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Immune Infiltration of Ulcerative Colitis and Detection of the m6A Subtype

Ulcerative colitis (UC) is an inflammatory bowel disease characterized by persistent colon inflammation. N6-methyladenosine (m6A) methylation is one of the most prevalent RNA modifications with key roles in both normal and illness, but m6A methylation in ulcerative colitis is unknown. This research...

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Autores principales: Gu, Chenzheng, Wu, Junlu, Zhang, Wei, Yao, Yiwen, Yan, Wenhui, Yuan, Yi, Wang, Weiwei, Shang, Anquan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9252851/
https://www.ncbi.nlm.nih.gov/pubmed/35795532
http://dx.doi.org/10.1155/2022/7280977
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author Gu, Chenzheng
Wu, Junlu
Zhang, Wei
Yao, Yiwen
Yan, Wenhui
Yuan, Yi
Wang, Weiwei
Shang, Anquan
author_facet Gu, Chenzheng
Wu, Junlu
Zhang, Wei
Yao, Yiwen
Yan, Wenhui
Yuan, Yi
Wang, Weiwei
Shang, Anquan
author_sort Gu, Chenzheng
collection PubMed
description Ulcerative colitis (UC) is an inflammatory bowel disease characterized by persistent colon inflammation. N6-methyladenosine (m6A) methylation is one of the most prevalent RNA modifications with key roles in both normal and illness, but m6A methylation in ulcerative colitis is unknown. This research investigated m6A methylation in UC. We examined the expression of known m6A RNA methylation regulators in UC using the Gene Expression Omnibus database (GEO database). First, we used m6A regulators to examine m6A change in UC samples. These two patient groups were created by clustering three m6A gene expression datasets. These genes were then utilized to build an m6A gene network using WGCNA and PPI. These networks were built using differentially expressed genes. The 12 m6A regulators were found to be dispersed throughout the chromosome. The study's data were then connected, revealing positive or negative relationships between genes or signaling pathways. Then, PCA of the 12 m6A-regulated genes indicated that the two patient groups could be discriminated in both PC1 and PC2 dimensions. The ssGSEA algorithm found that immune invading cells could be easily distinguished across diverse patient groups. Both groups had varied levels of popular cytokines. The differential gene analysis of the two samples yielded 517 genes like FTO and RFX7. It found 9 hub genes among 121 genes in the blue module, compared their expression in two groups of samples, and found that the differences in expression of these 9 genes were highly significant. The identification of 9 possible m6A methylation-dependent gene regulatory networks suggests that m6A methylation is involved in UC pathogenesis. Nine candidate genes have been identified as possible markers for assessing UC severity and developing innovative UC targeted therapeutic approaches.
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spelling pubmed-92528512022-07-05 Immune Infiltration of Ulcerative Colitis and Detection of the m6A Subtype Gu, Chenzheng Wu, Junlu Zhang, Wei Yao, Yiwen Yan, Wenhui Yuan, Yi Wang, Weiwei Shang, Anquan J Immunol Res Research Article Ulcerative colitis (UC) is an inflammatory bowel disease characterized by persistent colon inflammation. N6-methyladenosine (m6A) methylation is one of the most prevalent RNA modifications with key roles in both normal and illness, but m6A methylation in ulcerative colitis is unknown. This research investigated m6A methylation in UC. We examined the expression of known m6A RNA methylation regulators in UC using the Gene Expression Omnibus database (GEO database). First, we used m6A regulators to examine m6A change in UC samples. These two patient groups were created by clustering three m6A gene expression datasets. These genes were then utilized to build an m6A gene network using WGCNA and PPI. These networks were built using differentially expressed genes. The 12 m6A regulators were found to be dispersed throughout the chromosome. The study's data were then connected, revealing positive or negative relationships between genes or signaling pathways. Then, PCA of the 12 m6A-regulated genes indicated that the two patient groups could be discriminated in both PC1 and PC2 dimensions. The ssGSEA algorithm found that immune invading cells could be easily distinguished across diverse patient groups. Both groups had varied levels of popular cytokines. The differential gene analysis of the two samples yielded 517 genes like FTO and RFX7. It found 9 hub genes among 121 genes in the blue module, compared their expression in two groups of samples, and found that the differences in expression of these 9 genes were highly significant. The identification of 9 possible m6A methylation-dependent gene regulatory networks suggests that m6A methylation is involved in UC pathogenesis. Nine candidate genes have been identified as possible markers for assessing UC severity and developing innovative UC targeted therapeutic approaches. Hindawi 2022-06-25 /pmc/articles/PMC9252851/ /pubmed/35795532 http://dx.doi.org/10.1155/2022/7280977 Text en Copyright © 2022 Chenzheng Gu 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
Gu, Chenzheng
Wu, Junlu
Zhang, Wei
Yao, Yiwen
Yan, Wenhui
Yuan, Yi
Wang, Weiwei
Shang, Anquan
Immune Infiltration of Ulcerative Colitis and Detection of the m6A Subtype
title Immune Infiltration of Ulcerative Colitis and Detection of the m6A Subtype
title_full Immune Infiltration of Ulcerative Colitis and Detection of the m6A Subtype
title_fullStr Immune Infiltration of Ulcerative Colitis and Detection of the m6A Subtype
title_full_unstemmed Immune Infiltration of Ulcerative Colitis and Detection of the m6A Subtype
title_short Immune Infiltration of Ulcerative Colitis and Detection of the m6A Subtype
title_sort immune infiltration of ulcerative colitis and detection of the m6a subtype
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9252851/
https://www.ncbi.nlm.nih.gov/pubmed/35795532
http://dx.doi.org/10.1155/2022/7280977
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