ArticleFrontiers in cardiovascular medicine2022
Identification of differentially expressed ferroptosis-related genes in abdominal aortic aneurysm: Bioinformatics analysis.
Article in Frontiers in cardiovascular medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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4 citing papers in PubMed, 10 citations in OpenAlex.
- Comprehensive Bioinformatics Analysis Reveals the Role of Shared Cuproptosis- and Ferroptosis-Related DEG DLD in Abdominal Aortic Aneurysm.Journal of cellular and molecular medicine · 2025Article
- An emerging double‑edged sword role of ferroptosis in cardiovascular disease (Review).International journal of molecular medicine · 2025Review
- Integration of bulk/scRNA-seq and multiple machine learning algorithms identifies PIM1 as a biomarker associated with cuproptosis and ferroptosis in abdominal aortic aneurysm.Frontiers in immunology · 2024Article
- HMGB2 Deficiency Mitigates Abdominal Aortic Aneurysm by Suppressing Ang-II-Caused Ferroptosis and Inflammation via NF-Mediators of inflammation · 2023Article
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5 authors at 2 institutions in 1 country.
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Abstract
Purpose: Ferroptosis plays a crucial role in the development and progression of abdominal aortic aneurysm (AAA). The aim of this study was to identify differentially expressed genes associated with ferroptosis in AAA through bioinformatics analysis combined with experimental validation. Materials and methods: Firstly, the mRNA expression profile datasets GSE57691 and GSE47472 from Gene Expression Omnibus database were screened, and principal component analysis was carried out. Next, the R software (version 4.0.0) was used to analyze potentially differentially expressed genes associated with AAA and ferroptosis. Subsequently, protein-protein interaction analysis, gene ontology enrichment analysis, and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis were performed on the selected candidate genes. Finally, quantitative real-time polymerase chain reaction (qRT-PCR) was used to detect the expression levels of the first five selected abnormal ferroptosis-related genes in clinical samples obtained from patients with AAA and healthy controls. Results: Based on the information contained in the two datasets, a total of 20 differentially expressed ferroptosis-related genes (three upregulated genes and 17 downregulated genes) were selected. Protein-protein interaction analysis demonstrated interaction between these genes, while gene ontology enrichment analysis of ferroptosis genes with differential expression indicated that some enrichment items were associated with oxidative stress. The qRT-PCR results showed that the expression levels of interleukin-6 (IL-6), peroxiredoxin 1 (PRDX1), and stearoyl-CoA desaturase (SCD) were consistent with the bioinformatics prediction results obtained from the mRNA chip. Conclusion: Bioinformatics analysis identified 20 potential ferroptosis-related differentially expressed genes in AAA. Further verification by qRT-PCR showed that IL-6, PRXD1, and SCD might affect the process of AAA by regulating ferroptosis. Our results might assist in further understanding the pathogenesis of AAA and guiding treatment.
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