Identification and Analysis of Hub Genes and Immune Cells Associated with the Formation of Acute Aortic Dissection

Abstract

Background. Acute type A aortic dissection (AAD) is a catastrophic disease with high mortality, but the pathogenesis has not been fully elucidated. This study is aimed at identifying hub genes and immune cells associated with the pathogenesis of AAD. Methods. The datasets were downloaded from Gene Expression Omnibus (GEO). Gene Set Enrichment Analysis (GSEA), gene set variation analysis (GSVA), and differential analysis were performed. The differentially expressed genes (DEGs) were intersected with specific genes collected from MSigDB. The gene function and pathway enrichment analysis were also performed on intersecting genes. The key modules were selected by weighted gene coexpression network analysis (WGCNA). Hub genes were identified by least absolute shrinkage and selection operator (LASSO) analysis and were verified in the metadataset. The immune cell infiltration was analyzed by CIBERSORT, and the relationship between hub genes and immune cells was performed by Pearson’s correlation analysis. The single-cell RNA sequencing (scRNA-seq) dataset was used to verify the differences in DNA damage and repair signaling pathways and hub genes in different cell types. Results. The results of GSEA and GSVA indicated that DNA damage and repair processes were activated in the occurrence of AAD. The gene function and pathway enrichment analysis on differentially expressed DNA damage- and repair-related genes showed that these genes were mainly involved in the regulation of the cell cycle process, cellular response to DNA damage stimulus, response to wounding, p53 signaling pathway, and cellular senescence. Three key modules were identified by WGCNA. Five genes were screened as hub genes, including CDK2, EIF4A1, GLRX, NNMT, and SLCO2A1. Naive B cells and Gamma delta T cells (γδ T cells) were decreased in AAD, but monocytes and M0 macrophages were increased. scRNA-seq analysis included that DNA damage and repair processes were activated in smooth muscle cells (SMCs), tissue stem cells, and monocytes in the aortic wall of patients with AAD. Conclusions. Our results suggested that DNA damage- and repair-related genes may be involved in the occurrence of AAD by regulating many biological processes. The hub genes and immune cells reported in this study also increase the understanding of AAD.

Comparative Analysis of Transcriptome Profiles in Patients with Thromboangiitis Obliterans

“…In our results in TAO (a vascular disease that involves medium and small vessels without atherosclerosis and causes narrowing and occlusions as a result of the inflammation of arteries and veins) patients, we detected an increase in RNF149 expression. Zhong et al found that EIF4A1 expression was upregulated in the aortic wall tissues of patients with acute type A aortic dissection, a catastrophic disease with high mortality but whose pathogenesis is not fully elucidated [63]. Similarly, we found that EIF4A1 expression was upregulated in TAO disease with fine arterial occlusions.…”

Identification of Key Immune Infiltration Related Genes Involved in Aortic Dissection Using Bioinformatic Analyses and Experimental Verification

“…Several studies have identified hub genes in AD using bioinformatic strategies. [13][14][15][16] For example, Li et al calculated the immune scores of AD patients and identified key immune related genes by WGCNA and PPI analyses. 14 Zhong et al 16 and Luo et al 17 first identified AD associated genes via WGCNA and then calculated their correlations with immune cells.…”

“…[13][14][15][16] For example, Li et al calculated the immune scores of AD patients and identified key immune related genes by WGCNA and PPI analyses. 14 Zhong et al 16 and Luo et al 17 first identified AD associated genes via WGCNA and then calculated their correlations with immune cells. In addition, Zeng et al 18 and Ren et al 19 performed mass spectrometry to identify biomarkers in the serum of AD patients via differential expression and correlation analyses.…”

Identification of potential ferroptosis key genes and immune infiltration in rheumatoid arthritis by integrated bioinformatics analysis

“…Then, R software version 3.2 was applied to calculate the related coefficient between different immune-cells in the enrolled sample data and visualize the results, so as to analyze the differences between the RA and the control group as well as the correlation between each immune cell. Additionally, R software was used to conduct and visualize the correlation betwixt hub genes and immune infiltration [ 28 , 29 ].…”