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

BMC Oral Health
Liang SongBin Xu

Abstract

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 con...Continue Reading

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Citations

Apr 7, 2018·BMC Oral Health·Svenja MemmertJames Deschner
Jan 18, 2019·Journal of Periodontology·Esra Guzeldemir-AkcakanatHakan Savli
Nov 11, 2017·Journal of Lasers in Medical Sciences·Hojjat-Allah AbbaszadehMostafa Rezaei-Tavirani
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May 27, 2020·Oral Surgery, Oral Medicine, Oral Pathology and Oral Radiology·Valentina TaleviJean-Luc C Mougeot
Apr 5, 2021·Journal of Periodontology·Anders EsbergPernilla Lundberg

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Datasets Mentioned

BETA
GPL570

Software Mentioned

R
Cytoscape
preprocessCore
Linear Models for Microarray data ( limma ) R
MCODE
STRING ( Search Tool for the Retrieval of

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