocephalae Rhizoma-Poria Cocos combinations had the highest support in the same prescription. Atractylodis Macrocephalae Rhizoma-Poria Cocos-Citri Reticulatae Pericarpium-Glycyrrhizae Radix et Rhizoman were selected as the CMC by herb association network. Network pharmacology analysis showed that the 32 components of CMC were related to diabetic targets. Tetradeca-2，8，10-trien-4，6-diene-1，12，14-triol and atractylon derived from Atractylodis Macrocephalae Rhizoma， various sterols from Poria Cocos， naringenin from Citri Reticulatae Pericarpium， calycosin， licochalcone A and isoliquiritigenin from Glycyrrhizae Radix et Rhizoman were the main active components. KEGG results showed that CMC mainly affected lipid and atherosclerosis， endocrine resistance， cyclic adenosine monophosphate(cAMP) system signaling pathway and advanced glycation end products-receptor for advanced glycation end products(AGE-RAGE) system. AGE-RAGE system was closely related to diabetes， which contained the most core targets. [Conclusion] The treatment of diabetes with Chinese medicine of Ningbo school mainly focuses on replenishing Qi to invigorate the spleen， nourishing Yin and clearing heat， reflecting the characteristics of multi-components and multi-targets of Chinese medicine. The mechanism may be closely related to regulating the AGE-RAGE axis. This research provides a theoretical support for the treatment of diabetes in Chinese medicine of Ningbo school. |
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