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pmid:31721906

Identification of the molecular mechanisms associated with acute type A aortic dissection through bioinformatics methods.

Tao Jiang · Liangyi Si

Brazilian journal of medical and biological research = Revista brasileira de pesquisas medicas e biologica · 2019 doi:10.1590/1414-431X20198950

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complete

Experiment

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Data

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Record details sci_version · id · kind · revision · content_hash · schema · created_at · updated_at · generator
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pmid:31721906
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science-record
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created_at
2026-11-01T15:40:51Z
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2026-11-01T22:00:59Z
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paper object · 10 fields
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title
Identification of the molecular mechanisms associated with acute type A aortic dissection through bioinformatics methods.
doi
10.1590/1414-431X20198950
pmid
31721906
authors array · 2 items
[0]
Tao Jiang
[1]
Liangyi Si
journal
Brazilian journal of medical and biological research = Revista brasileira de pesquisas medicas e biologica
year
2019
abstract
Aortic dissection is characterized by the redirection of blood flow, which flows through an intimal tear into the aortic media. The purpose of this study was to find potential acute type A aortic dissection (AAAD)-related genes and molecular mechanisms by bioinformatics. The gene expression profiles of GSE52093 were obtained from Gene Expression Omnibus (GEO) database, including 7 AAAD samples and 5 normal samples. The differentially expressed genes (DEGs) were detected between AAAD and normal samples. The functional annotation and pathway enrichment analysis were conducted through the Database for Annotation, Visualization and Integration Discovery (DAVID). A protein-protein interaction network was established by the Search Tool for the Retrieval of Interacting Genes (STRING) software. The microRNAs (miRNAs) of these differentially expressed genes were predicted using <microRNA.org> database. Moreover, DEGs were analyzed in the comparative toxicogenomics (CTD) database to screen out the potential therapeutic small molecules. As a result, there were 172 DEGs identified in patients with AAAD. These DEGs were significantly enriched in 6 pathways, including cell cycle, oocyte meiosis, DNA replication, extracellular matrix-receptor interaction, and mineral absorption pathway. Notably, CDC20, CDK1, CHEK1, KIF20A, MCM10, PBK, PTTG1, RACGAP, and TOP2A were crucial genes with a high degree in the protein-protein interaction network. Furthermore, potential miRNAs (miR-301, miR-302 family, and miR-130 family) were identified. In addition, small molecules like azathioprine and zoledronic acid were identified to be potential drugs for AAAD.
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After background correction, data normalization, and determination of expression levels, the gene expression between AAAD and normal samples was compared using the linear regression model and empirical Bayes moderated t-test.
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sections[4] "Data preprocessing and identification of DEGs" paragraph 2
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After background correction, data normalization, and determination of expression levels, the gene expression between AAAD and normal samples was compared using the linear regression model and empirical Bayes moderated t-test.
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The gene expression profiles of GSE52093 (12) were obtained from the Gene Expression Omnibus (GEO) database (http://www.ncbi.nlm.nih.gov/geo/). This dataset includes five normal ascending aorta samples from normal donors and seven dissected ascending aorta samples from patients with AAAD. The Illumina HumanHT-12 v4.0 expression beadchip (USA) was employed to analyze the samples.
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sections[3] "Dataset" paragraph 2
quote
The gene expression profiles of GSE52093 (12) were obtained from the Gene Expression Omnibus (GEO) database (http://www.ncbi.nlm.nih.gov/geo/). This dataset includes five normal ascending aorta samples from normal donors and seven dissected ascending aorta samples from patients with AAAD. The Illumina HumanHT-12 v4.0 expression beadchip (USA) was employed to analyze the samples.
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The gene expression profiles of GSE52093 (12) were obtained from the Gene Expression Omnibus (GEO) database (http://www.ncbi.nlm.nih.gov/geo/). This dataset includes five normal ascending aorta samples from normal donors and seven dissected ascending aorta samples from patients with AAAD. The Illumina HumanHT-12 v4.0 expression beadchip (USA) was employed to analyze the samples.
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The gene expression profiles of GSE52093 (12) were obtained from the Gene Expression Omnibus (GEO) database (http://www.ncbi.nlm.nih.gov/geo/). This dataset includes five normal ascending aorta samples from normal donors and seven dissected ascending aorta samples from patients with AAAD. The Illumina HumanHT-12 v4.0 expression beadchip (USA) was employed to analyze the samples.
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Genome-wide analysis of gene expression of ascending aorta from patients with acute Stanford type A aortic dissection
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Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis of the differentially expressed genes (DEGs).
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GO functional annotation and pathway enrichment analysis
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Table 1.
caption
Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis of the differentially expressed genes (DEGs).
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DEGs
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KEGG Pathway
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[3]
9
[4]
BUB1, CDC20, CDC7, CHEK1, ESPL1, MAD2L2, MCM2, MCM4, PTTG1
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[1]
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COL6A3, HMMR, ITGA2, SPP1
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[1]
hsa04978: Mineral absorption
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[3]
3
[4]
MT1E, MT2A, STEAP1
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[0]
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[2]
0.0058
[3]
3
[4]
PER2, PER3, RORA
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PMC6853077
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Construction of PPI network and identification of hub genes
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Table 2.
caption
Protein-protein interaction network degree and gene expression of identified hub genes.
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[0]
Genes
[1]
Degree
[2]
Log FC
[3]
FDR
[1] array · 4 items
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CDC20
[1]
20.23
[2]
4.15
[3]
0.0249
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[0]
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[1]
28.52
[2]
2.85
[3]
0.0355
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[1]
22.54
[2]
3.01
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0.0276
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23.50
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5.31
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[1]
23.83
[2]
3.22
[3]
0.0370
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[1]
28.91
[2]
5.58
[3]
0.0344
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[1]
20.26
[2]
2.77
[3]
0.0334
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[0]
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24.80
[2]
1.82
[3]
0.0443
[9] array · 4 items
[0]
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29.14
[2]
4.43
[3]
0.0244
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Top 20 microRNAs of the differentially expressed genes.
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PMC6853077
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12
section_title
Potential microRNAs and small molecules associated with AAAD
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21
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4
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Table 3.
caption
Top 20 microRNAs of the differentially expressed genes.
rows array · 21 items
[0] array · 4 items
[0]
microRNA
[1]
FDR
[2]
Gene count
[3]
Target genes
[1] array · 4 items
[0]
miR-888
[1]
2.49E-14
[2]
25
[3]
TMEM30B, SPP1, NFKBIZ, FHOD3, ACTN4, etc.
[2] array · 4 items
[0]
miR-4262
[1]
3.52E-13
[2]
25
[3]
AKAP6, CDKN3, COL6A3, VCX3A, SLC25A4, etc.
[3] array · 4 items
[0]
miR-301b
[1]
1.97E-12
[2]
23
[3]
ANGPT2, POC1A, REEP1, CFL2, MYOZ2, etc.
[4] array · 4 items
[0]
miR-301a
[1]
2.02E-12
[2]
23
[3]
ANGPT2, POC1A, REEP1, CFL2, MYOZ2, etc.
[5] array · 4 items
[0]
miR-1264
[1]
4.50E-12
[2]
23
[3]
NID2, CAMK2G, PBK, MYOZ2, FHOD3, etc.
[6] array · 4 items
[0]
miR-130a
[1]
5.72E-12
[2]
21
[3]
AKAP6, POC1A, REEP1, CFL2, PBK, etc.
[7] array · 4 items
[0]
miR-499-5p
[1]
5.80E-12
[2]
20
[3]
TMEM30B, REEP1, CENPF, CFL2, GNG13, etc.
[8] array · 4 items
[0]
miR-130b
[1]
7.07E-12
[2]
21
[3]
AKAP6, POC1A, REEP1, CFL2, PBK, etc.
[9] array · 4 items
[0]
miR-2053
[1]
1.11E-11
[2]
24
[3]
AKAP6, NID2, DSTN, ANGPT2, CENPF, etc.
[10] array · 4 items
[0]
miR-141
[1]
1.51E-11
[2]
20
[3]
SLC25A4, MYOZ2, MAP3K7CL, MCM10, EZH2, etc.
[11] array · 4 items
[0]
miR-144
[1]
1.82E-11
[2]
24
[3]
AKAP6, CDKN3, TMEM30B, NID2, ANGPT2, etc.
[12] array · 4 items
[0]
miR-515-5p
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2.19E-11
[2]
22
[3]
AKAP6, NID2, MYOZ2, NFKBIZ, MAP3K7CL, etc.
[13] array · 4 items
[0]
miR-429
[1]
4.27E-11
[2]
23
[3]
ANGPT2, REEP1, SLC25A4, CFL2, ACTC1, etc.
[14] array · 4 items
[0]
miR-520g
[1]
5.08E-11
[2]
20
[3]
ANGPT2, SPP1, PBK, FHOD3, MAP3K7CL, etc.
[15] array · 4 items
[0]
miR-200c
[1]
1.20E-10
[2]
22
[3]
ANGPT2, REEP1, SLC25A4, CFL2, ACTC1, etc.
[16] array · 4 items
[0]
miR-302a
[1]
1.21E-10
[2]
20
[3]
ANGPT2, POC1A, CFL2, PBK, MCM10, etc.
[17] array · 4 items
[0]
miR-302c
[1]
1.44E-10
[2]
20
[3]
NID2, POC1A, CFL2, PBK, CASQ2, etc.
[18] array · 4 items
[0]
miR-520h
[1]
1.57E-10
[2]
19
[3]
ANGPT2, SPP1, PBK, FHOD3, MAP3K7CL, etc.
[19] array · 4 items
[0]
miR-302b
[1]
2.00E-10
[2]
20
[3]
POC1A, CFL2, SUN1, PBK, CASQ2, etc.
[20] array · 4 items
[0]
miR-589
[1]
2.09E-10
[2]
22
[3]
CAMK2G, NFKBIZ, CHST1, CHEK1, HMMR, etc.
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section[12]/table-wrap[1]#t03
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Top 20 small molecules of the differentially expressed genes.
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PMC6853077
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12
section_title
Potential microRNAs and small molecules associated with AAAD
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Table 4.
caption
Top 20 small molecules of the differentially expressed genes.
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[0] array · 4 items
[0]
Molecule in CTD
[1]
FDR
[2]
Gene count
[3]
Target gene
[1] array · 4 items
[0]
Palbociclib
[1]
9.49E-25
[2]
27
[3]
CDKN3, PTTG1, CENPF, PBK, OIP5, et al.
[2] array · 4 items
[0]
Dasatinib
[1]
1.52E-19
[2]
33
[3]
CDKN3, PTTG1, CENPF, PBK, ACTC1, et al.
[3] array · 4 items
[0]
Azathioprine
[1]
8.35E-19
[2]
36
[3]
CDKN3, NID2, CENPF, PBK, MCM2, et al.
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[0]
2,3-bis(3′-hydroxybenzyl) butyrolactone
[1]
1.52E-18
[2]
42
[3]
THSD4, CDKN3, PTTG1, CENPF, PBK, et al.
[5] array · 4 items
[0]
Troglitazone
[1]
1.21E-16
[2]
46
[3]
CDKN3, NID2, PTTG1, ANGPT2, CENPF, et al.
[6] array · 4 items
[0]
Vinylidene chloride
[1]
1.83E-16
[2]
48
[3]
ENTPD7, CDKN3, NID2, PHLDA1, et al.
[7] array · 4 items
[0]
Zoledronic acid
[1]
4.37E-15
[2]
46
[3]
CDKN3, NID2, CENPF, PBK, ACTG2, et al.
[8] array · 4 items
[0]
Trimellitic anhydride
[1]
4.78E-15
[2]
52
[3]
CDKN3, PTTG1, POC1A, SLC25A4, PBK, et al.
[9] array · 4 items
[0]
Amphotericin B, deoxycholate drug combination
[1]
6.20E-15
[2]
26
[3]
CENPF, SPP1, MCM2, NFKBIZ, MCM4, et al.
[10] array · 4 items
[0]
Fluorouracil
[1]
6.33E-15
[2]
44
[3]
CDKN3, COL6A3, PTTG1, ANGPT2, ACTC1, et al.
[11] array · 4 items
[0]
Coumestrol
[1]
7.33E-15
[2]
50
[3]
THSD4, CDKN3, PTTG1, POC1A, CENPF, et al.
[12] array · 4 items
[0]
Lucanthone
[1]
9.66E-13
[2]
19
[3]
CDKN3, CENPF, PBK, HMMR, MCM10, et al.
[13] array · 4 items
[0]
1,4-bis(2-(3,5- dichloropyridyloxy)) benzene
[1]
7.68E-12
[2]
44
[3]
CDKN3, POC1A, REEP1, PHLDA1, CENPF, et al.
[14] array · 4 items
[0]
Mustard Gas
[1]
1.78E-11
[2]
39
[3]
CDKN3, PHLDA1, SPP1, PBK, MCM2, et al.
[15] array · 4 items
[0]
Polychlorinated Biphenyls
[1]
4.97E-11
[2]
27
[3]
CDKN3, CENPF, SPP1, PBK, MCM2, et al.
[16] array · 4 items
[0]
Ozone
[1]
1.56E-10
[2]
37
[3]
CDKN3, MYOM1, PHLDA1, CENPF, SPP1, et al.
[17] array · 4 items
[0]
2,4,5,2′,4′,5′- hexachlorobiphenyl
[1]
1.64E-10
[2]
44
[3]
COL6A3, PTTG1, CENPF, SPP1, TMEM158, et al.
[18] array · 4 items
[0]
benzo(b)fluoranthene
[1]
3.46E-10
[2]
40
[3]
THSD4, CDKN3, TMEM30B, PTTG1, REEP1, et al.
[19] array · 4 items
[0]
propionaldehyde
[1]
4.91E-10
[2]
45
[3]
NID2, PTTG1, POC1A, PHLDA1, CENPF, et al.
[20] array · 4 items
[0]
2,4,4′-trichlorobiphenyl
[1]
5.09E-10
[2]
38
[3]
COL6A3, PTTG1, CENPF, GNG13, PBK, et al.
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[0]
asset:data:geo:GSE52093 not downloaded
[1]
asset:data:geo:GSE52093 licence not read
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After background correction, data normalization, and determination of expression levels, the gene expression between AAAD and normal samples was compared using the linear regression model and empirical Bayes moderated t-test.
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The gene expression profiles of GSE52093 (12) were obtained from the Gene Expression Omnibus (GEO) database (http://www.ncbi.nlm.nih.gov/geo/). This dataset includes five normal ascending aorta samples from normal donors and seven dissected ascending aorta samples from patients with AAAD. The Illumina HumanHT-12 v4.0 expression beadchip (USA) was employed to analyze the samples.
basis
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a result, there were 172 DEGs identified in patients with AAAD. These DEGs were significantly enriched
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After background correction, data normalization, and determination of expression levels, the gene expression between AAAD and normal samples was compared using the linear regression model and empirical Bayes moderated t-test.
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The purpose of this study was to find potential acute type A aortic dissection (AAAD)-related genes and molecular mechanisms by bioinformatics. The gene expression profiles of GSE52093 were obtained from Gene Expression Omnibus (GEO) database, including 7 AAAD samples and 5 normal samples. The differentially expressed genes (DEGs) were detected between AAAD and normal samples. The functional annotation and pathway enrichment analysis were conducted through the Database for Annotation, Visualization and Integration Discovery (DAVID). A protein-protein interaction network was established by the Search Tool for the Retrieval of Interacting Genes (STRING) software. The microRNAs (miRNAs) of these differentially expressed genes were predicted using <microRNA.org> database. Moreover, DEGs were analyzed in the comparative toxicogenomics (CTD) database to screen out the potential therapeutic small molecules. As a result, there were 172 DEGs identified in patients with AAAD. These DEGs were significantly enriched in 6 pathways, including cell cycle, oocyte meiosis, DNA replication, extracellular matrix-receptor interaction, and mineral absorption pathway. Notably, CDC20, CDK1, CHEK1, KIF20A, MCM10, PBK, PTTG1, RACGAP, and TOP2A were crucial genes with a high degree in the protein-protein interaction network. Furthermore, potential miRNAs (miR-301, miR-302 family, and miR-130 family) were identified. 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"row_count": 10, "column_count": 4}, "table": {"label": "Table 2.", "caption": "Protein-protein interaction network degree and gene expression of identified hub genes.", "rows": [["Genes", "Degree", "Log FC", "FDR"], ["CDC20", "20.23", "4.15", "0.0249"], ["CDK1", "28.52", "2.85", "0.0355"], ["CHEK1", "22.54", "3.01", "0.0276"], ["KIF20A", "23.50", "5.31", "0.0344"], ["MCM10", "23.83", "3.22", "0.0370"], ["PBK", "28.91", "5.58", "0.0344"], ["PTTG1", "20.26", "2.77", "0.0334"], ["RACGAP", "24.80", "1.82", "0.0443"], ["TOP2A", "29.14", "4.43", "0.0244"]], "row_count": 10, "column_count": 4, "numeric_cells": 30, "header_rows": 1, "locator": "section[11]/table-wrap[1]#t02"}}, {"id": "asset:table:pmid:31721906:3", "role": "table", "format": "jats-table", "media_type": "application/vnd.jats.table+json", "uri": null, "sha256": "sha256:13b3a17c472b9f09e7cde6b788e06bdaa20af8abb83182b7420f6a38e920d82d", "bytes": 1675, "access": "open", "state": "verified", "reader": "read_table", "reader_status": 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"column_count": 4, "numeric_cells": 68, "header_rows": 1, "locator": "section[12]/table-wrap[1]#t03"}}, {"id": "asset:table:pmid:31721906:4", "role": "table", "format": "jats-table", "media_type": "application/vnd.jats.table+json", "uri": null, "sha256": "sha256:a514ca4ca8a3c35f8201662f73e88e2712f2300603d45d76bb0a3acb7ee7037a", "bytes": 1942, "access": "open", "state": "verified", "reader": "read_table", "reader_status": "available", "identifier": "section[12]/table-wrap[2]#t04", "version": null, "note": "Top 20 small molecules of the differentially expressed genes.", "structure": {"pmcid": "PMC6853077", "section_index": 12, "section_title": "Potential microRNAs and small molecules associated with AAAD", "row_count": 21, "column_count": 4}, "table": {"label": "Table 4.", "caption": "Top 20 small molecules of the differentially expressed genes.", "rows": [["Molecule in CTD", "FDR", "Gene count", "Target gene"], ["Palbociclib", "9.49E-25", "27", "CDKN3, PTTG1, CENPF, PBK, OIP5, et al."], ["Dasatinib", "1.52E-19", "33", "CDKN3, PTTG1, CENPF, PBK, ACTC1, et al."], ["Azathioprine", "8.35E-19", "36", "CDKN3, NID2, CENPF, PBK, MCM2, et al."], ["2,3-bis(3′-hydroxybenzyl) butyrolactone", "1.52E-18", "42", "THSD4, CDKN3, PTTG1, CENPF, PBK, et al."], ["Troglitazone", "1.21E-16", "46", "CDKN3, NID2, PTTG1, ANGPT2, CENPF, et al."], ["Vinylidene chloride", "1.83E-16", "48", "ENTPD7, CDKN3, NID2, PHLDA1, et al."], ["Zoledronic acid", "4.37E-15", "46", "CDKN3, NID2, CENPF, PBK, ACTG2, et al."], ["Trimellitic anhydride", "4.78E-15", "52", "CDKN3, PTTG1, POC1A, SLC25A4, PBK, et al."], ["Amphotericin B, deoxycholate drug combination", "6.20E-15", "26", "CENPF, SPP1, MCM2, NFKBIZ, MCM4, et al."], ["Fluorouracil", "6.33E-15", "44", "CDKN3, COL6A3, PTTG1, ANGPT2, ACTC1, et al."], ["Coumestrol", "7.33E-15", "50", "THSD4, CDKN3, PTTG1, POC1A, CENPF, et al."], ["Lucanthone", "9.66E-13", "19", "CDKN3, CENPF, PBK, HMMR, MCM10, et al."], ["1,4-bis(2-(3,5- dichloropyridyloxy)) benzene", "7.68E-12", "44", "CDKN3, POC1A, REEP1, PHLDA1, CENPF, et al."], ["Mustard Gas", "1.78E-11", "39", "CDKN3, PHLDA1, SPP1, PBK, MCM2, et al."], ["Polychlorinated Biphenyls", "4.97E-11", "27", "CDKN3, CENPF, SPP1, PBK, MCM2, et al."], ["Ozone", "1.56E-10", "37", "CDKN3, MYOM1, PHLDA1, CENPF, SPP1, et al."], ["2,4,5,2′,4′,5′- hexachlorobiphenyl", "1.64E-10", "44", "COL6A3, PTTG1, CENPF, SPP1, TMEM158, et al."], ["benzo(b)fluoranthene", "3.46E-10", "40", "THSD4, CDKN3, TMEM30B, PTTG1, REEP1, et al."], ["propionaldehyde", "4.91E-10", "45", "NID2, PTTG1, POC1A, PHLDA1, CENPF, et al."], ["2,4,4′-trichlorobiphenyl", "5.09E-10", "38", "COL6A3, PTTG1, CENPF, GNG13, PBK, et al."]], "row_count": 21, "column_count": 4, "numeric_cells": 49, "header_rows": 1, "locator": "section[12]/table-wrap[2]#t04"}}], "gaps": ["asset:data:geo:GSE52093 not downloaded", "asset:data:geo:GSE52093 licence not read"]}, "analysis": {"state": "complete", "methods": [{"id": "method-1", "family": "regression_modelling", "specific": "ols", "label": "Regression modelling", "dsl_operations": ["ols_fit"], "missing_operations": [], "expressible": true, "parameters": {}, "data_shapes": ["predictors_and_outcome"], "evidence": {"score": 1.0, "band": "verbatim", "quote": "After background correction, data normalization, and determination of expression levels, the gene expression between AAAD and normal samples was compared using the linear regression model and empirical Bayes moderated t-test."}}, {"id": "method-2", "family": "network_analysis", "specific": "ppi_network", "label": "Network / pathway analysis", "dsl_operations": ["build_graph", "centrality_scores", "pathway_enrich"], "missing_operations": [], "expressible": true, "parameters": {}, "data_shapes": ["edge_list"], "evidence": {"score": 0.7, "band": "medium", "quote": "protein-protein interaction"}}, {"id": "method-3", "family": "network_analysis", "specific": "pathway_enrichment", "label": "Network / pathway analysis", "dsl_operations": ["pathway_enrich"], "missing_operations": [], "expressible": true, "parameters": {}, "data_shapes": ["edge_list"], "evidence": {"score": 0.7, "band": "medium", "quote": "pathway enrichment"}}, {"id": "method-4", "family": "contingency_analysis", "specific": "fisher_exact", "label": "Categorical (contingency table) analysis", "dsl_operations": ["contingency_table", "chi_square_test"], "missing_operations": [], "expressible": true, "parameters": {}, "data_shapes": ["categorical_cross_tabulation"], "evidence": {"score": 0.8, "band": "high", "quote": "Fisher's exact"}}], "targets": [], "gaps": []}, "capability": {"state": "complete", "requirements": [{"capability_id": "capability:computational_analysis", "label": "Computational analysis platform", "assay_families": ["meta_analysis", "machine_learning", "survival_analysis", "statistical_regression", "pca", "molecular_docking", "network_analysis", "differential_expression", "gwas"], "availability_state": "owned", "tier_unlocked": "R1", 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The physical bench the paper used is not, so a physical validation cannot be run here."}, "data": {"tier": "R1", "reachable": true, "accessions": ["GSE52093"], "resolved_accessions": ["GSE52093"], "statements": ["The gene expression profiles of GSE52093 (12) were obtained from the Gene Expression Omnibus (GEO) database (http://www.ncbi.nlm.nih.gov/geo/). This dataset includes five normal ascending aorta samples from normal donors and seven dissected ascending aorta samples from patients with AAAD. The Illumina HumanHT-12 v4.0 expression beadchip (USA) was employed to analyze the samples."], "basis": "The paper names GSE52093 in Gene Expression Omnibus (GEO) and the accession resolves in the repository. 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