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Identification of inflammation-related DNA methylation biomarkers in periodontitis patients based on weighted co-expression analysis
Evidence from past research has shown that DNA methylation plays a key role in the pathogenesis of periodontitis, regulating gene expression levels and thereby affecting the occurrence of various diseases. Three sample sets of methylation data and gene expression data were downloaded from Gene Expre...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Impact Journals
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8386560/ https://www.ncbi.nlm.nih.gov/pubmed/34347624 http://dx.doi.org/10.18632/aging.203378 |
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author | Wang, Pengcheng Wang, Bingbing Zhang, Zheng Wang, Zuomin |
author_facet | Wang, Pengcheng Wang, Bingbing Zhang, Zheng Wang, Zuomin |
author_sort | Wang, Pengcheng |
collection | PubMed |
description | Evidence from past research has shown that DNA methylation plays a key role in the pathogenesis of periodontitis, regulating gene expression levels and thereby affecting the occurrence of various diseases. Three sample sets of methylation data and gene expression data were downloaded from Gene Expression Omnibus (GEO) database. A diagnostic classifier is established based on gene expression data and CpG methylation data. Abnormal expression of immune-related pathways and methyltransferase-related genes in patients with periodontitis was detected. A total of 8,029 differentially expressed CpG (DMP) was annotated to the promoter region of 4,940 genes, of which 295 immune genes were significantly enriched. The CpG sites of 23 differentially co-expressed immune gene promoter regions were identified, and 13 CpG were generally hypermethylated in healthy group samples, while some were methylated in most patients. Five CpGs were screened as robust periodontitis biomarkers. The accuracy in the training data set, the two external verification data sets, and in the transcriptome was 95.5%, 80% and 78.3%, and 82.6%, respectively. This study provided new features for the diagnosis of periodontitis, and contributed to the personalized treatment of periodontitis. |
format | Online Article Text |
id | pubmed-8386560 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Impact Journals |
record_format | MEDLINE/PubMed |
spelling | pubmed-83865602021-08-27 Identification of inflammation-related DNA methylation biomarkers in periodontitis patients based on weighted co-expression analysis Wang, Pengcheng Wang, Bingbing Zhang, Zheng Wang, Zuomin Aging (Albany NY) Research Paper Evidence from past research has shown that DNA methylation plays a key role in the pathogenesis of periodontitis, regulating gene expression levels and thereby affecting the occurrence of various diseases. Three sample sets of methylation data and gene expression data were downloaded from Gene Expression Omnibus (GEO) database. A diagnostic classifier is established based on gene expression data and CpG methylation data. Abnormal expression of immune-related pathways and methyltransferase-related genes in patients with periodontitis was detected. A total of 8,029 differentially expressed CpG (DMP) was annotated to the promoter region of 4,940 genes, of which 295 immune genes were significantly enriched. The CpG sites of 23 differentially co-expressed immune gene promoter regions were identified, and 13 CpG were generally hypermethylated in healthy group samples, while some were methylated in most patients. Five CpGs were screened as robust periodontitis biomarkers. The accuracy in the training data set, the two external verification data sets, and in the transcriptome was 95.5%, 80% and 78.3%, and 82.6%, respectively. This study provided new features for the diagnosis of periodontitis, and contributed to the personalized treatment of periodontitis. Impact Journals 2021-08-04 /pmc/articles/PMC8386560/ /pubmed/34347624 http://dx.doi.org/10.18632/aging.203378 Text en Copyright: © 2021 Wang et al. https://creativecommons.org/licenses/by/3.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/3.0/) (CC BY 3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Paper Wang, Pengcheng Wang, Bingbing Zhang, Zheng Wang, Zuomin Identification of inflammation-related DNA methylation biomarkers in periodontitis patients based on weighted co-expression analysis |
title | Identification of inflammation-related DNA methylation biomarkers in periodontitis patients based on weighted co-expression analysis |
title_full | Identification of inflammation-related DNA methylation biomarkers in periodontitis patients based on weighted co-expression analysis |
title_fullStr | Identification of inflammation-related DNA methylation biomarkers in periodontitis patients based on weighted co-expression analysis |
title_full_unstemmed | Identification of inflammation-related DNA methylation biomarkers in periodontitis patients based on weighted co-expression analysis |
title_short | Identification of inflammation-related DNA methylation biomarkers in periodontitis patients based on weighted co-expression analysis |
title_sort | identification of inflammation-related dna methylation biomarkers in periodontitis patients based on weighted co-expression analysis |
topic | Research Paper |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8386560/ https://www.ncbi.nlm.nih.gov/pubmed/34347624 http://dx.doi.org/10.18632/aging.203378 |
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