Using Pathway-related Modules To Study Cardiac Protection Of Sevoflurane And Propofol In OPCABG Surgery

[Background]Cardiovascular diseases(CVDs)grow yearby year.Off-pump coronary artery bypass graft(OPCABG)surgery has recently emerged as a mean to avoid the sequelae of extracorporeal circulation,including the whole-body inflammatory response,coagulation disorders and multiple organ dysfunction.Sevoflurane and propofol have been widely used during the CABG.Propofol and sevoflurane both possess certain,although different,cardioprotective properties.Over the past decades,numerous experimental strategies(association studies,genome-wide linkage scan,proteomics and global microarray gene expression analysis amongst others and large efforts have been applied onto the studies.Lucchinetti performed direct comparisons between anesthetic gases and intravenous anesthetics in human hearts at the gene expression level.These results indicated that anesthetic-induced and constitutive gene regulatory control of myocardial substrate metabolism predicts postoperative cardiac function in patients undergoing off-pump CABG surgery.However,the underlying mechanisms of these anesthetics on the gene level remain unclear.Gene co-expression network contained genes that exhibited similar expression patterns across different organisms.Functionally related genes were frequently co-expressed across organisms constituting conserved transcription modules.By constructing a co-expression network,the underlying regulatory relationships under different conditions may be estimated.In order to define the adjacency matrix,one makes use of an adjacency function,which transforms the co-expression similarities into connection strengths.The node dissimilarity measure is used as input of a clustering method to define network modules(clusters of nodes).Furthermore,modules are groups of genes whose expression profiles are highly correlated across the samples.Network modules implement the hypothesis that a network can be divided into functional modules.In this case,significant interactions,such as key genes in significant pathways can be tested.Therefore,in the present study modules from the co-expression network based on genes enriched in significant pathways were identified,and these modules were defined as pathway-related modules.[Objective]The present study aimed to identify changed pathway-related modules in CAD patients undergoing off-pump CABG under sevoflurane or propofol anesthesia using bioinformatics method.Then to further understand the underlying mechanisms of these anesthetics on the CAD patients during the CABG process.[Methods]The gene expression profile was obtained from the Array Express database.The gene expression profile was initially conducted,and differentially expressed genes in CAD patients were identified before and after applying sevoflurane or propofol,respectively.Pathway analysis of the DEGs was performed using the Kyoto Encyclopedia of Genes and Genomes database(KEGG).A co-expression network was constructed by weighted gene co-expression network analysis(WGCNA),and pathway-related modules were mined.Significant pathway-related modules were identified by conducting analysis on the topological centralities of the co-expression network.1.Data recruitment and preprocessingThe gene expression profile of E-GEOD-4386 was obtained from the Array Express database(http://www.ebi.ac.uk/arrayexpress/).E-GEOD-4386 existed on the A-AFFY-44-Affymetrix Gene Chip Human Genome U133 Plus 2.0 Platform.The data were obtained from patients that had undergone off-pump CABG surgery,and they were allocated either to receive the anesthetic gas sevoflurane or the intravenous anesthetic propofol.The samples were then divided into two groups:Baseline sevoflurane(n=10)-sevoflurane(n=10)and baseline propofol(n=10)-propofol(n=10).Furthermore,the microarray data and annotation files were downloaded for further analysis.Background-corrected signal intensities were determined using the Micro Array Suite 5.0(MAS 5.0)software(Affymetrix,Inc.,Santa Clara,CA,USA).The normalization of datasets obtained from the Array Express database was performed using a robust multichip average method and quantile based algorithm.Meanwhile,the gene expression value was transformed to a comparable level.Additionally,a gene-filter package was used to screen the data.Each probe was mapped to one gene,and the probe was discarded if it did not match any genes.Furthermore,the expression value averaged over probes was used as the gene expression value if the gene had multiple probes.2.Identification of DEGsEmpirical Bayes method that implemented in the linear model for microarray data(LIMMA)package was used to identify DEGs in the sevoflurane and propofol groups,respectively.Furthermore,the false discovery rate was used to proofread the P-values.Values of[log Fold Change(FC)]>2.0 and P<0.01 were selected as the cut-off criteria.3.Functional enrichment analysis of DEGsThe KEGG database was applied to investigate the enrichment analysis of the DEGs that involved in patients that had undergone OPCABG surgery before and after applying sevoflurane or propofol,in order to find the biochemical pathways of them.The Database for Annotation,Visualization and Integrated Discovery(DAVID)was used to perform the KEGG pathway enrichment analysis with the P<0.05 and gene count>5.4.Co-expression network analysis and constructionIdentifying differential co-expression by WGCNA Gene co-expression networks,which represent a major application of correlation network methodology,are instrumental for describing the pair-wise relationships among gene transcripts and facilitate the understanding of their function and identification of their key players.A coefficient of variation(CV=μ/σ)filtering was applied to remove genes that were constitutively expressed,unexpressed or vary only modestly across experimental treatments or conditions.In this study,a CV cutoff value of 0.6 was selected to obtain co-expression interactions.The co-expression network was constructed using Cytoscape version 3.1.0.Meanwhile,the expression values of each node were mapped to the co-expression network,where different colors represent the differences in the expression value of the nodes.5.Pathway-related module mining and topological analysisGenes in each significant pathway of the two groups were explored and mapped into the co-expression network.Pathway genes in the network and their adjacent genes were captured to form a sub-network,which were also called pathway-related modules.Module topological analysis(the mean degree centrality of genes in the corresponding module)was conducted to evaluate significant pathway-related modules.[Results]1.Identificationof DEGsAfter having preprocessed the profile,a total of 269 DEGs were obtained in the group SEVOand a total of 129 DEGs in groupPROP([log(FC)]>2.0 and P<0.01).2.KEGG pathway analysis of DEGsEight significant pathways in groupSEVO including NOD-like receptor signaling pathway,cytokine-cytokine receptor interaction,complement and coagulation cascades,MAPKsignaling pathways,p53signaling pathways,chemokine and JAK-STAT signaling pathwayswere obtained.We get seven significant pathways in groupPROPincludingNOD-like receptor signaling pathway,cytokine-cytokine receptor interaction,MAPK signaling pathways,p53 signaling pathways,bladder cancer,epithelial cell signaling in Helicobacter pylori infection and complement and coagulation cascades.It was evident that NOD-like receptor signaling pathway,cytokine-cytokine receptor,complement and coagulation cascades,mitogen-activated protein kinase and p53 signaling pathways were enriched in both groups.While the chemokine cytokine-cytokine receptor interaction and JAK-STAT signaling pathways are only in group SEVO,epithelial cell signaling in Helicobacter pylori infection was only enriched in group PROP.3.Co-expression network construction and topological analysis813 co-expression interactions were obtained in group SEVOwhile 1,216 in group PROP.Wegetanetwork with expression values ineach group.It was evident that all of the pathway genes were upregulated.Gene IL-6 and IL-8 were most up-regulated in the 2 groups.In group SEVO,the fold change of gene IL-6 was 10.16and gene IL-8 was 8.17.In group PROP,the fold change of gene IL-6 was 9.47 and gene IL-8 was 8.50.Gene SERTAD1 located at the center ofthe co-expression network of group SEVOwith a degree centrality of 173.Gene SOCS3 located at the center of the co-expression network of group PROPwith a degree centrality of 114.4.Pathway-related module mining and topological analysisEight and seven pathway-related modules were obtained in t group SEVO and in group PROP,respectively.The mean degree of modules of complement and coagulation cascades related,p53 signaling related,NOD-like receptor signaling related and cytokine-cytokine receptor interaction related were>20 in both groups.Moreover,the complement and coagulation cascades pathway-related module revealed the highest mean degree in both groups,which in group SEVOhad a mean degree of 56.67,and in group PROP a mean degree of 71.88.However,the chemokine signaling pathway-related module only existed in group SEVO with a mean degree of 36.92,and epithelial cell signaling in H.pylori infection pathway-related module only existed in group PROP with a mean degree of 35.98.By conducting analysis on the frequency of genes contained in the pathway-related modules,it was identified that there were several genes that presented in more than one module in both groups.Furthermore,it was evident that in group SEVO,genes IL8,CXCL2,CCL2,IL6,IL1B,CXCL1,CCL11 and MYC had a frequency>3 and in the propofol group,genes IL8 and CXCL1 had a frequency>3.In addition,genes IL8,CXCL2,CCL2,CXCL1 and CCL11 were all enriched in the chemokine signaling pathway-related module of group SEVO,and genes IL8,CXCL1 were all enriched in epithelial cell signaling in H.pylori infection pathway-related module of the group PROP.[Conclusions]1.Surgery-related inflammatory in OPCABGmight be related to the activation of complement and coagulation cascades,p53 signaling pathway,NOD-like signaling pathway,cytokine-cytokine receptor interaction,and MAPK signaling pathway.Myocardial ischemia and injuryduring OPCABG might be related with complement and coagulation cascade and cytokine-cytokine receptor interaction pathway.Gene IL-6 and IL-8 may be involved in the inflammatory response and myocardial ischemia of OPCABG.2.Sevoflurane might provide the patients with more protection in angiogenesis during OPCABG through gene IL8,CXCL1,CCL2and gene MYC in chemokine signaling pathway.Andprotect cardiomyocytesfrom apoptosis through the gene SERTAD1.3.Propofol might protect OPCABG patients from inflammation by blocking chemokine signaling pathway and the JAK-STAT signaling pathway.The inactivation of the JAK-STAT signaling pathway may be related to gene SOCS3.And propofol mightmediated the stress ulcer through the Epithelial cell signaling in H.pylori infection pathway.