Gene Expression Profiles at Different Time Points after Acute Myocardial Infarction in Mice

doi:10.12116/j.issn.1004-5619.2021.410505

Abstract

Abstract:

Objective To explore the mRNA differential expressions and the sequential change pattern in acute myocardial infarction （AMI） mice. Methods The AMI mice relevant dataset GSE4648 was downloaded from Gene Expression Omnibus （GEO）. In the dataset， 6 left ventricular myocardial tissue samples were selected at 0.25， 1， 4， 12， 24 and 48 h after operation in AMI group and sham control group， and 6 left ventricular myocardial tissue samples were selected in blank control group， a total of 78 samples were analyzed. Differentially expressed genes （DEGs） were analyzed by R/Bioconductor package limma， functional pathway enrichment analysis was performed by clusterProfiler， protein-protein interaction （PPI） network was constructed by STRING database and Cytoscape software， the key genes were identified by Degree topological algorithm， cluster sequential changes on DEGs were analyzed by Mfuzz. Results A total of 1 320 DEGs were associated with the development of AMI. Functional enrichment results included cellular catabolic process， regulation of inflammatory response， development of muscle system and vasculature system， cell adhesion and signaling pathways mainly enriched in mitogen-activated protein kinase （MAPK） signaling pathway. The key genes of AMI included MYL7， TSC22D2， HSPA1A， BTG2， NR4A1， RYR2 were up-regulated or down-regulated at 0.25-48 h after the occurrence of AMI. Conclusion The functional signaling pathway of DEGs and the sequential expression of key genes in AMI may provide a reference for the forensic identification of AMI.

Key words: forensic pathology, bioinformatics, acute myocardial infarction, differentially expressed genes, sequential expression, mice

CLC Number:

DF795.1

Hao LI, Xiao JIA, Ya-qin BAI, Peng WU, Hua-lin GUO, Ke-ming YUN, Cai-rong GAO, Xiang-jie GUO. Gene Expression Profiles at Different Time Points after Acute Myocardial Infarction in Mice[J]. Journal of Forensic Medicine, 2022, 38(3): 343-349.

Figures/Tables 8

Fig. 1 The expression changes of DEG at different time points

Tab. 1 The number of differentially expressed gene at different time points after the ligations of left anterior decending coronary artery

时间点/h	上调	下调	合计
0.25	1	1	2
1	22	5	27
4	37	2	39
12	201	16	217
24	484	84	568
48	404	63	467

Fig. 2 The GO enrichment analysis of differentially expressed genes at different time points

Fig. 3 The KEGG enrichment analysis of differentially expressed genes at different time points

Fig. 4 The co-expression and interaction network of key genes

Fig. 5 The Venn diagram of the intersection of differentially expressed genes at different time points

Tab. 2 The post-AMI sequential expression of TSC22D2， NR4A1，MYL7， HSPA1A and BTG2

基因	0.25 h	1 h	4 h	12 h	24 h	48 h
TSC22D2	-	1.009 7	1.077 1	1.184 8	1.606 2	1.493 4
NR4A1	-	1.159 9	1.686 5	1.314 9	-	-
MYL7	-2.462 7	-3.086 4	-3.200 8	-3.113 9	-	-
HSPA1A	-	1.581 5	3.082 3	5.334 3	4.713 0	-
BTG2	-	1.149 4	1.265 9	1.397 0	-	-
RYR2	-	1.056 8	1.014 6	-	-	-

Fig. 6 The sequential expression of post-AMI of different expressed genes at 12 h， 24 h and 48 h

References 22

1	JENNINGS R B， GANOTE C E. Structural changes in myocardium during acute ischemia[J]. Circ Res，1974，35（S3）：156-172.
2	MICHAUD K， BASSO C， D’AMATI G， et al. Diagnosis of myocardial infarction at autopsy： AECVP reappraisal in the light of the current clinical classification[J]. Virchows Arch，2020，476（2）：179-194. doi：10.1007/s00428-019-02662-1 .
3	LORENZON DOS SANTOS J， SCHAAN DE QUADROS A， WESCHENFELDER C， et al. Oxidative stress biomarkers， nut-related antioxidants， and cardiovascular disease[J]. Nutrients，2020，12（3）：682. doi：10.3390/nu12030682 .
4	HARPSTER M H， BANDYOPADHYAY S， THOMAS D P， et al. Earliest changes in the left ventricular transcriptome post-myocardial infarction[J]. Mamm Genome，2006，17（7）：701-715. doi：10.1007/s00335-005-0120-1 .
5	THYGESEN K， ALPERT J S， JAFFE A S， et al. Fourth universal definition of myocardial infarction （2018）[J]. Eur Heart J，2018，40（3）：237-269. doi：10.1093/eurheartj/ehy462 .
6	郑大，殷坤，郑晶晶，等. 心脏性猝死的法医学研究进展[J].法医学杂志，2017，33（5）：457-469. doi：10.3969/j.issn.1004-5619.2017.05.002 .
	ZHENG D， YIN K， ZHENG J J， et al. Research progress of sudden cardiac death in forensic medicine[J]. Fayixue Zazhi，2017，33（5）：457-469.
7	MYERBURG R J， JUNTTILA M J. Sudden cardiac death caused by coronary heart disease[J]. Circulation，2012，125（8）：1043-1052. doi：10.1161/CIRCULATIONAHA.111.023846 .
8	MUSLIN A J. MAPK signalling in cardiovascular health and disease： Molecular mechanisms and therapeutic targets[J]. Clin Sci，2008，115（7）：203-218. doi：10.1042/CS20070430 .
9	WANG Q L， QU X Q， ZHENG L， et al. Atorvastatin improves cardiac function of mice with acute myocardial infarction by interfering in macrophages to activate mitogen-activated protein kinase pathway[J]. Panminerva Med，2021，63（2）：236-237. doi：10.23736/S0031-0808.19.03680-2 .
10	SURESH R， LI X， CHIRIAC A， et al. Transcriptome from circulating cells suggests dysregulated pathways associated with long-term recurrent events following first-time myocardial infarction[J]. J Mol Cell Cardiol，2014，74：13-21. doi：10.1016/j.yjmcc. 2014.04.017 .
11	NEWMAN M S， NGUYEN T， WATSON M J， et al. Transcriptome profiling reveals novel BMI- and sex-specific gene expression signatures for human cardiac hypertrophy[J]. Physiol Genom，2017，49（7）：355-367. doi：10.1152/physiolgenomics.00122.2016 .
12	KATUS H A， DIEDERICH K W， UELLNER M， et al. Myosin light chains release in acute myocardial infarction： Non-invasive estimation of infarct size[J]. Cardiovasc Res，1988，22（7）：456-463. doi：10.1093/cvr/22.7.456 .
13	ISOBE M， NAGAI R， UEDA S， et al. Quantitative relationship between left ventricular function and serum cardiac myosin light chain I levels after coronary reperfusion in patients with acute myocardial infarction[J]. Circulation，1987，76（6）：1251-1261. doi：10.1161/01.cir.76.6.1251 .
14	LIANG F， LI Q， LI X Y， et al. TSC22D2 interacts with PKM2 and inhibits cell growth in colorectal cancer[J]. Int J Oncol，2016，49（3）：1046-1056. doi：10.3892/ijo.2016.3599 .
15	XIAO L， WEI F， LIANG F， et al. TSC22D2 identified as a candidate susceptibility gene of multi-cancer pedigree using genome-wide linkage analysis and whole-exome sequencing[J]. Carcinogenesis，2019，40（7）：819-827. doi：10.1093/carcin/bgz095 .
16	HOOGSTRA-BERENDS F， MEIJERING R A M， ZHANG D L， et al. Heat shock protein-inducing compounds as therapeutics to restore proteostasis in atrial fibrillation[J]. Trends Cardiovasc Med，2012，22（3）：62-68. doi：10.1016/j.tcm.2012.06.013 .
17	ROY S， KHANNA S， KUHN D E， et al. Transcriptome analysis of the ischemia-reperfused remode-ling myocardium： Temporal changes in inflammation and extracellular matrix[J]. Physiol Genom，2006，25（3）：364-374. doi：10.1152/physiolgenomics.00013.2006 .
18	YUNIATI L， SCHEIJEN B， VAN DER MEER L T， et al. Tumor suppressors BTG1 and BTG2： Beyond growth control[J]. J Cell Physiol，2019，234（5）：5379-5389. doi：10.1002/jcp.27407 .
19	HU D X， GU Y， WU D， et al. Icariside II protects cardiomyocytes from hypoxia‑induced injury by upregulating the miR‑7‑5p/BTG2 axis and activating the PI3K/Akt signaling pathway[J]. Int J Mol Med，2020，46（4）：1453-1465. doi：10.3892/ijmm.2020.4677 .
20	LEE S O， LI X， KHAN S， et al. Targeting NR4A1 （TR3） in cancer cells and tumors[J]. Expert Opin Ther Targets，2011，15（2）：195-206. doi：10.1517/14728222.2011.547481 .
21	HILGENDORF I， GERHARDT L M S， TAN T C， et al. Ly-6Chigh monocytes depend on Nr4a1 to balance both inflammatory and reparative phases in the infarcted myocardium[J]. Circ Res，2014，114（10）：1611-1622. doi：10.1161/CIRCRESAHA.114.303204 .
22	MEISSNER G. The structural basis of ryanodine receptor ion channel function[J]. J Gen Physiol，2017，149（12）：1065-1089. doi：10.1085/jgp.201711878 .

[1]	Yong ZENG, Dong-hua ZOU, Ying FAN, Qing XU, Lu-yang TAO, Yi-jiu CHEN, Zheng-dong LI. Research Progress and Forensic Application of Human Vascular Finite Element Modeling and Biomechanics [J]. Journal of Forensic Medicine, 2023, 39(5): 471-477.
[2]	Yu-xin SUN, Xiao-juan GONG, Xiu-li HAO, Yu-xin TIAN, Yi-ming CHEN, Bao ZHANG, Chun-xia YAN. Screening of Genes Co-Associated with Sudden Infant Death Syndrome and Infectious Sudden Death in Infancy and Bioinformatics Analysis of Their Regulatory Networks [J]. Journal of Forensic Medicine, 2023, 39(5): 433-440.
[3]	Yu YANG, Fan-zhang LEI, Yu-you DONG, Jian-long MA, Qi-qiang SHI, Xue-song YE. Retrospective Analysis of Death Cases of Oral Diphenidol Hydrochloride Poisoning [J]. Journal of Forensic Medicine, 2023, 39(4): 393-398.
[4]	Qing-qing XIANG, Li-fang CHEN, Qin SU, Yu-kun DU, Pei-yan LIANG, Xiao-dong KANG, He SHI, Qu-yi XU, Jian ZHAO, Chao LIU, Xiao-hui CHEN. Research Progress on Microbial Community Succession in the Postmortem Interval Estimation [J]. Journal of Forensic Medicine, 2023, 39(4): 399-405.
[5]	Qin SU, Qian-ling CHEN, Wei-bin WU, Qing-qing XIANG, Cheng-liang YANG, Dong-fang QIAO, Zhi-gang LI. Metabonomics Analysis of Brain Stem Tissue in Rats with Primary Brain Stem Injury Caused Death [J]. Journal of Forensic Medicine, 2023, 39(4): 373-381.
[6]	Xu-dong ZHANG, Yao-ru JIANG, Xin-rui LIANG, Tian TIAN, Qian-qian JIN, Xiao-hong ZHANG, Jie CAO, Qiu-xiang DU, Jun-hong SUN. Postmortem Interval Estimation Using Protein Chip Technology Combined with Multivariate Analysis Methods [J]. Journal of Forensic Medicine, 2023, 39(2): 115-120.
[7]	Wu LONG, Peng-fei QU, Lin MA, Rui WANG, Yan-mei XI, Yu-hua LI, Sheng-jie NIE, Ting DUAN, Jin-liang DU, Xue TANG, Jing-feng ZHAO, Pu-ping LEI, Yue-bing WANG. Cytotoxicity of 4 Wild Mushrooms in a Case of Yunnan Sudden Unexplained Death [J]. Journal of Forensic Medicine, 2023, 39(2): 121-128.
[8]	Jun-wei GAO, Yang LU, Yan-jun LI, Dong-hua ZOU, Guang-long HE, Yan-bin WANG. Survey on the Construction Status of Forensic Virtual Autopsy Laboratory and the Applicability of Laboratory Accreditation [J]. Journal of Forensic Medicine, 2023, 39(2): 186-192.
[9]	Fang-Fang LIU, Hui WU, Wei WANG, Ying XIE. Changes of 1，5-AG in Vitreous Humor of Rabbit Cadavers with Hyperglycemic Metabolism [J]. Journal of Forensic Medicine, 2023, 39(1): 13-17.
[10]	Zhi-ling TIAN, Ruo-lin WANG, Jian-hua ZHANG, Ping HUANG, Zhi-qiang QIN, Zheng-dong LI, He-wen DONG, Dong-hua ZOU, Mao-wen WANG, Zhuo LI, Lei WAN, Xiao-tian YU, Ning-guo LIU. Comparison of CT Values between Thrombus and Postmortem Clot Based on Cadaveric Pulmonary Angiography [J]. Journal of Forensic Medicine, 2023, 39(1): 7-12.
[11]	Jia-yi WU, You-jia YU, Kai LI, Xin YIN, Han-ting FAN, Rong LI, Zhi-wei ZHANG, Wei TANG, Hui-jie HUANG, Feng CHEN. Report on Cardiac Gross Pathologic Measurements of Sudden Cardiac Death in Adults [J]. Journal of Forensic Medicine, 2023, 39(1): 1-6.
[12]	Hui WU, Fang-fang LIU, Jun-da WU, Ying XIE. Research Progress on Estimation of Postmortem Interval Based on Ocular Tissues Structure [J]. Journal of Forensic Medicine, 2023, 39(1): 50-56.
[13]	Tian-pu WU, Jian-long MA, Xin-biao LIAO, Dong-chuan ZHANG, Kai-jun MA, Yan-geng YU, Long CHEN. Research Progress on Molecular Changes in Pulmonary Hypoxia and Cause of Death Identification in Mechanical Asphyxia [J]. Journal of Forensic Medicine, 2023, 39(1): 57-65.
[14]	Yu-qing JIA, Tian-qi WANG, Rui ZHAO, Bao-li ZHU, Zhi-peng CAO. Effects of Postmortem Hemolysis and Ultrafiltration on Creatinine Detection Results [J]. Journal of Forensic Medicine, 2022, 38(6): 697-701.
[15]	Lan YANG, Xin WANG, Yong NIU. Research Progress of DNA-Based Technologies for Postmortem Interval Estimation [J]. Journal of Forensic Medicine, 2022, 38(6): 747-753.