4.7 Article

Comprehensive analysis of mitochondrial dysfunction and necroptosis in intracranial aneurysms from the perspective of predictive, preventative, and personalized medicine

Journal

APOPTOSIS
Volume 28, Issue 9-10, Pages 1452-1468

Publisher

SPRINGER
DOI: 10.1007/s10495-023-01865-x

Keywords

Intracranialaneurysm; Mitochondrial dysfunction; Necroptosis; Bioinformatics; 3P medicine

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Mitochondrial dysfunction and necroptosis play important roles in multiple cardiovascular diseases, and their implications in intracranial aneurysms (IAs) are unclear. This study aimed to explore their value in predictive, preventive, and personalized medicine for IAs. Key genes involved in mitochondrial dysfunction and necroptosis were identified, and their diagnostic value for IA was confirmed using machine learning. Single-cell sequencing analysis showed that mitochondrial dysfunction and necroptosis were up-regulated in monocytes/macrophages and vascular smooth muscle cells within IA lesions. Mitochondria-induced necroptosis may be a novel potential target for the diagnosis, prevention, and treatment of IA.
Mitochondrial dysfunction and necroptosis are closely associated, and play vital roles in the medical strategy of multiple cardiovascular diseases. However, their implications in intracranial aneurysms (IAs) remain unclear. In this study, we aimed to explore whether mitochondrial dysfunction and necroptosis could be identified as valuable starting points for predictive, preventive, and personalized medicine for IAs. The transcriptional profiles of 75 IAs and 37 control samples were collected from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs), weighted gene co-expression network analysis, and least absolute shrinkage and selection operator (LASSO) regression were used to screen key genes. The ssGSEA algorithm was performed to establish phenotype scores. The correlation between mitochondrial dysfunction and necroptosis was evaluated using functional enrichment crossover, phenotype score correlation, immune infiltration, and interaction network construction. The IA diagnostic values of key genes were identified using machine learning. Finally, we performed the single-cell sequencing (scRNA-seq) analysis to explore mitochondrial dysfunction and necroptosis at the cellular level. In total, 42 IA-mitochondrial DEGs and 15 IA-necroptosis DEGs were identified. Screening revealed seven key genes invovled in mitochondrial dysfunction (KMO, HADH, BAX, AADAT, SDSL, PYCR1, and MAOA) and five genes involved in necroptosis (IL1B, CAMK2G, STAT1, NLRP3, and BAX). Machine learning confirmed the high diagnostic value of these key genes for IA. The IA samples showed higher expression of mitochondrial dysfunction and necroptosis. Mitochondrial dysfunction and necroptosis exhibited a close association. Furthermore, scRNA-seq indicated that mitochondrial dysfunction and necroptosis were preferentially up-regulated in monocytes/macrophages and vascular smooth muscle cells (VSMCs) within IA lesions. In conclusion, mitochondria-induced necroptosis was involved in IA formation, and was mainly up-regulated in monocytes/macrophages and VSMCs within IA lesions. Mitochondria-induced necroptosis may be a novel potential target for diagnosis, prevention, and treatment of IA.

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