Identification and Validation of Aging- and Endoplasmic Reticulum Stress-Related Genes in Periodontitis Using a Competing Endogenous RNA Network.

Feng, X; Peng, D; Qiu, Y; Guo, Q; Zhang, X; Li, Z; Pan, C

Identification and Validation of Aging- and Endoplasmic Reticulum Stress-Related Genes in Periodontitis Using a Competing Endogenous RNA Network.

Feng, X Peng, D Qiu, Y Guo, Q Zhang, X Li, Z Pan, C

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Publisher:: SPRINGER/PLENUM PUBLISHERS
Publication Type:: Journal Article
Citation:: Inflammation, 2024
Issue Date:: 2024-08-13

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Field	Value	Language
dc.contributor.author	Feng, X
dc.contributor.author	Peng, D
dc.contributor.author	Qiu, Y
dc.contributor.author	Guo, Q
dc.contributor.author	Zhang, X
dc.contributor.author	Li, Z
dc.contributor.author	Pan, C
dc.date.accessioned	2024-09-25T05:27:27Z
dc.date.available	2024-08-06
dc.date.available	2024-09-25T05:27:27Z
dc.date.issued	2024-08-13
dc.identifier.citation	Inflammation, 2024
dc.identifier.issn	0360-3997
dc.identifier.issn	1573-2576
dc.identifier.uri	http://hdl.handle.net/10453/180975
dc.description.abstract	Periodontitis is a multifactorial chronic inflammatory disease that destroy periodontium. Apart from microbial infection and host immune responses, emerging evidence shows aging and endoplasmic reticulum stress (ER stress) play a key role in periodontitis pathogenesis. The aim of this study is to identify aging-related genes (ARGs) and endoplasmic reticulum stress-related genes (ERGs) in periodontitis. Data were obtained from the Gene Expression Omnibus (GEO), Human Ageing Genomic Resources (HAGR) and GeneCards databases to identify differentially expressed mRNAs/miRNAs/lncRNAs (DEmRNAs/DEmiRNAs/DElncRNAs), ARGs and ERGs, respectively. We used the MultiMiR database for the reverse prediction of miRNAs and predicted miRNA-lncRNA interactions using the STARBase database. Afterwards, we constructed a mRNA-miRNA-lncRNA ceRNA network. A total of 10 hub genes, namely LCK, LYN, CXCL8, IL6, HCK, IL1B, BTK, CXCL12, GNAI1 and FCER1G, and 5 DEmRNAs-ARGs-ERGs were then discovered. Further, weighted gene co-expression network analysis (WGCNA) and single sample gene set enrichment analysis (ssGSEA) were performed to explore co-expression modules and immune infiltration respectively. Finally, we used transmission electron microscope (TEM), inverted fluorescence microscopy, quantitative real-time polymerase chain reaction (qRT-PCR) and Western Blot to verify the bioinformatic results in periodontal ligament stem cells (PDLSCs) infected with Porphyromonas gingivalis (P. gingivalis). The experimental results broadly confirmed the accuracy of bioinformatic analysis. The present study established an aging- and ER stress-related ceRNA network in periodontitis, contributing to a deeper understanding of the pathogenesis of periodontitis.
dc.format	Print-Electronic
dc.language	eng
dc.publisher	SPRINGER/PLENUM PUBLISHERS
dc.relation.ispartof	Inflammation
dc.relation.isbasedon	10.1007/s10753-024-02124-0
dc.rights	info:eu-repo/semantics/restrictedAccess
dc.subject	1107 Immunology
dc.subject.classification	Immunology
dc.subject.classification	3204 Immunology
dc.title	Identification and Validation of Aging- and Endoplasmic Reticulum Stress-Related Genes in Periodontitis Using a Competing Endogenous RNA Network.
dc.type	Journal Article
utslib.location.activity	United States
utslib.for	1107 Immunology
pubs.organisational-group	University of Technology Sydney
pubs.organisational-group	University of Technology Sydney/Faculty of Health
pubs.organisational-group	University of Technology Sydney/Faculty of Health/School of Nursing and Midwifery
utslib.copyright.status	in_progress	*
dc.date.updated	2024-09-25T05:27:25Z
pubs.publication-status	Published online

Abstract:

Periodontitis is a multifactorial chronic inflammatory disease that destroy periodontium. Apart from microbial infection and host immune responses, emerging evidence shows aging and endoplasmic reticulum stress (ER stress) play a key role in periodontitis pathogenesis. The aim of this study is to identify aging-related genes (ARGs) and endoplasmic reticulum stress-related genes (ERGs) in periodontitis. Data were obtained from the Gene Expression Omnibus (GEO), Human Ageing Genomic Resources (HAGR) and GeneCards databases to identify differentially expressed mRNAs/miRNAs/lncRNAs (DEmRNAs/DEmiRNAs/DElncRNAs), ARGs and ERGs, respectively. We used the MultiMiR database for the reverse prediction of miRNAs and predicted miRNA-lncRNA interactions using the STARBase database. Afterwards, we constructed a mRNA-miRNA-lncRNA ceRNA network. A total of 10 hub genes, namely LCK, LYN, CXCL8, IL6, HCK, IL1B, BTK, CXCL12, GNAI1 and FCER1G, and 5 DEmRNAs-ARGs-ERGs were then discovered. Further, weighted gene co-expression network analysis (WGCNA) and single sample gene set enrichment analysis (ssGSEA) were performed to explore co-expression modules and immune infiltration respectively. Finally, we used transmission electron microscope (TEM), inverted fluorescence microscopy, quantitative real-time polymerase chain reaction (qRT-PCR) and Western Blot to verify the bioinformatic results in periodontal ligament stem cells (PDLSCs) infected with Porphyromonas gingivalis (P. gingivalis). The experimental results broadly confirmed the accuracy of bioinformatic analysis. The present study established an aging- and ER stress-related ceRNA network in periodontitis, contributing to a deeper understanding of the pathogenesis of periodontitis.

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http://hdl.handle.net/10453/180975