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The underlying molecular mechanisms and biomarkers of plaque vulnerability based on bioinformatics analysis

AIM: The study aimed to identify the underlying differentially expressed genes (DEGs) and mechanism of unstable atherosclerotic plaque using bioinformatics methods. METHODS: GSE120521, which includes four unstable samples and four stable atherosclerotic samples, was downloaded from the GEO database....

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Autores principales: Cheng, Rui, Xu, Xiaojiang, Yang, Shurong, mi, Zhongqian, Zhao, Yong, gao, Jinhua, Yu, Feiyan, Ren, Xiuyun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9615401/
https://www.ncbi.nlm.nih.gov/pubmed/36303246
http://dx.doi.org/10.1186/s40001-022-00840-7
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author Cheng, Rui
Xu, Xiaojiang
Yang, Shurong
mi, Zhongqian
Zhao, Yong
gao, Jinhua
Yu, Feiyan
Ren, Xiuyun
author_facet Cheng, Rui
Xu, Xiaojiang
Yang, Shurong
mi, Zhongqian
Zhao, Yong
gao, Jinhua
Yu, Feiyan
Ren, Xiuyun
author_sort Cheng, Rui
collection PubMed
description AIM: The study aimed to identify the underlying differentially expressed genes (DEGs) and mechanism of unstable atherosclerotic plaque using bioinformatics methods. METHODS: GSE120521, which includes four unstable samples and four stable atherosclerotic samples, was downloaded from the GEO database. DEGs were identified using LIMMA. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses of DEGs were performed using the Database for metascape Visualization online tool. Based on the STRING database, protein–protein interactions (PPIs) network among DEGs were constructed. Regulatory networks were visualized using Cytoscape. We use the xCell to analyze the different immune cell subtypes. RESULTS: A total of 1626 DEGs (1034 up-regulated and 592 down-regulated DEGs) were identified between unstable and stable samples. I pulled 62 transcription factors (34 up-regulated TFs and 28 down-regulated TFs) from the Trust database. The up-regulated TFs were mainly enrichment in positive regulation of myeloid leukocyte differentiation, and the down-regulated TFs were mainly enrichment in connective tissue development. In the PPI network, RB1, CEBPA, PPARG, BATF was the most significantly up-regulated gene in ruptured atherosclerotic samples. The immune cell composition enriched in CD cells and macrophages in the unstable carotid plaque. CONCLUSIONS: Upregulated RB1, CEBPA, PPARG, BATF and down-regulated SRF, MYOCD, HEY2, GATA6 might perform critical promotional roles in atherosclerotic plaque rupture, furthermore, number and polarization of macrophages may play an important role in vulnerable plaques. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s40001-022-00840-7.
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spelling pubmed-96154012022-10-29 The underlying molecular mechanisms and biomarkers of plaque vulnerability based on bioinformatics analysis Cheng, Rui Xu, Xiaojiang Yang, Shurong mi, Zhongqian Zhao, Yong gao, Jinhua Yu, Feiyan Ren, Xiuyun Eur J Med Res Research AIM: The study aimed to identify the underlying differentially expressed genes (DEGs) and mechanism of unstable atherosclerotic plaque using bioinformatics methods. METHODS: GSE120521, which includes four unstable samples and four stable atherosclerotic samples, was downloaded from the GEO database. DEGs were identified using LIMMA. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses of DEGs were performed using the Database for metascape Visualization online tool. Based on the STRING database, protein–protein interactions (PPIs) network among DEGs were constructed. Regulatory networks were visualized using Cytoscape. We use the xCell to analyze the different immune cell subtypes. RESULTS: A total of 1626 DEGs (1034 up-regulated and 592 down-regulated DEGs) were identified between unstable and stable samples. I pulled 62 transcription factors (34 up-regulated TFs and 28 down-regulated TFs) from the Trust database. The up-regulated TFs were mainly enrichment in positive regulation of myeloid leukocyte differentiation, and the down-regulated TFs were mainly enrichment in connective tissue development. In the PPI network, RB1, CEBPA, PPARG, BATF was the most significantly up-regulated gene in ruptured atherosclerotic samples. The immune cell composition enriched in CD cells and macrophages in the unstable carotid plaque. CONCLUSIONS: Upregulated RB1, CEBPA, PPARG, BATF and down-regulated SRF, MYOCD, HEY2, GATA6 might perform critical promotional roles in atherosclerotic plaque rupture, furthermore, number and polarization of macrophages may play an important role in vulnerable plaques. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s40001-022-00840-7. BioMed Central 2022-10-27 /pmc/articles/PMC9615401/ /pubmed/36303246 http://dx.doi.org/10.1186/s40001-022-00840-7 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Cheng, Rui
Xu, Xiaojiang
Yang, Shurong
mi, Zhongqian
Zhao, Yong
gao, Jinhua
Yu, Feiyan
Ren, Xiuyun
The underlying molecular mechanisms and biomarkers of plaque vulnerability based on bioinformatics analysis
title The underlying molecular mechanisms and biomarkers of plaque vulnerability based on bioinformatics analysis
title_full The underlying molecular mechanisms and biomarkers of plaque vulnerability based on bioinformatics analysis
title_fullStr The underlying molecular mechanisms and biomarkers of plaque vulnerability based on bioinformatics analysis
title_full_unstemmed The underlying molecular mechanisms and biomarkers of plaque vulnerability based on bioinformatics analysis
title_short The underlying molecular mechanisms and biomarkers of plaque vulnerability based on bioinformatics analysis
title_sort underlying molecular mechanisms and biomarkers of plaque vulnerability based on bioinformatics analysis
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9615401/
https://www.ncbi.nlm.nih.gov/pubmed/36303246
http://dx.doi.org/10.1186/s40001-022-00840-7
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