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Erschienen in: European Journal of Medical Research 1/2019

Open Access 01.12.2019 | Research

Identification of key genes involved in myocardial infarction

verfasst von: Linlin Qiu, Xueqing Liu

Erschienen in: European Journal of Medical Research | Ausgabe 1/2019

Abstract

Background

This study focuses on the identification of conserved genes involved in myocardial infarction (MI), and then analyzed the differentially expressed genes (DEGs) between the incident and recurrent events to identify MI-recurrent biomarkers.

Methods

Gene expression data of MI peripheral blood were downloaded from GSE97320 and GSE66360 datasets. We identified the common DEGs in these two datasets by functional enrichment analysis and protein–protein interaction (PPI) network analysis. GSE48060 was further analyzed to validate the conserved genes in MI and to compare the DEGs between the incident and recurrent MI.

Results

A total of 477 conserved genes were identified in the comparison between MI and control. Protein–protein interaction (PPI) network showed hub genes, such as MAPK14, STAT3, and MAPKAPK2. Part of those conserved genes was validated in the analysis of GSE48060. The DEGs in the incident and recurrent MI showed significant differences, including RNASE2 and A2M-AS1 as the potential biomarkers of MI recurrence.

Conclusions

The conserved genes in the pathogenesis of MI were identified, benefit for target therapy. Meanwhile, some specific genes may be used as markers for the prediction of recurrent MI.
Hinweise

Electronic supplementary material

The online version of this article (https://​doi.​org/​10.​1186/​s40001-019-0381-x) contains supplementary material, which is available to authorized users.

Publisher's Note

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Abkürzungen
MI
myocardial infarction
DEGs
differentially expressed genes
PPI
protein–protein-interaction
PCI
percutaneous coronary intervention
ECG
electrocardiogram
CKMB
MB (muscle/brain) fraction of creatine kinase
GO
gene ontology
KEGG
Kyoto Encyclopedia of Genes and Genomes
GEO
gene expression omnibus
MAPK
mitogen-activated protein kinase
MAPKAPK2
MAPK-activated protein kinase 2
STAT3
signal transducer and activator of transcription 3
EDN
eosinophil-derived neurotoxin
TLR2
toll-like receptor 2
RNASE2
human ribonuclease 2
A2M-AS1
A2M antisense RNA 1

Background

Myocardial infarction (MI) is defined as myocardial cell death due to prolonged ischemia [1]. Worldwide, about 15.9 million MI occurred in 2015. An MI was one of the top five most expensive conditions during inpatient hospitalizations in the US, with a cost of about $11.5 billion for 612,000 hospital stays as estimated in 2011 [2]. The main treatment strategy of MI is myocardial revascularization by the percutaneous coronary intervention (PCI) combined with management of cardiovascular risk factors [3]. Biomarkers are measurable and quantifiable biological parameters which serve as indices for health and physiology assessments. Diagnosis of MI is generally made by combining observation changes in a surface electrocardiogram (ECG) and blood levels of sensitive and specific biomarkers. Overall, the preferred biomarker for each specific category of MI is cTn (I or T) due to its high myocardial tissue specificity as well as high clinical sensitivity [1]. If a cTn assay is not available, the best alternative is MB (muscle/brain) fraction of creatine kinase (CKMB). Elevation of cTn or CKMB in the blood reflects injury leading to necrosis of myocardial cells [1]. In addition, myoglobin, N-terminal proBrain natriuretic peptide, and lactate dehydrogenase have also been considered as clinical diagnosis biomarkers of MI [4]. However, how these biomarkers function myocardial cells injury and necrosis are unclear.
In this study, we identified the conserved genes to investigate the molecular mechanism underlying MI development. Incident MI is defined as the first MI for patients, and it is considered to be a recurrent MI if characteristics of MI occur after 28 days following an incident MI [1, 5]. Differences between first and recurrent events on gene expression profiling are poorly described. Thus, we studied potential differences in the gene expression between patients with an incident and recurrent MI. In addition, little is known of the risk factors of recurrent MI at the transcriptome level. To address this issue, we further detected the potential biomarkers associated with recurrent MI occurrence.

Methods

Datasets

We searched the keywords “myocardial infarction”, “peripheral blood”, “GPL570” in the GEO datasets, and obtained 3 GEO datasets-GSE97320, GSE66360 and GSE48060.
GSE97320 and GSE66360 included gene expression profiles of peripheral blood from patients with MI and normal controls. GSE48060 contained gene expression profiling of patients with incident MI and that with recurrent events as well as normal controls. The platform used in these three datasets is GPL570 HG-U133_Plus_2 Affymetrix Human Genome U133 Plus 2.0 Array.

Differentially expressed gene (DEGs) screen

Gene expression data were first downloaded from each dataset, and the expression levels of genes in each sample were extracted from Series Matrix File(s). And then, R was used to pre-process the downloaded raw data via background correction and quantile normalization. Using Perl [6] probes were transformed into genes. Subsequently, “impute” package [7] was applied to complement the missing expression with its adjacent value.
To screen DEGs between the MI group and the control group, Limma [8] package in R was used. DEGs were screened with |log2(fold change)| > 0.45 and P < 0.05.

Functional enrichment analysis

To obtain the biological function and signaling pathways of conserved genes, GOstats and clusterProfiler [9] packages were used to detect gene ontology categories and KEGG pathways. The threshold of GO function and KEGG pathway of DEGs was all set as P < 0.05.

Protein–protein interaction (PPI) network analysis

To gain insights into the interaction between proteins encoded by DEGs, the database of HPRD [10], BIOGRID [11], and PIP [12] were used to retrieve the predicted interactions of the conserved genes. Then, the PPI network was visualized by the Cytoscape 3.2.1 [13]. A node in the PPI network denotes protein, and the edge denotes the interactions. Cytocluster was further performed to identify the sub-modules.

Statistical analysis

Data were expressed as mean ± SD. A value of P < 0.05 was considered significant.

Results

Identification of conserved genes in MI

To identify conserved genes involved in MI, comparisons between patients with MI and normal individuals were performed to identify differentially expressed genes (DEGs)in two datasets (GSE97320 and GSE66360), which included gene expression profiles in peripheral blood of patients with MI. A total of 2723 DEGs were identified as the fold change > 1.5 and P value < 0.05 in GSE97320, consisting of 1568 upregulated and 1137 downregulated genes (Fig. 1). In GSE66360, 2486 genes including 1141 upregulated genes and 1345 downregulated genes were differentially expressed between patients with MI and healthy individuals (Fig. 2). The genes regulated consistently in GSE97320 and GSE66360 were defined as the conserved genes. A total of 477 conserved genes were differentially expressed in both datasets, including 289 upregulated genes and 188 downregulated genes with the same consistently changed direction (Table 1). These conserved genes may play an important role in the development of MI.
Table 1
The conserved genes differentially expressed in both GSE97320 and GSE66360
Conserved genes
GSE97320
GSE66360
LogFC
P value
LogFC
P value
NAMPT
3.715416803
0.000290322
2.319993166
< 0.0001
ACSL1
2.19001047
0.003256902
2.383412763
< 0.0001
S100P
3.760092992
0.004065492
2.468096374
< 0.0001
BCL6
1.877766083
0.001336775
1.757327328
< 0.0001
NFIL3
1.931964423
0.000341343
2.848042441
< 0.0001
ADIPOR1
3.421860496
0.017438642
1.458088512
< 0.0001
MIR8085
0.891511885
0.011998793
1.376148893
< 0.0001
THBD
1.879835689
0.003477466
1.718774941
< 0.0001
IL1R2
3.149278731
0.005306621
2.412986325
< 0.0001
LOC100129518
2.250309635
0.000500285
1.859238466
< 0.0001
C5AR1
2.145806047
0.006632287
2.515427476
< 0.0001
FCN1
0.830570678
0.047479898
1.888141317
< 0.0001
ZFAND5
2.073315077
0.0000438
1.138660839
< 0.0001
IL1RN
1.806072308
0.000219741
1.400798053
< 0.0001
PDE4B
1.306346402
0.01467501
1.270678227
< 0.0001
NFKBIA
1.68182951
0.018260863
1.989220351
< 0.0001
DUSP1
2.764547251
0.000328017
1.271651227
< 0.0001
ZNF137P
− 1.202805686
0.027261213
− 1.682690294
< 0.0001
ITPRIP
1.212871872
0.043664444
1.254857254
< 0.0001
MAPKAPK2
0.765865504
0.038125016
0.778311524
< 0.0001
GADD45A
0.660265341
0.016856452
1.605988515
< 0.0001
BST1
1.232389286
0.029795796
2.187724267
< 0.0001
SERPINA1
3.878586998
0.0000872
1.638136049
< 0.0001
QPCT
2.085892271
0.01667478
2.001432298
< 0.0001
JDP2
1.310855377
0.017420794
1.215915653
< 0.0001
SLC25A37
3.9607872
0.018922169
1.064428591
< 0.0001
GLUL
3.004222492
0.000922447
1.282605825
< 0.0001
S100A9
0.941442135
0.008081851
2.138155827
< 0.0001
HAL
1.388152953
0.003229592
1.15652044
< 0.0001
CLEC7A
2.06910398
0.000914725
1.461369096
< 0.0001
ATP6V0C
1.606678644
0.004965952
1.126718923
< 0.0001
CDA
2.769525669
0.00898907
1.485180438
< 0.0001
TRIB1
2.679234011
0.00045788
1.121985648
< 0.0001
PPIF
1.359533482
0.04082833
1.408576461
< 0.0001
AIF1
1.518215926
0.002104306
1.698436828
< 0.0001
EIF1
1.442005776
0.00017885
0.863524366
< 0.0001
ICAM1
0.729995143
0.019983292
1.394025803
< 0.0001
POLH
− 0.566509776
0.049459364
− 0.737136085
< 0.0001
TREM1
1.502206913
0.019743677
2.603791299
< 0.0001
CCR5
− 0.776384955
0.01829638
− 1.95935621
< 0.0001
PLAUR
0.743728715
0.026751653
1.711115656
< 0.0001
CMTM2
2.866177199
0.00943438
2.053476388
< 0.0001
FOSL2
0.969762074
0.005618694
0.949529005
< 0.0001
LILRA5
1.939542124
0.003227223
1.238799783
< 0.0001
CXCL1
1.597284132
0.013637632
2.179973359
< 0.0001
FCGR2A
3.058858412
0.001506307
1.61933339
< 0.0001
PTAFR
1.254827529
0.021198075
1.110084724
< 0.0001
FCGR2C
1.387185414
0.026898778
0.997833095
< 0.0001
ETS2
1.008783969
0.022408169
1.453545191
< 0.0001
LOC401317
1.325609511
0.01449473
1.356511126
< 0.0001
ZFP3
− 1.181499024
0.028794617
− 1.616668145
< 0.0001
TNFAIP2
1.008366932
0.02131624
1.146286395
< 0.0001
ZNF557
− 0.480686383
0.027928556
− 1.236804343
< 0.0001
IL13RA1
2.154977188
0.007550323
1.297242172
< 0.0001
P2RY13
1.230745211
0.02057251
1.972782405
< 0.0001
SNN
1.528052824
0.001923619
1.00822514
< 0.0001
PADI2
2.10709958
0.000256162
0.906661034
< 0.0001
QKI
0.944951526
0.002191432
0.714960381
< 0.0001
MS4A6A
0.958109791
0.012432822
1.460308619
< 0.0001
LILRA2
1.272631449
0.00994245
1.148478416
< 0.0001
AQP9
2.333240109
0.018284882
2.131747969
< 0.0001
HCAR3
2.824751704
0.00472807
2.110183937
< 0.0001
GRINA
1.402640902
0.028502087
1.074225506
< 0.0001
LOC100128751
− 0.707207366
0.016384142
− 1.043483941
< 0.0001
KDM6B
0.66281941
0.024585326
0.754981016
< 0.0001
GIMAP1
− 0.835067476
0.045419126
− 1.223531516
< 0.0001
BCL2A1
1.943399108
0.021464182
1.895503232
< 0.0001
AMPD2
− 0.721354352
0.048955977
1.614895577
< 0.0001
FPR2
2.199274247
0.02941438
1.600783776
< 0.0001
CPD
0.821859648
0.048035987
1.078872501
< 0.0001
STX11
1.697322241
0.023704466
1.022277137
< 0.0001
TLE3
1.209440706
0.015391784
0.84564545
< 0.0001
GLT1D1
1.606386641
0.007085751
1.505836542
< 0.0001
DGAT2
1.588575564
0.040614788
0.966784955
< 0.0001
SIRPA
1.467435961
0.002424106
0.883668576
< 0.0001
CD93
0.672547012
0.025451375
1.354276298
< 0.0001
PAQR8
− 1.247490335
0.000854948
− 1.105178815
< 0.0001
HERPUD1
1.563752908
0.000217748
0.815993132
< 0.0001
CXCL8
2.613026128
0.003928869
1.549771356
< 0.0001
LOC101929819
0.819452437
0.024240235
0.847572886
< 0.0001
PYGL
1.989921497
0.025319691
1.582056104
< 0.0001
FPR1
2.973441365
0.000645968
1.446062497
< 0.0001
CEBPD
2.386813879
0.000921878
1.23662014
< 0.0001
STAT3
1.780855138
0.011714132
1.024539916
< 0.0001
BTG2
1.596394305
0.001901717
0.889101647
< 0.0001
SLC6A6
2.447756683
0.000438167
0.644662214
< 0.0001
CLEC12A
1.3493504
0.007738217
1.042625117
< 0.0001
SOCS1
0.674899289
0.031132314
0.803066827
< 0.0001
HOTS
0.47497249
0.043443589
1.235734387
< 0.0001
ZNF786
− 0.846155897
0.006163145
− 1.330967712
< 0.0001
KDELC2
− 1.126543214
0.013735129
− 0.871863341
< 0.0001
SEC14L1
3.222121
0.005523564
0.868185585
< 0.0001
CHI3L1
2.697015762
0.017524244
1.18798994
< 0.0001
RNASE2
0.907871679
0.001791958
1.849318307
< 0.0001
MPP1
1.44935076
0.039373731
1.457675515
< 0.0001
PQLC1
1.098874935
0.039814237
0.508070689
< 0.0001
TCEB3-AS1
− 0.694870463
0.04616438
− 1.433351491
< 0.0001
TIGD7
− 0.985252239
0.036510489
− 1.167389496
< 0.0001
PGD
1.901669081
0.000154316
0.565073179
< 0.0001
U2AF1
1.702264526
0.018461448
0.915025557
< 0.0001
AKIRIN2
1.785779636
0.00034891
0.657209785
< 0.0001
LBH
− 0.91504058
0.032471404
− 1.324336977
< 0.0001
RAD54B
− 0.538426791
0.036659702
− 1.414883543
< 0.0001
MME
2.276317524
0.047321026
1.137294855
< 0.0001
DOCK5
1.078051413
0.032816176
0.835988452
< 0.0001
ABHD5
0.735179941
0.03520765
0.727680923
0.000101662
PLBD1
0.969302605
0.032765571
1.798031132
0.000102992
BACH1
1.351200785
0.00167848
0.585528821
0.000107046
ZYX
1.085019322
0.010168639
0.715711002
0.000108507
FCGRT
0.70475403
0.01525679
0.91961625
0.000111858
GEMIN5
− 1.47500487
0.046026587
− 1.57933263
0.000112299
LOC221272
− 1.181714286
0.010168237
− 0.87301352
0.000115697
TNFRSF10C
1.988784507
0.016690641
0.687475626
0.000115702
TLR4
1.28311422
0.009728893
0.796509712
0.000120788
CDV3
1.709600858
0.0003786
0.756754733
0.000121731
USB1
1.012045755
0.00547019
0.525968344
0.000127289
MXD1
3.02456454
0.003699774
1.099434156
0.000129507
VNN2
2.180194614
0.0109879
1.397451606
0.00013196
SGK223
− 1.252002755
0.000726559
− 0.787841536
0.000138471
TET1
− 0.703607148
0.008657374
− 0.818610782
0.000149306
LPCAT2
0.85182211
0.047333209
0.936460647
0.000150743
MGAM
3.213431913
0.005317158
1.610096737
0.000154249
NPL
1.239490617
0.006173363
0.732825202
0.000169972
LY96
1.346013773
0.005411258
1.029764841
0.000170653
PTGS1
0.967130969
0.003641179
0.77481882
0.000179849
SLC2A14
1.291691746
0.017168802
1.307076894
0.000180583
GIN1
− 1.237598849
0.038502248
− 1.525016605
0.000185774
TKT
1.773187189
0.000256431
0.833485867
0.000189348
CSF2RB
2.200868771
0.008362239
1.631201272
0.000194977
MMP25
1.898237252
0.010803144
0.694482086
0.000198083
CNOT6L
1.556044518
0.003364024
0.596626207
0.000203962
TP53INP1
1.731770541
0.002114113
0.512674471
0.000205394
CLP1
0.660538961
0.039295856
0.702552153
0.000224265
FAM198B
1.263612775
0.018980734
1.063744226
0.000232443
ZNF606
− 1.021874256
0.010996345
− 0.986409189
0.000239356
PECAM1
1.133988939
0.002525393
0.812308902
0.000251335
CPEB2
0.509987239
0.029154597
0.733979649
0.000260216
SHQ1
− 0.690969237
0.034617547
− 1.158028865
0.000264123
FCGR3B
3.813483966
0.008808688
1.227532333
0.000268305
SIAH1
1.165012649
0.015051532
0.902135148
0.000293066
FCGR1B
1.510242008
0.044692504
1.262470054
0.000312948
ZNF30
− 1.110993329
0.02752944
− 0.993962406
0.00034754
MRPS17
− 0.696898862
0.030343011
− 0.929231267
0.00036119
EIF2B3
− 0.522846432
0.034922941
− 0.859607844
0.000415198
ZNF260
− 1.283202812
0.04751078
− 1.223608639
0.000416573
ZBTB3
− 0.838180298
0.021768338
− 1.025353413
0.000421081
SPI1
1.242116323
0.025822193
0.852205923
0.000421285
ELP4
− 0.985373014
0.031611917
− 1.13057002
0.000441549
STK17B
1.634772394
0.016110753
1.070768411
0.000443755
CXCL16
1.430929047
0.019642805
1.517379129
0.000445953
CYP4F3
2.891652429
0.012098196
1.083712332
0.000464153
ZCCHC17
− 0.527154589
0.03711239
− 0.703895685
0.000466123
BNIP3L
2.939399055
0.036736625
0.868766712
0.000480117
HLTF
− 2.085425559
0.00830834
− 0.92642157
0.000481112
ZNF280B
− 0.889975527
0.007382474
− 0.591810379
0.000482869
ENTPD1
0.833331837
0.013979206
0.872451565
0.00048829
SMARCAD1
− 1.536179035
0.00212696
− 1.388394318
0.000503169
ZDHHC18
0.970662172
0.03919739
0.464432831
0.000516733
SP3
0.566964411
0.027129826
0.45352211
0.000530533
DENND1C
− 0.994967054
0.005926672
− 0.720422053
0.000556354
ARHGEF40
0.677302641
0.00863392
0.949974076
0.000560322
VNN3
1.459070601
0.002685799
0.818145005
0.000567591
PTPN12
1.900952269
0.006990223
0.648074395
0.000590111
IL22
0.785725374
0.033763579
0.870706647
0.000608321
AKAP13
1.15374636
0.024380781
0.457987789
0.000610161
HIPK1
0.790715098
0.028493908
0.594190441
0.000620025
SLC2A3
1.277853147
0.005001915
0.975255592
0.000625103
MRPL18
− 0.962891471
0.001294926
− 0.810866571
0.000673172
PNRC1
0.84100527
0.038963808
0.771737601
0.000685328
SRPRB
− 0.572880851
0.02337171
− 0.794559375
0.000695958
IFNGR1
1.303124037
0.013360086
1.017612578
0.000703371
NIF3L1
− 0.869517958
0.043390346
− 1.019489489
0.00070353
XPA
− 0.90413844
0.041510611
− 0.80325959
0.000756448
MMP9
2.441007592
0.01581582
0.97531267
0.000777516
NCF1C
0.855445347
0.038108625
0.783883625
0.000784817
DET1
− 0.81533148
0.005926379
− 0.854080807
0.000803216
COQ10A
− 0.933289637
0.006719525
− 1.081765186
0.000832872
UBALD2
0.844767801
0.034723888
0.610479487
0.00088448
JMJD1C
1.363565695
0.045081671
0.806155508
0.000897176
GNB4
1.332152673
0.000181302
0.703062789
0.00092457
SIRPB1
1.376479024
0.015121968
0.783168056
0.000935223
TBXAS1
0.901392581
0.035582908
0.72491305
0.000938466
LOC100996286
− 1.15942957
0.001304937
− 1.10912258
0.000951423
FUNDC1
− 1.016071403
0.025599739
− 1.17719563
0.000962182
CDC42
1.293690918
0.001559527
0.617592666
0.000979709
CHMP4B
1.337085004
0.024622123
0.789355603
0.001035706
MIDN
1.798309942
0.003199858
0.549277047
0.001044485
ZNF232
− 0.974081458
0.026063953
− 1.280741756
0.001082083
S100A8
1.151105372
0.000612836
1.667435842
0.00114641
SIGLEC5
1.528578408
0.022982592
1.145057625
0.001148462
RAE1
0.786226017
0.04583837
0.646827746
0.001155134
FMNL3
− 0.911262187
0.006347222
− 0.708906078
0.001168614
FFAR2
3.054926626
0.007540706
1.110136702
0.001188049
KYNU
0.913892454
0.003039259
0.770873995
0.001243107
ASAH1
1.098421547
0.005150015
0.754043428
0.00125101
PLAC8
− 0.839086258
0.031308986
− 0.849482287
0.001277728
LINC00909
− 1.345332297
0.013596272
− 0.969000288
0.001316741
PTGS2
2.350439432
0.001568506
1.426523404
0.001319682
PIGF
− 0.808285785
0.036923826
− 0.594491349
0.001339096
ZNF284
− 2.184588821
0.040088141
− 0.93615243
0.001361012
LOC102724851
− 1.155228734
0.013040415
− 0.518495367
0.001376683
STT3A
− 0.929412935
0.006056463
− 0.913154729
0.001399971
ATG3
2.102229556
0.000178319
0.841794717
0.001410075
TIMM9
− 1.40383474
0.007805487
− 0.735973926
0.001444816
TOMM40L
− 0.779793242
0.021017904
1.086712809
0.001468786
ALPL
1.60229352
0.038415425
0.716082883
0.001490739
DSC2
0.98658481
0.010627222
0.567380206
0.001504916
HLX
1.349039117
0.020807799
0.513207382
0.001520858
LYL1
1.538740411
0.040216887
0.502710942
0.001523024
SESN3
2.636101881
0.004536708
0.494696947
0.00155925
RNF141
1.445983931
0.004029835
0.552945436
0.001562541
GABARAPL3
1.014160119
0.002281996
0.717868982
0.001606081
LOC105376805
− 1.365943289
0.001327507
− 0.595216422
0.001625267
GNAS
3.247649892
0.0000955
0.478498353
0.001735362
PTP4A1
0.778394075
0.009116649
0.636669015
0.001778326
UBASH3A
− 1.430887468
0.002003066
− 0.913772788
0.0018777
HSD17B7
− 1.721065936
0.009279288
− 0.835575098
0.001927602
TP53RK
− 0.505724162
0.044175513
− 0.997261329
0.00197887
SERPING1
0.915484027
0.029789731
0.839308791
0.002037968
DOCK4
0.713528467
0.026268016
0.661229341
0.002047801
RBM4B
− 0.754993386
0.025500124
− 0.973299711
0.002076982
GAS7
0.652023956
0.030611426
0.728288754
0.002160493
RNF10
2.292398494
0.033636936
0.623649579
0.002172112
LINC00623
− 1.165387619
0.00087698
− 0.539399165
0.002174586
YBX3
4.365021825
0.003169993
0.52927351
0.002242851
ERGIC1
1.693282707
0.006494326
0.482795744
0.002365768
MARCKS
1.896513739
0.011966121
1.008557895
0.00237302
FTH1
0.721676035
0.006408239
1.182091335
0.002417955
LMO2
1.861941801
0.004174164
0.544068211
0.002425819
ADM
1.851219504
0.008897467
1.254434919
0.002493206
SCYL3
− 1.011979188
0.035057218
− 0.710888004
0.002503157
ZNF140
− 1.418751894
0.021858458
− 0.821318547
0.002526554
RASSF5
1.494672795
0.000190407
0.666636746
0.002625559
ZNF746
1.43259319
0.038940531
0.546212963
0.002633285
NME6
− 0.610227552
0.041831331
− 0.803569365
0.002640731
TFRC
0.605142119
0.044216485
0.486955837
0.002659029
ASCC2
3.012960368
0.048869583
0.503342235
0.002691189
TCL1A
− 1.418926748
0.043956086
− 0.740787553
0.002719864
ADGRG3
1.756451065
0.026679736
0.924004639
0.002740384
RAB1A
2.053694233
0.000197952
0.451082876
0.002771411
CHST15
1.38976538
0.010674237
0.849343314
0.002942074
TNFAIP6
2.840950381
0.005912694
1.108939843
0.002978094
LOC102724229
− 1.48967097
0.03404748
− 1.014128699
0.003062724
MAPRE1
0.531042713
0.021090503
0.459089464
0.003165946
ABHD2
1.201422325
0.005387136
0.46795845
0.003218277
MNAT1
− 0.83937625
0.024109007
− 0.565184788
0.003355533
TMCC3
1.745352413
0.013173346
0.799248122
0.003376755
POLR1B
− 0.772923097
0.032500554
− 0.505466721
0.003452495
PLEKHG2
0.569547478
0.038813449
0.535246343
0.003585976
RBM47
1.784627427
0.001016962
0.678723979
0.003615633
POLE2
− 0.524011745
0.033009479
− 0.878657539
0.003617168
REPS2
1.718120007
0.003180389
0.644368871
0.003635816
GBP3
− 1.845504585
0.008969037
− 1.193440354
0.003699308
ERVK3-1
− 1.050961105
0.014574394
− 0.80126366
0.003700902
TIMP2
1.321414802
0.006004518
0.738209029
0.003701828
JUND
2.816842846
0.00000849
0.466923422
0.003713308
PTGER4
1.137141559
0.044765741
0.758160268
0.003753251
PHC2
1.794885166
0.00447288
0.579182361
0.003765784
RELL1
1.188903575
0.004557879
0.581780349
0.003843326
PDCD11
− 0.669519886
0.031226669
− 0.585698567
0.00386508
LOC101928291
− 0.607349146
0.02839692
− 0.994929526
0.003919704
DNAJC19
− 0.68231173
0.018596595
− 0.534281446
0.003949704
ITGAM
1.858485959
0.0000309
0.668737696
0.003973806
A2M-AS1
− 1.155442856
0.039842116
− 1.138539809
0.003974972
SMCHD1
1.604667418
0.010852317
0.712810012
0.003983746
ICAM2
− 0.984018887
0.017489313
− 0.88255297
0.004009051
CEBPB
0.598014744
0.031789552
1.317994945
0.004020206
SSFA2
1.066587737
0.002451362
0.624973739
0.004021925
PTPRCAP
− 0.866500312
0.011837444
− 0.726859417
0.004052694
POP1
− 0.925608754
0.030781593
− 0.818205615
0.004246787
BLNK
− 1.398591377
0.030430259
− 0.894692561
0.004288343
GALM
− 0.713557563
0.034952709
− 0.675235843
0.004443763
SEC61B
1.180469063
0.000723465
0.686145648
0.004453778
MAP7D3
− 0.553624737
0.025768455
− 0.507870015
0.004521575
GCA
1.509319178
0.004363002
1.192393745
0.004633368
LGALSL
1.21757196
0.044976788
0.671933026
0.004880392
ARAF
1.427113051
0.038366364
0.51978633
0.004913297
RNF144B
0.726950076
0.012122937
0.779524204
0.00500161
KCNJ15
1.979657868
0.039608194
0.628206301
0.005135068
CD40LG
− 0.792190382
0.044206155
− 1.032646424
0.005145558
CPPED1
1.076942495
0.036499438
0.612705064
0.005168794
RIOK3
2.075563218
0.002003992
0.521802306
0.005218069
DDX46
− 0.919216329
0.029662572
− 0.639785975
0.00523761
CDK17
1.128464094
0.013744211
0.693411752
0.005347246
MIR21
1.91559852
0.046387482
0.544304499
0.005431751
SPIN3
− 0.857422597
0.023843176
− 0.769503059
0.005588091
FAM46C
2.601440153
0.021586082
1.005819825
0.005625886
HIST2H2AA4
2.093741596
0.004304829
0.841019575
0.005688879
LOC101930115
− 0.68275475
0.040474709
− 0.607842314
0.005704428
LOC151657
− 1.607243608
0.001601903
− 0.717618669
0.005720524
CLU
2.316583335
0.001072876
0.563627036
0.005777839
AKTIP
− 0.847566702
0.040054537
− 0.633465882
0.006096883
NINJ1
0.945159729
0.010864115
0.87230313
0.006320781
ZFP30
− 1.038905821
0.010392043
− 0.871623208
0.006325373
EIF1B
3.692853038
0.000758987
0.878422088
0.006414737
LOC101930363
− 2.709073019
0.011781869
− 0.736376913
0.006454992
TANK
1.653093179
0.002146166
0.520972495
0.006474026
PARG
− 1.086961793
0.043658497
− 0.724468917
0.006491873
TEFM
− 1.027675228
0.023860331
− 0.667630909
0.006617711
ASAP1
1.098840052
0.016823868
0.514404458
0.006851203
CDKN2D
1.952060497
0.018541817
0.490974421
0.006891249
TSPYL1
2.709566348
0.001494149
0.60819847
0.006988834
CSTF3
− 1.18690418
0.003957706
− 0.491540334
0.006989296
MROH7-TTC4
− 1.067721766
0.016410638
− 0.919365541
0.007060206
RFX5
− 0.538517443
0.041897931
− 0.645397188
0.007076645
NKG7
− 1.070684122
0.010774919
− 0.945817311
0.007078395
DARS2
− 0.78027652
0.027042938
− 0.741649853
0.007137998
ZNF615
− 0.777419719
0.020695789
− 1.209541334
0.007310157
ADSS
1.070420831
0.006216282
− 0.538713686
0.00738181
OGFRL1
1.62280147
0.0000662
0.745837652
0.007530407
CD2
− 0.908924186
0.049667697
− 0.9371322
0.007535782
DYNLL1
− 0.757353509
0.012942379
− 1.226469494
0.007808299
SEPHS1
− 0.960674944
0.02404333
− 0.491689916
0.007844444
AGFG1
0.697014119
0.040811266
0.599122876
0.007932363
WTAP
1.415043348
0.013255137
0.504140918
0.008157105
RNASEH2A
− 0.567107275
0.048285518
− 0.588491225
0.008261927
LCLAT1
− 1.191926318
0.000330923
− 0.907358841
0.008467512
GNA13
2.465840893
0.000677556
0.803476183
0.008677402
HBD
4.363118946
0.03133988
0.714000351
0.008706877
CA5B
− 0.761733369
0.010733624
− 0.717511936
0.009153528
WDR26
1.795069926
0.006752784
0.554641276
0.009208138
BHLHE40
1.067828924
0.01253442
0.82013057
0.00931423
DCTN4
0.995446804
0.019331887
0.602818796
0.009817669
RARRES3
− 0.810774795
0.042801728
− 0.815285574
0.009897921
MRVI1
1.380868974
0.03671614
0.499460438
0.009923543
SLC7A6OS
− 0.747296638
0.003754511
− 0.683052886
0.010144899
LOC100289090
− 0.510049286
0.048064071
− 0.526694355
0.010151137
WDR1
1.684601866
0.000168948
0.468754984
0.010157612
ANXA2R
− 1.735263881
0.001346797
− 0.842518717
0.010211973
LOC101927929
− 0.911010924
0.036707986
− 1.056783587
0.010586272
DCP2
1.339414838
0.012814635
0.536456476
0.010623367
IL7R
− 1.38550515
0.027408601
− 1.003290446
0.010704747
DPY19L2P2
− 1.343859858
0.006832435
− 0.691688548
0.010708918
LRMP
1.425535165
0.019422696
0.548187496
0.010789867
HPR
0.823889667
0.033804337
0.511405624
0.01081264
CFB
1.123068147
0.049371972
0.457666939
0.010904784
LOC284513
− 0.892129855
0.004236477
− 0.701299207
0.010990889
RAB20
0.821602882
0.035312406
0.586702846
0.011071966
FBXO7
3.643752431
0.018286086
0.499532856
0.011346495
PHAX
− 0.789847996
0.035012859
− 0.532516036
0.011379085
BLVRB
2.656708226
0.011781419
0.642487027
0.01141343
WLS
1.657097425
0.028300616
0.62402017
0.012075619
MUT
− 1.050168894
0.002313509
− 0.626508717
0.012205507
LOC100287896
− 0.86494196
0.035810543
− 0.919630542
0.012517769
HSPC102
0.916580698
0.025392925
0.868444451
0.012523152
TSC22D3
2.405997523
0.0000286
0.488948844
0.012661968
PTENP1
2.094685709
0.000479594
0.618312388
0.012790096
ZNF57
− 1.343945962
0.010152991
− 0.929510368
0.012800761
MUTYH
− 0.936725766
0.008091841
− 0.553024313
0.013128222
HCST
− 0.791970019
0.007490591
− 0.50645902
0.013285635
LOC100507616
− 0.521527416
0.042217852
− 0.465453565
0.01346017
CYBB
2.398594516
0.000400338
0.626735409
0.013536222
TIMMDC1
− 0.747343418
0.014838492
− 0.93807409
0.013541407
KIF13A
0.930338853
0.011402054
0.515997085
0.014285432
C14orf169
− 1.092295613
0.006077514
− 0.461703063
0.014457478
ISCA2
− 0.673334196
0.014793629
− 0.801341203
0.014570854
CR1
0.980739302
0.03282439
0.564267726
0.014685731
SMYD4
− 0.743050454
0.008096331
− 0.756746486
0.014705624
MTURN
1.229572779
0.04943481
0.614334998
0.015126434
FASTKD1
− 1.54680628
0.002039946
− 0.7227908
0.015176612
PIGN
− 0.708552558
0.011836956
− 0.49162495
0.015256966
TESPA1
− 1.021501179
0.048240998
− 0.521959366
0.015269293
HOXB2
− 0.940925367
0.027917932
− 1.044582695
0.015348671
TAF3
− 0.874538712
0.016049188
− 0.520997598
0.015458366
MNDA
1.053933023
0.042861478
0.983216212
0.015528146
CDC42EP4
0.498947026
0.039781999
0.532259022
0.01560414
GPD1L
− 0.761261068
0.038421959
− 0.915958276
0.015789382
BBS10
− 1.031497448
0.038982743
− 0.656567662
0.016094327
OR2A9P
− 0.633389532
0.024730134
− 0.565938071
0.016339377
G6PD
0.871501908
0.006760087
0.459398494
0.016352781
TFG
0.720616794
0.006867605
0.487139927
0.016532991
FAM114A2
− 0.459915629
0.040407886
− 0.57057389
0.016675289
ATP1A1
1.12474105
0.013429616
0.707444754
0.01694022
GDE1
1.401322239
0.030249245
0.540437863
0.017493186
RNF170
− 0.504220106
0.023599634
− 0.490772966
0.017518558
SH3BGR
− 0.857459864
0.028655056
− 0.62930005
0.017522267
LOC283588
− 1.368743502
0.045421947
− 0.7194058
0.018040997
PRKCQ-AS1
− 1.188507039
0.019254615
− 0.481844821
0.018533389
THAP11
− 0.807250427
0.04032733
− 0.593943089
0.018861969
PTPRE
1.565506182
0.000241063
0.504255599
0.019290598
IL11RA
− 0.897536126
0.039623934
− 0.617587742
0.019315582
NARF
0.746465067
0.011958684
0.531794282
0.019361642
TMEM260
− 0.9858146
0.004981655
− 0.472649113
0.019517865
WDR89
0.78862198
0.017657719
− 0.536328947
0.019700691
VAMP3
0.895596534
0.040531984
0.742719501
0.019795093
NVL
− 1.329520343
0.020108611
− 0.660575451
0.020862258
IMPA2
1.710057922
0.008863916
0.55874936
0.020875373
TOP2B
− 1.224847791
0.046556803
− 0.69362205
0.021007495
BACH2
− 1.556070717
0.001593919
− 0.694884856
0.021047149
LOC643072
1.336393236
0.01614887
0.504133706
0.021762187
FAM171A1
− 1.297102946
0.021894851
− 0.857544073
0.021837971
LCN2
1.448749929
0.027264599
0.507488907
0.022287246
F10
0.859648855
0.03887727
0.517023862
0.022463119
RYBP
1.160448619
0.000744752
0.545754325
0.022565273
PVRIG
− 1.048927951
0.012237099
− 0.776672502
0.02315433
POLB
2.156199292
0.000161715
0.7079582
0.023329133
TOP2A
1.220573095
0.042212745
0.531989942
0.023745875
ABHD15
− 0.777671518
0.045324266
− 0.589823096
0.024034951
APOL3
− 1.132962428
0.009183684
− 0.730285885
0.024821715
GNPDA1
− 0.719174212
0.019491228
− 0.64401811
0.025225165
GK3P
0.645446255
0.041071202
0.643697479
0.025486345
MAPK14
1.349924696
0.003860436
0.536455945
0.025679675
CD46
1.670254596
0.020225563
0.612875503
0.025683037
NCF2
0.918872631
0.017642988
0.914126022
0.02604898
CD96
− 1.351341746
0.013543811
− 0.710127733
0.026235883
SLC12A6
1.234381987
0.002745557
0.547304178
0.026259281
LINC00667
− 0.665792667
0.023155853
− 0.564815214
0.026378969
ESYT1
− 1.058244984
0.001054047
− 0.826953028
0.026447069
HMGN3
− 2.10599538
0.01553089
− 0.497207909
0.026987572
POMT1
− 1.167869966
0.004599769
− 0.520023047
0.026988368
TP53TG1
− 0.569201302
0.031094948
− 0.596272312
0.02704165
MTX2
− 1.204498744
0.042747776
− 0.642851561
0.02728884
GPR89B
− 0.869944564
0.048485421
− 0.840069901
0.028144016
PELI2
1.87892659
0.001987193
0.564705661
0.028197457
ZC3H15
1.44627689
0.019429305
0.50345949
0.028393971
RALB
1.752718938
0.003130775
0.575320431
0.028530086
LOC101928615
1.332017065
0.016263326
0.494459535
0.028645539
TUBB2A
4.251553993
0.012679991
1.199901102
0.028677098
ZNF248
− 1.034241515
0.002317027
− 0.484456113
0.028925632
TLR8
1.879547329
0.008044138
0.740129485
0.028974804
STEAP4
2.827840977
0.000560671
0.787317104
0.029413926
ZBTB26
− 0.901579621
0.017961829
− 0.501560605
0.029565582
LINC00847
− 0.922866306
0.006809119
− 0.641852074
0.029566356
TCEAL1
− 1.2531277
0.007061712
− 0.596036376
0.02970108
HBM
5.520539519
0.023178652
0.550713859
0.029743279
POC5
− 1.203888482
0.007930781
− 0.658986077
0.030003161
SRSF4
1.114798217
0.030264809
0.528463588
0.030559463
SMAGP
− 0.654383803
0.009936511
− 0.68678699
0.03089042
MEGF9
2.144879987
0.007476155
0.608436445
0.032247264
CHP1
1.322302286
0.012852758
0.652948587
0.032468912
BIRC6
− 2.268727559
0.019075015
− 0.556815765
0.03283538
STX3
1.667825653
0.006010718
0.466255977
0.033357788
MIR3682
− 1.570178098
0.004819709
− 0.711241423
0.033548018
COTL1
0.98035553
0.005219866
0.498692271
0.034655618
CAMTA2
− 0.682771154
0.02493448
− 0.577222959
0.034861364
IFFO2
− 0.636343197
0.041034444
− 0.530941091
0.03495195
MSANTD2
− 2.400657198
0.014678726
− 0.731603673
0.034988311
MCOLN1
1.947875812
0.040982688
0.474949343
0.035736681
LIMK2
1.16830781
0.025026897
0.485791592
0.035797975
PIK3C2B
− 1.027026319
0.027220986
− 0.714521503
0.036380145
ZSCAN22
− 0.666311572
0.039577441
− 0.628566828
0.036444868
CASP6
− 0.863230967
0.019036775
− 0.452046604
0.036539336
TSEN34
1.100210028
0.014496871
0.502990424
0.036792225
SPIN2B
− 1.080530337
0.00665453
− 0.666560137
0.03687372
DIEXF
− 0.955502636
0.010542312
− 0.480916674
0.036910908
ZNF662
− 1.605391952
0.034739974
− 0.844003226
0.037112399
RLIM
1.517247205
0.002957978
0.48931493
0.037635609
LINC00685
− 0.865718364
0.002554534
− 0.78199725
0.037931288
TFDP1
1.382812362
0.026211996
0.463299209
0.038166365
CKS1B
− 1.260935738
0.035055341
− 0.639890721
0.038265438
MGC27345
− 0.929470759
0.001570377
− 0.765467099
0.038433223
FRG1KP
− 1.483977266
0.005642658
− 0.605037114
0.038906686
CD8A
− 1.035660576
0.011469096
− 0.907658416
0.039051501
LOC284023
− 1.398345512
0.020982512
− 0.659518005
0.039504033
RAB5A
1.022626328
0.002430413
0.457608665
0.039950411
ZNF253
− 0.913362956
0.016033415
− 0.47703892
0.040028712
LOC101929774
− 0.550046909
0.027706997
− 0.524598901
0.040718581
SIAH2
1.502345693
0.044823317
0.681313021
0.040969657
ATP7A
− 0.918566186
0.002800564
− 0.450035247
0.041283805
LRRC69
− 1.351928679
0.001824204
− 0.621229266
0.04146212
FLOT2
1.971830771
0.002734479
0.465792921
0.041477634
ZC3HC1
− 0.612226203
0.013427208
− 0.509214415
0.043063035
SNAP47
− 0.499297152
0.022945868
− 0.530827895
0.043372532
LOC101060391
− 0.684904432
0.010202625
− 0.993794933
0.04414896
CSNK1D
1.001221274
0.042629925
0.508848388
0.04469371
CBX4
1.30318413
0.025436191
0.477334295
0.044771824
LIN7A
1.532754726
0.000495311
0.455799985
0.04570228
AACS
− 0.731283656
0.020694677
− 0.504672718
0.045803274
NIFK-AS1
− 0.80617843
0.036522441
− 0.497446821
0.046488677
LOC100996809
2.815826722
0.0000284
0.475058618
0.047552317
SRGN
1.650008958
0.016200667
0.868334163
0.047684837
ZNF512
− 0.886897601
0.006033191
− 0.656172686
0.047861886
CUZD1
− 1.241274988
0.01051508
− 0.611980841
0.048008528
RPUSD4
− 1.130819146
0.003519244
− 0.475668046
0.048040194
POMP
1.852833565
0.0000716
0.461851078
0.048771334
PDCL3P4
− 1.187208867
0.031281982
− 0.505102304
0.048829835
FAM216A
− 1.516187864
0.019071979
− 0.51801104
0.049031871
C11orf98
− 0.841690629
0.007367045
− 0.618307314
0.049103832
CD160
− 1.475362673
0.02228208
− 0.73506652
0.04928663
PPTC7
1.06135742
0.042924534
0.537282644
0.049610902
PSMC5
− 1.054274949
0.022317354
− 0.67624194
0.049705735

Functional enrichment analysis and biological network analysis of the conserved genes

To study the biological function of the 477 conserved genes identified, GO enrichment and KEGG pathway analysis were performed. The GO enrichment analysis revealed 211 GO biological processes (Table 2). Response to lipopolysaccharide, response to molecule of bacterial origin and immune system process were the most significantly enriched biological processes. In addition, 23 KEGG pathways were identified through analyzing the conserved genes, among which osteoclast differentiation was considered as the most remarkably enriched pathway (Table 2).
Table 2
The top 50 significant GO biological processes and all KEGG pathways enriched by the conserved genes
 
P value
Term
GOBPID
GO:0032496
< 0.0001
Response to lipopolysaccharide
GO:0002237
< 0.0001
Response to molecule of bacterial origin
GO:0002376
< 0.0001
Immune system process
GO:0006954
< 0.0001
Inflammatory response
GO:0006950
< 0.0001
Response to stress
GO:0009617
< 0.0001
Response to bacterium
GO:0033993
< 0.0001
Response to lipid
GO:0043207
< 0.0001
Response to external biotic stimulus
GO:0051707
< 0.0001
Response to other organism
GO:0006952
< 0.0001
Defense response
GO:0006955
< 0.0001
Immune response
GO:0009607
< 0.0001
Response to biotic stimulus
GO:0009605
< 0.0001
Response to external stimulus
GO:1901700
< 0.0001
Response to oxygen-containing compound
GO:0002526
< 0.0001
Acute inflammatory response
GO:0050900
< 0.0001
Leukocyte migration
GO:0002682
< 0.0001
Regulation of immune system process
GO:0008219
< 0.0001
Cell death
GO:0016265
< 0.0001
Death
GO:0030595
< 0.0001
Leukocyte chemotaxis
GO:0072606
< 0.0001
Interleukin-8 secretion
GO:0001775
< 0.0001
Cell activation
GO:0034097
< 0.0001
Response to cytokine
GO:0071222
< 0.0001
Cellular response to lipopolysaccharide
GO:0019322
< 0.0001
Pentose biosynthetic process
GO:0012501
< 0.0001
Programmed cell death
GO:0050776
< 0.0001
Regulation of immune response
GO:0071219
< 0.0001
Cellular response to molecule of bacterial origin
GO:0006915
< 0.0001
Apoptotic process
GO:0030593
0.000127
Neutrophil chemotaxis
GO:0051704
0.000142
Multi-organism process
GO:0002523
0.000149
Leukocyte migration involved in inflammatory response
GO:0002253
0.000163
Activation of immune response
GO:1990266
0.000178
Neutrophil migration
GO:0002521
0.000181
Leukocyte differentiation
GO:0097530
0.000208
Granulocyte migration
GO:2001242
0.00022
Regulation of intrinsic apoptotic signaling pathway
GO:0045321
0.000232
Leukocyte activation
GO:0060326
0.000258
Cell chemotaxis
GO:0009048
0.000275
Dosage compensation by inactivation of X chromosome
GO:0034201
0.000275
Response to oleic acid
GO:0071216
0.000302
Cellular response to biotic stimulus
GO:0010033
0.000317
Response to organic substance
GO:2001243
0.000351
Negative regulation of intrinsic apoptotic signaling pathway
GO:0032637
0.000409
Interleukin-8 production
GO:0006796
0.000414
Phosphate-containing compound metabolic process
GO:0019362
0.000457
Pyridine nucleotide metabolic process
GO:0046496
0.000457
Nicotinamide nucleotide metabolic process
GO:0033554
0.000588
Cellular response to stress
GO:0070488
0.000596
Neutrophil aggregation
KEGG-ID
4380
< 0.0001
Osteoclast differentiation
5150
< 0.0001
Staphylococcus aureus infection
5140
< 0.0001
Leishmaniasis
4610
0.000291
Complement and coagulation cascades
4145
0.000318
Phagosome
4640
0.001751
Hematopoietic cell lineage
5340
0.00454
Primary immunodeficiency
5144
0.005142
Malaria
5145
0.008804
Toxoplasmosis
4670
0.010961
Leukocyte transendothelial migration
5120
0.020107
Epithelial cell signaling in Helicobacter pylori infection
4130
0.026082
SNARE interactions in vesicular transport
910
0.034802
Nitrogen metabolism
5131
0.043143
Shigellosis
4962
0.049527
Vasopressin-regulated water reabsorption
5146
0.050413
Amoebiasis
30
0.052454
Pentose phosphate pathway
4650
0.066291
Natural killer cell mediated cytotoxicity
4060
0.076786
Cytokine–cytokine receptor interaction
4666
0.076955
Fc gamma R-mediated phagocytosis
3410
0.0854
Base excision repair
5014
0.086122
Amyotrophic lateral sclerosis (ALS)
4370
0.092374
VEGF signaling pathway
To investigate the interaction between the proteins encoded by the conserved genes, protein–protein interaction (PPI) network was employed (Fig. 3). Then, further analysis of critical modules by Cytocluster was carried out. 16 key genes such as MAPK14, STAT3, and MAPKAPK2, were found according to the frequency of genes in critical modules their regulation, which was as follow.
Genes
GSE97320 (LogFC)
GSE66360 (LogFC)
MAPK14
1.349924696
0.536455945
STAT3
1.780855138
1.024539916
MAPKAPK2
0.765865504
0.778311524

Validation of the conserved genes using dataset GSE48060

GSE48060 dataset included gene expression profiles of the incident and recurrent MI. Comparison between incident MI and normal control (Comparison 1) revealed 89 DEGs, whereas comparison between recurrent MI and normal control (Comparison 2) showed 392 DEGs (Additional file 1: Table S1 and Table 2). To validate the conserved genes, we overlapped the DEGs of the incident and recurrent MI in GSE48060 and the 477 conserved genes gotten in Comparison 1 and Comparison 2. A total of 29 conserved genes was identified in the overlapping analysis.

Identification of the potential genes related to recurrent MI

To study the differences between primary and recurrent events of MI on gene expression profiling, we overlapped the DEGs in the incident and recurrent MI. In incident MI, 58 specific DEGs were identified (Table 3), accounting for 65% of the whole DEGs. And they were mainly enriched in 104 GO biological processes and 8 KEGG pathways (Additional file 1: Table S1). In recurrent MI, 361 specific genes were identified (Table 4) as 93% of the whole DEGs, and the functional enrichment analysis revealed 108 GO processes and 21 KEGG pathways (Additional file 2: Table S2). We further overlapped the specific genes in recurrent MI and conserved genes and found that RNASE2 and A2M-AS1 were potential genes associated with MI recurrence, the regulation of RNASE2 and A2M-AS1 were 0.629609108 and − 0.936691259.
Table 3
Specific DEGs in incident MI
Specific genes
LogFC
P value
Specific genes
LogFC
P value
LOC400499
0.582246
< 0.0001
ACSL1
0.596533
0.004943
GLT1D1
0.516067
0.000152
INSC
0.461016
0.005675
IL4R
0.53354
0.000156
VNN1
0.579557
0.005783
S100A12
0.870974
0.000159
FCGR1B
0.543697
0.006441
ADM
0.822549
0.000267
FCGR1CP
0.536577
0.006684
SULT1B1
0.565477
0.000335
KLRC2
− 0.59203
0.006728
S100A9
0.555066
0.000392
CYSTM1
0.483289
0.007051
SLPI
0.727612
0.00048
MGAM
0.632329
0.007444
DYSF
0.495236
0.000517
HCAR3
0.526422
0.007467
AQP9
0.623548
0.00055
FOLR3
0.801133
0.007741
NCF4
0.51435
0.000705
LOC100134822
0.482678
0.009538
CR1
0.512093
0.000721
TDRD9
0.549608
0.010174
ANXA3
0.967626
0.000879
FRG1KP
− 0.48373
0.012315
NFE4
0.567447
0.001066
KLRC3
− 0.54028
0.012488
DGAT2
0.477911
0.001101
SLC22A4
0.476108
0.014228
KCNJ15
0.508052
0.001276
TMEM176A
0.465741
0.014307
TXK
− 0.45008
0.001351
FPR2
0.463943
0.014871
SYTL2
− 0.45803
0.001867
NOG
− 0.54482
0.015882
PLBD1
0.512274
0.002083
BCL2A1
0.450316
0.016164
NFIL3
0.573991
0.002206
LRG1
0.505376
0.016586
LMNB1
0.453457
0.002292
MMP9
0.691968
0.023854
FFAR2
0.477117
0.002728
PROK2
0.476171
0.024835
TMEM45A
− 0.63912
0.002983
IL1R2
0.553946
0.029423
PI3
0.61154
0.003202
HSPC102
0.47054
0.033677
DSC2
0.537984
0.003448
LOC107985971
− 0.46157
0.038263
KLRC4
− 0.78034
0.003525
HP
0.529246
0.039574
KRT23
0.606275
0.003532
PFKFB3
0.456526
0.042279
PYGL
0.476712
0.003718
PF4V1
− 0.59584
0.046297
MCEMP1
0.723459
0.004702
HLA-DQA1
− 0.75073
0.048208
Table 4
Specific genes in recurrent MI
Specific genes
LogFC
P value
Specific genes
LogFC
P value
AW029203
− 0.82709
< 0.0001
AW628665
− 0.60526
0.006587
ZNF217
− 0.50883
< 0.0001
CCDC142
− 0.47917
0.006778
AA833902
− 0.67403
< 0.0001
IKBIP
− 0.47796
0.006847
BE552357
− 0.68364
< 0.0001
AA875908
− 0.58822
0.006867
SNAP23
− 0.47426
< 0.0001
CRIM1
− 0.48264
0.006945
AI220134
− 0.46462
< 0.0001
LOC100289230
− 0.46334
0.006947
AK024584
− 1.46739
< 0.0001
HYMAI
− 0.54139
0.007029
AL832672
− 0.70587
< 0.0001
BE219104
− 0.60986
0.007139
H88923
− 0.72215
< 0.0001
HIST1H2AH
− 0.50372
0.007146
PSMA3-AS1
− 0.4581
< 0.0001
AW298171
− 0.47988
0.007146
AK021987
− 0.78158
< 0.0001
LSR
0.455815
0.007277
AA436887
− 0.60722
< 0.0001
TMEM140
− 0.48446
0.007405
RRM2
− 0.53455
< 0.0001
AW771618
− 0.59027
0.007616
CA776505
− 0.76016
0.000117
BC012936
− 0.66788
0.007725
MIR15A
− 0.47975
0.000118
AK024136
− 0.47999
0.007726
BE178502
− 0.6111
0.000129
AW268884
− 0.52578
0.007825
FASLG
− 0.59841
0.000153
AL038450
− 0.53322
0.007986
AL117426
− 0.76868
0.000157
AW291332
− 0.5005
0.00799
AI492388
− 0.99174
0.00016
BQ707256
− 0.55734
0.008015
FOLR1
0.513119
0.000161
AI467945
− 0.60604
0.008019
INAFM2
− 0.62583
0.000165
RHOBTB1
− 0.91345
0.008033
BC043161
− 0.51524
0.000179
FRMD3
− 0.71032
0.008069
RAB27B
− 0.81299
0.000186
AW205919
− 0.46672
0.008619
AA827683
− 0.71156
0.00021
DHRS9
− 0.61396
0.008722
AW452419
− 0.48801
0.000218
AV700081
− 0.74002
0.008968
AL040360
− 0.48226
0.00024
BF509781
− 0.53265
0.009091
LOC100506748
− 0.49388
0.000248
MAP3K7CL
− 0.80885
0.009137
IGF2BP3
− 0.64067
0.000306
AU158247
− 0.53151
0.009175
LINC00877
− 0.50282
0.00031
TNFSF4
− 0.63779
0.00927
STON2
− 0.63358
0.000318
AL036532
− 0.56547
0.009411
BG430958
− 0.83639
0.000335
BE327727
− 0.60652
0.009559
RGS18
− 0.7158
0.00035
AA654772
− 0.4687
0.009566
AW194689
− 0.63151
0.000356
ALDH1A1
− 0.70634
0.009602
AA765387
− 0.63508
0.000363
AW962458
− 0.51864
0.009626
AU158358
− 0.49717
0.000365
PDGFD
− 0.59536
0.009662
AW973253
− 0.80497
0.000382
ZNF304
− 0.6224
0.010013
AW291535
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Discussion

The present study not only identifies conserved genes and dysregulated pathways in MI but also reveals several hub genes, such as MAPK14, STAT3, and MAPKAPK2. Gene expression alterations of the incident and recurrent MI reveals significant differences. RNASE2 and A2M-AS1 were identified as potential genes associated with MI recurrence. Those genes could serve as potential biomarkers for MI occurrence or recurrence prediction and diagnosis.
MAPK14, also known as p38α, is one of the four p38 MAPKs, including α, β, δ, and ε isoforms and is the most abundant isoform in human cardiac tissue [14, 15]. P38 MAPK was first reported to be activated by ischemia/reperfusion (I/R) injury [16]. During myocardial ischemia, MAPK14 is found to contribute to infarction, and short-term intraischemic inhibition of this MAPK14 in the intact heart reduces infarction [17]. However, the effect of p38 MAPK on MI is controversial. Mitra et al. has demonstrated that p38 MAPK actually decreases ischemic load during MI, and plays a dual role in pro-survival as well as cardioprotective during ischemia in the absence of reperfusion [18]. The presented study showed MAPK14 upregulation in MI compared with normal tissue. MAPKAPK2 (MAPK-activated protein kinase 2) gene encodes a member of the Ser/Thr protein kinase family. This kinase is regulated through direct phosphorylation by p38 MAP kinase [19]. Inhibition of p38 MAPK leads to a significant decrease in the phosphorylation status of MAPKAPK2 [18]. In conjunction with p38 MAP kinase, MAPKAPK2 is known to be involved in many cellular processes including stress and inflammatory responses, nuclear export, gene expression regulation and cell proliferation [19]. Heat shock protein HSP27 was shown to be one of the substrates of MAPKAPK2and MAPKAPK2 phosphorylates Akt in neutrophils [20]. The isolated perfused rat heart reveals that global ischemia activates MAPKAPK2, and this activation is maintained during reperfusion [16]. MAPKAPK2 has been regarded as a biomarker in MI early stage and recovery [4]. STAT3 (Signal transducer and activator of transcription 3) is required for myocardial capillary growth, control of interstitial matrix deposition, and heart protection from ischemic injury [21]. STAT3 deficiency causes enhanced susceptibility to myocardial ischemia/reperfusion injury and infarction with increased cardiac apoptosis, increased infarct sizes, and reduced cardiac function and survival [21]. In addition, knockout of STAT3 in mice treated with lipopolysaccharide leads to more cardiac THF production, and fibrosis [22]. Therefore, MAPK14, STAT3, and MAPKAPK2 might be regarded as biomarkers in MI, and the other hub genes are also deserved to be further studies.
Compared to incident cases of MI, recurrent cases of MI experienced more often heart failure, impaired left ventricular ejection fraction, and multivessel disease [23]. In this study, the gene expression profiling between first and recurrent MI showed significant differences, evidenced by that 93% of the whole DEGs in recurrent MI were its specific genes. RNASE2 and A2M-AS1 were regarded as potential genes associated with MI recurrence. RNASE2 gene encodes an enzyme in humans called eosinophil-derived neurotoxin (EDN) [24, 25]. EDN is one of the four major secretory proteins found in the specific granules of the human eosinophilic leukocyte and has been detected in eosinophils, specifically monocytes, and dendritic cells as well as in basophils and neutrophils [26]. EDN was first identified as a neurotoxin, and recent studies suggest that EDN plays a role in antiviral host defense, as a chemoattractant for human dendritic cells, and most recently, as an endogenous ligand for toll-like receptor (TLR) 2 [27]. TLR2 is reported to regulate myocardial ischemia, and sTLR2 may involve in the innate immune response in the pathogenesis of heart failure after acute MI [28]. Thus, we hypothesize that EDN/RNASE2 is likely to be associated with recurrent MI via its direct interactions with TLR2 and dendritic cells. Though little knowledge is available on A2M antisense RNA 1 (A2M-AS1), the relationship between A2M and MI has been reported. The cardiac isoform of A2M (cardiac A2M) is considered as an early marker in cardiac hypertrophy and left ventricular mass in humans. And the further study reveals that cardiac A2M is a valuable marker for the diagnosis of MI diabetic patients and differentiating them from diabetic patients without MI [29]. Thus, the role of A2M-AS1 in recurrent MI need to be further investigated in the future study.

Conclusions

Lacking animal models and cell culture experiment validation are limitations to our study. As an alternative way of validation, here we used GSE48060 dataset to validate the conserved genes. However, further functional experiments are needed to investigate the role of these candidate genes in myocardial infarction though we have reviewed their related functions reported in the previous publication. Meanwhile, the single-nucleotide polymorphism of these candidates may be associated with the risk of heart disease, also deserving for the future investigation. In addition, though myocardial tissues well reflect the characteristics of the injury areas, the blood samples may facilitate clinical diagnosis and treatment via the target genes in the future.

Acknowledgements

Not applicable.
Not applicable.
Not applicable.

Competing interests

The authors declare that they have no competing interests.
Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://​creativecommons.​org/​licenses/​by/​4.​0/​), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://​creativecommons.​org/​publicdomain/​zero/​1.​0/​) applies to the data made available in this article, unless otherwise stated.

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Metadaten
Titel
Identification of key genes involved in myocardial infarction
verfasst von
Linlin Qiu
Xueqing Liu
Publikationsdatum
01.12.2019
Verlag
BioMed Central
Erschienen in
European Journal of Medical Research / Ausgabe 1/2019
Elektronische ISSN: 2047-783X
DOI
https://doi.org/10.1186/s40001-019-0381-x

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