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Differential gene expression analysis and network construction of recurrent cardiovascular events.

Publication ,  Journal Article
Liao, J; Chen, Z; He, Q; Liu, Y; Wang, J
Published in: Mol Med Rep
February 2016

Recurrent cardiovascular events are vital to the prevention and treatment strategies in patients who have experienced primary cardiovascular events. However, the susceptibility of recurrent cardiovascular events varies among patients. Personalized treatment and prognosis prediction are urged. Microarray profiling of samples from patients with acute myocardial infarction (AMI), with or without recurrent cardiovascular events, were obtained from the Gene Expression Omnibus database. Bioinformatics analysis, including Gene Oncology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG), were used to identify genes and pathways specifically associated with recurrent cardiovascular events. A protein-protein interaction (PPI) network was constructed and visualized. A total of 1,329 genes were differentially expressed in the two group samples. Among them, 1,023 differentially expressed genes (DEGs; 76.98%) were upregulated in the recurrent cardiovascular events group and 306 DEGs (23.02%) were downregulated. Significantly enriched GO terms for molecular functions were nucleotide binding and nucleic acid binding, for biological processes were signal transduction and regulation of transcription (DNA-dependent), and for cellular component were cytoplasm and nucleus. The most significant pathway in our KEGG analysis was Pathways in cancer (P=0.000336681), and regulation of actin cytoskeleton was also significantly enriched (P=0.00165229). In the PPI network, the significant hub nodes were GNG4, MAPK8, PIK3R2, EP300, CREB1 and PIK3CB. The present study demonstrated the underlying molecular differences between patients with AMI, with and without recurrent cardiovascular events, including DEGs, their biological function, signaling pathways and key genes in the PPI network. With the use of bioinformatics and genomics these findings can be used to investigate the pathological mechanism, and improve the prevention and treatment of recurrent cardiovascular events.

Duke Scholars

Published In

Mol Med Rep

DOI

EISSN

1791-3004

Publication Date

February 2016

Volume

13

Issue

2

Start / End Page

1746 / 1764

Location

Greece

Related Subject Headings

  • Up-Regulation
  • Signal Transduction
  • Recurrence
  • Protein Interaction Maps
  • Oncology & Carcinogenesis
  • Middle Aged
  • Male
  • Humans
  • Gene Regulatory Networks
  • Gene Ontology
 

Citation

APA
Chicago
ICMJE
MLA
NLM
Liao, J., Chen, Z., He, Q., Liu, Y., & Wang, J. (2016). Differential gene expression analysis and network construction of recurrent cardiovascular events. Mol Med Rep, 13(2), 1746–1764. https://doi.org/10.3892/mmr.2015.4707
Liao, Jiangquan, Zhong Chen, Qinghong He, Yongmei Liu, and Jie Wang. “Differential gene expression analysis and network construction of recurrent cardiovascular events.Mol Med Rep 13, no. 2 (February 2016): 1746–64. https://doi.org/10.3892/mmr.2015.4707.
Liao J, Chen Z, He Q, Liu Y, Wang J. Differential gene expression analysis and network construction of recurrent cardiovascular events. Mol Med Rep. 2016 Feb;13(2):1746–64.
Liao, Jiangquan, et al. “Differential gene expression analysis and network construction of recurrent cardiovascular events.Mol Med Rep, vol. 13, no. 2, Feb. 2016, pp. 1746–64. Pubmed, doi:10.3892/mmr.2015.4707.
Liao J, Chen Z, He Q, Liu Y, Wang J. Differential gene expression analysis and network construction of recurrent cardiovascular events. Mol Med Rep. 2016 Feb;13(2):1746–1764.

Published In

Mol Med Rep

DOI

EISSN

1791-3004

Publication Date

February 2016

Volume

13

Issue

2

Start / End Page

1746 / 1764

Location

Greece

Related Subject Headings

  • Up-Regulation
  • Signal Transduction
  • Recurrence
  • Protein Interaction Maps
  • Oncology & Carcinogenesis
  • Middle Aged
  • Male
  • Humans
  • Gene Regulatory Networks
  • Gene Ontology