Identification of differentially expressed ferroptosis-related genes in abdominal aortic aneurysm: Bioinformatics analysis

Kun Wang; Yancheng Song; Hong Li; Jianshu Song; Shizhong Wang

doi:10.3389/fcvm.2022.991613

Identification of differentially expressed ferroptosis-related genes in abdominal aortic aneurysm: Bioinformatics analysis

Front Cardiovasc Med. 2022 Sep 29:9:991613. doi: 10.3389/fcvm.2022.991613. eCollection 2022.

Authors

Kun Wang¹, Yancheng Song², Hong Li³, Jianshu Song¹, Shizhong Wang¹

Affiliations

¹ Department of Cardiovascular Surgery, The Affiliated Hospital of Qingdao University, Qingdao, China.
² Department of Gastrointestinal Surgery, The Affiliated Hospital of Qingdao University, Qingdao, China.
³ Clinical Laboratory, The Affiliated Qingdao Hiser Hospital of Qingdao University, Qingdao, China.

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.

Keywords: AAA; IL-6; bioinformatics analysis; ferroptosis; gene expression.