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Bioinformatics analysis to identify potential biomarkers for the pulmonary artery hypertension associated with the basement membrane
Pulmonary arterial hypertension (PAH) is a rapidly progressing cardiopulmonary disease. It is characterized by increased pulmonary artery pressure and vascular resistance. The most notable histopathological characteristic is vascular remodeling. The changes in the basement membrane (BM) are believed...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
De Gruyter
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10523280/ https://www.ncbi.nlm.nih.gov/pubmed/37772261 http://dx.doi.org/10.1515/biol-2022-0730 |
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author | Li, Qian Zhang, Hu |
author_facet | Li, Qian Zhang, Hu |
author_sort | Li, Qian |
collection | PubMed |
description | Pulmonary arterial hypertension (PAH) is a rapidly progressing cardiopulmonary disease. It is characterized by increased pulmonary artery pressure and vascular resistance. The most notable histopathological characteristic is vascular remodeling. The changes in the basement membrane (BM) are believed to be related to vascular remodeling. It is crucial to identify potential biomarkers associated with the BM in PAH, to guide its treatment. The microarray datasets GSE117261 and GSE113439 were downloaded from the Gene Expression Omnibus. Two data sets were examined to identify genes associated with the BM by analyzing gene expression changes. Next, we analyzed the relevant genes in the Kyoto Encyclopedia of Genes and Genomes using Gene Ontology and Disease Ontology annotationand conducted pathway enrichment analysis. We conducted a protein–protein interaction network analysis on the genes related to BMs and used the cell cytoHubba plug-in to identify the hub genes. Furthermore, we conducted an immune infiltration analysis and implemented a histogram model. Finally, we predicted and analyzed potential therapeutic drugs for PAH and set up a miRNA network of genetic markers. Six candidate genes related to BMs, namely Integrin Subunit Alpha V, Integrin Subunit Alpha 4, ITGA2, ITGA9, Thrombospondin 1, and Collagen Type IV Alpha 3 Chain, were identified as potential modulators of the immune process in PAH. Furthermore, ginsenoside Rh1 was found to significantly impact drug targeting based on its interactions with the six BM-related genes identified earlier. A novel biomarker related to the BM, which plays a crucial role in the development of PAH, has been identified. |
format | Online Article Text |
id | pubmed-10523280 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | De Gruyter |
record_format | MEDLINE/PubMed |
spelling | pubmed-105232802023-09-28 Bioinformatics analysis to identify potential biomarkers for the pulmonary artery hypertension associated with the basement membrane Li, Qian Zhang, Hu Open Life Sci Research Article Pulmonary arterial hypertension (PAH) is a rapidly progressing cardiopulmonary disease. It is characterized by increased pulmonary artery pressure and vascular resistance. The most notable histopathological characteristic is vascular remodeling. The changes in the basement membrane (BM) are believed to be related to vascular remodeling. It is crucial to identify potential biomarkers associated with the BM in PAH, to guide its treatment. The microarray datasets GSE117261 and GSE113439 were downloaded from the Gene Expression Omnibus. Two data sets were examined to identify genes associated with the BM by analyzing gene expression changes. Next, we analyzed the relevant genes in the Kyoto Encyclopedia of Genes and Genomes using Gene Ontology and Disease Ontology annotationand conducted pathway enrichment analysis. We conducted a protein–protein interaction network analysis on the genes related to BMs and used the cell cytoHubba plug-in to identify the hub genes. Furthermore, we conducted an immune infiltration analysis and implemented a histogram model. Finally, we predicted and analyzed potential therapeutic drugs for PAH and set up a miRNA network of genetic markers. Six candidate genes related to BMs, namely Integrin Subunit Alpha V, Integrin Subunit Alpha 4, ITGA2, ITGA9, Thrombospondin 1, and Collagen Type IV Alpha 3 Chain, were identified as potential modulators of the immune process in PAH. Furthermore, ginsenoside Rh1 was found to significantly impact drug targeting based on its interactions with the six BM-related genes identified earlier. A novel biomarker related to the BM, which plays a crucial role in the development of PAH, has been identified. De Gruyter 2023-09-26 /pmc/articles/PMC10523280/ /pubmed/37772261 http://dx.doi.org/10.1515/biol-2022-0730 Text en © 2023 the author(s), published by De Gruyter https://creativecommons.org/licenses/by/4.0/This work is licensed under the Creative Commons Attribution 4.0 International License. |
spellingShingle | Research Article Li, Qian Zhang, Hu Bioinformatics analysis to identify potential biomarkers for the pulmonary artery hypertension associated with the basement membrane |
title | Bioinformatics analysis to identify potential biomarkers for the pulmonary artery hypertension associated with the basement membrane |
title_full | Bioinformatics analysis to identify potential biomarkers for the pulmonary artery hypertension associated with the basement membrane |
title_fullStr | Bioinformatics analysis to identify potential biomarkers for the pulmonary artery hypertension associated with the basement membrane |
title_full_unstemmed | Bioinformatics analysis to identify potential biomarkers for the pulmonary artery hypertension associated with the basement membrane |
title_short | Bioinformatics analysis to identify potential biomarkers for the pulmonary artery hypertension associated with the basement membrane |
title_sort | bioinformatics analysis to identify potential biomarkers for the pulmonary artery hypertension associated with the basement membrane |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10523280/ https://www.ncbi.nlm.nih.gov/pubmed/37772261 http://dx.doi.org/10.1515/biol-2022-0730 |
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