2017  0,977
2016  0,799
2015  0,662
2014  0,740
2013  0,739
2012  0,637
2011  0,658
2010  0,654
2009  0,570
2008  0,849
2007  0,805
2006  0,330
2005  0,435
2004  0,623
2003  0,567
2002  0,641
2001  0,490
2000  0,477
1999  0,762
1998  0,785
1997  0,507
1996  0,518
1995  0,502
Vol 50(2016) N 1 p. 124-131; DOI 10.1134/S0026893316010192 Full Text

G.P. Sun1*, T. Jiang2, P.F. Xie3, J. Lan4

Identification of the Disease-Associated Genes in Periodontitis Using the Co-expression Network

1Department of Stomatology, the Third Hospital of Ji'nan, Ji'nan, Shandong, China
2General Department, Ji'nan Stomatological Hospital, Ji'nan, Shandong, China
3Department of Oral and Maxillofacial Surgery, Ji'nan Stomatological Hospital, Ji'nan, Shandong, China
4Department of Prosthodontics, College of Stomatology, Shandong University, Ji'nan, Shandong, China

Received - 2014-08-12; Accepted - 2015-02-18

The aim of this study was to investigate the disease-associated genes in periodontitis. In the present experiments, the topological analysis of the differential co-expression network was proposed. Using the GSE16134 dataset downloaded from the European Molecular Biology Laboratory-European Bioinformatics Institute, a co-expression network was constructed after the differentially expressed genes (DEGs) were identified between the diseased (242 samples) and healthy (69 samples) gingival tissues from periodontitis patients. The topological properties of the modules obtained from the network as well as an analysis of transcription factors (TFs) were used to determine the disease-associated genes. The gene ontology and pathway enrichment analysis was performed to investigate the underlying mechanisms of these disease related genes. A total of 524 DEGs, including 19 TFs were identified and a co-expression network with 2569 edges was obtained. Among the 7 modules gained in the network, the TFs (ZNF215, ZEN273, NFAT5, TRPS1, MEF2C and FLI1) were considered to be important in periodontitis. The functional and pathway enrichment analysis revealed that the DEGs were highly involved in the immune system. The co-expression network analysis and TFs identified in periodontitis may provide opportunities for biomarker development and novel insights into the therapeutics of periodontitis.

periodontitis, differentially expressed genes, co-expression