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pmid:30662576

Identification of Core Gene Biomarkers in Patients with Diabetic Cardiomyopathy.

Ning Li · Haiming Wu · Rongxin Geng · Qizhu Tang

Disease markers · 2018 doi:10.1155/2018/6025061

Paper

complete

Experiment

partial

Data

partial

Analysis

partial

Execution

absent

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Record details sci_version · id · kind · revision · content_hash · schema · created_at · updated_at · generator
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pmid:30662576
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https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json
created_at
2026-11-01T15:40:40Z
updated_at
2026-11-01T22:00:17Z
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paper object · 10 fields
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complete
title
Identification of Core Gene Biomarkers in Patients with Diabetic Cardiomyopathy.
doi
10.1155/2018/6025061
pmid
30662576
authors array · 4 items
[0]
Ning Li
[1]
Haiming Wu
[2]
Rongxin Geng
[3]
Qizhu Tang
journal
Disease markers
year
2018
abstract
Diabetic cardiomyopathy (DCM) is a disorder of the myocardium in diabetic patients, which is one of the critical complications of diabetes giving rise to an increased mortality. However, the underlying mechanisms of DCM remain incompletely understood presently. This study was designed to screen the potential molecules and pathways implicated with DCM. GSE26887 involving 5 control individuals and 7 DCM patients was selected from the GEO database to identify the differentially expressed genes (DEGs). DAVID was applied to perform gene ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses. A protein-protein interaction (PPI) network was also constructed to visualize the interactions among these DEGs. To further validate significant genes and pathways, quantitative real-time PCR (qPCR) and Western blot were performed. A total of 236 DEGs were captured, including 134 upregulated and 102 downregulated genes. GO, KEGG, and the PPI network disclosed that inflammation, immune disorders, metabolic disturbance, and mitochondrial dysfunction were significantly enriched in the development of DCM. Notably, IL6 was an upregulated hub gene with the highest connectivity degree, suggesting that it may interact with a great many molecules and pathways. Meanwhile, SOCS3 was also one of the top 15 hub genes in the PPI network. Herein, we detected the protein level of STAT3 and SOCS3 in a mouse model with DCM. Western blot results showed that the protein level of SOCS3 was significantly lower while phosphorylated-STAT3 (P-STAT3) was activated in mice with DCM. In vitro results also uncovered the similar alterations of SOCS3 and P-STAT3 in cardiomyocytes and cardiac fibroblasts induced by high glucose (HG). However, overexpression of SOCS3 could significantly reverse HG-induced cardiomyocyte hypertrophy and collagen synthesis of cardiac fibroblasts. Taken together, our analysis unveiled potential biomarkers and molecular mechanisms in DCM, which could be helpful to the diagnosis and treatment of DCM.
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The obtained data were presented as mean ± SD (standard deviation) and assessed by the two-tailed Student's t-test.
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sections[11] "2.9. Statistical Analysis" paragraph 2
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The obtained data were presented as mean ± SD (standard deviation) and assessed by the two-tailed Student's t-test.
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The data used to support the findings of this study are available from the corresponding author upon request.
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sections[25] "Data Availability" paragraph 2
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The data used to support the findings of this study are available from the corresponding author upon request.
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GSM662158
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GSM662159
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[4]
GSM662162
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GSM662163
[6]
GSM662164
[7]
GSM662165
[8]
GSM662166
[9]
GSM662167
[10]
GSM662168
[11]
GSM662169
[12]
GSM662170
[13]
GSM662171
[14]
GSM662172
[15]
GSM662173
[16]
GSM662174
[17]
GSM662175
[18]
GSM662176
[19]
GSM662177
[20]
GSM662178
[21]
GSM662179
[22]
GSM662180
[23]
GSM662181
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6244
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Homo sapiens
title
Transcriptome analysis of diabetic and non diabetic patients affected by post-ischemic heart failure
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2026-11-01T15:39:54Z
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The top 5 upregulated and downregulated differentially expressed genes in patients with diabetic cardiomyopathy.
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PMC6313979
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13
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3.1. Identification of DEGs
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Table 1
caption
The top 5 upregulated and downregulated differentially expressed genes in patients with diabetic cardiomyopathy.
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[0]
DEGs
[1]
Gene title
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Gene symbol
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LogFC
[4]
Biological function
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[0]
Upregulated
[1]
Natriuretic peptide A
[2]
NPPA
[3]
3.53
[4]
Extracellular fluid volume and electrolyte homeostasis
[2] array · 4 items
[0]
Secreted frizzled related protein 4
[1]
SFRP4
[2]
2.71
[3]
Soluble modulators of Wnt signaling
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[0]
Desmocollin 1
[1]
DSC1
[2]
2.44
[3]
Calcium-dependent glycoprotein
[4] array · 4 items
[0]
Nebulin
[1]
NEB
[2]
2.4
[3]
Cytoskeleton
[5] array · 4 items
[0]
Frizzled-related protein
[1]
FRZB
[2]
2.36
[3]
Soluble modulators of Wnt signaling
[6] array · 1 item
[0]
[7] array · 5 items
[0]
Downregulated
[1]
Serpin family E member 1
[2]
SERPINE1
[3]
−2.48
[4]
Inhibitor of fibrinolysis
[8] array · 4 items
[0]
Serpin family A member 3
[1]
SERPINA3
[2]
−2.44
[3]
Anti-inflammatory and antioxidant effects
[9] array · 4 items
[0]
Ankyrin repeat domain 2
[1]
ANKRD2
[2]
−2.16
[3]
Modulator of NF-κB-mediated inflammatory
[10] array · 4 items
[0]
X-ray repair cross-complementing 4
[1]
XRCC4
[2]
−2.05
[3]
DNA repair
[11] array · 4 items
[0]
S100 calcium-binding protein A8
[1]
S100A8
[2]
−1.98
[3]
Regulating inflammation and oxidative stress, activatingTLR4 signaling
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Gene ontology analysis of differentially expressed genes in patients with diabetic cardiomyopathy.
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PMC6313979
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14
section_title
3.2. GO Enrichment Analysis
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Table 2
caption
Gene ontology analysis of differentially expressed genes in patients with diabetic cardiomyopathy.
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[0] array · 5 items
[0]
Expression
[1]
Category
[2]
Term
[3]
Count
[4]
%
[1] array · 5 items
[0]
Upregulated
[1]
GOTERM_BP_DIRECT
[2]
GO:0035589~G-protein-coupled purinergic nucleotide receptor signaling pathway
[3]
9
[4]
0.05
[2] array · 4 items
[0]
GOTERM_BP_DIRECT
[1]
GO:0007155~fatty acid metabolism
[2]
8
[3]
0.05
[3] array · 4 items
[0]
GOTERM_BP_DIRECT
[1]
GO:0001501~mitochondrial membrane potential
[2]
6
[3]
0.04
[4] array · 4 items
[0]
GOTERM_BP_DIRECT
[1]
GO:0030198~extracellular matrix organization
[2]
6
[3]
0.04
[5] array · 4 items
[0]
GOTERM_BP_DIRECT
[1]
GO:0007409~mitochondrial permeability transition
[2]
5
[3]
0.03
[6] array · 4 items
[0]
GOTERM_CC_DIRECT
[1]
GO:0016021~integral component of membrane
[2]
42
[3]
0.25
[7] array · 4 items
[0]
GOTERM_CC_DIRECT
[1]
GO:0005886~plasma membrane
[2]
37
[3]
0.22
[8] array · 4 items
[0]
GOTERM_CC_DIRECT
[1]
GO:0070062~extracellular exosome
[2]
29
[3]
0.17
[9] array · 4 items
[0]
GOTERM_CC_DIRECT
[1]
GO:0005615~extracellular space
[2]
22
[3]
0.13
[10] array · 4 items
[0]
GOTERM_CC_DIRECT
[1]
GO:0005576~extracellular region
[2]
20
[3]
0.11
[11] array · 4 items
[0]
GOTERM_MF_DIRECT
[1]
GO:0008270~glucose transporter
[2]
13
[3]
0.08
[12] array · 4 items
[0]
GOTERM_MF_DIRECT
[1]
GO:0005509~calcium ion binding
[2]
11
[3]
0.07
[13] array · 4 items
[0]
GOTERM_MF_DIRECT
[1]
GO:0008201~heparin binding
[2]
7
[3]
0.05
[14] array · 4 items
[0]
GOTERM_MF_DIRECT
[1]
GO:0005518~collagen binding
[2]
5
[3]
0.03
[15] array · 4 items
[0]
GOTERM_MF_DIRECT
[1]
GO:0050661~NADP binding
[2]
4
[3]
0.03
[16] array · 1 item
[0]
[17] array · 5 items
[0]
Downregulated
[1]
GOTERM_BP_DIRECT
[2]
GO:0006954~inflammatory response
[3]
11
[4]
0.07
[18] array · 4 items
[0]
GOTERM_BP_DIRECT
[1]
GO:0008284~lipid intake
[2]
9
[3]
0.06
[19] array · 4 items
[0]
GOTERM_BP_DIRECT
[1]
GO:0042493~response to drug
[2]
6
[3]
0.04
[20] array · 4 items
[0]
GOTERM_BP_DIRECT
[1]
GO:0006955~immune response
[2]
6
[3]
0.04
[21] array · 4 items
[0]
GOTERM_BP_DIRECT
[1]
GO:0002576~platelet degranulation
[2]
5
[3]
0.04
[22] array · 4 items
[0]
GOTERM_CC_DIRECT
[1]
GO:0005886~plasma membrane
[2]
31
[3]
0.21
[23] array · 4 items
[0]
GOTERM_CC_DIRECT
[1]
GO:0005615~extracellular space
[2]
23
[3]
0.15
[24] array · 4 items
[0]
GOTERM_CC_DIRECT
[1]
GO:0005576~extracellular region
[2]
21
[3]
0.14
[25] array · 4 items
[0]
GOTERM_CC_DIRECT
[1]
GO:0070062~extracellular exosome
[2]
21
[3]
0.14
[26] array · 4 items
[0]
GOTERM_CC_DIRECT
[1]
GO:0005789~endoplasmic reticulum membrane
[2]
13
[3]
0.09
[27] array · 4 items
[0]
GOTERM_MF_DIRECT
[1]
GO:0005515~protein binding
[2]
58
[3]
0.39
[28] array · 4 items
[0]
GOTERM_MF_DIRECT
[1]
GO:0008083~mitochondrial uncoupling
[2]
5
[3]
0.03
[29] array · 4 items
[0]
GOTERM_MF_DIRECT
[1]
GO:0005125~cytokine activity
[2]
5
[3]
0.03
[30] array · 4 items
[0]
GOTERM_MF_DIRECT
[1]
GO:0003779~actin binding
[2]
5
[3]
0.03
[31] array · 4 items
[0]
GOTERM_MF_DIRECT
[1]
GO:0016791~phosphatase activity
[2]
3
[3]
0.03
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KEGG pathway analysis of differentially expressed genes in patients with diabetic cardiomyopathy.
structure object · 5 fields
pmcid
PMC6313979
section_index
15
section_title
3.3. KEGG Pathway Analysis
row_count
8
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table object · 8 fields
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Table 3
caption
KEGG pathway analysis of differentially expressed genes in patients with diabetic cardiomyopathy.
rows array · 8 items
[0] array · 6 items
[0]
Category
[1]
Term
[2]
Count
[3]
%
[4]
P value
[5]
Genes
[1] array · 6 items
[0]
Downregulated DEGs
[1]
hsa04151:PI3K-Akt signaling pathway
[2]
8
[3]
0.05
[4]
0.01
[5]
FGF18, CDKN1A, IL6, FGF7, TNC, LAMC2, MYC, and SPP1
[2] array · 5 items
[0]
hsa04010:MAPK signaling pathway
[1]
6
[2]
0.04
[3]
0.03
[4]
DUSP5, FGF18, FGF7, MAP2K3, FLNC, and MYC
[3] array · 5 items
[0]
hsa04066:HIF-1 signaling pathway
[1]
4
[2]
0.02
[3]
0.03
[4]
CDKN1A, IL6, and TFRC
[4] array · 5 items
[0]
hsa04668:TNF signaling pathway
[1]
4
[2]
0.02
[3]
0.04
[4]
IL6, SOCS3, MAP2K3, and SELE
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[0]
hsa04620:Toll-like receptor signaling pathway
[1]
4
[2]
0.02
[3]
0.04
[4]
IL6, LY96, MAP2K3, and SPP1
[6] array · 1 item
[0]
[7] array · 6 items
[0]
Upregulated DEGs
[1]
hsa00982:Drug metabolism-cytochrome P450
[2]
5
[3]
0.03
[4]
0.001
[5]
FMO4, FMO2, FMO3, ADH1B, and UGT2B4
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Top 15 hub genes with higher degree of connectivity.
structure object · 5 fields
pmcid
PMC6313979
section_index
16
section_title
3.4. PPI Analysis
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label
Table 4
caption
Top 15 hub genes with higher degree of connectivity.
rows array · 16 items
[0] array · 3 items
[0]
Gene
[1]
Degree of connectivity
[2]
P value
[1] array · 3 items
[0]
IL6
[1]
29
[2]
5.48E − 04
[2] array · 3 items
[0]
MYC
[1]
17
[2]
3.99E − 03
[3] array · 3 items
[0]
ACTA2
[1]
14
[2]
9.78E − 06
[4] array · 3 items
[0]
SERPINE1
[1]
14
[2]
1.16E − 02
[5] array · 3 items
[0]
ASPN
[1]
12
[2]
9.15E − 03
[6] array · 3 items
[0]
SPP1
[1]
11
[2]
4.04E − 02
[7] array · 3 items
[0]
KIT
[1]
11
[2]
4.54E − 03
[8] array · 3 items
[0]
TFRC
[1]
9
[2]
3.34E − 04
[9] array · 3 items
[0]
FMOD
[1]
9
[2]
3.42E − 04
[10] array · 3 items
[0]
PDE5A
[1]
9
[2]
2.96E − 04
[11] array · 3 items
[0]
MYH6
[1]
8
[2]
1.55E − 03
[12] array · 3 items
[0]
FPR1
[1]
8
[2]
1.71E − 06
[13] array · 3 items
[0]
C3
[1]
7
[2]
1.18E − 02
[14] array · 3 items
[0]
CDKN1A
[1]
7
[2]
3.94E − 04
[15] array · 3 items
[0]
SOCS3
[1]
7
[2]
1.02E − 03
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Gene-specific primers used in quantitative real-time PCR.
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section_title
3.4. PPI Analysis
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Table 5
caption
Gene-specific primers used in quantitative real-time PCR.
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[0] array · 4 items
[0]
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[3]
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[0]
Mouse
[1]
GAPDH
[2]
Forward
[3]
5′-ACTCCACTCACGGCAAATTC-3′
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[0]
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5′-TCTCCATGGTGGTGAAGACA-3′
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[0]
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NPPA
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5′-CCCTCCGATAGATCTGCCCT-3′
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5′-GTCAATCCTACCCCCGAAGC-3′
[6] array · 1 item
[0]
[7] array · 4 items
[0]
Mouse
[1]
SFRP4
[2]
Forward
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5′-AAAAGCCGTCCAGAGGAGTG-3′
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[2]
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Complete file
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This study was designed to screen the potential molecules and pathways implicated with DCM. GSE26887 involving 5 control individuals and 7 DCM patients was selected from the GEO database to identify the differentially expressed genes (DEGs). DAVID was applied to perform gene ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses. A protein-protein interaction (PPI) network was also constructed to visualize the interactions among these DEGs. To further validate significant genes and pathways, quantitative real-time PCR (qPCR) and Western blot were performed. A total of 236 DEGs were captured, including 134 upregulated and 102 downregulated genes. GO, KEGG, and the PPI network disclosed that inflammation, immune disorders, metabolic disturbance, and mitochondrial dysfunction were significantly enriched in the development of DCM. Notably, IL6 was an upregulated hub gene with the highest connectivity degree, suggesting that it may interact with a great many molecules and pathways. Meanwhile, SOCS3 was also one of the top 15 hub genes in the PPI network. Herein, we detected the protein level of STAT3 and SOCS3 in a mouse model with DCM. Western blot results showed that the protein level of SOCS3 was significantly lower while phosphorylated-STAT3 (P-STAT3) was activated in mice with DCM. In vitro results also uncovered the similar alterations of SOCS3 and P-STAT3 in cardiomyocytes and cardiac fibroblasts induced by high glucose (HG). However, overexpression of SOCS3 could significantly reverse HG-induced cardiomyocyte hypertrophy and collagen synthesis of cardiac fibroblasts. 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