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Comprehensive analysis of epigenomics and transcriptome data to identify potential target genes associated with obesity
DNA methylation is closely related to the occurrence and development of many diseases, but its role in obesity is still unclear. This study aimed to find the potential differentially methylated genes associated with obesity occurrence and development. By combining methylation and transcriptome analy...
Autores principales: | , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9614047/ https://www.ncbi.nlm.nih.gov/pubmed/36313453 http://dx.doi.org/10.3389/fgene.2022.1024300 |
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author | Wu, Peili Guo, Lei Li, Xuelin Du, Yuejun Lin, Xiaochun Ma, Xiaoqin Lin, Yingbei Wen, Churan Yang, Chuyi Liu, Nannan Feng, Qijian Xue, Yaoming Guan, Meiping |
author_facet | Wu, Peili Guo, Lei Li, Xuelin Du, Yuejun Lin, Xiaochun Ma, Xiaoqin Lin, Yingbei Wen, Churan Yang, Chuyi Liu, Nannan Feng, Qijian Xue, Yaoming Guan, Meiping |
author_sort | Wu, Peili |
collection | PubMed |
description | DNA methylation is closely related to the occurrence and development of many diseases, but its role in obesity is still unclear. This study aimed to find the potential differentially methylated genes associated with obesity occurrence and development. By combining methylation and transcriptome analysis, we identified the key genes in adipose tissue affecting the occurrence and development of obesity and revealed the possible molecular mechanisms involved in obesity pathogenesis. We first screened 14 methylation-related differential genes and verified their expression in adipose tissue by quantitative polymerase chain reaction (qPCR). Seven genes with the same expression pattern were identified as key genes, namely, CCRL2, GPT, LGALS12, PC, SLC27A2, SLC4A4, and TTC36. Then, the immune microenvironment of adipose tissue was quantified by CIBERSORT, and we found that the content of M0 macrophages and T follicular helper cells in adipose tissue was significantly increased and decreased, respectively, in the obese group. Furthermore, the relationship between key genes and the immune microenvironment was analyzed. Additionally, the metabolic pathway activity of each sample was calculated based on the ssGSEA algorithm, and the key gene–metabolic network was constructed. Moreover, we performed a CMAP analysis based on the differential genes in adipose tissue to screen out drugs potentially effective in obesity treatment. In conclusion, we identified seven methylation-related key genes closely related to obesity pathogenesis and explored the potential mechanism of their role in obesity. This study provided novel insights into the molecular mechanisms and management of obesity. |
format | Online Article Text |
id | pubmed-9614047 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-96140472022-10-29 Comprehensive analysis of epigenomics and transcriptome data to identify potential target genes associated with obesity Wu, Peili Guo, Lei Li, Xuelin Du, Yuejun Lin, Xiaochun Ma, Xiaoqin Lin, Yingbei Wen, Churan Yang, Chuyi Liu, Nannan Feng, Qijian Xue, Yaoming Guan, Meiping Front Genet Genetics DNA methylation is closely related to the occurrence and development of many diseases, but its role in obesity is still unclear. This study aimed to find the potential differentially methylated genes associated with obesity occurrence and development. By combining methylation and transcriptome analysis, we identified the key genes in adipose tissue affecting the occurrence and development of obesity and revealed the possible molecular mechanisms involved in obesity pathogenesis. We first screened 14 methylation-related differential genes and verified their expression in adipose tissue by quantitative polymerase chain reaction (qPCR). Seven genes with the same expression pattern were identified as key genes, namely, CCRL2, GPT, LGALS12, PC, SLC27A2, SLC4A4, and TTC36. Then, the immune microenvironment of adipose tissue was quantified by CIBERSORT, and we found that the content of M0 macrophages and T follicular helper cells in adipose tissue was significantly increased and decreased, respectively, in the obese group. Furthermore, the relationship between key genes and the immune microenvironment was analyzed. Additionally, the metabolic pathway activity of each sample was calculated based on the ssGSEA algorithm, and the key gene–metabolic network was constructed. Moreover, we performed a CMAP analysis based on the differential genes in adipose tissue to screen out drugs potentially effective in obesity treatment. In conclusion, we identified seven methylation-related key genes closely related to obesity pathogenesis and explored the potential mechanism of their role in obesity. This study provided novel insights into the molecular mechanisms and management of obesity. Frontiers Media S.A. 2022-10-14 /pmc/articles/PMC9614047/ /pubmed/36313453 http://dx.doi.org/10.3389/fgene.2022.1024300 Text en Copyright © 2022 Wu, Guo, Li, Du, Lin, Ma, Lin, Wen, Yang, Liu, Feng, Xue and Guan. 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 Wu, Peili Guo, Lei Li, Xuelin Du, Yuejun Lin, Xiaochun Ma, Xiaoqin Lin, Yingbei Wen, Churan Yang, Chuyi Liu, Nannan Feng, Qijian Xue, Yaoming Guan, Meiping Comprehensive analysis of epigenomics and transcriptome data to identify potential target genes associated with obesity |
title | Comprehensive analysis of epigenomics and transcriptome data to identify potential target genes associated with obesity |
title_full | Comprehensive analysis of epigenomics and transcriptome data to identify potential target genes associated with obesity |
title_fullStr | Comprehensive analysis of epigenomics and transcriptome data to identify potential target genes associated with obesity |
title_full_unstemmed | Comprehensive analysis of epigenomics and transcriptome data to identify potential target genes associated with obesity |
title_short | Comprehensive analysis of epigenomics and transcriptome data to identify potential target genes associated with obesity |
title_sort | comprehensive analysis of epigenomics and transcriptome data to identify potential target genes associated with obesity |
topic | Genetics |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9614047/ https://www.ncbi.nlm.nih.gov/pubmed/36313453 http://dx.doi.org/10.3389/fgene.2022.1024300 |
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