Construction And Application Of Knowledge Base For Myocardial Infarction

With the development of biomedical big data and people's increasing attention to myocardial infarction(MI),studies related to MI are also increasing.Therefore,it is necessary to construct databases for integrating MI-related studies,and provide valuable research resources for MI-related researchers and medical workers.The study was mainly composed of three parts.In the first part,we constructed a risk knowledge base called MIRKB(MI Risk Knowledge Base,http://sysbio.org.cn/MIRKB/).The database includes 8738 records from 4548 original articles,involving 1924 single factors,163 combined factors,and 197 risk models.In the second part,we constructed a gene database called MIGD(MI Gene Database,http://sysbio.org.cn/MIGD/).Gene collection through literature mining and microarray analysis of gene expression profiles,819 genes were included in MIGD,including 692 protein-coding genes,148 non-coding RNAs,and 12 other types of genes.In the third part,based on the data in MIGD,we explored the molecular pathogenesis of MI by analyzing functional enrichment and biological networks.It was found that MI-related genes are mainly enriched in biological processes including the regulation of cellular process,macromolecule metabolic process,etc.,and signal pathways including rheumatoid arthritis,cytokine-cytokine receptor interaction,etc.We constructed a scale-free PPI network with 486 nodes and 3670 edges,and obtained 6 core modules and 159 core genes through module analysis.Some modules shared common signal pathway.In MI-related miRNA-mRNA network,the regulation relationships between miRNAs and target genes include one-to-one,one-to-many and many-to-many;more than 80%of MI-related genes are included in this network.15 key miRNAs and 11 key target genes were screened in the light of the degree centrality,between centrality and closeness centrality of nodes,and the miRNA-mRNA key subnetwork was constructed.Key target genes were apparently enriched in 7 biological processes including negative regulation of cell differentiation,etc.,and 3 KEGG signaling pathways including breast cancer,etc.In addition,we merged and intersected key target genes and core genes to obtain two overlapping genes,VEGFA and IGF 1,which may play a key role in the occurrence and development of MI.The MIRKB database and MIGD database constructed in this study have the characteristics of reliability,humanization and operability,which provide important academic resources for MI research.In addition,we found out the key genes of MI through bioinformatics analysis,and provide references for the research of the molecular mechanism of MI.