ArticleJournal of cardiothoracic surgery2025
Identification of hub genes in aortic dissection based on weighted gene co-expression network analysis and Mendelian randomization study.
Article in Journal of cardiothoracic surgery, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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6 authors.
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Abstract
backgroundAortic dissection (AD) is a cardiovascular emergency with high mortality and poor prognosis. This study aimed to identify hub genes associated AD and to assess their predictive efficacy in AD occurrence and their potential biological roles.
methodsGene microarray data were obtained from the Gene Expression Omnibus database. The mRNA data of ascending aortic tissues from AD and control groups were analyzed for differentially expressed genes (DEGs) by three methods: DESeq2, limma and edgeR. Additionally, weighted gene co-expression network analysis (WGCNA) was performed, and the intersection genes identified by the former methods were considered candidate hub genes for AD. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) methods were utilized to explore the potential biological functions of these candidate hub genes. The top 10 hub genes and significant co-expression genes were identified using a protein-protein interaction network and Cytoscape software. Furthermore, the potential causal relationship between the most significant hub gene and AD was analyzed by Mendelian randomization method.
resultsA total of 1162 DEGs for AD were identified using DESeq2, limma, and edgeR methods. WGCNA clustered AD-related genes into 15 modules. The most relevant modules of AD were intersected with DEGs, resulting in the identification of 201 candidate hub genes. GO and KEGG analyses revealed that these genes were primarily associated with hypoxia, inflammation, cell death, and extracellular matrix (ECM) regulation. The top 10 hub genes for AD were identified as PAI-1, MMP14, ITGA5, CCL2, ITGB3, THBS2, COL18A1, CD68, NFKBIA, and PLAUR. PAI-1 was significantly co-expressed with MMP14, ITGA5, CCL2, and THBS2 in AD. A significant positive correlation between PAI-1 and AD risk was found using inverse variance weighted method (OR = 1.086; 95% CI = 1.006–1.173; P = 0.034).
conclusionsAD patients exhibit significant alterations in gene expression. PAI-1 might serve as a potential biomarker and therapeutic target for AD by regulating processes such as hypoxia, inflammation, cell death, and degradation of the ECM.
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