Identification of candidate target genes for human peripheral arterial disease using weighted gene co‑expression network analysis

Yin,De‑Xin; Zhao,Hao‑Min; Sun,Da‑Jun; Yao,Jian; Ding,Da‑Yong

doi:10.3892/mmr.2015.4450

December-2015 Volume 12 Issue 6

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December-2015 Volume 12 Issue 6

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Article

Identification of candidate target genes for human peripheral arterial disease using weighted gene co‑expression network analysis

Authors:
- De‑Xin Yin
- Hao‑Min Zhao
- Da‑Jun Sun
- Jian Yao
- Da‑Yong Ding
View Affiliations / Copyright

Affiliations: Department of Vascular Surgery, China-Japan Union Hospital of Jilin University, Changchun, Jilin 130033, P.R. China, Department of Thoracic Surgery, Jilin Hospital of Jilin Province People's Hospital, Changchun, Jilin 130031, P.R. China, Department of Gastroenterology Surgery, China‑Japan Union Hospital of Jilin University, Changchun, Jilin 130033, P.R. China
Pages: 8107-8112
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Published online on: October 15, 2015

https://doi.org/10.3892/mmr.2015.4450
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Abstract

The aim of the present study was to identify the potential treatment targets of peripheral arterial disease (PAD) and provide further insights into the underlying mechanism of PAD, based on a weighted gene co‑expression network analysis (WGCNA) method. The mRNA expression profiles (accession. no. GSE27034), which included 19 samples from patients with PAD and 18 samples from normal control individuals were extracted from the Gene Expression Omnibus database. Subsequently, the differentially expressed genes (DEGs) were obtained using the Limma package and the co‑expression network modules were screened using the WGCNA approach. In addition, the protein‑protein interaction network for the DEGs in the most significant module was constructed using Cytoscape software. Functional enrichment analyses of the DEGs in the most significant module were also performed using the Database for Annotation, Visualization and Integrated Discovery and Kyoto Encyclopedia of Genes and Genomes (KEGG) Orthology‑Based Annotation System, respectively. A total of 148 DEGs were identified in PAD, which were used to construct the WGCN, in which two modules (gray module and turquoise module) were identified, with the gray module exhibiting a higher gene significance (GS) value than the turquoise module. In addition, a co‑expression network was constructed for 60 DEGs in the gray module. The functional enrichment results showed that the DEGs in the gray module were enriched in five Gene Ontology terms and four KEGG pathways. For example, cyclin‑dependent kinase inhibitor 1A (CDKN1A), FBJ murine osteosarcoma viral oncogene homolog (FOS) and prostaglandin‑endoperoxide synthase 2 (PTGS2) were enriched in response to glucocorticoid stimulus. The results of the present study suggested that DEGs in the gray module, including CDKN1A, FOS and PTGS2, may be associated with the pathogenesis of PAD, by modulating the cell cycle, and may offer potential for use as candidate treatment targets for PAD.

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