Association of Circulating, Inflammatory-Response Exosomal mRNAs With Acute Myocardial Infarction

Circulating extracellular vesicles as biomarkers in the diagnosis, prognosis and therapy of cardiovascular diseases

Cardiovascular disease (CVD) ranks among the primary contributors to worldwide mortality. Hence, the importance of constant research on new circulating biomarkers for the improvement of early diagnosis and prognostication of different CVDs and the development and refinement of therapeutic measures is critical. Extracellular vesicles (EV) have a great potential as diagnostic and prognostic markers, as they represent their parent cell by enclosing cell-specific molecules, which can differ in quality and quantity based on cell state. Assuming that all cell types of the cardiovascular system are capable of releasing EV into circulation, an emerging body of evidence has investigated the potential role of serum- or plasma-derived EV in CVD. Comprehensive research has unveiled alterations in EV quantity and EV-bound cargo in the form of RNA, proteins and lipids in the context of common CVDs such as coronary artery disease, atrial fibrillation, heart failure or inflammatory heart diseases, highlighting their diagnostic and prognostic relevance. In numerous in vitro and in vivo models, EV also showed promising therapeutic potential. However, translation of EV studies to a preclinical or clinical setting has proven to be challenging. This review is intended to provide an overview of the most relevant studies in the field of serum or plasma-derived EV.

Detecting early-warning biomarkers associated with heart-exosome genetic-signature for acute myocardial infarction: A source-tracking study of exosome

The genetic information of plasma total-exosomes originating from tissues have already proven useful to assess the severity of coronary artery diseases (CAD). However, plasma total-exosomes include multiple sub-populations secreted by various tissues. Only analysing the genetic information of plasma total-exosomes is perturbed by exosomes derived from other organs except the heart. We aim to detect early-warning biomarkers associated with heart-exosome genetic-signatures for acute myocardial infarction (AMI) by a source-tracking analysis of plasma exosome. The source-tracking of AMI plasma total-exosomes was implemented by deconvolution algorithm. The final early-warning biomarkers associated with heart-exosome genetic-signatures for AMI was identified by integration with single-cell sequencing, weighted gene correction network and machine learning analyses. The correlation between biomarkers and clinical indicators was validated in impatient cohort. A nomogram was generated using early-warning biomarkers for predicting the CAD progression. The molecular subtypes landscape of AMI was detected by consensus clustering. A higher fraction of exosomes derived from spleen and blood cells was revealed in plasma exosomes, while a lower fraction of heart-exosomes was detected. The gene ontology revealed that heart-exosomes genetic-signatures was associated with the heart development, cardiac function and cardiac response to stress. We ultimately identified three genes associated with heart-exosomes defining early-warning biomarkers for AMI. The early-warning biomarkers mediated molecular clusters presented heterogeneous metabolism preference in AMI. Our study introduced three early-warning biomarkers associated with heart-exosome genetic-signatures, which reflected the genetic information of heart-exosomes carrying AMI signals and provided new insights for exosomes research in CAD progression and prevention.

Identification of immune-related biomarkers co-occurring in acute ischemic stroke and acute myocardial infarction

Background

Acute ischemic stroke (AIS) and acute myocardial infarction (AMI) share several features on multiple levels. These two events may occur in conjunction or in rapid succession, and the occurrence of one event may increase the risk of the other. Owing to their similar pathophysiologies, we aimed to identify immune-related biomarkers common to AIS and AMI as potential therapeutic targets.

Methods

We identified differentially expressed genes (DEGs) between the AIS and control groups, as well as AMI and control groups using microarray data (GSE16561 and GSE123342). A weighted gene co-expression network analysis (WGCNA) approach was used to identify hub genes associated with AIS and/or AMI progression. The intersection of the four gene sets identified key genes, which were subjected to functional enrichment and protein-protein interaction (PPI) network analyses. We confirmed the expression levels of hub genes using two sets of gene expression profiles (GSE58294 and GSE66360), and the ability of the genes to distinguish patients with AIS and/or AMI from control patients was assessed by calculating the receiver operating characteristic values. Finally, the investigation of transcription factor (TF)-, miRNA-, and drug-gene interactions led to the discovery of therapeutic candidates.

Results

We identified 477 and 440 DEGs between the AIS and control groups and between the AMI and control groups, respectively. Using WGCNA, 2,776 and 2,811 genes in the key modules were identified for AIS and AMI, respectively. Sixty key genes were obtained from the intersection of the four gene sets, which were used to identify the 10 hub genes with the highest connection scores through PPI network analysis. Functional enrichment analysis revealed that the key genes were primarily involved in immunity-related processes. Finally, the upregulation of five hub genes was confirmed using two other datasets, and immune infiltration analysis revealed their correlation with certain immune cells. Regulatory network analyses indicated that GATA2 and hsa-mir-27a-3p might be important regulators of these genes.

Conclusion

Using comprehensive bioinformatics analyses, we identified five immune-related biomarkers that significantly contributed to the pathophysiological mechanisms of both AIS and AMI. These biomarkers can be used to monitor and prevent AIS after AMI, or vice versa.

Bioinformatic analysis of underlying mechanisms of Kawasaki disease via Weighted Gene Correlation Network Analysis (WGCNA) and the Least Absolute Shrinkage and Selection Operator method (LASSO) regression model

BACKGROUND

Kawasaki disease (KD) is a febrile systemic vasculitis involvingchildren younger than five years old. However, the specific biomarkers and precise mechanisms of this disease are not fully understood, which can delay the best treatment time, hence, this study aimed to detect the potential biomarkers and pathophysiological process of KD through bioinformatic analysis.

METHODS

The Gene Expression Omnibus database (GEO) was the source of the RNA sequencing data from KD patients. Differential expressed genes (DEGs) were screened between KD patients and healthy controls (HCs) with the "limma" R package. Weighted gene correlation network analysis (WGCNA) was performed to discover the most corresponding module and hub genes of KD. The node genes were obtained by the combination of the least absolute shrinkage and selection operator (LASSO) regression model with the top 5 genes from five algorithms in CytoHubba, which were further validated with the receiver operating characteristic curve (ROC curve). CIBERSORTx was employed to discover the constitution of immune cells in KDs and HCs. Functional enrichment analysis was performed to understand the biological implications of the modular genes. Finally, competing endogenous RNAs (ceRNA) networks of node genes were predicted using online databases.

RESULTS

A total of 267 DEGs were analyzed between 153 KD patients and 92 HCs in the training set, spanning two modules according to WGCNA. The turquoise module was identified as the hub module, which was mainly enriched in cell activation involved in immune response, myeloid leukocyte activation, myeloid leukocyte mediated immunity, secretion and leukocyte mediated immunity biological processes; included type II diabetes mellitus, nicotinate and nicotinamide metabolism, O-glycan biosynthesis, glycerolipid and glutathione metabolism pathways. The node genes included ADM, ALPL, HK3, MMP9 and S100A12, and there was good performance in the validation studies. Immune cell infiltration analysis revealed that gamma delta T cells, monocytes, M0 macrophage, activated dendritic cells, activated mast cells and neutrophils were elevated in KD patients. Regarding the ceRNA networks, three intact networks were constructed: NEAT1/NORAD/XIST-hsa-miR-524-5p-ADM, NEAT1/NORAD/XIST-hsa-miR-204-5p-ALPL, NEAT1/NORAD/XIST-hsa-miR-524-5p/hsa-miR-204-5p-MMP9.

CONCLUSION

To conclude, the five-gene signature and three ceRNA networks constructed in our study are of great value in the early diagnosis of KD and might help to elucidate our understanding of KD at the RNA regulatory level.

Expression Profiles and Functional Analysis of Plasma Exosomal Circular RNAs in Acute Myocardial Infarction

Acute myocardial infarction (AMI) is a common cardiovascular disease with high rates of morbidity and mortality globally. The dysregulation of circular RNAs (circRNAs) has been shown to be closely related to various pathological aspects of AMI. However, the function of exosomal circRNAs in AMI has yet to be investigated. The purpose of this study was to investigate the expression profiles of plasma exosomal circRNAs in AMI and explore their potential functionality. The expression profiles of plasma exosomal circRNAs in patients with AMI, stable coronary heart atherosclerotic disease (CAD), and healthy controls were obtained from a GEO expression dataset (GSE159657). We also analyzed bioinformatics functionality, potential pathways, and interaction networks related to the microRNAs associated with the differentially expressed circRNAs. A total of 253 exosomal circRNAs (184 up- and 69 down-regulated) and 182 exosomal circRNAs (94 up- and 88 down-regulated) were identified as being differentially expressed between the control group and the AMI and CAD patients, respectively. Compared with the CAD group, 231 different exosomal circRNAs (177 up- and 54 down-regulated) were identified in the AMI group. Functional analysis suggested that the parental genes of exosomal has_circ_0061776 were significantly enriched in the biological process of lysine degradation. Pathway interaction network analysis further indicated that exosomal has_circ_0061776 was associated with has-miR-133a, has-miR-214, has-miR-423, and has-miR-217 and may play a role in the pathogenesis of AMI through the MAPK signaling pathway. This study identified the differential expression and functionality of exosomal circRNAs in AMI and provided further understanding of the potential pathogenesis of an exosomal circRNA-related competing endogenous RNA (ceRNA) network in AMI.

m6A regulator-mediated RNA methylation modification patterns are involved in immune microenvironment regulation of coronary heart disease

Background

Although the roles of m6A modification in the immune responses to human diseases have been increasingly revealed, their roles in immune microenvironment regulation in coronary heart disease (CHD) are poorly understood.

Methods

The GSE20680 and GSE20681 datasets related to CHD were acquired from the Gene Expression Omnibus (GEO) database. A total of 30 m6A regulators were used to perform LASSO regression to identify the significant genes involved in CHD. Unsupervised clustering analysis was conducted using the m6A regulators to distinguish the m6A RNA methylation patterns in patients with CHD. The differentially expressed genes (DEGs) and biological characteristics, including GO and KEGG enrichment results, were assessed for the different m6A patterns to analyse the impacts of m6A regulators on CHD. Hub genes were identified, and subsequent microRNAs-mRNAs (miRNAs–mRNAs) and mRNAs-transcriptional factors (mRNA-TFs) interaction networks were constructed by the protein and protein interaction (PPI) network method using Cytoscape software. The infiltrating proportion of immune cells was assessed by ssGSEA and the CIBERSORT algorithm. Quantitative real-time PCR (qRT-PCR) was performed to detect the expression of the significant m6A regulators and hub genes.

Results

Four of 30 m6A regulators (HNRNPC, YTHDC2, YTHDF3, and ZC3H13) were identified to be significant in the development of CHD. Two m6A RNA methylation clusters were distinguished by unsupervised clustering analysis based on the expression of the 30 m6A regulators. A total of 491 genes were identified as DEGs between the two clusters. A PPI network including 308 mRNAs corresponding to proteins was constructed, and 30 genes were identified as hub genes that were enriched in the bioprocesses of peptide cross-linking, keratinocyte differentiation. Twenty-seven hub genes were found to be related to miRNAs, and seven hub genes were found to be related to TFs. Moreover, among the 30 hub genes, eight genes were found to be upregulated in CHD, and three were found to be downregulated in CHD compared to the normal people. The high m6A modification pattern was associated with a higher infiltrated abundance of immune cells.

Conclusion

Our findings demonstrated that m6A modification plays crucial roles in the diversity and complexity of the immune microenvironment in CHD.

Biological Features of Extracellular Vesicles and Challenges

Extracellular vesicles (EVs) are vesicles with a lipid bilayer membrane on the outside, which are widely found in various body fluids and contain biological macromolecules such as DNA, RNA, lipids and proteins on the inside. EVs were once thought to be vesicles for the removal of waste materials, but are now known to be involved in a variety of pathophysiological processes in many diseases. This study examines the advantage of EVs and the challenges associated with their application. A more rational use of the advantageous properties of EVs such as composition specificity, specific targeting, circulatory stability, active penetration of biological barriers, high efficient drug delivery vehicles and anticancer vaccines, oxidative phosphorylation activity and enzymatic activity, and the resolution of shortcomings such as isolation and purification methods, storage conditions and pharmacokinetics and biodistribution patterns during drug delivery will facilitate the clinical application of EVs.

Association between Exosomal miRNAs and Coronary Artery Disease by Next-Generation Sequencing

BACKGROUND

Among various bio-informative molecules transferred by exosomes between cells, micro RNAs (miRNAs), which remain remarkably stable even after freeze-and-thaw cycles, are excellent candidates for potential biomarkers for coronary artery disease (CAD).

METHODS

Blood samples were collected from the coronary arteries of 214 patients diagnosed with three-vessel CAD and 140 without CAD. After precipitation extraction, the amounts of exosomes were found to decrease with increased age and three-vessel CAD. Next-generation sequencing was performed to further explore the possible relationship between exosomal miRNAs and CAD.

RESULTS

Eight exosomal miRNAs showed altered expression associated with CAD. The up-regulated miRNAs in CAD were miRNA-382-3p, miRNA-432-5p, miRNA-200a-3p, and miRNA-3613-3p. The down-regulated miRNAs were miRNA-125a-5p, miRNA-185-5p, miRNA-151a-3p, and miRNA-328-3p.

CONCLUSION

We successfully demonstrated particular exosomal miRNAs that may serve as future biomarkers for CAD.