Comprehensive Analysis of Regulated Cell Death in Intracranial Aneurysms

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.