Literature DB >> 24748432

Interaction network analysis revealed biomarkers in myocardial infarction.

Tong Zhang1, Li-Li Zhao, Zhuo-Ran Zhang, Pei-De Fu, Zhen-Dong Su, Li-Chun Qi, Xue-Qi Li, Yu-Mei Dong.   

Abstract

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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Year:  2014        PMID: 24748432     DOI: 10.1007/s11033-014-3366-4

Source DB:  PubMed          Journal:  Mol Biol Rep        ISSN: 0301-4851            Impact factor:   2.316


  33 in total

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