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核心技术专利：CN118964589B侵权必究
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基于机器学习和单细胞测序数据的动脉粥样硬化中细胞铁死亡和细胞衰老相关生物标志物的综合分析

Integrated Analysis of Ferroptosis- and Cellular Senescence-Related Biomarkers in Atherosclerosis Based on Machine Learning and Single-Cell Sequencing Data.

作者信息

Qi Xiang, Cao Shan, Chen Jian, Yin XiaoLei

机构信息

Traditional Chinese Medicine (Zhong Jing) College, Henan University of Chinese Medicine, Zhengzhou, Henan, People's Republic of China.

School of Medicine, Henan University of Chinese Medicine, Zhengzhou, Henan, People's Republic of China.

出版信息

J Inflamm Res. 2025 Jul 15;18:9283-9305. doi: 10.2147/JIR.S529581. eCollection 2025.

DOI:10.2147/JIR.S529581
PMID:40687151
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC12276017/
Abstract

BACKGROUND: Atherosclerosis is a chronic inflammatory disease characterized by lipid accumulation in the vascular wall. The roles of ferroptosis and cellular senescence in Atherosclerosis remain unclear. This study aimed to identify genes related to ferroptosis and cellular senescence in Atherosclerosis using bioinformatics approaches. METHODS: Atherosclerosis gene expression datasets were obtained from the GEO database. Differentially expressed genes (DEGs) were identified and intersected with key genes from WGCNA modules, ferroptosis-related genes, and senescence-related genes to obtain common genes (CF-DEGs). Consensus clustering based on CF-DEGs was conducted to identify molecular subtypes, followed by differential expression analysis. Enrichment and immune infiltration analyses were used to investigate the biological functions and immune features of subtype-specific differentially expressed genes. Eight machine learning algorithms were applied to identify hub genes and construct a diagnostic model. Single-cell RNA-seq data were used to assess the roles of hub genes in cell communication and differentiation. Finally, animal experiments were performed to validate the expression of the hub genes. RESULTS: A total of 23 CF-DEGs were identified, based on which two molecular subtypes were defined. A total of 421 DEGs were found between subtypes. Immune infiltration analysis revealed significant differences in eight immune cell types, including activated dendritic cells, macrophages, NK cells, and several T cell subsets. Enrichment analysis showed that these genes were involved in fatty acid metabolism, inflammation, and immune regulation. and were identified as hub genes. Single-cell analysis indicated that their expression changed during the monocyte-to-macrophage transition and influenced cell communication. In Atherosclerosis animal models, both genes were significantly upregulated. CONCLUSION: and are potential diagnostic biomarkers associated with ferroptosis and cellular senescence in Atherosclerosis. These findings may offer new insights into the mechanisms and diagnosis of Atherosclerosis.

摘要

背景：动脉粥样硬化是一种慢性炎症性疾病，其特征是脂质在血管壁中积累。铁死亡和细胞衰老在动脉粥样硬化中的作用仍不清楚。本研究旨在使用生物信息学方法鉴定与动脉粥样硬化中铁死亡和细胞衰老相关的基因。 方法：从基因表达综合数据库（GEO数据库）中获取动脉粥样硬化基因表达数据集。鉴定差异表达基因（DEGs），并将其与加权基因共表达网络分析（WGCNA）模块中的关键基因、铁死亡相关基因和衰老相关基因进行交集分析，以获得共同基因（CF-DEGs）。基于CF-DEGs进行共识聚类以鉴定分子亚型，随后进行差异表达分析。使用富集分析和免疫浸润分析来研究亚型特异性差异表达基因的生物学功能和免疫特征。应用八种机器学习算法来鉴定枢纽基因并构建诊断模型。使用单细胞RNA测序数据评估枢纽基因在细胞通讯和分化中的作用。最后，进行动物实验以验证枢纽基因的表达。 结果：共鉴定出23个CF-DEGs，据此定义了两种分子亚型。在亚型之间共发现421个DEGs。免疫浸润分析显示八种免疫细胞类型存在显著差异，包括活化的树突状细胞、巨噬细胞、自然杀伤细胞和几个T细胞亚群。富集分析表明这些基因参与脂肪酸代谢、炎症和免疫调节。[具体基因名称1]和[具体基因名称2]被鉴定为枢纽基因。单细胞分析表明它们的表达在单核细胞向巨噬细胞转变过程中发生变化，并影响细胞通讯。在动脉粥样硬化动物模型中，这两个基因均显著上调。 结论：[具体基因名称1]和[具体基因名称2]是与动脉粥样硬化中铁死亡和细胞衰老相关的潜在诊断生物标志物。这些发现可能为动脉粥样硬化的机制和诊断提供新的见解。

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本文引用的文献

[1]
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Pro-ferroptotic signaling promotes arterial aging via vascular smooth muscle cell senescence.

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IL-1β-associated NNT acetylation orchestrates iron-sulfur cluster maintenance and cancer immunotherapy resistance.

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Atherosclerosis. 2023-6

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