| Objective:This study explores the potential mechanisms underlying the occurrence and development of atrial fibrillation with phlegm turbidity syndrome in coronary heart disease using 4D data independent acquisition(DIA)proteomics research technology,providing a reference for experimental and clinical research.Based on proteomics research,a regression model was constructed to predict the potential therapeutic compounds of traditional Chinese medicine for atrial fibrillation with phlegm turbidity syndrome in coronary heart disease.Furthermore,the formula rules of traditional Chinese medicine(TCM)for atrial fibrillation with phlegm turbidity syndrome in coronary heart disease was explored,providing a reference for clinical diagnosis and treatment in traditional Chinese medicine.Methods and Materials:Eighty patients with coronary heart disease and sinus rhythm and 80 patients with atrial fibrillation due to coronary heart disease who were admitted to the Cardiovascular Department of Guang’anmen Hospital from June 2022 to December 2022 were included.In addition,30 healthy participants who underwent physical examinations were selected from the Department of Preventive Health Care.Demographic information,TCM four diagnostic information,medical history,blood cell parameters,and blood biochemistry indicators were collected for all included cases.According to TCM four diagnostic information,patients with coronary heart disease and atrial fibrillation were classified into phlegm turbidity syndrome and non-phlegm turbidity syndrome groups.Fasting venous blood samples were collected from all participants in the morning,and serum was extracted according to the standards for proteomics specimen collection.Ten cases of coronary heart disease with sinus rhythm,10 healthy control participants,10 cases of coronary heart disease with phlegm turbidity syndrome and atrial fibrillation,and 10 cases of coronary heart disease with non-phlegm turbidity syndrome and atrial fibrillation were selected.The protein expression levels in the serum of the four groups were detected using 4D-DIA proteomics technology.Bioinformatics analysis methods were used to screen differentially expressed proteins between groups,and protein-protein interaction network analysis methods were used to further identify the core differentially expressed proteins with biological interactions.Gene Ontology(GO)enrichment analysis.Kyoto Encyclopedia of Genes and Genomes(KEGG)pathway enrichment analysis,and Disease Ontology(DO)enrichment analysis were performed on the core differentially expressed proteins to explore the mechanisms of disease occurrence and development.Based on the selection of core differentially expressed proteins in the phlegm turbidity syndrome of coronary heart disease with atrial fibrillation,LASSO regression(Least Absolute Shrinkage and Selection Operator Regression)and random forest regression algorithms were further used to screen the core differentially expressed proteins in the phlegm turbidity syndrome of coronary heart disease with atrial fibrillation.Download relevant information about the compounds used in this study from the ChEMBL and HERB databases and calculate molecular fingerprints and descriptors.The best explanatory variables were selected using feature selection methods,and random forest regression and gradient boosting regression models were constructed.Multiple parameters were used to evaluate the regression models and select the best model to predict the traditional Chinese medicine compounds with high target protein activity.Based on the traditional Chinese medicine sources of the compounds,corresponding Chinese herb were analyzed one by one,and the formula rules for treating phlegm turbidity syndrome in coronary heart disease with atrial fibrillation were explored.The normal distribution is used to represent continuous data in statistical analysis as mean and standard deviation(x±s),while non-normal distribution of continuous data is represented by median(lower quartile,upper quartile).Categorical data is described using frequency and composition ratio.The Welch’s t-test or Wilcoxon rank-sum test is used for continuous data,while the chi-squared test or Fisher’s exact test is used for comparing two groups of categorical data.Results:1.This study included 80 patients with coronary heart disease sinus rhythm and 30 healthy controls.The level of systemic inflammatory response index in coronary heart disease sinus rhythm group was higher than that in healthy control group:[0.85(0.67,1.31)]VS[0.63(0.53,0.97)],and the difference was statistically significant(P<0.05).There was no significant difference in gender,age and other blood cell parameters between the two groups(P>0.05).2.This study included 80 patients with coronary heart disease and atrial fibrillation and 80 patients with coronary heart disease and sinus rhythm.Compared with clinical basic data of patients with coronary heart disease and sinus rhythm,there were differences and statistically significant between the two groups in the history of sleep apnea syndrome,history of cerebral infarction,lymphocyte count(LYMPH)and platelet count(PLT):sleep apnea syndrome[8(10%)]VS[1(1.3%)],history of cerebral infarction[36(45%)]VS[18(22%)],LYMPH[1.41(1.18,1.76)×109/L]VS[1.61(1.32,1.90)]×109/L and PLT[187(146,218)]×109/L VS[216(191,260)]×109/L.There was no statistically significant difference in other clinical basic data between the two groups(P>0.05).3.This study divided 80 patients with coronary heart disease and atrial fibrillation into 42 cases of phlegm turbidity syndrome and 38 cases of non-phlegm turbidity syndrome based on traditional Chinese medicine(TCM)diagnosis.The comparison of clinical data showed that there was no statistically significant difference in demographic information,past medical history,blood cell parameters,and biochemical indicators between the two groups(P>0.05).4.In the proteomics differential analysis between the coronary heart disease sinus rhythm group and the healthy control group,19 core differentially expressed proteins were identified that met the screening criteria.These proteins were MPO,CTSD,LRP1,THBS1,COPB1,CD109,GSTM2,AKT3,CLU,C4BPB,PKM,C4BPA,ECM1,TAGLN2,HSPA2,KIF5A,PPIA,CFL1,and APOC2.The GO enrichment analysis of the core differentially expressed proteins showed enrichment in 524 biological processes,50 cellular components,and 63 molecular functions.The KEGG pathway enrichment analysis included 74 signaling pathways,and the DO enrichment analysis revealed associations with 62 diseases.5.In the protein differential analysis between the coronary heart disease atrial fibrillation group and the coronary heart disease sinus rhythm group,11 core differential proteins met the set criteria,namely C6,C4BPB,NUP98,PLEC,APOA2,MASP1,F10,AGRN,CD44,SERPINA1,HSPA8.The 11 core differential proteins were enriched in 212 biological processes,35 cellular components,and 46 molecular functions.Additionally,they were enriched in 19 signaling pathways,and DO enrichment analysis showed that there was a correlation between coronary heart disease atrial fibrillation and 38 other diseases.6.In the comparison between phlegm turbidity syndrome and non-phlegm turbidity syndrome in patients with atrial fibrillation and coronary heart disease.10 core differentially expressed proteins were screened,which were LTF,HBA2,CA2,PRDX2,HBB,ACTB,S100A9,PLGLB2,CA1,and CFL1.These 10 core differentially expressed proteins were enriched in 237 biological processes,28 cell components,and 34 molecular functions.They were also associated with 37 signaling pathways and were found to be correlated with 30 diseases in DO enrichment analysis.7.According to two machine learning screening methods and target protein data stored in the ChEMBL database,CA2 protein was selected as the target protein.3096 compounds with standard activity data were obtained from the ChEMBL database,while 24438 traditional Chinese medicine compounds met the standards in the HERB database.Among the calculated and screened molecular fingerprints or descriptors,57 feature variables were the best explanatory variables and were included in the prediction model to build the dataset.In the comparison of prediction model performance,random forest regression was found to be the best regression prediction model.Using the random forest regression model,203 Chinese herbal compounds with high excitatory activity against CA2 protein were predicted.These 203 compounds corresponded to 472 traditional Chinese medicines,and after removing duplicates,there were 234 remaining Chinese medicines.In the analysis of traditional Chinese medicine efficacy,it was found that 31 Chinese medicines had the effect of resolving phlegm,60 Chinese medicines had the effect of dispelling or resolving dampness,15 Chinese medicines had the effect of promoting diuresis,41 Chinese medicines had the effect of promoting blood circulation and removing blood stasis,41 Chinese medicines had the effect of dispelling wind,60 Chinese medicines had the effect of clearing heat,and 12 Chinese medicines had the effect of invigorating the spleen.Conclusion:1.The comparative analysis of the three groups in terms of proteomics,including the coronary heart disease with sinus rhythm group and the healthy control group,the coronary heart disease with atrial fibrillation group and the coronary heart disease with sinus rhythm group,and the coronary heart disease with atrial fibrillation phlegm turbidity syndrome group and the non-phlegm turbidity syndrome group,showed differences.2.Coronary heart disease with sinus rhythm is closely associated with mechanisms such as inflammatory response,thrombosis,lipid metabolism disorders,oxidative stress response,cell proliferation,and cell migration in patients with coronary heart disease.3.The biological processes such as inflammatory infiltration,endothelial dysfunction,and complement activation are associated with the concomitant occurrence of atrial fibrillation in patients with coronary heart disease.4.Coronary heart disease with atrial fibrillation phlegm turbidity syndrome is closely associated with mechanisms such as inflammatory response,oxidative stress,abnormal expression of cell adhesion molecules,and inflammatory cytokines.5.Preliminary exploration of the formula rules of phlegm turbidity syndrome in coronary heart disease with atrial fibrillation suggests that the main focus should be on traditional Chinese herbs that have the function of regulating water metabolism,such as those that can relieve phlegm,dry dampness,and promote diuresis.In addition,other herbs that have the effects of dispelling wind,tonifying the spleen,promoting blood circulation,and clearing heat can also be used as complementary treatment. |
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