IMR Press / FBL / Volume 28 / Issue 11 / DOI: 10.31083/j.fbl2811289
Open Access Original Research
Comprehensive Analysis of Regulated Cell Death in Intracranial Aneurysms
Jianyu Zhu1,2,3Zhicheng Wang1,2,3Jiebo Li1,2,3Dezhi Kang1,2,3,*
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1 Department of Neurosurgery, National Regional Medical Center, Binhai Campus of the First Affiliated Hospital, Fujian Medical University, 350212 Fuzhou, Fujian, China
2 Department of Neurosurgery, The First Affiliated Hospital, Fujian Medical University, 350005 Fuzhou, Fujian, China
3 Fujian Institute of Neurology, The First Affiliated Hospital, Fujian Medical University, 350005 Fuzhou, Fujian, China
*Correspondence: kdz99988@vip.sina.com (Dezhi Kang)
Front. Biosci. (Landmark Ed) 2023, 28(11), 289; https://doi.org/10.31083/j.fbl2811289
Submitted: 23 March 2023 | Revised: 25 June 2023 | Accepted: 5 July 2023 | Published: 16 November 2023
Copyright: © 2023 The Author(s). Published by IMR Press.
This is an open access article under the CC BY 4.0 license.
Abstract

Background: Abnormalities in regulated cell death (RCD) are involved in multiple diseases. However, the role of RCD in intracranial aneurysms (IA) remains unknown. The aim of this study was to explore different RCD processes in the pathogenesis of IA. Methods: Four microarray datasets (GSE75436, GSE54083, GSE13353, GSE15629) and one RNA sequencing (RNA-seq) dataset (GSE122897) were extracted from the Gene Expression Omnibus (GEO) database. The microarray datasets were merged to form the training set, while the RNA-seq dataset was used as the validation set. Differentially expressed genes (DEGs), gene set enrichment analysis (GSEA), and gene set variation analysis (GSVA) were used to investigate the role of different types of RCD, including apoptosis, necroptosis, autophagy, ferroptosis and pyroptosis in the formation of IA. A novel cell death classification system for IA was established using an unsupervised consensus clustering algorithm based on cell death signature genes. Differences in functional enrichment, cell death-related regulators, and immune infiltration between two cell death clusters were evaluated. Finally, predictive genes were identified using the least absolute shrinkage and selection operator (LASSO) regression, random forest and logistic regression, allowing a prediction model to be constructed for IA rupture. Results: Multiple RCD processes were significantly activated in IAs compared to controls. A total of 33 signature genes related to cell death were identified. The IA samples were divided into two clusters based on the cell death signature. The cell death-high subtype had a relatively higher rate of rupture, and higher enrichment levels for multiple cell death processes and several signal transduction and immune-related pathways. Immune infiltration analysis showed that cell death scores were correlated with multiple immune cell types, including macrophages, mast cells, T cells and B cells. A six-gene prediction model was constructed to predict rupture. The area under curves (AUCs) for predicting rupture in the training and validation cohorts were 0.924 and 0.855, respectively. Conclusions: Comprehensively analysis of RCD in IA and found that multiple RCD types are likely to be involved in IA formation and rupture. These cell death processes were correlated with inflammation and immunity. We present novel insights into the mechanism of IA pathogenesis that should help to guide further research.

Keywords
intracranial aneurysm
regulated cell death
rupture
inflammation
immunity
Funding
82171327/National Nature Science Foundation of China
2022QH2029/Startup Fund for scientific research, Fujian Medical University
Figures
Fig. 1.
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