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pmid:31608184

Identification of crucial genes in abdominal aortic aneurysm by WGCNA.

Siliang Chen · Dan Yang · Chuxiang Lei · Yuan Li · Xiaoning Sun · Mengyin Chen · Xiao Wu · Yuehong Zheng

PeerJ · 2019 doi:10.7717/peerj.7873

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complete

Experiment

complete

Data

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Analysis

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Record details sci_version · id · kind · revision · content_hash · schema · created_at · updated_at · generator
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pmid:31608184
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science-record
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sha256:28bbe26f4f7bf1076be0510fe6bbe20525e9000146a7a32490ad835b109d8f88
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created_at
2026-11-01T15:40:50Z
updated_at
2026-11-01T22:00:54Z
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paper object · 10 fields
state
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title
Identification of crucial genes in abdominal aortic aneurysm by WGCNA.
doi
10.7717/peerj.7873
pmid
31608184
authors array · 8 items
[0]
Siliang Chen
[1]
Dan Yang
[2]
Chuxiang Lei
[3]
Yuan Li
[4]
Xiaoning Sun
[5]
Mengyin Chen
[6]
Xiao Wu
[7]
Yuehong Zheng
journal
PeerJ
year
2019
abstract
BACKGROUND: Abdominal 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. METHODS: Three 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). RESULTS: In 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. CONCLUSION: Based 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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sections[6] "Functional and pathway enrichment of gene modules" paragraph 2
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Chi-square tests were used to compare the percentages.
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Data is available at NCBI GEO: GSE7084, GSE47472 and GSE57691.
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Differential gene expression in the proximal neck of human abdominal aortic aneurysm
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Differential gene expression in human abdominal aortic aneurysm and atherosclerosis
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Expression data from the abdominal aorta and abdominal aortic aneurysm
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Basic information of three datasets.
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[0] array · 4 items
[0]
Year
[1]
Series
[2]
Platform
[3]
Samples (AAA:Normal)
[1] array · 4 items
[0]
2007
[1]
GSE7084
[2]
GPL2507 Sentrix Human-6 expression beadchip
[3]
7:8
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[0]
2013
[1]
GSE47472
[2]
GPL10558 Illumina HumanHT-12 V4.0 expression beadchip
[3]
14:8
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GPL10558 Illumina HumanHT-12 V4.0 expression beadchip
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49:10
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Comparison between AAA and normal co-expression network.
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Comparison of the co-expression patterns between the AAA and normal conditions
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Table 2
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Comparison between AAA and normal co-expression network.
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[5]
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[6]
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Genes in the hub gene cluster of DEG co-expression network.
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14
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Mining crucial genes mediating AAA
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Table 3
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Genes in the hub gene cluster of DEG co-expression network.
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[0] array · 4 items
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[1]
Gene ID
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[1]
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[2]
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[3]
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[0]
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[1]
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[2]
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[3]
RAB GTPase activating protein 1
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[0]
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[1]
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[3]
Ankyrin repeat domain 46
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[3]
Glycerol-3-phosphate dehydrogenase 1 like
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[0]
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[1]
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[3]
Progesterone receptor membrane component 2
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[0]
6
[1]
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[3]
HIG1 hypoxia inducible domain family member 1A
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Matrix Gla protein
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[3]
Solute carrier family 25 member 4
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[1]
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[3]
Niban apoptosis regulator 1
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The area under the curve (AUC) of 10 genes in the cluster detected by MCODE.
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Mining crucial genes mediating AAA
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Table 4
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The area under the curve (AUC) of 10 genes in the cluster detected by MCODE.
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<0.001
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<0.001
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<0.001
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0.811
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<0.001
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section[14]/table-wrap[2]#table-4
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[4]
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Complete file
{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:31608184", "kind": "science-record", "revision": 7, "content_hash": "sha256:28bbe26f4f7bf1076be0510fe6bbe20525e9000146a7a32490ad835b109d8f88", "created_at": "2026-11-01T15:40:50Z", "updated_at": "2026-11-01T22:00:54Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Identification of crucial genes in abdominal aortic aneurysm by WGCNA.", "doi": "10.7717/peerj.7873", "pmid": "31608184", "authors": ["Siliang Chen", "Dan Yang", "Chuxiang Lei", "Yuan Li", "Xiaoning Sun", "Mengyin Chen", "Xiao Wu", "Yuehong Zheng"], "journal": "PeerJ", "year": 2019, "abstract": "BACKGROUND: Abdominal 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.\nMETHODS: Three 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).\nRESULTS: In 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.\nCONCLUSION: Based 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. 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