Bioinformatic screening for key miRNAs and genes associated with myocardial infarction

Recent Advances of Using Exosomes as Diagnostic Markers and Targeting Carriers for Cardiovascular Disease

Cardiovascular diseases (CVDs) are the leading cause of human death worldwide. Exosomes act as endogenous biological vectors; they possess advantages of low immunogenicity and low safety risks, also providing tissue selectivity, including the inherent targeting the to heart. Therefore, exosomes not only have been applied as biomarkers for diagnosis and therapeutic outcome confirmation but also showed potential as drug carriers for cardiovascular targeting delivery. This review aims to summarize the progress and challenges of exosomes as novel biomarkers, especially many novel exosomal noncoding RNAs (ncRNAs), and also provides an overview of the improved targeting functions of exosomes by unique engineered approaches, the latest developed administration methods, and the therapeutic effects of exosomes used as the biocarriers of medications for cardiovascular disease treatment. Also, the possible therapeutic mechanisms and the potentials for transferring exosomes to the clinic for CVD treatment are discussed. The advances, in vivo and in vitro applications, modifications, mechanisms, and challenges summarized in this review will provide a general understanding of this promising strategy for CVD treatment.

Potential roles of endothelial cells-related non-coding RNAs in cardiovascular diseases

Endothelial dysfunction is identified by a conversion of the endothelium toward decreased vasodilation and prothrombic features and is known as a primary pathogenic incident in cardiovascular diseases. An insight based on particular and promising biomarkers of endothelial dysfunction may possess vital clinical significances. Currently, non-coding RNAs due to their participation in critical cardiovascular processes like initiation and progression have gained much attention as possible diagnostic as well as prognostic biomarkers in cardiovascular diseases. Emerging line of proof has demonstrated that abnormal expression of non-coding RNAs is nearly correlated with the pathogenesis of cardiovascular diseases. In the present review, we focus on the expression and functional effects of various kinds of non-coding RNAs in cardiovascular diseases and negotiate their possible clinical implications as diagnostic or prognostic biomarkers and curative targets.

HSPA6 and its role in cancers and other diseases

Heat Shock Protein Family A (Hsp70) Member 6 (HSPA6) (Online Mendelian Inheritance in Man: 140555) belongs to the HSP70 family and is a partially conserved inducible protein in mammals. The HSPA6 gene locates on the human chromosome 1q23.3 and encodes a protein containing two important structural domains: The N-terminal nucleotide-binding domain and the C-terminal substrate-binding domain. Currently, studies have found that HSPA6 not only plays a role in the tumorigenesis and tumor progresses but also causes non-tumor-related diseases. Furthermore, HSPA6 exhibits to inhibit tumorigenesis and tumor progression in some types of cancers but promotes in others. Even though HSPA6 research has increased, its exact roles and mechanisms are still unclear. This article reviews the structure, expression, function, research progress, possible mechanism, and perspective of HSPA6 in cancers and other diseases, highlighting its potential role as a targeted therapeutic and prognostic marker.

The association of plasma levels of miR-146a, miR-27a, miR-34a, and miR-149 with coronary artery disease

BACKGROUND

Coronary artery disease (CAD) is considered to be one of the most pivotal causes of death in the world. Over the past two decades, significant changes occurred in the diagnosis, prognosis, and treatment of CAD, which has helped reduce mortality rates. microRNAs (miRs) are a class of more than 5000 non-encoding RNA molecules (21-25 nucleotides across the length) that regulate complex biological processes. Today, miRNAs are used to study cardiovascular diseases. In the present study, the expression of miR-146a،miR-27, miR-149, and miR-34a in plasma suffering from CAD and the control group were investigated.

METHODS AND RESULTS

The present research was performed on 30 men with CAD and 30 healthy men as controls. The expression levels of miR-146a, miR-27a, miR-149, and miR-34a in the plasma of patients with CAD and the control group were measured using real-time PCR. Also, the correlation between the expression of circulating miRs levels and biochemical LDL-C, HDL-C, BMI, and total cholesterol was evaluated. The expression of miR-27a in the plasma of the CAD group was higher than in the control group (p = 0.020). The expression of miR-146a was downregulated in CAD patients compared to normal subjects (p = 0. 026). However, the expression of miR-34a, miR-149 in the plasma of CAD patients was not significantly different with the control group. In addition to, a direct correlation was found between the expression of miR-146a and HDL-c, the expression of miR-27a and LDL-C and the expression of miR-34a and total cholesterol. Also, the negative correlation between expressions of miR-149 with BMI was reported.

CONCLUSION

The obtained results demonstrated that miRs were closely related to biochemical factors and it points out the fact that miRNAs can be applied as a potential strategy for diagnosis and treatment of CAD.

Screening for Regulatory Network of miRNA–Inflammation, Oxidative Stress and Prognosis-Related mRNA in Acute Myocardial Infarction: An in silico and Validation Study

Background

Acute myocardial infarction (AMI), which commonly leads to heart failure, is among the leading causes of mortality worldwide. The aim of this study was to find potential regulatory network for miRNA-inflammation, oxidative stress and prognosis-related mRNA to uncover molecular mechanisms of AMI.

Methods

The expression profiles of miRNA and mRNA in the blood samples from AMI patients were downloaded from the Gene Expression Omnibus (GEO) dataset for differential expression analysis. Weighted gene co-expression network analysis (WGCNA) was used to further identify important mRNAs. The negatively regulatory network construction of miRNA–inflammation, oxidative stress and prognosis-related mRNAs was performed, followed by protein–protein interaction (PPI) and functional analysis of mRNAs.

Results

A total of three pairs of negatively regulatory network of miRNA–inflammation and prognosis-related mRNAs (hsa-miR-636/hsa-miR-491-3p/hsa-miR-188-5p/hsa-miR-188-3p-AQP9, hsa-miR-518a-3p-C5AR1 and hsa-miR-509-3-5p/hsa-miR-127-5p-PLAUR), two pairs of negatively regulatory network of miRNA–oxidative stress and prognosis-related mRNAs (hsa-miR-604-TLR4 and hsa-miR-139-5p-CXCL1) and three pairs of negatively regulatory network of miRNA-inflammation, oxidative stress and prognosis-related mRNA (hsa-miR-634/hsa-miR-591-TLR2, hsa-miR-938-NFKBIA and hsa-miR-520h/hsa-miR-450b-3p-ADM) were identified. In the KEGG analysis, some signaling pathways were identified, such as complement and coagulation cascades, pathogenic Escherichia coli infection, chemokine signaling pathway and cytokine–cytokine receptor interaction and Toll-like receptor signaling pathway.

Conclusion

Identified negatively regulatory network of miRNA-inflammation/oxidative stress and prognosis-related mRNA may be involved in the process of AMI. Those inflammation/oxidative stress and prognosis-related mRNAs may be diagnostic and prognostic biomarkers for AMI.

Identification of Biomarkers Related to Immune Cell Infiltration with Gene Coexpression Network in Myocardial Infarction

Background

There is evidence that the immune system plays a key critical role in the pathogenesis of myocardial infarction (MI). However, the exact mechanisms associated with immunity have not been systematically uncovered.

Methods

This study used the weighted gene coexpression network analysis (WGCNA) and the CIBERSORT algorithm to analyze the MI expression data from the Gene Expression Omnibus database and then identify the module associated with immune cell infiltration. In addition, we built the coexpression network and protein-protein interactions network analysis to identify the hub genes. Furthermore, the relationship between hub genes and NK cell resting was validated by using another dataset GSE123342. Finally, receiver operating characteristic (ROC) curve analyses were used to assess the diagnostic value of verified hub genes.

Results

Monocytes and neutrophils were markedly increased, and T cell CD8, T cell CD4 naive, T cell CD4 memory resting, and NK cell resting were significantly decreased in MI groups compared with stable coronary artery disease (CAD) groups. The WGCNA results showed that the pink model had the highest correlation with the NK cell resting infiltration level. We identified 11 hub genes whose expression correlated to the NK cell resting infiltration level, among which, 7 hub genes (NKG7, TBX21, PRF1, CD247, KLRD1, FASLG, and EOMES) were successfully validated in GSE123342. And these 7 genes had diagnostic value to distinguish MI and stable CAD.

Conclusions

NKG7, TBX21, PRF1, CD247, KLRD1, FASLG, and EOMES may be a diagnostic biomarker and therapeutic target associated with NK cell resting infiltration in MI.

Crosstalk between Circulatory Microenvironment and Vascular Endothelial Cells in Acute Myocardial Infarction

Background

The reason of high mortality of acute myocardial infarction (AMI) was the lack of exploring the cellular and molecular mechanism of AMI. Therefore, we explored the crosstalk among cells, as well as its potential molecular mechanism of mediating AMI.

Methods

The gene expression profile of peripheral blood, endothelial, platelets and mononuclear cells were applied to differentially expressed genes (DEGs) analysis. ClusterProfiler and the package of gene set enrichment analysis (GSEA) were applied to explore the potential functional pathways of DEGs in 3 types of intravascular cells (endothelial, platelets and mononuclear cells) and peripheral blood. Subsequently, we extracted the surface receptors, secreted proteins and extracellular matrix from the up-regulated DEGs to explore their potential interactions mechanism of AMI by crosstalk and pivot analysis.

Findings

A total 11 common regulated DEGs (CDEGs) were identified, which might be potential biomarkers for AMI diagnosis. The abnormal pathways involved in DEGs of 3 types of intravascular cells and peripheral blood were shown, which also verified by GSEA. Afterwards, it was found that there was crosstalk in 3 types of intravascular cells and peripheral blood. Furthermore, we constructed a cell–cell interaction map among cells in AMI regulated by exosome lncRNA, which was involved in the development of AMI. Finally, we identified 8 hub genes, which might be potential biomarkers of AMI.

Interpretation

The result of this study can not only be used as a reference for subsequent experiments and further exploration, but also contribute to the development of novel cell and molecular therapies.

Uncovering Potential lncRNAs and mRNAs in the Progression From Acute Myocardial Infarction to Myocardial Fibrosis to Heart Failure

Background: Morbidity and mortality of heart failure (HF) post-myocardial infarction (MI) remain elevated. The aim of this study was to find potential long non-coding RNAs (lncRNAs) and mRNAs in the progression from acute myocardial infarction (AMI) to myocardial fibrosis (MF) to HF.

Methods: Firstly, blood samples from AMI, MF, and HF patients were used for RNA sequencing. Secondly, differentially expressed lncRNAs and mRNAs were obtained in MF vs. AMI and HF vs. MF, followed by functional analysis of shared differentially expressed mRNAs between two groups. Thirdly, interaction networks of lncRNA-nearby targeted mRNA and lncRNA-co-expressed mRNA were constructed in MF vs. AMI and HF vs. MF. Finally, expression validation and diagnostic capability analysis of selected lncRNAs and mRNAs were performed.

Results: Several lncRNA-co-expressed/nearby targeted mRNA pairs including AC005392.3/AC007278.2-IL18R1, AL356356.1/AL137145.2-PFKFB3, and MKNK1-AS1/LINC01127-IL1R2 were identified. Several signaling pathways including TNF and cytokine–cytokine receptor interaction, fructose and mannose metabolism and HIF-1, hematopoietic cell lineage and fluid shear stress, and atherosclerosis and estrogen were selected. IL1R2, IRAK3, LRG1, and PLAC4 had a potential diagnostic value for both AMI and HF.

Conclusion: Identified AC005392.3/AC007278.2-IL18R1, AL356356.1/AL137145.2-PFKFB3, and MKNK1-AS1/LINC01127-IL1R2 lncRNA-co-expressed/nearby targeted mRNA pairs may play crucial roles in the development of AMI, MF, and HF.

TFEB Signalling-Related MicroRNAs and Autophagy

The oncogenic Transcription Factor EB (TFEB), a member of MITF-TFE family, is known to be the most important regulator of the transcription of genes responsible for the control of lysosomal biogenesis and functions, autophagy, and vesicles flux. TFEB activation occurs in response to stress factors such as nutrient and growth factor deficiency, hypoxia, lysosomal stress, and mitochondrial damage. To reach the final functional status, TFEB is regulated in multimodal ways, including transcriptional rate, post-transcriptional regulation, and post-translational modifications. Post-transcriptional regulation is in part mediated by miRNAs. miRNAs have been linked to many cellular processes involved both in physiology and pathology, such as cell migration, proliferation, differentiation, and apoptosis. miRNAs also play a significant role in autophagy, which exerts a crucial role in cell behaviour during stress or survival responses. In particular, several miRNAs directly recognise TFEB transcript or indirectly regulate its function by targeting accessory molecules or enzymes involved in its post-translational modifications. Moreover, the transcriptional programs triggered by TFEB may be influenced by the miRNA-mediated regulation of TFEB targets. Finally, recent important studies indicate that the transcription of many miRNAs is regulated by TFEB itself. In this review, we describe the interplay between miRNAs with TFEB and focus on how these types of crosstalk affect TFEB activation and cellular functions.

MicroRNA-139-5p inhibits vascular endothelial cell viability and serves as a diagnostic biomarker in acute myocardial infarction patients

BACKGROUND

Acute myocardial infarction (AMI) is a cardiovascular disease with high morbidity and mortality, and microRNA-139-5p (miR-139-5p) has been reported to be closely related with myocardial viability. This study aimed to investigate the effects of miR-139-5p on vascular endothelial cells, detect miR-139-5p expression in AMI patients and evaluate its diagnostic value.

METHODS

A dual-luciferase reporter assay was utilized to confirm the interaction of miR-139-5p with vascular endothelial growth factor receptor-1 (VEGFR-1). Quantitative real-time PCR was used to detect the levels of miR-139-5p and VEGFR-1 in serum and cells. The viability of human umbilical vein endothelial cells (HUVECs) was measured using a cell counting kit-8 assay. The correlation between miR-139-5p and VEGFR-1 was analyzed by Pearson correlation analysis. The diagnostic value of miR-139-5p, cardiac troponin I (cTnI) and creatine kinase isoenzymes (CK-MB) was identified by receiver operating characteristic analysis.

RESULTS

miR-139-5p suppressed cell viability by directly targeting VEGFR-1 in HUVECs. Increased miR-139-5p and decreased VEGFR-1 levels were found in AMI patients and hypoxia-treated HUVECs, and miR-139-5p and VEGFR-1 were shown to be negatively correlated. The diagnostic value of miR-139-5p for AMI screening was high, and the combination of cTnI, CK-MB and miR-139-5p had the highest diagnostic accuracy. miR-139-5p inhibited cell viability by inhibiting VEGFR-1 in hypoxia-treated HUVECs.

CONCLUSION

miR-139-5p inhibits endothelial cell viability of AMI by inhibiting VEGFR-1, and increased miR-139-5p expression in AMI patients has high diagnostic value for AMI screening, indicating that miR-139-5p may serve as a diagnostic biomarker and molecular therapeutic target for AMI.

Identification of functional lncRNAs through constructing a lncRNA-associated ceRNA network in myocardial infarction

Myocardial infarction (MI) is a type of coronary heart disease, which refers to the ischemic necrosis of the heart muscle. A large number of studies have discussed the mechanism of MI from the perspective of competing endogenous RNA (ceRNA) network. However, the mechanisms underlying the function of lncRNAs in MI have still not been explained in an explicit manner. Therefore, we constructed a scale-free lncRNA-associated ceRNA network to identify some crucial lncRNAs in MI. Results showed that the given disease genes for MI were involved in the network, the degrees of which were significantly larger than the other nodes of the network. For measuring the network centrality, we then constructed a hub subnetwork. The miRNAs and mRNAs in the hub subnetwork have been validated to function in MI-related biological function. In addition, we identified 2 MI-related functional modules from the lncRNA-associated ceRNA network, which suggested that lncRNA exerted function in local network. Enrichment analysis showed that these functional modules corresponded to some similar and different pathways related to cardiovascular disease. More importantly, 3 MI-related crucial lncRNAs, CTD-3092A11.2, RP5-821D11.7 and CTC-523E23.1 were detected as potential biomarkers, which may be involved in MI-related biological progresses. Our study identified 20 functional lncRNAs based on ceRNA network analysis, which may provide novel diagnosis and therapeutic targets for MI from the ceRNA network perspective.

Promoting roles of KLF5 in myocardial infarction in mice involving microRNA-27a suppression and the following GFPT2/TGF-β/Smad2/3 axis activation

Myocardial infarction (MI) is a major atherosclerotic cardiovascular disease which represents a leading cause of death worldwide. Kruppel-like factor 5 (KLF5) is a member of the kruppel-like transcription factor family which has been reported with pro-apoptotic functions in myocardial cells. This work focuses on the function of KLF5 in the pathogenesis of MI and the molecules involved. A mouse model with MI was established. Hypoxia/reoxygenation (H/R)-treated H9C2 cells were applied for in vitro experiments. A KLF5-specific inhibitor ML264 was administrated in cell and animal models. ML264 significantly reduced apoptosis, expression of fibrosis-related markers, reactive oxygen species in the H/R-treated H9C2 cells, and it reduced myocardial injury, infarct size, apoptosis and fibrosis in the myocardial tissues in model mice through specific downregulation of KLF5. A microRNA (miRNA) microarray analysis was performed, which suggested miR-27a as the most upregulated miRNA in the H/R-treated cells after ML264 treatment. miR-27a mimic reduced apoptosis and fibrosis in H/R-treated cells, while miR-27a inhibition blocked the protective roles of ML264. The integrated bioinformatic analyses and luciferase assays confirmed glutamine fructose-6-phosphate transaminase 2 (GFPT2) mRNA as a target of miR-27a. Overexpression of GFPT2 counteracted the protective functions of miR-27a against MI through the activation of the TGF-β/Smad2/3 signaling pathway. To conclude, this study evidenced that KLF5 possibly induces cell and tissue damage in MI through downregulation of miR-27a and the subsequent activation of GFPT2/TGF-β/Smad2/3 axis. This study may offer novel thoughts into MI treatment.

Identification of Genetic Biomarkers for Diagnosis of Myocardial Infarction Compared with Angina Patients

Background

Myocardial infarction (MI) is the most terrible appearance of cardiovascular disease. The incidence of heart failure, one of the complications of MI, has increased in the past few decades. Therefore, the identification of MI from angina patients and the determination of new diagnoses and therapies of MI are increasingly important. The present study was aimed at identifying differentially expressed genes and miRNAs as biomarkers for the clinical and prognosis factors of MI compared with angina using microarray data analysis.

Methods

Differentially expressed miRNAs and genes were manifested by GEO2R. The biological function of differentially expressed genes (DEGs) was examined by GO and KEGG. The construction of a protein-protein network was explored by STRING. cytoHubba was utilized to screen hub genes. Analysis of miRNA-gene pairs was executed by the miRWalk 3.0 database. The miRNA-target pairs overlapped with hub genes were seen as key genes. Logistic regressive analysis was performed by SPSS.

Results

A number of 779 DEGs were recorded. The biological function containing extracellular components, signaling pathways, and cell adhesion was enriched. Twenty-four hub genes and three differentially expressed miRNAs were noted. Eight key genes were demonstrated, and 6 out of these 8 key genes were significantly related to clinical and prognosis factors following MI.

Conclusions

CALCA, CDK6, MDM2, NRXN1, SOCS3, VEGFA, SMAD4, NCAM1, and hsa-miR-127-5p were thought to be potential diagnosis biomarkers for MI. Meanwhile, CALCA, CDK6, NRXN1, SMAD4, SOCS3, and NCAM1 were further identified to be potential diagnosis and therapy targets for MI.

Myocardial infarction biomarker discovery with integrated gene expression, pathways and biological networks analysis

Myocardial infarction (MI) is the most prevalent coronary heart disease caused by the complex molecular interactions between multiple genes and environment. Here, we aim to identify potential biomarkers for the disease development and for prognosis of MI. We have used gene expression dataset (GSE66360) generated from 51 healthy controls and 49 patients experiencing acute MI and analyzed the differentially expressed genes (DEGs), protein-protein interactions (PPI), gene network-clusters to annotate the candidate pathways relevant to MI pathogenesis. Bioinformatic analysis revealed 810 DEGs. Their functional annotations have captured several MI targeting biological processes and pathways like immune response, inflammation and platelets degranulation. PPI network identify seventeen hub and bottleneck genes, whose involvement in MI was further confirmed by DisGeNET database. OpenTarget Platform reveal unique bottleneck genes as potential target for MI. Our findings identify several potential biomarkers associated with early stage MI providing a new insight into molecular mechanism underlying the disease.

Circulating miR-1 as a potential predictor of left ventricular remodeling following acute ST-segment myocardial infarction using cardiac magnetic resonance

Background

The identification of patients with a high likelihood of left ventricular (LV) remodeling with a high-risk prognosis has critical implications for risk stratification after acute ST-segment elevation myocardial infarction (STEMI). This study aimed to evaluate the relationship between circulating miR-1 and 6-month post-infarct LV remodeling based on cardiac magnetic resonance (CMR) imaging.

Methods

A total of 80 patients with a first STEMI treated with primary percutaneous coronary intervention (PCI) who underwent CMR imaging 1 week and 6 months after STEMI were evaluated. The percentage changes of LV ejection fraction (LVEF), LV end-diastolic volume (LVEDV), LV end-systolic volume index (LVESV) at 1 week and 6 months after PCI (%ΔLVEF, %ΔLVEDV and %ΔLVESV) were calculated. miR-1 was measured using polymerase chain reaction (PCR)-based technologies in plasma samples that were collected at admission. The study group was divided into two groups based on a 10% cutoff value for the percentage of change in the LV end-diastolic volume (%ΔLVEDV): remodeling at high risk of major adverse cardiac events (MACEs) (%ΔLVEDV ≥10%, termed the LV remodeling group) and remodeling at lower risk of MACEs (%ΔLVEDV <10%, termed the non-LV remodeling group). The associations of miR-1 expression with the %ΔLVEDV, percentage change in the LV end-systolic volume (%ΔLVESV), and percentage change in the LV ejection fraction at follow-up were estimated.

Results

Twenty-two patients (27.5%) showed adverse LV remodeling, and 58 patients (72.5%) did not show adverse LV remodeling at the 6-month follow-up of CMR. The mean LVEF, LVEDV index, and LVESV index values at 1 week were 50.6%±8.2%, 74.6±12.8 mL/m², and 37.2±10.2 mL/m², respectively. Mean LVEF at follow-up (53.5%±10.6%) was increased compared with baseline (P<0.001). There were significant decreases in LVEDV index and LVESV index values at follow-up (72.0±14.9 mL/m² and 33.7±11.0 mL/m², respectively; P=0.009 and P<0.001, respectively). The expression of miR-1 at admission was positively correlated with the %ΔLVEDV (r=0.611, P<0.001) and %ΔLVESV (r=0.268, P=0.016). Receiver operating characteristic (ROC) analysis showed that miR-1 expression predicted LV remodeling with an area under the curve (AUC) value of 0.68 (95% CI: 0.56-0.78). Compared with the clinical factors of peak creatine kinase-myocardial band (CK-MB) and peak troponin T level, peak logNT-proBNP showed the highest predictive power, with an AUC value of 0.75 (95% CI: 0.64-0.84). A model including the clinical, CMR, and miR-1 factors showed greater predictive power (P=0.034) than a model including only clinical and CMR factors, with AUCs of 0.89 (95% CI: 0.80-0.95) and 0.81 (95% CI: 0.71-0.89), respectively.

Conclusions

Circulating miR-1 at admission is an independent predictor of LV remodeling 6 months after STEMI. miR-1 showed incremental value in predicting LV remodeling compared with the clinical and CMR measurements.

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.

Overexpression of miR-375 Protects Cardiomyocyte Injury following Hypoxic-Reoxygenation Injury

The aim of the study was to evaluate the clinical significance of microRNA-375 in acute myocardial infarction patients and its mimic action in hypoxia/reoxygenation- (H/R-) induced ventricular cardiomyocyte H9c2 injury. In the current study, 90 ST-elevated acute MI patients (STEMI), 75 non-ST-elevated acute MI patients (NSTEMI), 90 healthy subjects, 14 weeks old mice, and ventricular cardiomyocyte H9c2 were included. The expressions of plasma microRNA-375 in patients with STEMI and NSTEMI and AMI mouse models were remarkably decreased than in controls (P < 0.001). The areas under the curve (AUC) of plasma microRNA-375 were revealed 0.939 in STEMI and 0.935 in NSTEMI subjects. Moreover, microRNA-375 levels in H/R-exposed cardiac H9c2 cells were evidently downregulated and significantly increased apoptosis rate and caspase-3 activity levels, while overexpression of miR-375 remarkably reduced apoptosis percentage and caspase-3 levels as compared with normal cells. Furthermore, this study also demonstrated that Nemo-like kinase (NLK), NLK mRNA, and protein expression levels were significantly downregulated in H/R-injured H9c2 cells, on the contrary, H9c2 cells transfected with mimic-miR-375 greatly upregulated NLK mRNA and protein expression. Plasma microRNA-375 may serve as an essential clinical biomarker for diagnosis of early-stage AMI. Mimic expression of miR-375 significantly prevented H/R-induced cardiomyocyte injury by decreasing caspase-3 activity through upregulation of the NLK gene, recommended as a new therapeutic option for AMI patient.

Epigenetic Biomarkers in Cardiovascular Diseases

Cardiovascular diseases are the number one cause of death worldwide and greatly impact quality of life and medical costs. Enormous effort has been made in research to obtain new tools for efficient and quick diagnosis and predicting the prognosis of these diseases. Discoveries of epigenetic mechanisms have related several pathologies, including cardiovascular diseases, to epigenetic dysregulation. This has implications on disease progression and is the basis for new preventive strategies. Advances in methodology and big data analysis have identified novel mechanisms and targets involved in numerous diseases, allowing more individualized epigenetic maps for personalized diagnosis and treatment. This paves the way for what is called pharmacoepigenetics, which predicts the drug response and develops a tailored therapy based on differences in the epigenetic basis of each patient. Similarly, epigenetic biomarkers have emerged as a promising instrument for the consistent diagnosis and prognosis of cardiovascular diseases. Their good accessibility and feasible methods of detection make them suitable for use in clinical practice. However, multicenter studies with a large sample population are required to determine with certainty which epigenetic biomarkers are reliable for clinical routine. Therefore, this review focuses on current discoveries regarding epigenetic biomarkers and its controversy aiming to improve the diagnosis, prognosis, and therapy in cardiovascular patients.

Exploration of Novel Biomarkers in Vasculitis by Integrated Bioinfomatic Approaches

Angiitis, also known as vasculitis, is a chronic inflammatory disease characterized by the infiltration of inflammatory cells in surroundings of blood vessels, accompanied by vascular damage including fibrin deposition, collagen fiber degeneration, myocyte, and endotheliocyte necrosis. This work aimed to perform an integrated bioinformatic analysis of three data sets concerning vasculitis to explore and examine the potential diagnostic and therapeutic makers contributing to illuminating the pathomechanisms of vasculitis. We collected three sets of gene expression data designed by dual-channel method from Gene Expression Omnibus, which were based on the same platform (Agilent-014850 Whole Human Genome Microarray 4x44K G4112F). The meta-analysis was used to analyze the gene expression profiles and screen the differentially expressed genes followed by functional features identification. Subsequently, a protein-protein interaction and transcriptional regulation network were conducted for further investigation of expression mechanisms of vasculitis. Totally, 73 consistently upregulated genes, 49 consistently downregulated genes, and 26 genes with different expression directions were identified. Functional enrichment and transcription regulation analysis suggested upregulated genes (PPBP, PLAU, and HIST1H2BH) and downregulated genes such as IL23A gene were predominately associated with immune responses and cytokine receptors function. In addition, specific cancer-related genes such as MRVI1 was also extracted and considered as promising biomarkers of the development and progression of vasculitis. This study established an integrated meta-analysis approach and identified novel biomarkers involved in vasculitis, which further facilitate to explore and unravel the etiopathogenesis of vasculitis.

Un-JAMming atherosclerotic arteries: JAM-L as a target to attenuate plaque development

Atherosclerosis is a chronic inflammatory disease and a major driver of heart attack and stroke. Atherosclerosis development is driven by the infiltration of leukocytes, including monocytes and neutrophils, among other inflammatory cells into the artery wall, monocyte differentiation to macrophages and uptake of oxidized low density lipoprotein. Macrophage activation and inflammatory cytokine production are major factors which drive ongoing inflammation and plaque development. Identification of novel pathways driving this on-going inflammatory process may provide new opportunities for therapeutic intervention. In their article published in Clinical Science (2019) (vol 133, 1215-1228), Sun and colleagues demonstrate a novel role for the junction adhesion molecule-like (JAML) protein in driving on-going atherosclerotic plaque inflammation and plaque development. They report that JAML is expressed in macrophages and other cells in atherosclerotic plaques in both humans and mice, and that silencing JAML expression attenuates atherosclerotic plaque progression in mouse models of early and late stage plaque development. They demonstrate that JAML is required for oxidized-low density lipoprotein (OxLDL)-induced up-regulation of inflammatory cytokine production by macrophages, pointing to it as a potential therapeutic target for reducing ongoing plaque inflammation.

Identification of key genes involved in myocardial infarction

Background

This study focuses on the identification of conserved genes involved in myocardial infarction (MI), and then analyzed the differentially expressed genes (DEGs) between the incident and recurrent events to identify MI-recurrent biomarkers.

Methods

Gene expression data of MI peripheral blood were downloaded from GSE97320 and GSE66360 datasets. We identified the common DEGs in these two datasets by functional enrichment analysis and protein–protein interaction (PPI) network analysis. GSE48060 was further analyzed to validate the conserved genes in MI and to compare the DEGs between the incident and recurrent MI.

Results

A total of 477 conserved genes were identified in the comparison between MI and control. Protein–protein interaction (PPI) network showed hub genes, such as MAPK14, STAT3, and MAPKAPK2. Part of those conserved genes was validated in the analysis of GSE48060. The DEGs in the incident and recurrent MI showed significant differences, including RNASE2 and A2M-AS1 as the potential biomarkers of MI recurrence.

Conclusions

The conserved genes in the pathogenesis of MI were identified, benefit for target therapy. Meanwhile, some specific genes may be used as markers for the prediction of recurrent MI.

Electronic supplementary material

The online version of this article (10.1186/s40001-019-0381-x) contains supplementary material, which is available to authorized users.