Identifying key genes associated with acute myocardial infarction

Unraveling the Signaling Dynamics of Small Extracellular Vesicles in Cardiac Diseases

Effective intercellular communication is essential for cellular and tissue balance maintenance and response to challenges. Cellular communication methods involve direct cell contact or the release of biological molecules to cover short and long distances. However, a recent discovery in this communication network is the involvement of extracellular vesicles that host biological contents such as proteins, nucleic acids, and lipids, influencing neighboring cells. These extracellular vesicles are found in body fluids; thus, they are considered as potential disease biomarkers. Cardiovascular diseases are significant contributors to global morbidity and mortality, encompassing conditions such as ischemic heart disease, cardiomyopathies, electrical heart diseases, and heart failure. Recent studies reveal the release of extracellular vesicles by cardiovascular cells, influencing normal cardiac function and structure. However, under pathological conditions, extracellular vesicles composition changes, contributing to the development of cardiovascular diseases. Investigating the loading of molecular cargo in these extracellular vesicles is essential for understanding their role in disease development. This review consolidates the latest insights into the role of extracellular vesicles in diagnosis and prognosis of cardiovascular diseases, exploring the potential applications of extracellular vesicles in personalized therapies, shedding light on the evolving landscape of cardiovascular medicine.

Microarray Analysis for Transcriptomic Profiling of Myocardium in Patients with Fatal Myocardial Infarction

Transcriptomic evidence from human myocardium in myocardial infarction (MI) is still not sufficient. Thus, there is a need for studies on human cardiac samples in relation to the clinical data of patients. The purpose of our pilot study was to investigate the transcriptomic profile of myocardium in the infarct zone, in comparison to the remote myocardium, in patients with fatal MI, via microarray analysis. This study included four patients with fatal MI type 1. We selected histologically verified samples from within the infarct area (n = 4) and remote myocardium (n = 4). The whole transcriptome was evaluated using microarray analysis. Differentially expressed genes (DEGs) clustered in the infarct area and in the remote myocardium allowed their differentiation. We identified a total of 1785 DEGs (8.32%) in the infarct area, including 1692 up-regulated (94.79%) and 93 down-regulated (5.21%) genes. The top 10 up-regulated genes were TRAIL, SUCLA2, NAE1, PDCL3, OSBPL5, FCGR2C, SELE, CEP63, ST3GAL3 and C4orf3. In the infarct area, we found up-regulation of seventeen apoptosis-related genes, eleven necroptosis-related, and six necrosis-related genes. Transcriptome profiling of the myocardium in patients with MI remains a relevant area of research for the formation of new scientific hypotheses and a potential way to increase the translational significance of studies into myocardial infarction.

ACSL1, CH25H, GPCPD1, and PLA2G12A as the potential lipid-related diagnostic biomarkers of acute myocardial infarction

Lipid metabolism plays an essential role in the genesis and progress of acute myocardial infarction (AMI). Herein, we identified and verified latent lipid-related genes involved in AMI by bioinformatic analysis. Lipid-related differentially expressed genes (DEGs) involved in AMI were identified using the GSE66360 dataset from the Gene Expression Omnibus (GEO) database and R software packages. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were conducted to analyze lipid-related DEGs. Lipid-related genes were identified by two machine learning techniques: least absolute shrinkage and selection operator (LASSO) regression and support vector machine recursive feature elimination (SVM-RFE). The receiver operating characteristic (ROC) curves were used to descript diagnostic accuracy. Furthermore, blood samples were collected from AMI patients and healthy individuals, and real-time quantitative polymerase chain reaction (RT-qPCR) was used to determine the RNA levels of four lipid-related DEGs. Fifty lipid-related DEGs were identified, 28 upregulated and 22 downregulated. Several enrichment terms related to lipid metabolism were found by GO and KEGG enrichment analyses. After LASSO and SVM-RFE screening, four genes (ACSL1, CH25H, GPCPD1, and PLA2G12A) were identified as potential diagnostic biomarkers for AMI. Moreover, the RT-qPCR analysis indicated that the expression levels of four DEGs in AMI patients and healthy individuals were consistent with bioinformatics analysis results. The validation of clinical samples suggested that 4 lipid-related DEGs are expected to be diagnostic markers for AMI and provide new targets for lipid therapy of AMI.

Systematic Bioinformatics Analysis Based on Public and Second-Generation Sequencing Transcriptome Data: A Study on the Diagnostic Value and Potential Mechanisms of Immune-Related Genes in Acute Myocardial Infarction

Acute myocardial infarction (AMI) is one of the most serious cardiovascular diseases worldwide. Advances in genomics have provided new ideas for the development of novel molecular biomarkers of potential clinical value for AMI.

NR4A3 and CCL20 clusters dominate the genetic networks in CD146+ blood cells during acute myocardial infarction in humans

BACKGROUND

CD146 is a tight junction-associated molecule involved in maintaining endothelial barrier, and balancing immune-inflammation response, in cardiovascular disease. Notably, peripheral CD146+ cells significantly upsurge under vessel dyshomeostasis such as acute myocardial injury (AMI), appearing to be a promising therapeutic target. In this study, with a new view of gene correlation, we aim at deciphering the complex underlying mechanism of CD146+ cells' impact in the development of AMI.

METHODS

Transcription dataset GSE 66,360 of CD146+ blood cells from clinical subjects was downloaded from NCBI. Pearson networks were constructed and the clustering coefficients were calculated to disclose the differential connectivity genes (DCGs). Analysis of gene connectivity and gene expression were performed to reveal the hub genes and hub gene clusters followed by gene enrichment analysis.

RESULTS AND CONCLUSIONS

Among the total 23,520 genes, 27 genes out of 126 differential expression genes were identified as DCGs. These DCGs were found in the periphery of the networks under normal condition, but transferred to the functional center after AMI. Moreover, it was revealed that DCGs spontaneously crowded together into two functional models, CCL20 cluster and NR4A3 cluster, influencing the CD146-mediated signaling pathways during the pathology of AMI for the first time.

MiR-182 Promotes Ischemia/Reperfusion-Induced Acute Kidney Injury in Rat by Targeting FoxO3

BACKGROUND

Renal ischemia/reperfusion (I/R) injury (RIRI) is the main cause of acute kidney injury (AKI) in patients. We investigated the role of miR-182 after renal ischemia/reperfusion (I/R) in rat to characterize the microRNA (miRNA) network activated during development and recovery from RIRI.

METHODS AND RESULTS

12 h after lethal (45 min) renal ischemia, AKI was verified by renal histology (tubular necrosis and regeneration), blood urea nitrogen level, and renal mRNA expression in Wistar rats. We found that miR-182 markedly increased after renal I/R. In cell hypoxia/reoxygenation model, we found similar upregulation of miR-182. In function gain/loss assay, we confirmed an impaired effect of miR-182 and identified Forkhead box O3 (FoxO3) as a direct downstream target of it. By using miR-182 antagomir, the I/R injury was markedly ameliorated.

CONCLUSIONS

Our results demonstrate that miR-182 promotes cell apoptosis and I/R injury through directly binding to FoxO3. The present study will provide potential therapeutic targets for renal I/R-induced AKI, and open a new avenue for AKI treatment by manipulating miRNAs levels.

Specific protein 1 inhibitor mithramycin A protects cardiomyocytes from myocardial infarction via interacting with PARP

Specific protein 1 (SP1) might act as a critical transcription regulator in myocardial infarction (MI), but little evidence about its function in regulating cardiac apoptosis, a major cause of MI development, has been revealed. This study tried to investigate the role of SP1 in MI and its interaction with poly-ADP-ribose polymerase (PARP)-1 by using SP1 inhibitor, mithramycin A (mithA). Primary mouse cardiomyocytes and commercial mouse cardiomyocytes were subjected to mithA treatment under hypoxia conditions, while cell viability, Nix promoter activity, and its expression were detected correspondingly. PARP overexpression and knockdown were conducted, respectively, in mithA-treated and SP1-overexpressing cells. Co-immunoprecipitation was used to verify the interaction between PARP and SP1. For in vivo experiments, mithA administration was performed after the injections of adenovirus for PARP overexpression, and then, MI introduction was carried out. Infarct size and lactate dehydrogenase level were measured to assess MI injury. SP1 inhibitor mithA attenuated hypoxia-induced decrease of cell viability and Nix transcriptional activation, which could be inhibited by PARP overexpression. Knockdown of PARP prevented SP1-induced transcription of Nix and cell viability change, and PARP showed direct interaction with SP1. Furthermore, mithA administration reduced MI injuries, while PARP overexpression could suppress the improvement. The cardioprotective role of SP1 inhibitor mithA was demonstrated here expanding the role of SP1 in MI development involving hypoxia-induced cardiac apoptosis. Moreover, PARP acted as a transcriptional coactivator in Nix transcription involving its interaction with SP1.

MiR-324/SOCS3 Axis Protects Against Hypoxia/Reoxygenation-Induced Cardiomyocyte Injury and Regulates Myocardial Ischemia via TNF/NF-κB Signaling Pathway

We aimed at exploring the function of microRNA-324/cytokine signaling 3 (miR-324/SOCS3) axis in hypoxia/reoxygenation (H/R) -induced cardiomyocyte injury and its underlying mechanism. The differential expression genes were analyzed based on the GSE83500 and GSE48060 datasets from the Gene Expression Omnibus (GEO) database. Then, to conduct the function enrichment analysis, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) databases were used. The upstream regulatory microRNAs (miRNAs) of the identified genes were predicted by miRanda, miRWalk, and TargetScan websites. MiR-324 expression was measured with quantitative real-time polymerase chain reaction (qRT-PCR). The target binding of miR-324 and SOCS3 was established by dual-luciferase reporter assay. Cardiomyocyte proliferation was analyzed by cell counting kit-8 (CCK-8) assay, whereas the apoptosis was investigated via flow cytometry. The expression of TNF pathway-related proteins was detected by western blot analysis. SOCS3 was upregulated in patients with myocardial infarction (MI), and function enrichment analyses proved that SOCS3 was enriched in TNF signaling pathway. Moreover, we found that miR-324 was the upstream regulatory miRNA of SOCS3 and negatively regulated SOCS3 expression. MiR-324 was downregulated in cardiomyocytes with H/R-induced injury, inhibiting cell proliferation. In the H/R model, SOCS3 suppresses cardiomyocyte proliferation, which was recovered by miR-324, and induces cell apoptosis, which was repressed by miR-324 via regulating the expression of cleaved caspase-3 and p P38-MAPK. MiR-324 upregulation decreased the protein levels of TNF-α, p-P65, and p-IκBα in cardiomyocytes that suffered from H/R, which was reversed with SOCS3 overexpression. MiR-324/SOCS3 axis could improve the H/R-induced injury of cardiomyocytes via regulating TNF/NF-κB signaling pathway, and this might provide a new therapy strategy for myocardial ischemia.

MetaDE-Based Analysis of circRNA Expression Profiles Involved in Gastric Cancer

BACKGROUND

Circular RNAs (circRNAs) could play carcinogenic roles in gastric cancer (GC) and have potential to be biomarkers for GC early diagnosis, which needs to be further excavated and supported by more evidence.

AIMS

The study aims to identify more authentic circRNA expression profiles that could function as potential biomarkers in GC.

METHODS

circRNA expression data in three microarrays were downloaded from Gene Expression Omnibus datasets. A systematic meta-analysis based on an integrated dataset pre-processed from the three microarrays was conducted to identify a panel of differentially expressed circRNAs (DEcircs) by using the metaDE package. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes term enrichment were used to note the corresponding functions of DEcircs. Quantitative real-time polymerase chain reaction was applied to verify the DEcircs expression in cancer tissues and adjacent paracancerous tissues. A GC risk-related circRNAs-miRNAs-mRNAs network was further constructed and analyzed.

RESULTS

MetaDE analysis suggested 64 DEcircs between cancer tissues and adjacent normal tissues. GO and KEGG analysis showed that the parental genes of these DEcircs were mainly associated with histone methylation, Wnt signalosome and histone methylation activity. Hsa_circ_0005927 and hsa_circ_0067934 were verified in GC tissues, and a GC risk-related network was constructed.

CONCLUSION

MetaDE-based circRNA expression profiles revealed a series of potential biomarkers involved in GC. Two circRNAs, hsa_circ_0005927 and hsa_circ_0067934, could be more authentic biomarkers for GC screening. The GC risk-related network of hsa_circ_0005927/hsa_circ_0067934 and their downstream targets will provide new genetic insights for GC research.

Adverse Cardiac Remodelling after Acute Myocardial Infarction: Old and New Biomarkers

The prevalence of heart failure (HF) due to cardiac remodelling after acute myocardial infarction (AMI) does not decrease regardless of implementation of new technologies supporting opening culprit coronary artery and solving of ischemia-relating stenosis with primary percutaneous coronary intervention (PCI). Numerous studies have examined the diagnostic and prognostic potencies of circulating cardiac biomarkers in acute coronary syndrome/AMI and heart failure after AMI, and even fewer have depicted the utility of biomarkers in AMI patients undergoing primary PCI. Although complete revascularization at early period of acute coronary syndrome/AMI is an established factor for improved short-term and long-term prognosis and lowered risk of cardiovascular (CV) complications, late adverse cardiac remodelling may be a major risk factor for one-year mortality and postponded heart failure manifestation after PCI with subsequent blood flow resolving in culprit coronary artery. The aim of the review was to focus an attention on circulating biomarker as a promising tool to stratify AMI patients at high risk of poor cardiac recovery and developing HF after successful PCI. The main consideration affects biomarkers of inflammation, biomechanical myocardial stress, cardiac injury and necrosis, fibrosis, endothelial dysfunction, and vascular reparation. Clinical utilities and predictive modalities of natriuretic peptides, cardiac troponins, galectin 3, soluble suppressor tumorogenicity-2, high-sensitive C-reactive protein, growth differential factor-15, midregional proadrenomedullin, noncoding RNAs, and other biomarkers for adverse cardiac remodelling are discussed in the review.

Collapsing the list of myocardial infarction-related differentially expressed genes into a diagnostic signature

BACKGROUND

Myocardial infarction (MI) is one of the most severe manifestations of coronary artery disease (CAD) and the leading cause of death from non-infectious diseases worldwide. It is known that the central component of CAD pathogenesis is a chronic vascular inflammation. However, the mechanisms underlying the changes that occur in T, B and NK lymphocytes, monocytes and other immune cells during CAD and MI are still poorly understood. One of those pathogenic mechanisms might be the dysregulation of intracellular signaling pathways in the immune cells.

METHODS

In the present study we performed a transcriptome profiling in peripheral blood mononuclear cells of MI patients and controls. The machine learning algorithm was then used to search for MI-associated signatures, that could reflect the dysregulation of intracellular signaling pathways.

RESULTS

The genes ADAP2, KLRC1, MIR21, PDGFD and CD14 were identified as the most important signatures for the classification model with L1-norm penalty function. The classifier output quality was equal to 0.911 by Receiver Operating Characteristic metric on test data. These results were validated on two independent open GEO datasets. Identified MI-associated signatures can be further assisted in MI diagnosis and/or prognosis.

CONCLUSIONS

Thus, our study presents a pipeline for collapsing the list of differential expressed genes, identified by high-throughput techniques, in order to define disease-associated diagnostic signatures.

Identification of Post-myocardial Infarction Blood Expression Signatures Using Multiple Feature Selection Strategies

Myocardial infarction (MI) is a type of serious heart attack in which the blood flow to the heart is suddenly interrupted, resulting in injury to the heart muscles due to a lack of oxygen supply. Although clinical diagnosis methods can be used to identify the occurrence of MI, using the changes of molecular markers or characteristic molecules in blood to characterize the early phase and later trend of MI will help us choose a more reasonable treatment plan. Previously, comparative transcriptome studies focused on finding differentially expressed genes between MI patients and healthy people. However, signature molecules altered in different phases of MI have not been well excavated. We developed a set of computational approaches integrating multiple machine learning algorithms, including Monte Carlo feature selection (MCFS), incremental feature selection (IFS), and support vector machine (SVM), to identify gene expression characteristics on different phases of MI. 134 genes were determined to serve as features for building optimal SVM classifiers to distinguish acute MI and post-MI. Subsequently, functional enrichment analyses followed by protein-protein interaction analysis on 134 genes identified several hub genes (IL1R1, TLR2, and TLR4) associated with progression of MI, which can be used as new diagnostic molecules for MI.

MiRNA-Mediated Mechanisms of Cardiac Protection in Ischemic and Remote Ischemic Preconditioning-A Qualitative Systematic Review

BACKGROUND

Ischemic preconditioning (IPC) and remote ischemic preconditioning (RIPC) protect myocardial tissue against subsequent ischemia and reperfusion injury (IRI) and have a high potential to improve patient outcome. The mediators and mechanisms of protection through IPC and RIPC remain largely unknown, but micro-RNAs (miRNAs) are promising candidates.

METHODS

Systematic review of Medline and Embase databases for biomedical scientific literature.

RESULTS

A total of 26 relevant publications (21 full-text original articles and 5 conference abstracts) were identified, 8 describing cell culture experiments, 14 animal experiments, and 4 randomized clinical trials in humans. Most commonly reported miRNAs with differential expression between preconditioned and control groups include miR-1, miR-21, and miR-144. Experimental designs and procedures differ widely, thereby limiting the potential to compare results between studies. Two of the four RCTs did not find any differentially expressed miRNAs.

CONCLUSIONS

Results from RCTs should feed back into basic research and focused studies confirming or rejecting hypotheses generated by these RCTs are needed.

Metabolic Disturbances Identified in Plasma Samples from ST-Segment Elevation Myocardial Infarction Patients

ST-segment elevation myocardial infarction (STEMI) is the most severe form of myocardial infarction (MI) and the main contributor to morbidity and mortality caused by MI worldwide. Frequently, STEMI is caused by complete and persistent occlusion of a coronary artery by a blood clot, which promotes heart damage. STEMI impairment triggers changes in gene transcription, protein expression, and metabolite concentrations, which grants a biosignature to the heart dysfunction. There is a major interest in identifying novel biomarkers that could improve the diagnosis of STEMI. In this study, the phenotypic characterization of STEMI patients (n = 15) and healthy individuals (n = 19) was performed, using a target metabolomics approach. Plasma samples were analyzed by UPLC-MS/MS (ultra-high-performance liquid chromatography-tandem mass spectrometry) and FIA-MS (MS-based flow injection analysis). The goal was to identify novel plasma biomarkers and metabolic signatures underlying STEMI. Concentrations of phosphatidylcholines, lysophosphatidylcholines, sphingomyelins, and biogenic amines were altered in STEMI patients in relation to healthy subjects. Also, after multivariate analysis, it was possible to identify alterations in the glycerophospholipids, alpha-linolenic acid, and sphingolipid metabolisms in STEMI patients.

Using NGS-methylation profiling to understand the molecular pathogenesis of young MI patients who have subsequent cardiac events

Globally, ischaemic heart disease is a major contributor to premature morbidity and mortality. A significant number of young Myocardial Infarction (MI) patients (aged <55 y) have subsequent cardiac events within a year of their index event. This study used Next Generation Sequencing (NGS) methylation to understand the pathogenesis in this subset of young MI patients, comparing them to a cohort of patients without recurrent events. Cases and controls were matched for age, gender, ethnicity, and comorbidities. Differential methylation analyses were performed on Reduced Representation Bisulphite Sequencing (RRBS) data. Across the group and within case-control pairs' variation were analysed. Pairwise comparisons across each matched case-control pair resulted in a list of genes that were consistently significantly differentially methylated between all 16 matched pairs. This gene list was input into pathway analysis databases. Of particular relevance to cardiac pathology the following pathways were identified as over-represented in the patients with recurrent events; cell adhesion, transcription regulation and cardiac electrical conduction, specifically relating to calcium channel activity. This study looked at methylation differences between two populations of young MI patients. There were significantly different methylation profiles between the two groups studied; key pathways were identified as specifically affected in the patients with recurrent cardiac events. Matched pairwise comparisons and detailed interpretations of DNA methylation data may help to elucidate complex pathogeneses within and between clinical subtypes. Further analysis will determine whether these epigenomic differences can be useful as predictive biomarkers of clinical progression.

In Silico Analysis of Differential Gene Expression in Three Common Rat Models of Diastolic Dysfunction

Standard therapies for heart failure with preserved ejection fraction (HFpEF) have been unsuccessful, demonstrating that the contribution of the underlying diastolic dysfunction pathophysiology differs from that of systolic dysfunction in heart failure and currently is far from being understood. Complicating the investigation of HFpEF is the contribution of several comorbidities. Here, we selected three established rat models of diastolic dysfunction defined by three major risk factors associated with HFpEF and researched their commonalities and differences. The top differentially expressed genes in the left ventricle of Dahl salt sensitive (Dahl/SS), spontaneous hypertensive heart failure (SHHF), and diabetes 1 induced HFpEF models were derived from published data in Gene Expression Omnibus and used for a comprehensive interpretation of the underlying pathophysiological context of each model. The diversity of the underlying transcriptomic of the heart of each model is clearly observed by the different panel of top regulated genes: the diabetic model has 20 genes in common with the Dahl/SS and 15 with the SHHF models. Advanced analytics performed in Ingenuity Pathway Analysis (IPA^®) revealed that Dahl/SS heart tissue transcripts triggered by upstream regulators lead to dilated cardiomyopathy, hypertrophy of heart, arrhythmia, and failure of heart. In the heart of SHHF, a total of 26 genes were closely linked to cardiovascular disease including cardiotoxicity, pericarditis, ST-elevated myocardial infarction, and dilated cardiomyopathy. IPA Upstream Regulator analyses revealed that protection of cardiomyocytes is hampered by inhibition of the ERBB2 plasma membrane-bound receptor tyrosine kinases. Cardioprotective markers such as natriuretic peptide A (NPPA), heat shock 27 kDa protein 1 (HSPB1), and angiogenin (ANG) were upregulated in the diabetes 1 induced model; however, the model showed a different underlying mechanism with a majority of the regulated genes involved in metabolic disorders. In conclusion, our findings suggest that multiple mechanisms may contribute to diastolic dysfunction and HFpEF, and thus drug therapies may need to be guided more by phenotypic characteristics of the cardiac remodeling events than by the underlying molecular processes.