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

TitleSimilarity and Potential Relation Between Periimplantitis and Rheumatoid Arthritis on Transcriptomic Level: Results of a Bioinformatics Study
Authors
KeywordsPeriimplantitis
Rheumatoid arthritis
Bioinformatics
Cross-talk genes
CD14
FCGR2B
Issue Date2021
PublisherFrontiers Research Foundation. The Journal's web site is located at http://www.frontiersin.org/immunology
Citation
Frontiers in Immunology, 2021, v. 12, article no. 702661 How to Cite?
AbstractBackground: This bioinformatics study aimed to reveal potential cross-talk genes, related pathways, and transcription factors between periimplantitis and rheumatoid arthritis (RA). Methods: The 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. Results: Periimplantitis 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. Conclusions: This 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.
Persistent Identifierhttp://hdl.handle.net/10722/309372
ISSN
2023 Impact Factor: 5.7
2023 SCImago Journal Rankings: 1.868
PubMed Central ID
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorLi, S-
dc.contributor.authorZhou, C-
dc.contributor.authorXu, Y-
dc.contributor.authorWang, Y-
dc.contributor.authorLi, L-
dc.contributor.authorPelekos, G-
dc.contributor.authorZiebolz, D-
dc.contributor.authorSchmalz, G-
dc.contributor.authorQin, Z-
dc.date.accessioned2021-12-29T02:14:10Z-
dc.date.available2021-12-29T02:14:10Z-
dc.date.issued2021-
dc.identifier.citationFrontiers in Immunology, 2021, v. 12, article no. 702661-
dc.identifier.issn1664-3224-
dc.identifier.urihttp://hdl.handle.net/10722/309372-
dc.description.abstractBackground: This bioinformatics study aimed to reveal potential cross-talk genes, related pathways, and transcription factors between periimplantitis and rheumatoid arthritis (RA). Methods: The 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. Results: Periimplantitis 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. Conclusions: This 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.-
dc.languageeng-
dc.publisherFrontiers Research Foundation. The Journal's web site is located at http://www.frontiersin.org/immunology-
dc.relation.ispartofFrontiers in Immunology-
dc.rightsThis work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.-
dc.subjectPeriimplantitis-
dc.subjectRheumatoid arthritis-
dc.subjectBioinformatics-
dc.subjectCross-talk genes-
dc.subjectCD14-
dc.subjectFCGR2B-
dc.titleSimilarity and Potential Relation Between Periimplantitis and Rheumatoid Arthritis on Transcriptomic Level: Results of a Bioinformatics Study-
dc.typeArticle-
dc.identifier.emailPelekos, G: george74@hku.hk-
dc.identifier.authorityPelekos, G=rp01894-
dc.description.naturepublished_or_final_version-
dc.identifier.doi10.3389/fimmu.2021.702661-
dc.identifier.pmid34858391-
dc.identifier.pmcidPMC8630748-
dc.identifier.scopuseid_2-s2.0-85120413602-
dc.identifier.hkuros331345-
dc.identifier.volume12-
dc.identifier.spagearticle no. 702661-
dc.identifier.epagearticle no. 702661-
dc.identifier.isiWOS:000733709900001-
dc.publisher.placeSwitzerland-

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