Gene/Protein Disease Symptom Drug Enzyme Compound
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Query: UMLS:C0018799 (heart disease)
 34,133 document(s) hit in 31,850,051 MEDLINE articles (0.00 seconds)

Myocardial infarction (MI) is a serious heart disease. The cardiac cells of patients with MI will die due to lack of blood for a long time. In this study, we aimed to find new targets for MI diagnosis and therapy. We downloaded GSE22229 including 12 blood samples from healthy persons and GSE29111 from Gene Expression Omnibus including 36 blood samples from MI patients. Then we identified differentially expressed genes (DEGs) in patients with MI compared to normal controls with p value < 0.05 and |logFC| > 1. Furthermore, interaction network and sub-network of these of these DEGs were constructed by NetBox. Linker genes were screened in the Global Network database. The degree of linker genes were calculated by igraph package in R language. Gene ontology and kyoto encyclopedia of genes and genomes pathway analysis were performed for DEGs and network modules. A total of 246 DEGs were identified in MI, which were enriched in the immune response. In the interaction network, LCK, CD247, CD3D, FYN, HLA-DRA, IL2, CD8A CD3E, CD4, CD3G had high degree, among which CD3E, CD4, CD3G were DEGs while others were linker genes screened from Global Network database. Genes in the sub-network were also enriched in the immune response pathway. The genes with high degree may be biomarkers for MI diagnosis and therapy.
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PMID:Interaction network analysis revealed biomarkers in myocardial infarction. 2474 32

Acute myocardial infarction (AMI) is one of the most common cardiovascular emergencies, of which the molecular pathogenesis is still not fully understood. This study aimed to explore the differentially expressed genes (DEGs) and then identify the critical genes in AMI thus screening out potential biomarkers for the early diagnosis of this serious heart disease. The gene expression data of AMI patients (GSE19339) were downloaded from gene expression omnibus database. After preprocessing with affy package, the DEGs were screened out by significance analysis of microarray (SAM) algorithm within samr package. Then function and pathway enrichment analyses of the DEGs were carried out using DAVID (database for annotation visualization and integrated discovery software) online tools. Further, the relevant genes of AMI were screened out with GENETIC_ASSOCIATION_DB_DISEASE analysis and blastp alignment. Finally, the novel genes were subjected to transcription factor and protein-protein interaction network analyses. A total of 633 DEGs, including 378 up-regulated and 255 down-regulated, were screened out between AMI patients and normal control samples. Among those genes, several important ones such as PPAR, CCL2, HMOX1 and NPR1 were demonstrated to be related to AMI. Most importantly, a novel gene LCK (lymphocyte-specific protein tyrosine kinase) was significantly differentially expressed in AMI. Further analyses showed that LCK was involved in the expression regulation of CXCL12 (chemokine (C-X-C motif) ligand 12) and the expression of LCK can be regulated by different transcription factors. In this study, we provided a new insight into the mechanism of AMI and raised LCK as an attractive marker candidate in the diagnosis of this serious heart disease.
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PMID:LCK: a new biomarker candidate for the early diagnosis of acute myocardial infarction. 2628 44