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01.12.2015 | Research article | Ausgabe 1/2015 Open Access

BMC Oral Health 1/2015

Genes related to inflammation and bone loss process in periodontitis suggested by bioinformatics methods

BMC Oral Health > Ausgabe 1/2015
Liang Song, Jueqi Yao, Zhijing He, Bin Xu
Wichtige Hinweise

Electronic supplementary material

The online version of this article (doi:10.​1186/​s12903-015-0086-7) contains supplementary material, which is available to authorized users.

Competing interests

The authors declare that they have no competing interests.

Authors’ contributions

LS conceived of this study, participated in the design, and he performed the statistical analysis. JY carried out the study, together with ZH, collected important background information, and drafted the manuscript. BX participated in the design and helped to draft the manuscript. All authors read and approved the final manuscript.



Despite of numerous studies on periodontitis, the mechanism underlying the progression of periodontitis still remains largely unknown. This study aimed to have an expression profiling comparison between periodontitis and normal control and to identify more candidate genes involved in periodontitis and to gain more insights into the molecular mechanisms of periodontitis progression.


The gene expression profile of GSE16134, comprising 241 gingival tissue specimens and 69 healthy samples as control which were obtained from 120 systemically healthy patients with periodontitis (65 with chronic and 55 with aggressive periodontitis), was downloaded from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) in periodontitis samples were screened using the limma package in R compared with control samples. Gene Ontology (GO) and pathway enrichment analysis upon the DEGs were carried out using Hypergeometric Distribution test. Protein-protein interaction (PPI) network of the DEGs was constructed using Cytoscape, followed by module selection from the PPI network using MCODE plugin. Moreover, transcription factors (TFs) of these DEGs were identified based on TRANSFAC database and then a regulatory network was constructed.


Totally, 762 DEGs (507 up- and 255 down-regulated) in periodontitis samples were identified. DEGs were enriched in different GO terms and pathways, such as immune system process, cell activation biological processes, cytokine-cytokine receptor interaction, and metabolic pathways. Cathepsin S (CTSS) and pleckstrin (PLEK) were the hub proteins in the PPI network and 3 significant modules were selected. Moreover, 19 TFs were identified including interferon regulatory factor 8 (IRF8), and FBJ murine osteosarcoma viral oncogene homolog B (FOSB).


This study identified genes (CTSS, PLEK, IRF-8, PTGS2, and FOSB) that may be involved in the development and progression of periodontitis.
Additional file 1: Table S1. All the differentially expressed genes (DEGs) in periodontitis samples with their corresponding modules (DOCX 102 kb)
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