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Shared Molecular Mechanisms between Alzheimer's Disease and Periodontitis Revealed by Transcriptomic Analysis
OBJECTIVE: To investigate the genetic crosstalk mechanisms that link periodontitis and Alzheimer's disease (AD). BACKGROUND: Periodontitis, a common oral infectious disease, is associated with Alzheimer's disease (AD) and considered a putative contributory factor to its progression. Howeve...
Autores principales: | , , , , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8032519/ https://www.ncbi.nlm.nih.gov/pubmed/33869630 http://dx.doi.org/10.1155/2021/6633563 |
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author | Jin, Jieqi Guang, Mengkai Ogbuehi, Anthony Chukwunonso Li, Simin Zhang, Kai Ma, Yihong Acharya, Aneesha Guo, Bihan Peng, Zongwu Liu, Xiangqiong Deng, Yupei Fang, Zhaobi Zhu, Xiongjie Hua, Shiting Li, Cong Haak, Rainer Ziebolz, Dirk Schmalz, Gerhard Liu, Lei Xu, Baohua Huang, Xiaofeng |
author_facet | Jin, Jieqi Guang, Mengkai Ogbuehi, Anthony Chukwunonso Li, Simin Zhang, Kai Ma, Yihong Acharya, Aneesha Guo, Bihan Peng, Zongwu Liu, Xiangqiong Deng, Yupei Fang, Zhaobi Zhu, Xiongjie Hua, Shiting Li, Cong Haak, Rainer Ziebolz, Dirk Schmalz, Gerhard Liu, Lei Xu, Baohua Huang, Xiaofeng |
author_sort | Jin, Jieqi |
collection | PubMed |
description | OBJECTIVE: To investigate the genetic crosstalk mechanisms that link periodontitis and Alzheimer's disease (AD). BACKGROUND: Periodontitis, a common oral infectious disease, is associated with Alzheimer's disease (AD) and considered a putative contributory factor to its progression. However, a comprehensive investigation of potential shared genetic mechanisms between these diseases has not yet been reported. METHODS: Gene expression datasets related to periodontitis were downloaded from the Gene Expression Omnibus (GEO) database, and differential expression analysis was performed to identify differentially expressed genes (DEGs). Genes associated with AD were downloaded from the DisGeNET database. Overlapping genes among the DEGs in periodontitis and the AD-related genes were defined as crosstalk genes between periodontitis and AD. The Boruta algorithm was applied to perform feature selection from these crosstalk genes, and representative crosstalk genes were thus obtained. In addition, a support vector machine (SVM) model was constructed by using the scikit-learn algorithm in Python. Next, the crosstalk gene-TF network and crosstalk gene-DEP (differentially expressed pathway) network were each constructed. As a final step, shared genes among the crosstalk genes and periodontitis-related genes in DisGeNET were identified and denoted as the core crosstalk genes. RESULTS: Four datasets (GSE23586, GSE16134, GSE10334, and GSE79705) pertaining to periodontitis were included in the analysis. A total of 48 representative crosstalk genes were identified by using the Boruta algorithm. Three TFs (FOS, MEF2C, and USF2) and several pathways (i.e., JAK-STAT, MAPK, NF-kappa B, and natural killer cell-mediated cytotoxicity) were identified as regulators of these crosstalk genes. Among these 48 crosstalk genes and the chronic periodontitis-related genes in DisGeNET, C4A, C4B, CXCL12, FCGR3A, IL1B, and MMP3 were shared and identified as the most pivotal candidate links between periodontitis and AD. CONCLUSIONS: Exploration of available transcriptomic datasets revealed C4A, C4B, CXCL12, FCGR3A, IL1B, and MMP3 as the top candidate molecular linkage genes between periodontitis and AD. |
format | Online Article Text |
id | pubmed-8032519 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Hindawi |
record_format | MEDLINE/PubMed |
spelling | pubmed-80325192021-04-16 Shared Molecular Mechanisms between Alzheimer's Disease and Periodontitis Revealed by Transcriptomic Analysis Jin, Jieqi Guang, Mengkai Ogbuehi, Anthony Chukwunonso Li, Simin Zhang, Kai Ma, Yihong Acharya, Aneesha Guo, Bihan Peng, Zongwu Liu, Xiangqiong Deng, Yupei Fang, Zhaobi Zhu, Xiongjie Hua, Shiting Li, Cong Haak, Rainer Ziebolz, Dirk Schmalz, Gerhard Liu, Lei Xu, Baohua Huang, Xiaofeng Biomed Res Int Research Article OBJECTIVE: To investigate the genetic crosstalk mechanisms that link periodontitis and Alzheimer's disease (AD). BACKGROUND: Periodontitis, a common oral infectious disease, is associated with Alzheimer's disease (AD) and considered a putative contributory factor to its progression. However, a comprehensive investigation of potential shared genetic mechanisms between these diseases has not yet been reported. METHODS: Gene expression datasets related to periodontitis were downloaded from the Gene Expression Omnibus (GEO) database, and differential expression analysis was performed to identify differentially expressed genes (DEGs). Genes associated with AD were downloaded from the DisGeNET database. Overlapping genes among the DEGs in periodontitis and the AD-related genes were defined as crosstalk genes between periodontitis and AD. The Boruta algorithm was applied to perform feature selection from these crosstalk genes, and representative crosstalk genes were thus obtained. In addition, a support vector machine (SVM) model was constructed by using the scikit-learn algorithm in Python. Next, the crosstalk gene-TF network and crosstalk gene-DEP (differentially expressed pathway) network were each constructed. As a final step, shared genes among the crosstalk genes and periodontitis-related genes in DisGeNET were identified and denoted as the core crosstalk genes. RESULTS: Four datasets (GSE23586, GSE16134, GSE10334, and GSE79705) pertaining to periodontitis were included in the analysis. A total of 48 representative crosstalk genes were identified by using the Boruta algorithm. Three TFs (FOS, MEF2C, and USF2) and several pathways (i.e., JAK-STAT, MAPK, NF-kappa B, and natural killer cell-mediated cytotoxicity) were identified as regulators of these crosstalk genes. Among these 48 crosstalk genes and the chronic periodontitis-related genes in DisGeNET, C4A, C4B, CXCL12, FCGR3A, IL1B, and MMP3 were shared and identified as the most pivotal candidate links between periodontitis and AD. CONCLUSIONS: Exploration of available transcriptomic datasets revealed C4A, C4B, CXCL12, FCGR3A, IL1B, and MMP3 as the top candidate molecular linkage genes between periodontitis and AD. Hindawi 2021-04-01 /pmc/articles/PMC8032519/ /pubmed/33869630 http://dx.doi.org/10.1155/2021/6633563 Text en Copyright © 2021 Jieqi Jin et al. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Article Jin, Jieqi Guang, Mengkai Ogbuehi, Anthony Chukwunonso Li, Simin Zhang, Kai Ma, Yihong Acharya, Aneesha Guo, Bihan Peng, Zongwu Liu, Xiangqiong Deng, Yupei Fang, Zhaobi Zhu, Xiongjie Hua, Shiting Li, Cong Haak, Rainer Ziebolz, Dirk Schmalz, Gerhard Liu, Lei Xu, Baohua Huang, Xiaofeng Shared Molecular Mechanisms between Alzheimer's Disease and Periodontitis Revealed by Transcriptomic Analysis |
title | Shared Molecular Mechanisms between Alzheimer's Disease and Periodontitis Revealed by Transcriptomic Analysis |
title_full | Shared Molecular Mechanisms between Alzheimer's Disease and Periodontitis Revealed by Transcriptomic Analysis |
title_fullStr | Shared Molecular Mechanisms between Alzheimer's Disease and Periodontitis Revealed by Transcriptomic Analysis |
title_full_unstemmed | Shared Molecular Mechanisms between Alzheimer's Disease and Periodontitis Revealed by Transcriptomic Analysis |
title_short | Shared Molecular Mechanisms between Alzheimer's Disease and Periodontitis Revealed by Transcriptomic Analysis |
title_sort | shared molecular mechanisms between alzheimer's disease and periodontitis revealed by transcriptomic analysis |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8032519/ https://www.ncbi.nlm.nih.gov/pubmed/33869630 http://dx.doi.org/10.1155/2021/6633563 |
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