Similarity and Potential Relation Between Periimplantitis and Rheumatoid Arthritis on Transcriptomic Level: Results of a Bioinformatics Study

BackgroundThis bioinformatics study aimed to reveal potential cross-talk genes, related pathways, and transcription factors between periimplantitis and rheumatoid arthritis (RA).MethodsThe datasets GSE33774 (seven periimplantitis and eight control samples) and GSE106090 (six periimplantitis and six...

Descripción completa

Guardado en:

Detalles Bibliográficos
Autores principales:	Shiyi Li, Changqing Zhou, Yongqian Xu, Yujia Wang, Lijiao Li, George Pelekos, Dirk Ziebolz, Gerhard Schmalz, Zeman Qin
Formato:	article
Lenguaje:	EN
Publicado:	Frontiers Media S.A. 2021
Materias:	periimplantitis rheumatoid arthritis bioinformatics cross-talk genes CD14 FCGR2B Immunologic diseases. Allergy RC581-607
Acceso en línea:	https://doaj.org/article/62a06dfdf2ee4398afa91494eb197141
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

id	oai:doaj.org-article:62a06dfdf2ee4398afa91494eb197141
record_format	dspace
spelling	oai:doaj.org-article:62a06dfdf2ee4398afa91494eb1971412021-11-09T06:36:51ZSimilarity and Potential Relation Between Periimplantitis and Rheumatoid Arthritis on Transcriptomic Level: Results of a Bioinformatics Study1664-322410.3389/fimmu.2021.702661https://doaj.org/article/62a06dfdf2ee4398afa91494eb1971412021-11-01T00:00:00Zhttps://www.frontiersin.org/articles/10.3389/fimmu.2021.702661/fullhttps://doaj.org/toc/1664-3224BackgroundThis bioinformatics study aimed to reveal potential cross-talk genes, related pathways, and transcription factors between periimplantitis and rheumatoid arthritis (RA).MethodsThe datasets GSE33774 (seven periimplantitis and eight control samples) and GSE106090 (six periimplantitis and six control samples) were included from the National Center for Biotechnology Information (NCBI) Gene Expression Omnibus (GEO). A differential expression analysis (p < 0.05 and \|logFC (fold change)\| ≥ 1) and a functional enrichment analysis (p < 0.05) were performed. Based on this, a protein–protein interaction (PPI) network was constructed by Cytoscape. RA-related genes were extracted from DisGeNET database, and an overlap between periimplantitis-related genes and these RA-related genes was examined to identify potential cross-talk genes. Gene expression was merged between two datasets, and feature selection was performed by Recursive Feature Elimination (RFE) algorithm. For the feature selection cross-talk genes, support vector machine (SVM) models were constructed. The expression of these feature genes was determined from GSE93272 for RA. Finally, a network including cross-talk genes, related pathways, and transcription factors was constructed.ResultsPeriimplantitis datasets included 138 common differentially expressed genes (DEGs) including 101 up- and 37 downregulated DEGs. The PPI interwork of periimplantitis comprised 1,818 nodes and 2,517 edges. The RFE method selected six features, i.e., MERTK, CD14, MAPT, CCR1, C3AR1, and FCGR2B, which had the highest prediction. Out of these feature genes, CD14 and FCGR2B were most highly expressed in periimplantitis and RA. The final activated pathway–gene network contained 181 nodes and 360 edges. Nuclear factor (NF) kappa B signaling pathway and osteoclast differentiation were identified as potentially relevant pathways.ConclusionsThis current study revealed FCGR2B and CD14 as the most relevant potential cross-talk genes between RA and periimplantitis, which suggests a similarity between RA and periimplantitis and can serve as a theoretical basis for future research.Shiyi LiChangqing ZhouYongqian XuYujia WangLijiao LiGeorge PelekosDirk ZiebolzGerhard SchmalzZeman QinFrontiers Media S.A.articleperiimplantitisrheumatoid arthritisbioinformaticscross-talk genesCD14FCGR2BImmunologic diseases. AllergyRC581-607ENFrontiers in Immunology, Vol 12 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	periimplantitis rheumatoid arthritis bioinformatics cross-talk genes CD14 FCGR2B Immunologic diseases. Allergy RC581-607
spellingShingle	periimplantitis rheumatoid arthritis bioinformatics cross-talk genes CD14 FCGR2B Immunologic diseases. Allergy RC581-607 Shiyi Li Changqing Zhou Yongqian Xu Yujia Wang Lijiao Li George Pelekos Dirk Ziebolz Gerhard Schmalz Zeman Qin Similarity and Potential Relation Between Periimplantitis and Rheumatoid Arthritis on Transcriptomic Level: Results of a Bioinformatics Study
description	BackgroundThis bioinformatics study aimed to reveal potential cross-talk genes, related pathways, and transcription factors between periimplantitis and rheumatoid arthritis (RA).MethodsThe datasets GSE33774 (seven periimplantitis and eight control samples) and GSE106090 (six periimplantitis and six control samples) were included from the National Center for Biotechnology Information (NCBI) Gene Expression Omnibus (GEO). A differential expression analysis (p < 0.05 and \|logFC (fold change)\| ≥ 1) and a functional enrichment analysis (p < 0.05) were performed. Based on this, a protein–protein interaction (PPI) network was constructed by Cytoscape. RA-related genes were extracted from DisGeNET database, and an overlap between periimplantitis-related genes and these RA-related genes was examined to identify potential cross-talk genes. Gene expression was merged between two datasets, and feature selection was performed by Recursive Feature Elimination (RFE) algorithm. For the feature selection cross-talk genes, support vector machine (SVM) models were constructed. The expression of these feature genes was determined from GSE93272 for RA. Finally, a network including cross-talk genes, related pathways, and transcription factors was constructed.ResultsPeriimplantitis datasets included 138 common differentially expressed genes (DEGs) including 101 up- and 37 downregulated DEGs. The PPI interwork of periimplantitis comprised 1,818 nodes and 2,517 edges. The RFE method selected six features, i.e., MERTK, CD14, MAPT, CCR1, C3AR1, and FCGR2B, which had the highest prediction. Out of these feature genes, CD14 and FCGR2B were most highly expressed in periimplantitis and RA. The final activated pathway–gene network contained 181 nodes and 360 edges. Nuclear factor (NF) kappa B signaling pathway and osteoclast differentiation were identified as potentially relevant pathways.ConclusionsThis current study revealed FCGR2B and CD14 as the most relevant potential cross-talk genes between RA and periimplantitis, which suggests a similarity between RA and periimplantitis and can serve as a theoretical basis for future research.
format	article
author	Shiyi Li Changqing Zhou Yongqian Xu Yujia Wang Lijiao Li George Pelekos Dirk Ziebolz Gerhard Schmalz Zeman Qin
author_facet	Shiyi Li Changqing Zhou Yongqian Xu Yujia Wang Lijiao Li George Pelekos Dirk Ziebolz Gerhard Schmalz Zeman Qin
author_sort	Shiyi Li
title	Similarity and Potential Relation Between Periimplantitis and Rheumatoid Arthritis on Transcriptomic Level: Results of a Bioinformatics Study
title_short	Similarity and Potential Relation Between Periimplantitis and Rheumatoid Arthritis on Transcriptomic Level: Results of a Bioinformatics Study
title_full	Similarity and Potential Relation Between Periimplantitis and Rheumatoid Arthritis on Transcriptomic Level: Results of a Bioinformatics Study
title_fullStr	Similarity and Potential Relation Between Periimplantitis and Rheumatoid Arthritis on Transcriptomic Level: Results of a Bioinformatics Study
title_full_unstemmed	Similarity and Potential Relation Between Periimplantitis and Rheumatoid Arthritis on Transcriptomic Level: Results of a Bioinformatics Study
title_sort	similarity and potential relation between periimplantitis and rheumatoid arthritis on transcriptomic level: results of a bioinformatics study
publisher	Frontiers Media S.A.
publishDate	2021
url	https://doaj.org/article/62a06dfdf2ee4398afa91494eb197141
work_keys_str_mv	AT shiyili similarityandpotentialrelationbetweenperiimplantitisandrheumatoidarthritisontranscriptomiclevelresultsofabioinformaticsstudy AT changqingzhou similarityandpotentialrelationbetweenperiimplantitisandrheumatoidarthritisontranscriptomiclevelresultsofabioinformaticsstudy AT yongqianxu similarityandpotentialrelationbetweenperiimplantitisandrheumatoidarthritisontranscriptomiclevelresultsofabioinformaticsstudy AT yujiawang similarityandpotentialrelationbetweenperiimplantitisandrheumatoidarthritisontranscriptomiclevelresultsofabioinformaticsstudy AT lijiaoli similarityandpotentialrelationbetweenperiimplantitisandrheumatoidarthritisontranscriptomiclevelresultsofabioinformaticsstudy AT georgepelekos similarityandpotentialrelationbetweenperiimplantitisandrheumatoidarthritisontranscriptomiclevelresultsofabioinformaticsstudy AT dirkziebolz similarityandpotentialrelationbetweenperiimplantitisandrheumatoidarthritisontranscriptomiclevelresultsofabioinformaticsstudy AT gerhardschmalz similarityandpotentialrelationbetweenperiimplantitisandrheumatoidarthritisontranscriptomiclevelresultsofabioinformaticsstudy AT zemanqin similarityandpotentialrelationbetweenperiimplantitisandrheumatoidarthritisontranscriptomiclevelresultsofabioinformaticsstudy
_version_	1718441201093312512

Similarity and Potential Relation Between Periimplantitis and Rheumatoid Arthritis on Transcriptomic Level: Results of a Bioinformatics Study

Ejemplares similares