ArticleJournal of immunology research2022
Crucial Genes in Aortic Dissection Identified by Weighted Gene Coexpression Network Analysis.
Article in Journal of immunology research, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed, 10 citations in OpenAlex.
- Identification and Validation of Differentially Expressed mRNAs From Peripheral Leukocytes for Acute Stanford Type A Aortic Dissection.Journal of the American Heart Association · 2025Article
- Identification of hub genes in aortic dissection based on weighted gene co-expression network analysis and Mendelian randomization study.Journal of cardiothoracic surgery · 2025Article
- Knockdown of CLEC4D alleviates myoblast dysfunction and inflammation in sarcopenia by inhibiting the JAK/STAT pathway.BMC musculoskeletal disorders · 2025Article
- Weekend Effect and Mortality Outcomes in Aortic Dissection: A Prospective Analysis.Journal of critical care medicine (Universitatea de Medicina si Farmacie din Targu-Mures) · 2024Article
- Downregulation of LILRB4 Promotes Human Aortic Smooth Muscle Cell Contractile Phenotypic Switch and Apoptosis in Aortic Dissection.Cardiovascular toxicology · 2024Article
- Article
- Comparison of Transcriptomic Signatures between Monkeypox-Infected Monkey and Human Cell Lines.Journal of immunology research · 2022Article
- Identification of Immune-Related Gene Signature in Stanford Type A Aortic Dissection.Frontiers in genetics · 2022Article
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Authors and funding
14 authors at 5 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundAortic dissection (AD) is a lethal vascular disease with high mortality and morbidity. Though AD clinical pathology is well understood, its molecular mechanisms remain unclear. Specifically, gene expression profiling helps illustrate the potential mechanism of aortic dissection in terms of gene regulation and its modification by risk factors. This study was aimed at identifying the genes and molecular mechanisms in aortic dissection through bioinformatics analysis.
methodNine patients with AD and 10 healthy controls were enrolled. The gene expression in peripheral mononuclear cells was profiled through next-generation RNA sequencing. Analyses including differential expressed gene (DEG) via DEGseq, weighted gene coexpression network (WGCNA), and VisANT were performed to identify crucial genes associated with AD. The Database for Annotation, Visualization, and Integrated Discovery (DAVID) was also utilized to analyze Gene Ontology (GO).
resultsDEG analysis revealed that 1,113 genes were associated with AD. Of these, 812 genes were markedly reduced, whereas 301 genes were highly expressed, in AD patients. DEGs were rich in certain categories such as MHC class II receptor activity, MHC class II protein complex, and immune response genes. Gene coexpression networks via WGCNA identified 3 gene hub modules, with one positively and 2 negatively correlated with AD, respectively. Specifically, module 37 was the most strongly positively correlated with AD with a correlation coefficient of 0.72. Within module 37, five hub genes (AGFG1, MCEMP1, IRAK3, KCNE1, and CLEC4D) displayed high connectivity and may have clinical significance in the pathogenesis of AD.
conclusionOur analysis provides the possible association of specific genes and gene modules for the involvement of the immune system in aortic dissection. AGFG1, MCEMP1, IRAK3, KCNE1, and CLEC4D in module M37 were highly connected and strongly linked with AD, suggesting that these genes may help understand the pathogenesis of aortic dissection.
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