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Transcriptomic analysis reveals shared gene signatures and molecular mechanisms between obesity and periodontitis
BACKGROUND: Both obesity (OB) and periodontitis (PD) are chronic non-communicable diseases, and numerous epidemiological studies have demonstrated the association between these two diseases. However, the molecular mechanisms that could explain the association between OB and PD are largely unclear. T...
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/PMC10090675/ https://www.ncbi.nlm.nih.gov/pubmed/37063877 http://dx.doi.org/10.3389/fimmu.2023.1101854 |
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author | Cai, Yisheng Zuo, Xuemei Zuo, Yuyang Wu, Shuang Pang, Weiwei Ma, Keqiang Yi, Qiaorong Tan, Lijun Deng, Hongwen Qu, Xiaochao Chen, Xiangding |
author_facet | Cai, Yisheng Zuo, Xuemei Zuo, Yuyang Wu, Shuang Pang, Weiwei Ma, Keqiang Yi, Qiaorong Tan, Lijun Deng, Hongwen Qu, Xiaochao Chen, Xiangding |
author_sort | Cai, Yisheng |
collection | PubMed |
description | BACKGROUND: Both obesity (OB) and periodontitis (PD) are chronic non-communicable diseases, and numerous epidemiological studies have demonstrated the association between these two diseases. However, the molecular mechanisms that could explain the association between OB and PD are largely unclear. This study aims to investigate the common gene signatures and biological pathways in OB and PD through bioinformatics analysis of publicly available transcriptome datasets. METHODS: The RNA expression profile datasets of OB (GSE104815) and PD (GSE106090) were used as training data, and GSE152991 and GSE16134 as validation data. After screening for differentially expressed genes (DEGs) shared by OB and PD, gene enrichment analysis, protein-protein interaction (PPI) network construction, GeneMANIA analysis, immune infiltration analysis and gene set enrichment analysis (GSEA) were performed. In addition, receiver operating characteristic (ROC) curves were used to assess the predictive accuracy of the hub gene. Finally, we constructed the hub gene-associated TF-miRNA-mRNA regulatory network. RESULTS: We identified a total of 147 DEGs shared by OB and PD (38 down-regulated and 109 up-regulated). Functional analysis showed that these genes were mainly enriched in immune-related pathways such as B cell receptor signalling, leukocyte migration and cellular defence responses. 14 hub genes (FGR, MNDA, NCF2, FYB1, EVI2B, LY86, IGSF6, CTSS, CXCR4, LCK, FCN1, CXCL2, P2RY13, MMP7) showed high sensitivity and specificity in the ROC curve analysis. The results of immune infiltration analysis showed that immune cells such as macrophages, activated CD4 T cells and immune B cells were present at high infiltration levels in both OB and PD samples.The results of GeneMANIA analysis and GSEA analysis suggested that five key genes (FGR, LCK, FYB1, LY86 and P2RY13) may be strongly associated with macrophages. Finally, we constructed a TF-miRNA-mRNA regulatory network consisting of 233 transcription factors (TFs), 8 miRNAs and 14 mRNAs based on the validated information obtained from the database. CONCLUSIONS: Five key genes (FGR, LCK, FYB1, LY86, P2RY13) may be important biomarkers of OB and PD. These genes may play an important role in the pathogenesis of OB and PD by affecting macrophage activity and participating in immune regulation and inflammatory responses. |
format | Online Article Text |
id | pubmed-10090675 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-100906752023-04-13 Transcriptomic analysis reveals shared gene signatures and molecular mechanisms between obesity and periodontitis Cai, Yisheng Zuo, Xuemei Zuo, Yuyang Wu, Shuang Pang, Weiwei Ma, Keqiang Yi, Qiaorong Tan, Lijun Deng, Hongwen Qu, Xiaochao Chen, Xiangding Front Immunol Immunology BACKGROUND: Both obesity (OB) and periodontitis (PD) are chronic non-communicable diseases, and numerous epidemiological studies have demonstrated the association between these two diseases. However, the molecular mechanisms that could explain the association between OB and PD are largely unclear. This study aims to investigate the common gene signatures and biological pathways in OB and PD through bioinformatics analysis of publicly available transcriptome datasets. METHODS: The RNA expression profile datasets of OB (GSE104815) and PD (GSE106090) were used as training data, and GSE152991 and GSE16134 as validation data. After screening for differentially expressed genes (DEGs) shared by OB and PD, gene enrichment analysis, protein-protein interaction (PPI) network construction, GeneMANIA analysis, immune infiltration analysis and gene set enrichment analysis (GSEA) were performed. In addition, receiver operating characteristic (ROC) curves were used to assess the predictive accuracy of the hub gene. Finally, we constructed the hub gene-associated TF-miRNA-mRNA regulatory network. RESULTS: We identified a total of 147 DEGs shared by OB and PD (38 down-regulated and 109 up-regulated). Functional analysis showed that these genes were mainly enriched in immune-related pathways such as B cell receptor signalling, leukocyte migration and cellular defence responses. 14 hub genes (FGR, MNDA, NCF2, FYB1, EVI2B, LY86, IGSF6, CTSS, CXCR4, LCK, FCN1, CXCL2, P2RY13, MMP7) showed high sensitivity and specificity in the ROC curve analysis. The results of immune infiltration analysis showed that immune cells such as macrophages, activated CD4 T cells and immune B cells were present at high infiltration levels in both OB and PD samples.The results of GeneMANIA analysis and GSEA analysis suggested that five key genes (FGR, LCK, FYB1, LY86 and P2RY13) may be strongly associated with macrophages. Finally, we constructed a TF-miRNA-mRNA regulatory network consisting of 233 transcription factors (TFs), 8 miRNAs and 14 mRNAs based on the validated information obtained from the database. CONCLUSIONS: Five key genes (FGR, LCK, FYB1, LY86, P2RY13) may be important biomarkers of OB and PD. These genes may play an important role in the pathogenesis of OB and PD by affecting macrophage activity and participating in immune regulation and inflammatory responses. Frontiers Media S.A. 2023-03-29 /pmc/articles/PMC10090675/ /pubmed/37063877 http://dx.doi.org/10.3389/fimmu.2023.1101854 Text en Copyright © 2023 Cai, Zuo, Zuo, Wu, Pang, Ma, Yi, Tan, Deng, Qu and Chen 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 | Immunology Cai, Yisheng Zuo, Xuemei Zuo, Yuyang Wu, Shuang Pang, Weiwei Ma, Keqiang Yi, Qiaorong Tan, Lijun Deng, Hongwen Qu, Xiaochao Chen, Xiangding Transcriptomic analysis reveals shared gene signatures and molecular mechanisms between obesity and periodontitis |
title | Transcriptomic analysis reveals shared gene signatures and molecular mechanisms between obesity and periodontitis |
title_full | Transcriptomic analysis reveals shared gene signatures and molecular mechanisms between obesity and periodontitis |
title_fullStr | Transcriptomic analysis reveals shared gene signatures and molecular mechanisms between obesity and periodontitis |
title_full_unstemmed | Transcriptomic analysis reveals shared gene signatures and molecular mechanisms between obesity and periodontitis |
title_short | Transcriptomic analysis reveals shared gene signatures and molecular mechanisms between obesity and periodontitis |
title_sort | transcriptomic analysis reveals shared gene signatures and molecular mechanisms between obesity and periodontitis |
topic | Immunology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10090675/ https://www.ncbi.nlm.nih.gov/pubmed/37063877 http://dx.doi.org/10.3389/fimmu.2023.1101854 |
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