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Discovering genetic linkage between periodontitis and type 1 diabetes: A bioinformatics study
Background: Relationship between periodontitis (PD) and type 1 diabetes (T1D) has been reported, but the detailed pathogenesis requires further elucidation. This study aimed to reveal the genetic linkage between PD and T1D through bioinformatics analysis, thereby providing novel insights into scient...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10083320/ https://www.ncbi.nlm.nih.gov/pubmed/37051594 http://dx.doi.org/10.3389/fgene.2023.1147819 |
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author | Liu, Junqi Zhang, Bo Zhu, Guanyin Liu, Chenlu Wang, Shuangcheng Zhao, Zhihe |
author_facet | Liu, Junqi Zhang, Bo Zhu, Guanyin Liu, Chenlu Wang, Shuangcheng Zhao, Zhihe |
author_sort | Liu, Junqi |
collection | PubMed |
description | Background: Relationship between periodontitis (PD) and type 1 diabetes (T1D) has been reported, but the detailed pathogenesis requires further elucidation. This study aimed to reveal the genetic linkage between PD and T1D through bioinformatics analysis, thereby providing novel insights into scientific research and clinical treatment of the two diseases. Methods: PD-related datasets (GSE10334, GSE16134, GSE23586) and T1D-related datasets(GSE162689)were downloaded from NCBI Gene Expression Omnibus (GEO). Following batch correction and merging of PD-related datasets as one cohort, differential expression analysis was performed (adjusted p-value <0.05 and ∣log(2 ) fold change| > 0.5), and common differentially expressed genes (DEGs) between PD and T1D were extracted. Functional enrichment analysis was conducted via Metascape website. The protein-protein interaction (PPI) network of common DEGs was generated in The Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) database. Hub genes were selected by Cytoscape software and validated by receiver operating characteristic (ROC) curve analysis. Results: 59 common DEGs of PD and T1D were identified. Among these DEGs, 23 genes were commonly upregulated, and 36 genes were commonly downregulated in both PD- and T1D-related cohorts. Functional enrichment analysis indicated that common DEGs were mainly enriched in tube morphogenesis, supramolecular fiber organization, 9 + 0 non-motile cilium, plasma membrane bounded cell projection assembly, glomerulus development, enzyme-linked receptor protein signaling pathway, endochondral bone morphogenesis, positive regulation of kinase activity, cell projection membrane and regulation of lipid metabolic process. After PPI construction and modules selection, 6 hub genes (CD34, EGR1, BBS7, FMOD, IGF2, TXN) were screened out and expected to be critical in linking PD and T1D. ROC analysis showed that the AUC values of hub genes were all greater than 70% in PD-related cohort and greater than 60% in T1D-related datasets. Conclusion: Shared molecular mechanisms between PD and T1D were revealed in this study, and 6 hub genes were identified as potential targets in treating PD and T1D. |
format | Online Article Text |
id | pubmed-10083320 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-100833202023-04-11 Discovering genetic linkage between periodontitis and type 1 diabetes: A bioinformatics study Liu, Junqi Zhang, Bo Zhu, Guanyin Liu, Chenlu Wang, Shuangcheng Zhao, Zhihe Front Genet Genetics Background: Relationship between periodontitis (PD) and type 1 diabetes (T1D) has been reported, but the detailed pathogenesis requires further elucidation. This study aimed to reveal the genetic linkage between PD and T1D through bioinformatics analysis, thereby providing novel insights into scientific research and clinical treatment of the two diseases. Methods: PD-related datasets (GSE10334, GSE16134, GSE23586) and T1D-related datasets(GSE162689)were downloaded from NCBI Gene Expression Omnibus (GEO). Following batch correction and merging of PD-related datasets as one cohort, differential expression analysis was performed (adjusted p-value <0.05 and ∣log(2 ) fold change| > 0.5), and common differentially expressed genes (DEGs) between PD and T1D were extracted. Functional enrichment analysis was conducted via Metascape website. The protein-protein interaction (PPI) network of common DEGs was generated in The Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) database. Hub genes were selected by Cytoscape software and validated by receiver operating characteristic (ROC) curve analysis. Results: 59 common DEGs of PD and T1D were identified. Among these DEGs, 23 genes were commonly upregulated, and 36 genes were commonly downregulated in both PD- and T1D-related cohorts. Functional enrichment analysis indicated that common DEGs were mainly enriched in tube morphogenesis, supramolecular fiber organization, 9 + 0 non-motile cilium, plasma membrane bounded cell projection assembly, glomerulus development, enzyme-linked receptor protein signaling pathway, endochondral bone morphogenesis, positive regulation of kinase activity, cell projection membrane and regulation of lipid metabolic process. After PPI construction and modules selection, 6 hub genes (CD34, EGR1, BBS7, FMOD, IGF2, TXN) were screened out and expected to be critical in linking PD and T1D. ROC analysis showed that the AUC values of hub genes were all greater than 70% in PD-related cohort and greater than 60% in T1D-related datasets. Conclusion: Shared molecular mechanisms between PD and T1D were revealed in this study, and 6 hub genes were identified as potential targets in treating PD and T1D. Frontiers Media S.A. 2023-03-27 /pmc/articles/PMC10083320/ /pubmed/37051594 http://dx.doi.org/10.3389/fgene.2023.1147819 Text en Copyright © 2023 Liu, Zhang, Zhu, Liu, Wang and Zhao. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Genetics Liu, Junqi Zhang, Bo Zhu, Guanyin Liu, Chenlu Wang, Shuangcheng Zhao, Zhihe Discovering genetic linkage between periodontitis and type 1 diabetes: A bioinformatics study |
title | Discovering genetic linkage between periodontitis and type 1 diabetes: A bioinformatics study |
title_full | Discovering genetic linkage between periodontitis and type 1 diabetes: A bioinformatics study |
title_fullStr | Discovering genetic linkage between periodontitis and type 1 diabetes: A bioinformatics study |
title_full_unstemmed | Discovering genetic linkage between periodontitis and type 1 diabetes: A bioinformatics study |
title_short | Discovering genetic linkage between periodontitis and type 1 diabetes: A bioinformatics study |
title_sort | discovering genetic linkage between periodontitis and type 1 diabetes: a bioinformatics study |
topic | Genetics |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10083320/ https://www.ncbi.nlm.nih.gov/pubmed/37051594 http://dx.doi.org/10.3389/fgene.2023.1147819 |
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