Expression characteristics of neutrophil and mononuclear-phagocyte related genes mRNA in the stable angina pectoris and acute myocardial infarction stages of coronary artery disease

Exploring the underlying molecular mechanisms of acute myocardial infarction after SARS-CoV-2 infection

An increase in acute myocardial infarction (AMI)-related deaths has been reported during the COVID-19 pandemic. Despite evidence suggesting the association between severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and AMI, the underlying mechanisms remain unclear. Here, we integrated mRNA and microRNA expression profiles related to SARS-CoV-2 infection and AMI from public databases. We then performed transcriptomic analysis using bioinformatics and systems biology approaches to explore the potential molecular mechanisms of SARS-CoV-2 infection affects AMI. First, twenty-one common differentially expressed genes (DEGs) were identified from SARS-CoV-2 infection and AMI patients in endothelial cells datasets and then we performed functional analysis to predict the roles of these DEGs. The functional analysis emphasized that the endothelial cell response to cytokine stimulus due to excessive inflammation was essential in these two diseases. Importantly, the tumor necrosis factor and interleukin-17 signaling pathways appeared to be integral factors in this mechanism. Interestingly, most of these common genes were also upregulated in transcriptomic datasets of SARS-CoV-2-infected cardiomyocytes, suggesting that these genes may be shared in cardiac- and vascular-related injuries. We subsequently built a protein-protein interaction network and extracted hub genes and essential modules from this network. At the transcriptional and post-transcriptional levels, regulatory networks with common DEGs were also constructed, and some key regulator signatures were further identified and validated. In summary, our research revealed that a highly activated inflammatory response in patients with COVID-19 might be a crucial factor for susceptibility to AMI and we identified some candidate genes and regulators that could be used as biomarkers or potential therapeutic targets.

Identification of key genes for atherosclerosis in different arterial beds

Atherosclerosis (AS) is the pathologic basis of various cardiovascular and cerebrovascular events, with a high degree of heterogeneity among different arterial beds. However, mechanistic differences between arterial beds remain unexplored. The aim of this study was to explore key genes and potential mechanistic differences between AS in different arterial beds through bioinformatics analysis. Carotid atherosclerosis (CAS), femoral atherosclerosis (FAS), infrapopliteal atherosclerosis (IPAS), abdominal aortic atherosclerosis (AAS), and AS-specific differentially expressed genes (DEGs) were screened from the GSE100927 and GSE57691 datasets. Immune infiltration analysis was used to identify AS immune cell infiltration differences. Unsupervised cluster analysis of AS samples from different regions based on macrophage polarization gene expression profiles. Weighted gene co-expression network analysis (WGCNA) was performed to identify the most relevant module genes with AS. Hub genes were then screened by LASSO regression, SVM-REF, and single-gene differential analysis, and a nomogram was constructed to predict the risk of AS development. The results showed that differential expression analysis identified 5, 4, 121, and 62 CAS, FAS, IPAS, AAS-specific DEGs, and 42 AS-common DEGs, respectively. Immune infiltration analysis demonstrated that the degree of macrophage and mast cell enrichment differed significantly in different regions of AS. The CAS, FAS, IPAS, and AAS could be distinguished into two different biologically functional and stable molecular clusters based on macrophage polarization gene expression profiles, especially for cardiomyopathy and glycolipid metabolic processes. Hub genes for 6 AS (ADAP2, CSF3R, FABP5, ITGAX, MYOC, and SPP1), 4 IPAS (CLECL1, DIO2, F2RL2, and GUCY1A2), and 3 AAS (RPL21, RPL26, and RPL10A) were obtained based on module gene, gender stratification, machine learning algorithms, and single-gene difference analysis, respectively, and these genes were effective in differentiating between different regions of AS. This study demonstrates that there are similarities and heterogeneities in the pathogenesis of AS between different arterial beds.

Acute Pulmonary Embolism and Immunity in Animal Models

Venous thromboembolism, encompassing acute pulmonary embolism (APE) and deep vein thrombosis (DVT), is a potentially fatal disease with complex pathophysiology. Traditionally, the Virchow triad provided a framework for understanding the pathogenic contributors to thrombus formation, which include endothelial dysfunction, alterations in blood flow and blood hypercoagulability. In the last years, it has become apparent that immunity plays a central role in thrombosis, interacting with classical prothrombotic mechanisms, oxidative stress and vascular factors. Thrombosis amplifies inflammation, and exaggerated inflammatory processes can trigger thrombosis mainly due to the activation of leukocytes, platelets, and endothelial cells. APE-related endothelium injury is a major trigger for immune system activation. Endothelium is also a key component mediating inflammatory reaction and it is relevant to maintain vascular permeability. Exaggerated right ventricular wall stress and overload, with coexisting systemic hypotension and hypoxemia, result in myocardial injury and necrosis. Hypoxia, tissue factor activation and cytokine storm are engaged in the thrombo-inflammatory processes. Thrombus development is characterized by inflammatory state vascular wall caused mainly by an early extravasation of leukocytes and intense selectins and cytokines production. Nevertheless, immunity of DVT is well described, little is known about potential chemokine and cellular differences between thrombus that develops in the vein and thrombus that detaches and lodges in the pulmonary circulation being a cause of APE. There is a paucity of data considering inflammatory state in the pulmonary artery wall during an acute episode of pulmonary embolism. The main aim of this review is to summarize the knowledge of immunity in acute phase of pulmonary embolism in experimental models.

Screening of Potential Circulating Diagnostic Biomarkers and Molecular Mechanisms of Systemic Lupus Erythematosus-Related Myocardial Infarction by Integrative Analysis

Background

The risk of acute myocardial infarction (AMI) is elevated in patients with systemic lupus erythematosus (SLE), and it is of great clinical value to identify potential molecular mechanisms and diagnostic markers of AMI associated with SLE by analyzing public database data and transcriptome sequencing data.

Methods

AMI and SLE-related sequencing datasets GSE62646, GSE60993, GSE50772 and GSE81622 were downloaded from the Gene Expression Omnibus (GEO) database and divided into prediction and validation cohorts. To identify the key genes associated with AMI related to SLE, WGCNA and DEGs analysis were performed for the prediction and validation cohorts, respectively. The related signaling pathways were identified by GO/KEGG enrichment analysis. Peripheral blood mononuclear cells (PBMCs) from patients with AMI were collected for transcriptome sequencing to validate the expression of key genes in patients with AMI. Least absolute shrinkage and selection operator (LASSO) regression analysis was applied to screen diagnostic biomarkers. The diagnostic efficacy of biomarkers was validated by ROC analysis, and the CIBERSORTx platform was used to analyze the composition of immune cells in AMI and SLE.

Results

A total of 108 genes closely related to AMI and SLE were identified in the prediction cohort, and GO/KEGG analysis showed significantly enriched signaling pathways. The results of differential analysis in validation cohort were consistent with them. By transcriptional sequencing of PBMCs from peripheral blood of AMI patients, combined with the results of prediction and validation cohort analysis, seven genes were finally screened out. LASSO analysis finally identifies DYSF, LRG1 and CSF3R as diagnostic biomarkers of SLE-related-AMI. CIBERSORTx analysis revealed that the biomarkers were highly correlated with neutrophils.

Conclusion

Neutrophil degranulation and NETs formation play important roles in SLE-related AMI, and DYSF, LRG1 and CSF3R were identified as important diagnostic markers for the development and progression of SLE-related AMI.

Biodata Mining of Differentially Expressed Genes between Acute Myocardial Infarction and Unstable Angina Based on Integrated Bioinformatics

Acute coronary syndrome (ACS) is a complex syndrome of clinical symptoms. In order to accurately diagnose the type of disease in ACS patients, this study is aimed at exploring the differentially expressed genes (DEGs) and biological pathways between acute myocardial infarction (AMI) and unstable angina (UA). The GSE29111 and GSE60993 datasets containing microarray data from AMI and UA patients were downloaded from the Gene Expression Omnibus (GEO) database. DEG analysis of these 2 datasets is performed using the “limma” package in R software. DEGs were also analyzed using protein-protein interaction (PPI), Molecular Complex Detection (MCODE) algorithm, Gene Ontology (GO), and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis. Correlation analysis and “cytoHubba” were used to analyze the hub genes. A total of 286 DEGs were obtained from GSE29111 and GSE60993, including 132 upregulated genes and 154 downregulated genes. Subsequent comprehensive analysis identified 20 key genes that may be related to the occurrence and development of AMI and UA and were involved in the inflammatory response, interaction of neuroactive ligand-receptor, calcium signaling pathway, inflammatory mediator regulation of TRP channels, viral protein interaction with cytokine and cytokine receptor, human cytomegalovirus infection, and cytokine-cytokine receptor interaction pathway. The integrated bioinformatical analysis could improve our understanding of DEGs between AMI and UA. The results of this study might provide a new perspective and reference for the early diagnosis and treatment of ACS.

Genes associated with inflammation and the cell cycle may serve as biomarkers for the diagnosis and prognosis of acute myocardial infarction in a Chinese population

The present study aimed to identify biomarkers for the clinical diagnosis of acute myocardial infarction (AMI) in a Chinese population using microarray data collected from the Gene Expression Omnibus database under accession number GSE97320. This included the peripheral blood samples of three patients with AMI and three controls. Differentially expressed genes (DEGs) were identified using the limma package and protein-protein interaction networks were constructed using data from the Search Tool for the Retrieval of Interacting Genes database, followed by module analysis to screen for hub genes. Functional enrichment analyses were performed using the Database for Annotation, Visualization and Integrated Discovery. The identified genes were verified by overlapping with the target genes of microRNAs (miRs) known to be associated with AMI, as well as the DEGs identified in other AMI datasets, including GSE24519, GSE34198 and GSE48060. As a result, 752 DEGs (449 upregulated and 303 downregulated) were identified in the GSE97320 dataset. The upregulated DEGs were predicted to participate in inflammatory pathways, including the toll-like receptor (TLR) signaling pathway, including ras-related C3 botulinum toxin substrate 1 (RAC1), TLR4, C-C motif chemokine receptor (CCR)1; cytokine-cytokine receptor interaction, including signal transducer and activator of transcription (STAT)3; chemokine signaling pathway, including CCR10; pathways associated with cancer, including colony stimulating factor 3 receptor (CSF3R); and leukocyte transendothelial migration, including matrix metallopeptidase 9 (MMP9). The downregulated DEGs were associated with the cell cycle, including alstrom syndrome protein 1 (ALMS1). These conclusions were made following functional analysis of the genes in the three identified modules. MMP9, TLR4, STAT3, CCR1 and ALMS1 were regulated by miR-21-5p, whereas RAC1 was regulated by miR-30c-5p. A comparison among the four datasets confirmed the roles of CSF3R and CCR10. HtrA serine peptidase 1 (HTRA1) was the only gene associated with both mortality and recurrence. In conclusion, inflammation-associated genes, including STAT3, CCR1, RAC1, MMP9, CCR10, CSF3R and HTRA1, as well as cell cycle-associated genes such as ALMS1, may be biomarkers for the diagnosis and prognosis of AMI in Chinese people.

MicroRNA-145-5p and microRNA-320a encapsulated in endothelial microparticles contribute to the progression of vasculitis in acute Kawasaki Disease

Kawasaki Disease (KD) is an acute inflammatory disease that takes the form of systemic vasculitis. Endothelial microparticles (EMPs) have been recognized as an important transcellular delivery system. We hypothesized whether EMPs are involved in vasculitis in acute KD. Fifty patients with acute KD were enrolled, divided into two subgroups: those with coronary artery lesions (CAL) (n = 5) and those without CAL (NCAL) (n = 45). EMPs were measured using flow cytometry, and microRNA (miR) expression profiling was performed by microRNA array. The percentage of EMPs in acute KD was significantly higher than in controls (P < 0.0001). EMPs in patients with CAL rapidly increased after the initial treatment, and was significantly higher than those in NCAL (P < 0.001). In patients with CAL, we identified 2 specific miRs encapsulated in EMPs, hsa-miR-145-5p and hsa-miR-320a, which are predicted to affect monocyte function using in silico analysis, and were demonstrated to upregulate inflammatory cytokine mRNAs in THP-1 monocytes. In situ hybridization confirmed that hsa-miR-145-5p was preferentially expressed in CAL. EMPs may serve as a sensitive marker for the severity of vasculitis in acute KD. Moreover, these 2 specific miRs encapsulated in EMPs might be involved in inflammatory cytokine regulation and the pathogenesis of vasculitis in acute KD.

Gene Expression Profiling of Pulmonary Artery in a Rabbit Model of Pulmonary Thromboembolism

Acute pulmonary thromboembolism (PTE) refers to the obstruction of thrombus in pulmonary artery or its branches. Recent studies have suggested that PTE-induced endothelium injury is the major physiological consequence of PTE. And it is reasonal to use PTE-induced endothelium injury to stratify disease severity. According to the massive morphologic and histologic findings, rabbit models could be applied to closely mimic the human PE. Genomewide gene expression profiling has not been attempted in PTE. In this study, we determined the accuracy of rabbit autologous thrombus PTE model for human PTE disease, then we applied gene expression array to identify gene expression changes in pulmonary arteries under PTE to identify potential molecular biomarkers and signaling pathways for PTE. We detected 1343 genes were upregulated and 923 genes were downregulated in PTE rabbits. The expression of several genes (IL-8, TNF-α, and CXCL5) with functional importance were further confirmed in transcript and protein levels. The most significantly differentially regulated genes were related to inflammation, immune disease, pulmonary disease, and cardiovascular diseases. Totally 87 genes were up-regulated in the inflammatory genes. We conclude that gene expression profiling in rabbit PTE model could extend the understanding of PTE pathogenesis at the molecular level. Our study provides the fundamental framework for future clinical research on human PTE, including identification of potential biomarkers for prognosis or therapeutic targets for PTE.