Study On The Mechanism Of Chinese Medicine For Treating Diabetic Kidney Disease Based On Network Pharmacology

Diabetic kidney disease is one of the common microvascular complications of diabetes,and its patient population has increased year by year,but there is still a lack of recognized special treatment.Traditional Chinese medicine has accumulated rich experience and great advantages in the prevention and treatment of diabetic kidney disease.However,its many components and complex mechanisms lack comprehensive and systematic pharmacological research,which limits the development and application of traditional Chinese medicine to a certain extent.With the rise and cross-integration of many disciplines such as systems biology and multi-directional pharmacology,it is possible to explore the pharmacodynamic mechanism of traditional Chinese medicine compound by using new technologies.Therefore,this paper explores the core side through data mining methods,and applies network pharmacology technology from the perspective of the overall network,and studies the mechanism of the core of treating diabetic kidney disease,in order to provide guidance for further experimental research.Purpose:Firstly,through the analysis of the prescription of traditional Chinese medicine for the treatment of diabetic kidney disease,to find the core Chinese medicine for treating diabetic kidney disease.Secondly,using network pharmacology technology to explore the mechanism of the treatment of diabetic kidney disease with core Chinese medicine from a holistic and systematic perspective..Method:This study derives data on patients with diabetic kidney disease from the inpatient department of Guangdong Provincial Hospital of Traditional Chinese Medicine,and collects Chinese medicine prescriptions and related information for the first inpatient medical records of patients who meet the inclusion criteria.According to the glomerular filtration rate and the stage of chronic kidney disease,the prescriptions were divided into A,B,C,and D4 groups.First,the distribution of the syndrome types of the Chinese medicine prescriptions was counted.Secondly,the frequency statistics of the Chinese medicines of the whole sample and the grouped samples were respectively performed.The high-frequency Chinese medicine was clustered and analyzed.Again,the Apriori association rule analysis was carried out on the high-frequency Chinese medicine of the whole sample.The compatibility rules of the prescription for treating diabetic kidney disease were analyzed by the above methods and the core Chinese medicine was screened out.According to the above results,find all known components of the core Chinese medicine in the TCMSP platform,and screen the traditional Chinese medicine ingredients with oral bioavailability(?)30%and drug-like(?)0.18 as potential active ingredients,and find potential activity on the TCMSP platform again.The target of the component is to construct a potential active component and its corresponding target data set.The DKD target database was constructed by searching related targets in disease target related databases such as TTD,GAD,DRUDGBANK,and OMIM.Information data on the interaction between the component target and the DKD disease target was obtained from the Protein Interaction Information Database String database.The above information was imported into Cytoscape 3.6.1 composition software to construct a visual PPI network model of active components,component targets,and interactions between DKD disease targets.The topological parameters of the network model were analyzed to screen out key targets in the network.Points and compounds,followed by KEGG pathway enrichment analysis of common targets of component targets and DKD disease targets and key targets derived only from TCM,and Omicshare for KEGG pathway enrichment analysis of key targets The results were visualized to predict the primary mechanism of action of the core of the treatment of DKD.Result:This study included a total of 271 Chinese medicine prescriptions,and statistics on the prescriptions of Chinese medicine prescriptions.It was found that the prescriptions for this type of deficiency included the spleen and kidney qi deficiency syndrome,spleen and kidney yang deficiency syndrome,and qi and yin deficiency.Certificates,etc.,of which spleen and kidney qi deficiency accounted for about 67.5%of all prescriptions;the standard evidence mainly includes blood stasis,damp heat,water and so on,and blood stasis syndrome accounted for about 97%of all prescriptions.The frequency analysis of traditional Chinese medicines found that traditional Chinese medicines such as Astragalus,Codonopsis,Atractylodes Rhizome,Radix Salviae Miltiorrhizae,Radix Salviae Miltiorrhizae,Yam,and Taoren 8 were the first 8 flavors of high-frequency Chinese medicines for the whole sample and each group of samples.DKD four groups have 25 flavors of the same high-frequency Chinese medicine,according to the effect can be simply classified into spleen and qi,tonifying kidney,promoting blood circulation and removing phlegm,and dampness and dampness.In addition,each group has unique high-frequency Chinese medicine classification,group A and group B are mainly for nourishing kidney and liver and clearing yin and yin deficiency;group C and D are mainly for qi and collaterals and tonifying kidney and tonifying turbidity.·In the cluster analysis of traditional Chinese medicine,the high-frequency Chinese medicines of A,B,C and D are divided into 5,2,5 and 2 categories.The overall high-frequency Chinese medicine cluster analysis has obtained 2 kinds of traditional Chinese medicine combinations,the first type of combination,Salvia miltiorrhiza,Codonopsis pilosula,sassafras,yam,Astragalus,Atractylodes,and other drugs in combination with the second type have no obvious significance.The analysis of the association rules of the overall high-frequency Chinese medicine shows that after increasing support,confidence and promotion,eight groups of fourth-order association rules can be obtained:Astragalus or Codonopsis,Peach Kernel,Salted Silk,Atractylodes;Peach Kernel,Yam,Atractylodes,Astragalus membranaceus;salt scorpion,Codonopsis,Astragalus,Atractylodes;peach kernel,salt scorpion,scorpion,atractylodes;Heshouwu,scorpion,Atractylodes,Astragalus;salt scorpion,Codonopsis,Salvia,Atractylodes;peach kernel,Codonopsis,Atractylodes,Astragalus.According to the results of data mining,combined with literature review and clinical experience,the core prescriptions for treating DKD spleen and kidney qi deficiency and blood stasis syndrome are as follows:Astragalus,ginseng,sassafras,yam,medlar,atractylodes,salvia miltiorrhiza,and peach kernel.In this study,126 active components of Astragalus,Ginseng,Cuscuta,Yam,Radix,Atractylodes Rhizome,Salvia miltiorrhiza,and Taoren 8 traditional Chinese medicines and their corresponding 261 target were predicted by TCMSP platform in TTD,GAD,DRUDGBANK,OMIM disease gene database.We found 109 targets for diabetic kidney disease,and obtained data on the interaction information of 6487 pairs of 327 targets in the Srting database,and then established the PPI network model of the target of Chinese medicine ingredients-DKD disease target."Chinese medicine ingredient-ingredient target-DKD disease target" PPI network model.By analyzing the“Degree value of the node in the PPI network of“Chinese medicine ingredient-component target-DKD disease target”,the top 6 Chinese medicine active ingredients in the order of Degree are quercetin,kaempferol,luteolin,7-0-A Isobutachlor,tanshinone,carnosol,and stigmasterol.69 key targets were screened by analyzing the topological parameters of the PPI network model of the target of Chinese medicine ingredients-DKD disease target,including 44 targets derived from only Chinese medicine components,25 DKD disease targets and 14 common targets.Target,the key target of DC value>120,followed by AKT1,IL6,TP53,VEGFA,TNF,MAPK1,EGFR,CASP3,MAPK8,EGF,MYC,JUN,MMP9,STAT3,CXCL8.ClueGO was used to perform KEGG pathway enrichment analysis on 27 common targets related to DKD disease,and 22 statistically significant enrichment entries were obtained,including 5 biological pathways:HIF-1 signaling pathway,IL-17 Signaling pathway,TNF signaling pathway,Relaxin signaling pathway,AGE-RAGE signaling pathway in diabetic complications;Secondly,KEGG pathway enrichment analysis was performed on 44 targets of only 69 key targets derived from the action of traditional Chinese medicine components.After enrichment,96 statistically significant entries were obtained,including 29 biological pathways involving immune response,inflammatory response,regulation of cellular functions,glycolipid metabolism,oxidative stress,anti-fibrosis,and hormonal regulation.Table 3-5.Using Omicshare to visualize the results of KEGG pathway enrichment analysis of key targets,combined with p-value,enriched gene number and enrichment index,found that AGE-RAGE signaling pathway in diabetic complications,IL-17 signaling pathway,TNF signaling pathway,Multiple pathways such as HIF-1 signaling pathway and Toll-like receptor signaling pathway may be the main pathways for core treatment of DKD.Conclusion:Spleen and kidney qi deficiency syndrome and blood stasis syndrome are the most common syndromes of diabetic kidney disease.Astragalus,Codonopsis,Cuscuta,Yam,Radix,Atractylodes,Salvia,and Taoren are the core Chinese medicines for the treatment of diabetic kidney disease.The core ingredient consisting of 8 kinds of medicines such as Astragalus,Ginseng,Dodder,Chinese yam,Chinese wolfberry,Atractylodes,Salvia,and peach kernel.The main active ingredients for treating diabetic kidney disease include quercetin,kaempferol,luteolin and isoflavone II.Etc.The main targets include AKT1,IL6,VEGFA,TNF,MAPK1,EGFR,MAPK8,EGF,JUN,MMP9,STAT3,CXCL8,etc.The main pathways include AGE-RAGE signaling pathway in diabetic complications,IL-17 signaling pathway,TNF.Signaling pathway,HIF-1 signaling pathway,Toll-like receptor signaling pathway,etc.This study reveals that the main mechanism of action of the core prescription for the treatment of diabetic kidney disease involves regulating immune inflammation,regulating glucose metabolism,anti-oxidative stress,anti-fibrosis,and regulating cell proliferation and apoptosis.It also reflects the core compound for the treatment of diabetic kidney disease.A complex mechanism that interacts with multiple targets.