ArticlePeerJ2019
Identification of crucial genes in abdominal aortic aneurysm by WGCNA.
Article in PeerJ, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 70 papers, 1 of them a synthesis that pooled it.
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Who cites it
70 citing papers in PubMed, 1 synthesis or guideline pooled it, 108 citations in OpenAlex.
- Integrative bioinformatics frameworks for abdominal aortic aneurysm using GWAS meta-analysis, biological network construction, and structural modeling.Scientific reports · 2025Pooled it
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- ATG4B as a novel biomarker for abdominal aortic aneurysm: integrated evaluation through experimental and bioinformatics analyses.Molecular and cellular biochemistry · 2025Article
- Single-Cell RNA Sequencing, Cell Communication, and Network Pharmacology Reveal the Potential Mechanism ofPharmaceuticals (Basel, Switzerland) · 2024Article
- Diagnostic value of uric acid to high-density lipoprotein cholesterol ratio in abdominal aortic aneurysms.Annals of medicine · 2024Article
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- Identifying the signature of NAD+ metabolism-related genes for immunotherapy of gastric cancer.Heliyon · 2024Article
- Burden of aortic aneurysm in Iran from 1990 to 2019: an analysis based on global burden of disease study.Annals of medicine and surgery (2012) · 2024Article
- Revealing the potential role of hub metabolism-related genes and their correlation with immune cells in acute ischemic stroke.IET systems biology · 2024Article
- Machine learning-based identification of novel hub genes associated with oxidative stress in lupus nephritis: implications for diagnosis and therapeutic targets.Lupus science & medicine · 2024Article
- Gene set correlation enrichment analysis for interpreting and annotating gene expression profiles.Nucleic acids research · 2024Article
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- Immunogenic profiling of metastatic uveal melanoma discerns a potential signature related to prognosis.Journal of cancer research and clinical oncology · 2024Article
- Identification of CD8Aging · 2024Article
- Transcriptome meta-analysis reveals the hair genetic rules in six animal breeds and genes associated with wool fineness.Frontiers in genetics · 2024Article
- Feature genes identification and immune infiltration assessment in abdominal aortic aneurysm using WGCNA and machine learning algorithms.Frontiers in cardiovascular medicine · 2024Article
10 more citing papers are in PubMed but not listed here.
Corrections and comments
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Authors and funding
8 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundAbdominal aortic aneurysm (AAA) is the full thickness dilation of the abdominal aorta. However, few effective medical therapies are available. Thus, elucidating the molecular mechanism of AAA pathogenesis and exploring the potential molecular target of medical therapies for AAA is of vital importance.
methodsThree expression datasets (GSE7084, GSE47472 and GSE57691) were downloaded from the Gene Expression Omnibus (GEO). These datasets were merged and then normalized using the "sva" R package. Differential expressed gene (DEG) analysis and weighted gene co-expression network analysis (WGCNA) were conducted. We compared the co-expression patterns between AAA and normal conditions, and hub genes of each functional module were identified. DEGs were mapped to co-expression network under AAA condition and a DEG co-expression network was generated. Crucial genes were identified using molecular complex detection (MCODE) (a plugin in Cytoscape).
resultsIn our study, 6 and 10 gene modules were detected for the AAA and normal conditions, respectively, while 143 DEGs were screened. Compared to the normal condition, genes associated with immune response, inflammation and muscle contraction were clustered in three gene modules respectively under the AAA condition; the hub genes of the three modules were MAP4K1, NFIB and HPK1, respectively. A DEG co-expression network with 102 nodes and 303 edges was identified, and a hub gene cluster with 10 genes from the DEG co-expression network was detected. YIPF6, RABGAP1, ANKRD6, GPD1L, PGRMC2, HIGD1A, GMDS, MGP, SLC25A4 and FAM129A were in the cluster. The expression levels of these 10 genes showed potential diagnostic value.
conclusionBased on WGCNA, we detected 6 modules under the AAA condition and 10 modules in the normal condition. Hub genes of each module and hub gene clusters of the DEG co-expression network were identified. These genes may act as potential targets for medical therapy and diagnostic biomarkers. Further studies are needed to elucidate the detailed biological function of these genes in the pathogenesis of AAA.
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