Comprehensive Analysis of miRNA-mRNA Regulatory Network And Potential Drugs In Chronic Chagasic Cardiomyopathy Across Human And Mouse

Abstract

Background: Chronic chagasic cardiomyopathy (CCC) is the leading cause of heart failure in Latin America and often causes severe inflammation and fibrosis in the heart. Studies on myocardial function and its molecular mechanisms in patients with Chronic chagasic cardiomyopathy are very limited. In order to understand the development and progression of Chronic chagasic cardiomyopathy and find targets for its diagnosis and treatment, the field needs to better understand the exact molecular mechanisms involved in these processes.

Methods: The mRNA microarray datasets GSE84796 (human) and GSE24088 (mouse) were obtained from the Gene Expression Omnibus (GEO) database. Homologous genes between the two species were identified using the online database mining tool Biomart, followed by differential expression analysis, gene enrichment analysis and protein-protein interaction (PPI) network construction. Cytohubba plug-in of Cytoscape software was used to identify Hub gene, and miRNet was used to construct the corresponding miRNA-mRNA regulatory network. Furthermore, Comparative Toxicogenomics Database (CTD) was used to identify hub gene-related drugs.

Results: A total of 86 homologous genes were significantly differentially expressed in the two datasets, including 73 genes with high expression and 13 genes with low expression. These differentially expressed genes were mainly enriched in the terms of innate immune response, signal transduction, protein binding, Natural killer cell mediated cytotoxicity, Tuberculosis, Chemokine signaling pathway, Chagas disease and PI3K−Akt signaling pathway. The top 10 hub genes LAPTM5, LCP1, HCLS1, CORO1A, CD48, TYROBP, RAC2, ARHGDIB, FERMT3 and NCF4 were identified from the PPI network. A total of 122 miRNAs were identified to target these hub genes and 30 of them regulated two or more hub genes at the same time. Finally, 49 drugs, such as Gentamicins, acetamide, Isotretinoin, Nimesulide, Oxyquinoline, Quercetin and Resveratrol were identified to target these hub genes.

Conclusions: In this study, the potential genes associated with Chronic chagasic cardiomyopathy are identified and a miRNA-mRNA regulatory network is constructed. This study explores the molecular mechanisms of Chronic chagasic cardiomyopathy and provides important clues for finding new therapeutic targets.

Introduction

Chronic Chagasic Cardiomyopathy (CCC), first reported by Carlos Chagas in 1909, is a myocardial disease caused by a protozoan parasite, Trypanosoma cruzi[1, 2]. CCC is characterized by severe cardiac inflammation and myocardial fibrosis and is the leading cause of myocardial diseases and heart failure in Latin America [3]. The incidence of CCC has declined as living conditions have improved, but the current trend of people moving from rural to urban areas complicates the situation[4]. Studies have shown that chagas disease still affects 6 to 8 million people and kills about 12,000 people a year[5] and the positive rate of T. cruzi in serum of Latin American immigrants with non-ischemic cardiomyopathy in the United States ranges from 13–19%[6].

CCC often causes symptoms of palpitations or syncope from arrhythmia, chest pain from microvascular dysfunction and heart failure from left ventricular dysfunction.

The pathogenesis of chronic chagas cardiomyopathy is very complex. At present, there are four hypotheses: direct injury caused by parasites[7], inflammatory reaction[8], microvascular injury[9] and autonomic nerve dysfunction[10]. Patients eventually died of malignant arrhythmia (55%-65%) in early adulthood, mainly because persistent ventricular tachycardia (VT) degenerated into ventricular fibrillation[11]. There are many studies on CCC, but there is still no effective treatment at present, and the prognosis of chagas cardiomyopathy is very poor.

Animal models of CCC, especially mouse models, have attracted researchers' attention due to the high homologous and identity of human and mouse genome[12, 13]. The research on the similarity of the molecular characteristics of human and mouse diseases has led to the rapid development of disease prognosis and treatment. Studies have shown that RARP1 plays an important role in CCC, which leads to the increase of mtROS and oxidative stress in chagasic myocardium through the decrease of Pol γ-dependent mtDNA content, mtDNA coding gene expression and mitochondrial respiratory function[14]. This indicates that RARP1 may be an important therapeutic target of CCC. Furthermore, TGF-β inhibitor therapy can decreases fibrosis and stimulates cardiac improvement in CCC[15]. The dysregulation of microRNAs (miRNAs), including: miR-19a-3p, miR-21-5p, miR29b-3p, miR-21, miR-146 are reported to be related with CCC development[16–18]. However, the identity of miRNA-mRNA regulations in CCC had not been reported till now.

This study was performed to identify the co-differently expressed miRNA-mRNA regulatory networks and developmental programs in CCC between human and mouse. The GSE84796 and GSE24088 datasets were downloaded and homologous genes between human and mouse CCC models were identified and analyzed using bioinformatics analyses. Our study would provide new insights of molecular mechanisms involved CCC, aiming to understand the development and progression of CCC and find targets for its diagnosis and treatment. The workflow of the specific analysis is shown in Fig. 1.

Methods

Results

Discussion

CCC is an inflammatory dilated cardiomyopathy caused by a protozoan parasite, Trypanosoma cruzi [32]. In the past hundred years, a large number of studies have been conducted on CCC. However, the research on the molecular mechanism of CCC and the effective treatment methods are very limited. We use bioinformatics method to conduct data mining on CCC-related datasets, extract relevant biological information from high-dimensional data, and find the key pathways and hub genes that affect CCC occurrence. This method is the new trend of precision medical era disease research. These identified molecules have the potential to be used as disease biomarkers for patient-specific treatment and to improve the diagnosis, treatment, and prevention of CCC.

In the present study, we screened 86 Homologous genes including 73 upregulated and 13 downregulated genes which were significantly differentially expressed in the two datasets across human and mouse. GO and KEGG pathway enrichment analysis showed that these Homologous DEGs were significantly enriched in immune-related functions and pathways. These genes functions in immune-related biological processes such as innate immune response, leukocyte migration, signal transduction, adaptive immune response, phagocytic vesicle membrane, Toll − like receptor binding and protein binding. Furthermore, these Homologous DEGs are involved in Natural killer cell mediated cytotoxicity, Leukocyte transendothelial migration, Chemokine signaling pathway, PI3K − Akt signaling pathway and Chagas disease (American trypanosomiasis). The PPI network of these Homologous DEGs was analyzed by String and Visualized by Cytoscape software. Based on analyzing of this network, 10 hub genes, LAPTM5, LCP1, HCLS1, CORO1A, CD48, TYROBP, RAC2, ARHGDIB, FERMT3 and NCF4 were identified. These genes are enriched in the pathway of Natural killer cell mediated cytotoxicity.

Several studies had been published about Natural killer cell mediated cytotoxicity pathway in CCC. Killer cell-mediated parasite death, which known as "microbiological programmed cell death" is similar to mammalian apoptosis and results in membrane potential decomposition, vesiculation, phospholipserine exposure, mitochondrial swelling, chromatin condensation, and DNA damage. Antimicrobial peptide granulysin (GNLY), pore-forming perforin (PFN) and granzyme (GZM) can eliminate intracellular protozoan parasites by Natural killer cell mediated cytotoxicity pathway [33]. It has been shown that infection with a virulent T. cruzi strain alters NK cell-mediated regulation of adaptive immune responses induced by DC cells[34]. Therefore, by intervening in this pathway, it is possible to eliminate pathogens infected cells and delay the progression of CCC. What’s more, Leukocyte transendothelial migration[35], Chemokine signaling pathway[36] and PI3K − Akt signaling pathway[37] may also be key pathways to the regulation of CCC.

As for hub genes, many studies have linked them to cardiomyopathy. For example, a genome-wide association study identifies the functional relationships between the associated variant and FERMT3 (Fermitin family homolog 3) in CCC[38]. TYROBP (TYRO protein tyrosine kinase-binding protein) shows significant increasing expression levels in model HCM (Hypertrophic cardiomyopathy) rats and affected the immune system significantly[39]. NCF4 (Neutrophil cytosol factor 4) is the component of the NADPH-oxidase. RAC2 (Ras-related C3 botulinum toxin substrate 2) can augment the production of reactive oxygen species (ROS) by NADPH oxidase. L7DG (luteolin-7-diglucuronide) pretreatment can block ISO-stimulated expression of the NCF4 and RAC2, protecting the heart against developing ISO-induced injury and fibrosis[40]. CD48 is the ligand of CD2, may facilitate interaction between activated lymphocytes and involve in regulating T-cell activation[41]. LCP1 (L-plastin, also known as plastin-2) binds to αMβ2 integrin and maintains its inactivity, thus regulating leukocyte adhesion to integrin ligand in the flow state[42]. These studies suggest that these hub genes are involved in the process of inflammatory response and myocardial remodeling and may play an important role in the development of CCC.

miRNAs are endogenous approximately 23nt RNAs that pairing with mRNAs of protein-coding genes to guide their post-transcriptional suppression[43]. These hub genes have reported to be a direct target of several miRNAs including miR-125a-5p[44], miR-375[45], miR-125[46],miR-183[47]. Based on these hub genes, miRNAs (such as hsa-miR-34a-5p, hsa-miR-30d-5p, hsa-miR-27a-3p, hsa-miR-24-3p, hsa-miR-203a-3p, hsa-miR-16-5p, hsa-miR-155-5p, hsa-miR-1-3p, hsa-miR-129-2-3p and hsa-miR-124-3p) that may regulate CCC were predicted by miRNet tool. Many studies have linked these miRNAs to cardiomyopathy. Inhibition of miR-34a in mice attenuates moderate cardiac dysfunction by inhibiting atrial expandatrial enlargement[48]. miR-30 participates in ventricular remodeling through autophagy, apoptosis, oxidative stress and inflammation[49]. Mir-24-3p regulates KEAR1-NRF2 pathway and protects myocardial cells after ischemia/reperfusion injury in mice[50]. These results demonstrated the potential roles of these miRNAs in regulating inflammation and fibrosis of the heart in CCC.

At present, Bennidazole or nifurtimox is the main treatment for Chagas’ disease. However, there is currently no effective treatment for CCC. A total of 50 Drugs (such as Gentamicins, acetamide, Isotretinoin, nimesulide, Oxyquinoline, Quercetin and Resveratrol) that may regulate CCC were predicted by CTD database. These drugs can protect the heart by regulating inflammation, autophagy, apoptosis and other pathways[51–53]. These drugs can serve as a starting point for follow-up studies.

The analysis of high differentially expressed homologous genes in human and mouse is helpful to understand the common characteristics and pathogenesis of CCC among species. Further experiments to verify the functions of these genes will give a more realistic picture of what happens in the human body. However, this study is based on published datasets and has some limitations. Further in vivo and in vitro studies, as well as large sample multicenter clinical studies, are required to explore better diagnostic and therapeutic methods for CCC.

Conclusions

In conclusion, we identified there were 86 homologous DEGs in CCC between human and mouse. Bioinformatics analyses showed 122 miRNAs and 10 hub genes were associated with CCC pathogenesis via “Natural killer cell mediated cytotoxicity, Chemokine signaling pathway, Chagas disease and PI3K − Akt signaling pathway” pathways. A total of 49 drugs were predicted and may be candidates for the treatment of CCC. However, the present study is a preliminary analysis, and further studies, both in vivo and in vitro, are needed to confirm these insights.

Abbreviations

CCC Chronic Chagasic Cardiomyopathy

GEO database Gene Expression Omnibus database.

DEG Differently expressed genes

GO Gene Ontology

BP Biological process

CC Cellular component

MF Molecular function

KEGG Kyoto Encyclopedia of Genes and Genomes

DAVID Database for Annotation, Visualization, and Integrated Discovery

PPI network Protein-Protein interaction network

MCC Maximal Clique Centrality

CTD Comparative Toxicogenomics Database

NC Natural killer

DC Dendritic cells

GNLY Granulysin

PFN Pore-forming perforin

GZM Granzyme

HCM Hypertrophic cardiomyopathy

Declarations

Ethical approval and consent to participate

This article does not contain any studies with human participants or animals performed by any of the authors. Therefore, ethical approval and informed consent are not required.

Consent for publication

Not applicable.

Availability of data and materials

The following information was supplied regarding data availability: Data is available at NCBI GEO: GSE84796 and GSE24088 

Competing interests

The authors declare that they have no conflicts of interest.

Funding

This study was supported by a grant from The National Natural Science foundation of China (No.81370308, Xiaorong Hu) and a grant from Zhongnan Hospital of Wuhan University Science, Technology and Innovation Seed Fund (N0. znpy2018099, Xiaorong Hu) and the research fund from medical Sci-Tech innovation platform of Zhongnan Hospital, Wuhan University (No. ptxm2021009, Jianlei Cao)

Authors' Contributions

Jiahe Wu performed the data analysis and drafted the manuscript.

Yongzhen Fan and Chenze Li prepared the figures and contributed towards the study design.

Xiaorong Hu and Jianlei Cao revised the figures, designed and supervised the study.

All authors have read and approved the final manuscript.        

Acknowledgments

We sincerely appreciate the researchers for providing their GEO database information online, we are truly honored to acknowledge their contributions.

Online Database address:

Gene Expression Omnibus (GEO) database. (https://www.ncbi.nlm.nih.gov/)

Biomart (v2.3.6; https://bioconductor.org/packages/release/bioc/html/biomaRt.html)

Venn diagram web tool (http://bioinformatics.psb.ugent.be/webtools/Venn/)

Gene Ontology (GO; http://www.geneontology.org) 

KEGG (http://www.kegg.jp/orhttp://www.genome.jp/kegg/)

DAVID (version6.8; https://david.ncifcrf.gov)

String database (version10.0; http://string-db.org)

KOBAS (version 3.0; http://kobas.cbi.pku.edu.cn/)

miRNet (https://www.mirnet.ca)

CTD (http://ctdbase.org/)

miRDB ( http://mirdb.org)

Targetscan (version7.2; http://targetscan.org)

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