Identification of Potential core genes in Sevoflurance induced Myocardial Energy Metabolism in Patients Undergoing Off-pump Coronary Artery Bypass Graft Surgery using Bioinformatics analysis

Background: Myocardial ischemia-reperfusion injury always happened after Oﬀ-pump coronary artery bypass graft(OPCABG), and this can not be avoided altogether. In this study, we tried to detect potential genes of sevoflurane-induced myocardial energy metabolism in patients undergoing OPCABG using bioinformatics analysis. Methods: We download and analyze the gene expression profile data from the Gene Expression Omnibus(GEO) database using bioinformatics methods. We downloded the gene expression data from the Gene Expression Omnibus(GEO) database using bioinformatics methods. Gene Ontology(GO) functional annotation analysis and Kyoto Encyclopedia of Genes and Genomes(KEGG) pathway enrichment analysis were used to analysis the screened differentially expressed genes(DEGs). Then, we established a protein–protein interaction (PPI) network to find hub genes associated with myocardial energy metabolism. Results: Through PPI network, we find ten hub genes, including JUN, EGR1, ATF3, FOSB, JUNB, DUSP1, EGR2, NR4A1, BTG2, NR4A2. Conclusions: In conclusion, the proteins encoded by EGR1ATF3c-FosBtg2JunB DUSP1NR4A1BTG2 and NR4A2 were related to cardiac function. ATF3, FOSB, JUNB, DUSP1, NR4A1, NR4A2 are related to apoptosis of cardiomyocytes. The protein encoded by BTG2 is related to hypertrophy. Sevoflurane regulates cell transcription, inflammatory and apoptosis through those hub genes to protect myocardial.

Off-pump coronary artery bypass graft(OPCABG) surgery is an effective way to avoid the side effect of extracorporeal circulation, like the whole-body inflammatory syndrome, Postoperative cognitive dysfunction, coagulation disorders, and multiple organ dysfunction syndromes. At present, gas anaesthesia, sevoflurane has been widely used during the CABG.1 Coronary artery bypass grafting(CABG) is an effective way to treat left primary coronary disease or three-vessel disease. Lousy lifestyle and habits cause the happening of coronary artery disease(CAD) in China increased gradually. Patients with clinical symptoms and multiple CAD need surgery. Off-pump coronary artery bypass graft(OPCABG) is a right choice of surgical procedure. Even so, after OPCABG, myocardial ischemia-reperfusion injury can also not be avoided entirely and happened high probability. 3,5 In this study, we tried to detect potential genes of sevoflurane-induced myocardial energy metabolism in patients undergoing OPCABG. To find the differentially expressed genes (DEGs) between before inhalation (baseline sevoflurane) and after inhalation (sevoflurane), We download and analyze the gene expression profile data from the Gene Expression Omnibus(GEO) database using bioinformatics methods. Gene Ontology(GO) functional annotation analysis and Kyoto Encyclopedia of Genes and Genomes(KEGG) pathway enrichment analysis were performed for the screened DEGs. Then, we established a protein-protein interaction (PPI) network to find hub genes related to myocardial energy metabolism.
Functional analysis of DEGs was selected using Gene Ontology(GO) database and signal pathway of DEGs was carried out using the Kyoto Encyclopedia of Genes and Genomes(KEGG). Then, through the search tools, protein-protein interaction(PPI) network and hub genes related to myocardial energy metabolism were selected.

Materials and methods
We download a database from the GEO database(https://www.ncbi.nlm.nih. gov/geo/) to obtain the gene expression datasets. One series(GDS2772) was selected out from the database about sevoflurane affect human myocardial energy metabolism. GDS2772 was based on the Agilent GPL570:  Affymetrix Human Genome U133 Plus 2.0 Array. This data was available online searched by "sevoflurane" and "myocardial energy metabolism". This study has not been reported by any experiment on humans and declared by any other authors.
Data processing of DEGs R: The R Project for Statistical Computing(https://www.r-project.org/) was used to detect the DEGs between before inhalation(baseline sevoflurane) and after inhalation(sevoflurane) samples, and the adjusted P-value and |logFC| were calculated. We selected the DEGs by adjusting P 0.01 and |logFC|≥2.0.
GO and KEGG pathway analysis of DEGs GO analysis is a widely used method for functional enrichment studied. Also, gene functions were composed of biological process (BP), molecular function (MF), and cellular component (CC) three parts. KEGG is a large-scale used database, including vast amounts of genomes, biological pathways, diseases, chemicals, and drugs. We use the Database for Annotation, Visualization, and Integrated Discovery (DAVID) tools (https://david.ncifcrf.gov/) to analysis the DEGs through GO annotation analysis and KEGG pathway enrichment analysis. Once P 0.01 and gene counts≥10, the genes were considered statistically significant. 1 PPI network construction and hub gene identification In this study, we use the Search Tool for the Retrieval of Interacting Genes (STRING) database (http://string-db.org/) and GeneMANIA online database (https://genemania.org/) to analyze the PPI information and evaluate the potential PPI relationship. They were also used to identify the DEGs to analysis the PPI information. A combined score was set to 0.4, and then the PPI network was visualized by Cytoscape software (www.cytoscape.org/). The stability of the entire system was guaranteed by a higher degree node of connectivity. We calculated the degree of each protein node by using CytoHubba, a plugin in Cytoscape. Through those steps, we can select ten hub genes. 1

Identification of DEGs
Gene expression profile (GDS2772) was selected in this study using the following keywords: "sevoflurane," and "myocardial energy metabolism." GDS2772 contained      find that JunB can protect heart failure HF from inflammatory cardiomyopathy, 19 while in zebrafish decreased JunB leads to HF. 20 The protein encoded by DUSP1 is an anti-apoptotic phosphatase, and exited in a wide variety of organizations, especially having a high level in the heart. 21

Ethics approval and consent to participate
Not applicable.

Consent for publication
Not applicable.

Availability of data and materials
The datasets used and analysed during the current study are available from the corresponding author upon reasonable request.

Competing interests
The authors declare that they have no competing interests.

Funding
There was no external funding. Support was provided solely from institutional and/or departmental sources.

Authors' contributions
Hua Lin analyzed and interpreted the data and was a major contributor in writing the manuscript. All authors read and approved the final manuscript. Ten hub genes