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Identifying and validating key genes mediating intracranial aneurysm rupture using weighted correlation network analysis and exploration of personalized treatment

BACKGROUND: Intracranial aneurysmal subarachnoid hemorrhage (aSAH) is a dangerous and highly fatal condition if ruptured. Significant advances have been made in the treatment of unruptured intracranial aneurysms (UIAs), but risk assessment methods for early diagnosis of intracranial aneurysm (IA) ru...

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Autores principales: Wu, Ji, Chen, Zhi-Jun, Liang, Jing, Lai, Chang-Sheng, Li, Xue-Yu, Yang, Zhao-Jian
Formato: Online Artículo Texto
Lenguaje:English
Publicado: AME Publishing Company 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9622481/
https://www.ncbi.nlm.nih.gov/pubmed/36330394
http://dx.doi.org/10.21037/atm-22-4068
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author Wu, Ji
Chen, Zhi-Jun
Liang, Jing
Lai, Chang-Sheng
Li, Xue-Yu
Yang, Zhao-Jian
author_facet Wu, Ji
Chen, Zhi-Jun
Liang, Jing
Lai, Chang-Sheng
Li, Xue-Yu
Yang, Zhao-Jian
author_sort Wu, Ji
collection PubMed
description BACKGROUND: Intracranial aneurysmal subarachnoid hemorrhage (aSAH) is a dangerous and highly fatal condition if ruptured. Significant advances have been made in the treatment of unruptured intracranial aneurysms (UIAs), but risk assessment methods for early diagnosis of intracranial aneurysm (IA) rupture remain limited. METHODS: The datasets of IA GSE13353, GSE15629, and GSE54083 were downloaded through the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) in unruptured and ruptured aneurysms were identified by R software using methods such as gene set enrichment analysis (GSEA) and weighted gene co-expression network analysis (WGCNA). Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis were performed on the DEGs, and logistic regression models were used to construct a prediction model to discriminate UIA from healthy samples. We then performed GSEA on the genes in the model, followed by model validation using the GSE54083 dataset. Finally, we used the single-sample (ss)GSEA method to investigate the relationship between the diagnostic model genes and immune cells and immune function. RESULTS: A total of 79 DEGs were obtained in patients with IA rupture compared to unruptured controls. The results of KEGG and GO enrichment analysis showed that neutrophil activation is involved in immune response, neutrophil mediated immunity, and positive regulation of angiogenesis. Interestingly, the results of immunoassays demonstrated that the break in IA may be associated with immune T cells. We used DEGs and WGCNA to determine common genes. The logistic regression model was trained based on 24 intersecting genes, and eventually retained 2 genes, KIAA0226L and UPP1, which we found to be reliable using the validation set, and GSEA revealed that the diagnostic model was associated with the Hippo signaling pathway and vascular smooth muscle contraction, and viral protein interaction with cytokine and cytokine were also associated. Finally explored using the CMap database, Tivozanib could be a potential small molecule drug for the treatment of ruptured intracranial aneurysms (RIAs). CONCLUSIONS: We identified new diagnostic genes associated with IA rupture, which may provide a new way of aneurysm diagnosis.
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spelling pubmed-96224812022-11-02 Identifying and validating key genes mediating intracranial aneurysm rupture using weighted correlation network analysis and exploration of personalized treatment Wu, Ji Chen, Zhi-Jun Liang, Jing Lai, Chang-Sheng Li, Xue-Yu Yang, Zhao-Jian Ann Transl Med Original Article BACKGROUND: Intracranial aneurysmal subarachnoid hemorrhage (aSAH) is a dangerous and highly fatal condition if ruptured. Significant advances have been made in the treatment of unruptured intracranial aneurysms (UIAs), but risk assessment methods for early diagnosis of intracranial aneurysm (IA) rupture remain limited. METHODS: The datasets of IA GSE13353, GSE15629, and GSE54083 were downloaded through the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) in unruptured and ruptured aneurysms were identified by R software using methods such as gene set enrichment analysis (GSEA) and weighted gene co-expression network analysis (WGCNA). Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis were performed on the DEGs, and logistic regression models were used to construct a prediction model to discriminate UIA from healthy samples. We then performed GSEA on the genes in the model, followed by model validation using the GSE54083 dataset. Finally, we used the single-sample (ss)GSEA method to investigate the relationship between the diagnostic model genes and immune cells and immune function. RESULTS: A total of 79 DEGs were obtained in patients with IA rupture compared to unruptured controls. The results of KEGG and GO enrichment analysis showed that neutrophil activation is involved in immune response, neutrophil mediated immunity, and positive regulation of angiogenesis. Interestingly, the results of immunoassays demonstrated that the break in IA may be associated with immune T cells. We used DEGs and WGCNA to determine common genes. The logistic regression model was trained based on 24 intersecting genes, and eventually retained 2 genes, KIAA0226L and UPP1, which we found to be reliable using the validation set, and GSEA revealed that the diagnostic model was associated with the Hippo signaling pathway and vascular smooth muscle contraction, and viral protein interaction with cytokine and cytokine were also associated. Finally explored using the CMap database, Tivozanib could be a potential small molecule drug for the treatment of ruptured intracranial aneurysms (RIAs). CONCLUSIONS: We identified new diagnostic genes associated with IA rupture, which may provide a new way of aneurysm diagnosis. AME Publishing Company 2022-10 /pmc/articles/PMC9622481/ /pubmed/36330394 http://dx.doi.org/10.21037/atm-22-4068 Text en 2022 Annals of Translational Medicine. All rights reserved. https://creativecommons.org/licenses/by-nc-nd/4.0/Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0 (https://creativecommons.org/licenses/by-nc-nd/4.0/) .
spellingShingle Original Article
Wu, Ji
Chen, Zhi-Jun
Liang, Jing
Lai, Chang-Sheng
Li, Xue-Yu
Yang, Zhao-Jian
Identifying and validating key genes mediating intracranial aneurysm rupture using weighted correlation network analysis and exploration of personalized treatment
title Identifying and validating key genes mediating intracranial aneurysm rupture using weighted correlation network analysis and exploration of personalized treatment
title_full Identifying and validating key genes mediating intracranial aneurysm rupture using weighted correlation network analysis and exploration of personalized treatment
title_fullStr Identifying and validating key genes mediating intracranial aneurysm rupture using weighted correlation network analysis and exploration of personalized treatment
title_full_unstemmed Identifying and validating key genes mediating intracranial aneurysm rupture using weighted correlation network analysis and exploration of personalized treatment
title_short Identifying and validating key genes mediating intracranial aneurysm rupture using weighted correlation network analysis and exploration of personalized treatment
title_sort identifying and validating key genes mediating intracranial aneurysm rupture using weighted correlation network analysis and exploration of personalized treatment
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9622481/
https://www.ncbi.nlm.nih.gov/pubmed/36330394
http://dx.doi.org/10.21037/atm-22-4068
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