Analysis of the differences in immune-related genes and immune cell subtypes in acute myocardial infarction.

Acute myocardial infarction (AMI) continues to be a leading cause of death globally, with distinct immune cell dynamics in ST-segment elevation myocardial infarction (STEMI) and non-ST-segment elevation myocardial infarction (NSTEMI) playing a critical role in disease progression and patient outcomes. Sample data for STEMI and NSTEMI were downloaded from the Sequence Read Archive (SRA) database (https://www.ncbi.nlm.nih.gov/sra). Differences and correlations of immune infiltrating cells were assessed by CIBERSORT. Differentially expressed genes (DEGs) were identified between STEMI and NSTEMI, followed by functional analysis. Immune-related DEGs were further identified. Some immune-related DEGs were selected to perform expression verification using real-time PCR. There was a significant difference in immune cells between STEMI and NSTEMI, including activated dendritic cells, memory CD4 T cells, mast cells, and CD8 T cells. A total of 229 DEGs were identified, with functions related to inflammatory regulation and drug metabolism. A total of 21 immune-related DEGs, which may play important roles in STEMI and NSTEMI, were identified. Among the 21 immune-related DEGs, genes like CCL18, NRP2, CXCR2, CXCL9, KIR2DL4, BPIFB1, and IL33 were significantly correlated with immune cells and had a tendency for differential expression between STEMI and NSTEMI patients. Our study reveals differences in the distribution of immune cell subsets between STEMI and NSTEMI, highlighting key immune-related genes and their association with immune cells, which may provide new insights into the treatment of AMI.

Circular RNA Profile in Atherosclerotic Disease: Regulation during ST-Elevated Myocardial Infarction.

Circular (circ) RNAs are non-coding RNAs with important functions in the nervous system, cardiovascular system, and cancer. Their role in atherosclerosis and myocardial infarction (MI) remains poorly described. We aim to investigate the potential circRNAs in immune cells during atherogenesis and examine the most regulated during MI and the modulation by interleukin (IL)-6 receptor inhibition by tocilizumab. Wild-type (WT) and ApoE-/- mice were fed an atherogenic diet for 10 weeks, and the circRNA profile was analyzed by circRNA microarray. Whole blood from patients with ST-elevated MI (STEMI) and randomized to tocilizumab (n = 21) or placebo (n = 19) was collected at admission, 3-7 days, and at 6 months, in addition to samples from healthy controls (n = 13). Primers for human circRNA were designed, and circRNA levels were measured using RT-qPCR. mRNA regulation of predicted circRNA targets was investigated by RNA sequencing. The expression of 867 circRNAs differed between atherogenic and WT mice. In STEMI patients, circUBAC2 was significantly lower than in healthy controls. CircANKRD42 and circUBAC2 levels were inversely correlated with troponin T, and for circUBAC2, an inverse correlation was also seen with final infarct size at 6 months. The predicted mRNA targets for circUBAC2 and circANKRD42 were investigated and altered levels of transcripts involved in the regulation of inflammatory/immune cells, apoptosis, and mitochondrial function were found. Finally, tocilizumab induced an up-regulation of circANKRD42 and circUBAC2 3-7 days after percutaneous coronary intervention. CircRNA levels were dysregulated in STEMI, potentially influencing the immune system, apoptosis, and mitochondrial function.

Pericardial Fluid Accumulates microRNAs That Regulate Heart Fibrosis after Myocardial Infarction.

Pericardial fluid (PF) has been suggested as a reservoir of molecular targets that can be modulated for efficient repair after myocardial infarction (MI). Here, we set out to address the content of this biofluid after MI, namely in terms of microRNAs (miRs) that are important modulators of the cardiac pathological response. PF was collected during coronary artery bypass grafting (CABG) from two MI cohorts, patients with non-ST-segment elevation MI (NSTEMI) and patients with ST-segment elevation MI (STEMI), and a control group composed of patients with stable angina and without previous history of MI. The PF miR content was analyzed by small RNA sequencing, and its biological effect was assessed on human cardiac fibroblasts. PF accumulates fibrotic and inflammatory molecules in STEMI patients, namely causing the soluble suppression of tumorigenicity 2 (ST-2), which inversely correlates with the left ventricle ejection fraction. Although the PF of the three patient groups induce similar levels of fibroblast-to-myofibroblast activation in vitro, RNA sequencing revealed that PF from STEMI patients is particularly enriched not only in pro-fibrotic miRs but also anti-fibrotic miRs. Among those, miR-22-3p was herein found to inhibit TGF-ß-induced human cardiac fibroblast activation in vitro. PF constitutes an attractive source for screening diagnostic/prognostic miRs and for unveiling novel therapeutic targets in cardiac fibrosis.

PCSK9 gene variations in the clinical setting of premature cardiovascular disease: A critical appraisal.

INTRODUCTION: Information about PCSK9 gene variations and its association with cardiovascular (CV) disease is controversial. We aimed to evaluate 3 reported polymorphisms in PSCK9 in a cohort of young patients with myocardial infarction with ST segment elevation (STEMI). METHODS: Retrospective study of consecutive patients with premature STEMI (2018-2023). 216 patients with STEMI due atherothrombotic coronary artery disease (CAD), confirmed by coronary angiogram, were included. We genotyped 3 polymorphisms in PCSK9 (rs12117661, rs2483205, rs505151) in 207 patients (DNA unavailable in 9) and a control group (N = 200). RESULTS: Mean age 49.4 ± 6,6 years (82.4% men). Genotypes frequencies distribution in patient's and control's cohorts did not deviate from the expected by Hardy-Weinberg equilibrium and there were no significant differences between patients and controls. Among patients, we did not find any association between PSCK9 genotypes and clinical variables (gender, age, CV risk factors, cholesterol levels, family history of premature CAD or number of coronary arteries affected). CONCLUSION: We did not find any association between PSCK9 genotypes (RS12117661, RS2483205 and RS505151) and any CV risk factors or the extent of CAD in a cohort of patients with premature STEMI. There were not differences in the genotype distribution between patients and controls.

Single-Cell Dissection of the Immune Response After Acute Myocardial Infarction.

BACKGROUND: The immune system's role in ST-segment-elevated myocardial infarction (STEMI) remains poorly characterized but is an important driver of recurrent cardiovascular events. While anti-inflammatory drugs show promise in reducing recurrence risk, their broad immune system impairment may induce severe side effects. To overcome these challenges, a nuanced understanding of the immune response to STEMI is needed. METHODS: For this, we compared peripheral blood mononuclear single-cell RNA-sequencing (scRNA-seq) and plasma protein expression over time (hospital admission, 24 hours, and 6-8 weeks post-STEMI) in 38 patients and 38 controls (95 995 diseased and 33 878 control peripheral blood mononuclear cells). RESULTS: Compared with controls, classical monocytes were increased and CD56dim natural killer cells were decreased in patients with STEMI at admission and persisted until 24 hours post-STEMI. The largest gene expression changes were observed in monocytes, associating with changes in toll-like receptor, interferon, and interleukin signaling activity. Finally, a targeted cardiovascular biomarker panel revealed expression changes in 33/92 plasma proteins post-STEMI. Interestingly, interleukin-6R, MMP9 (matrix metalloproteinase-9), and LDLR (low-density lipoprotein receptor) were affected by coronary artery disease-associated genetic risk variation, disease status, and time post-STEMI, indicating the importance of considering these aspects when defining potential future therapies. CONCLUSIONS: Our analyses revealed the immunologic pathways disturbed by STEMI, specifying affected cell types and disease stages. Additionally, we provide insights into patients expected to benefit most from anti-inflammatory treatments by identifying the genetic variants and disease stage at which these variants affect the outcome of these (drug-targeted) pathways. These findings advance our knowledge of the immune response post-STEMI and provide guidance for future therapeutic studies.

Identification of Potential Crucial Biomarkers in STEMI Through Integrated Bioinformatic Analysis. / Identificação de Potenciais Biomarcadores Cruciais em IAMCSST por Meio de Análise Bioinformática Integrada.

BACKGROUND: ST-segment elevation myocardial infarction (STEMI) is one of the leading causes of fatal cardiovascular diseases, which have been the prime cause of mortality worldwide. Diagnosis in the early phase would benefit clinical intervention and prognosis, but the exploration of the biomarkers of STEMI is still lacking. OBJECTIVES: In this study, we conducted a bioinformatics analysis to identify potential crucial biomarkers in the progress of STEMI. METHODS: We obtained GSE59867 for STEMI and stable coronary artery disease (SCAD) patients. Differentially expressed genes (DEGs) were screened with the threshold of |log2fold change| > 0.5 and p <0.05. Based on these genes, we conducted enrichment analysis to explore the potential relevance between genes and to screen hub genes. Subsequently, hub genes were analyzed to detect related miRNAs and DAVID to detect transcription factors for further analysis. Finally, GSE62646 was utilized to assess DEGs specificity, with genes demonstrating AUC results exceeding 75%, indicating their potential as candidate biomarkers. RESULTS: 133 DEGs between SCAD and STEMI were obtained. Then, the PPI network of DEGs was constructed using String and Cytoscape, and further analysis determined hub genes and 6 molecular complexes. Functional enrichment analysis of the DEGs suggests that pathways related to inflammation, metabolism, and immunity play a pivotal role in the progression from SCAD to STEMI. Besides, related-miRNAs were predicted, has-miR-124, has-miR-130a/b, and has-miR-301a/b regulated the expression of the largest number of genes. Meanwhile, Transcription factors analysis indicate that EVI1, AML1, GATA1, and PPARG are the most enriched gene. Finally, ROC curves demonstrate that MS4A3, KLRC4, KLRD1, AQP9, and CD14 exhibit both high sensitivity and specificity in predicting STEMI. CONCLUSIONS: This study revealed that immunity, metabolism, and inflammation are involved in the development of STEMI derived from SCAD, and 6 genes, including MS4A3, KLRC4, KLRD1, AQP9, CD14, and CCR1, could be employed as candidate biomarkers to STEMI.

FUNDAMENTO: O infarto do miocárdio com elevação do segmento ST (IAMCSST) é uma das principais causas de doenças cardiovasculares fatais, que têm sido a principal causa de mortalidade em todo o mundo. O diagnóstico na fase inicial beneficiaria a intervenção clínica e o prognóstico, mas ainda falta a exploração dos biomarcadores do IAMCSST. OBJETIVOS: Neste estudo, conduzimos uma análise bioinformática para identificar potenciais biomarcadores cruciais no progresso do IAMCSST. MÉTODOS: Obtivemos GSE59867 para pacientes com IAMCSST e doença arterial coronariana estável (DACE). Genes diferencialmente expressos (GDEs) foram selecionados com o limiar de |log2fold change| > 0,5 e p < 0,05. Com base nesses genes, conduzimos análises de enriquecimento para explorar a relevância potencial entre genes e para rastrear genes centrais. Posteriormente, os genes centrais foram analisados para detectar miRNAs relacionados e DAVID para detectar fatores de transcrição para análise posterior. Finalmente, o GSE62646 foi utilizado para avaliar a especificidade dos GDEs, com genes demonstrando resultados de AUC superiores a 75%, indicando seu potencial como candidatos a biomarcadores. Posteriormente, os genes centrais foram analisados para detectar miRNAs relacionados e DAVID para detectar fatores de transcrição para análise posterior. Finalmente, o GSE62646 foi utilizado para avaliar a especificidade dos GDEs, com genes demonstrando resultados de AUC superiores a 75%, indicando seu potencial como candidatos a biomarcadores. RESULTADOS: 133 GDEs entre DACE e IAMCSST foram obtidos. Em seguida, a rede PPI de GDEs foi construída usando String e Cytoscape, e análises posteriores determinaram genes centrais e 6 complexos moleculares. A análise de enriquecimento funcional dos GDEs sugere que as vias relacionadas à inflamação, metabolismo e imunidade desempenham um papel fundamental na progressão de DACE para IAMCSST. Além disso, foram previstos miRNAs relacionados, has-miR-124, has-miR-130a/b e has-miR-301a/b regularam a expressão do maior número de genes. Enquanto isso, a análise dos fatores de transcrição indica que EVI1, AML1, GATA1 e PPARG são os genes mais enriquecidos. Finalmente, as curvas ROC demonstram que MS4A3, KLRC4, KLRD1, AQP9 e CD14 exibem alta sensibilidade e especificidade na previsão de IAMCSST. CONCLUSÕES: Este estudo revelou que imunidade, metabolismo e inflamação estão envolvidos no desenvolvimento de IAMCSST derivado de DACE, e 6 genes, incluindo MS4A3, KLRC4, KLRD1, AQP9, CD14 e CCR1, poderiam ser empregados como candidatos a biomarcadores para IAMCSST.

Serum circRNA (Circ)_0051386 assists in the diagnosis of acute ST-segment elevation myocardial infarction and prediction of the occurrence of major adverse cardiovascular events after percutaneous coronary intervention.

BACKGROUND: This study aimed to uncover the diagnostic value of circRNA (Circ)_0051386 in acute ST-segment elevation myocardial infarction (STEMI) and its predictive value for the occurrence of adverse major adverse cardiovascular events (MACEs). METHODS: This study included 166 patients with STEMI and 83 health donors. The expression levels of serum Circ_0051386 in these participants were quantified using real-time quantitative polymerase chain reaction (RT-qPCR). Additionally, the incidence of MACEs during a 6-month follow-up period after percutaneous coronary intervention (PCI) was collected in the STEMI patient cohort. RESULTS: Before and after propensity score matching (PSM), Circ_0051386 all had higher expression levels in the patients with STEMI than the normal subjects (all p < .001)and robust diagnosis values for the STEMI (AUC = 0.766, 0.779). Kaplan-Meier curves showed the high expression Circ_0051386 group had a higher occurrence rate of MACEs during a 6-month follow-up after PCI in patients with STEMI and this phenomenon was confirmed by internal validation (all p < .05). In addition, the multivariate COX regression showed gensini score (HR = 1.020, 95% CI = 1.002 - 1.038, p = .028) and Circ_0051386 (HR = 2.468, 95% CI =1.548-3.935, p < .001)were independent risk factors of the occurrence of MACEs in patients with STEMI after PCI. Pearson analysis presented that Circ_0051386 was positively correlated with gensini scores (r = 0.33), IL-1ß (r = 0.55)and TNF-α(r = 0.41). CONCLUSION: Our study indicated that Circ_0051386 is a biomarker of the diagnostic for STEMI and the predictor of the MACEs in STEMI patients after PCI. Its potential role in STEMI may be the regulation of inflammation in the vascular endothelial.

Differential gene expression patterns in ST-elevation Myocardial Infarction and Non-ST-elevation Myocardial Infarction.

The ST-elevation Myocardial Infarction (STEMI) and Non-ST-elevation Myocardial Infarction (NSTEMI) might occur because of coronary artery stenosis. The gene biomarkers apply to the clinical diagnosis and therapeutic decisions in Myocardial Infarction. The aim of this study was to introduce, enrich and estimate timely the blood gene profiles based on the high-throughput data for the molecular distinction of STEMI and NSTEMI. The text mining data (50 genes) annotated with DisGeNET data (144 genes) were merged with the GEO gene expression data (5 datasets) using R software. Then, the STEMI and NSTEMI networks were primarily created using the STRING server, and improved using the Cytoscape software. The high-score genes were enriched using the KEGG signaling pathways and Gene Ontology (GO). Furthermore, the genes were categorized to determine the NSTEMI and STEMI gene profiles. The time cut-off points were identified statistically by monitoring the gene profiles up to 30 days after Myocardial Infarction (MI). The gene heatmaps were clearly created for the STEMI (high-fold genes 69, low-fold genes 45) and NSTEMI (high-fold genes 68, low-fold genes 36). The STEMI and NSTEMI networks suggested the high-score gene profiles. Furthermore, the gene enrichment suggested the different biological conditions for STEMI and NSTEMI. The time cut-off points for the NSTEMI (4 genes) and STEMI (13 genes) gene profiles were established up to three days after Myocardial Infarction. The study showed the different pathophysiologic conditions for STEMI and NSTEMI. Furthermore, the high-score gene profiles are suggested to measure up to 3 days after MI to distinguish the STEMI and NSTEMI.

Endothelial nitric oxide synthase (eNOS) gene polymorphism (Glu298asp) and nitric oxide (NO) levels in patients with ST-segment elevation myocardial infarction (STEMI).

BACKGROUND: Genetic polymorphism in endothelial Nitric Oxide Synthase (eNOS) are associated with occurrence of multiple cardiovascular diseases (CVDs). METHODS: This study included 300 young ST-segment elevation myocardial infarction (STEMI) patients and 300 healthy controls. STEMI patients were divided into two groups: premature coronary artery disease [CAD] (STEMI<40 years of age) and older STEMI (>40 years of age). Genetic polymorphisms in the eNOS gene (894G/T) was evaluated in both subjects and controls. Plasma levels of nitric oxide (NO) were estimated for both patients as well as controls. RESULTS: Mean age of the study population was 49.7 ± 9.2 years with premature CAD being present in 58 (19.3 %) patients. No significant difference at genotypic (P = 0.589, odds ratio (OR) = 0.9, 95 % CI = 0.6-1.6) and allelic level (P = 0.173, OR = 1.2, 95 % CI = 0.9-1.4) was observed between STEMI patients and healthy controls. Genotype 894 TT had significantly higher frequency in STEMI patients >40 years (P = 0.047, OR: 2.5; 95 % CI = 1.0-6.0). No significant difference at genotypic (P = 0.279) and allelic level (P = 0.493) was observed between premature CAD (STEMI age <40 years) and healthy controls. NO levels (131 ± 59.6 µM vs 118.11 ± 49.96 µM; P = 0.001) was significantly higher in healthy controls as compared to STEMI patients >40 years of age (P= 0.001). CONCLUSION: There was significant association of eNOS gene polymorphism Glu298Asp with STEMI patients > 40 years. However, this association was not observed in premature CAD patients. Lower levels of NO in STEMI patients >40 years suggests its potential role as a marker of CVD.

miR-619-5p and cardiogenic shock in patients with ST-segment elevation myocardial infarction.

BACKGROUND: Cardiogenic shock (CS) is a severe myocardial dysfunction secondary to various cardiac conditions including ST-segment elevation acute myocardial infarction (STEMI) and associated with a high risk of death. Little is known on epigenetic determinants in CS. Here, we investigated plasma miRNAs in relation to CS stratification in STEMI-patients. METHODS: STEMI-patients (n = 49), with (CS, n = 25) and without CS (non-CS, n = 24) fulfilling inclusion criteria were included from HSCSP-cohort (Derivation-cohort). CS-miRNAs were analysed by Affymetrix-microarray and RT-PCR. Results were validated in a second cohort of CS-patients (CardShock: n = 35) with similar inclusion/exclusion criteria as the derivation cohort. In silico analysis were performed to identify potential miRNA target genes. RESULTS: Of the 5-miRNA signature obtained from microarray analysis, miR-619-5p showed higher levels in CS than in Non-CS patients (p = .003) and discriminating power for CS by ROC (AUC: .752, p = .003). miR-619-5p directly associated with risk scores [GRACE, p = .001; CardShock, p < .001]. Furthermore, miR-619-5p showed discrimination power for death in CS. Thus, miRNA levels were significantly higher in patients with mortality outcome both in the Derivation HSCSP-cohort (p = .02; AUC: .78 ± .095) and the Validation CardShock-cohort (p = .017; AUC: .737 ± .086) By in silico analysis, miR-619-5p target genes and TNF-alpha were involved in the regulation of inflammation. miR-619-5p and TNF-alpha levels discriminated mortality outcome in CS-patients during 30-day follow-up (Validation-Cohort: ROC: .812, p = .002; HR: 9.99, p = .003). CONCLUSIONS: Up-regulation of miR-619-5p is found in the plasma of STEMI-patients with CS and mortality outcome. These findings highlight the specificity of epigenetic regulation of inflammation on the disease severity of MI.

Transcription factor 21 rs12190287 polymorphism is related to stable angina and ST elevation myocardial infarction in a Chinese Population.

Background: Transcription factor 21 (TCF21, epicardin, capsuling, pod-1) is expressed in the epicardium and is involved in the regulation of cell fate and differentiation via epithelial-mesenchymal transformation during development of the heart. In addition, TCF21 can suppress the differentiation of epicardial cells into vascular smooth muscle cells and promote cardiac fibroblast development. This study aimed to explore whether TCF21 gene (12190287G/C) variants affect coronary artery disease risk. Methods: We enrolled 381 patients who had stable angina, 138 with ST elevation myocardial infarction (STEMI), and 276 healthy subjects. Genotyping of rs12190287 of the TCF21 gene was performed. Results: Higher frequencies of the CC genotype were found in the patients with stable angina/STEMI than in the healthy controls. After adjusting for diabetes mellitus, hypertension, age, sex, smoking, body mass index and hyperlipidemia, the patients with the CC genotype of the TCF21 gene were associated with 2.49- and 9.19-fold increased risks of stable angina and STEMI, respectively, compared to the patients with the GG genotype. Furthermore, TCF21 CC genotypes showed positive correlations with both stable angina and STEMI, whereas TCF21 GG genotypes exhibited a negative correlation with STEMI. Moreover, the stable angina and STEMI patients with the CC genotype had significantly elevated high-sensitivity C-reactive protein levels than those with the GG genotype. In addition, significant associations were found between type 2 diabetes mellitus, hypertension, and hyperlipidemia with TCF21 gene polymorphisms (p for trend < 0.05). Conclusion: TCF21 gene polymorphisms may increase susceptibility to stable angina and STEMI.

Platelet Function and Maturity and Related microRNA Expression in Whole Blood in Patients with ST-Segment Elevation Myocardial Infarction.

BACKGROUND: Reduced effect of antiplatelet therapy has been reported in patients with ST-segment elevation myocardial infarction (STEMI). MicroRNAs (miRs) may influence platelet function and maturity, and subsequently the effect of antiplatelet therapy. OBJECTIVES: We aimed to explore the association between miR expression and platelet function and maturity in patients with acute STEMI and healthy individuals. METHODS: We performed an observational study of STEMI patients admitted directly to primary percutaneous coronary intervention. Patients were treated with antiplatelet therapy according to guidelines. Within 24 hours after admission, blood samples were obtained to measure: the expression of 10 candidate miRs, platelet function markers using advanced flow cytometry, platelet aggregation, serum thromboxane B2, and platelet maturity markers. Furthermore, blood samples from healthy individuals were obtained to determine the normal variation. RESULTS: In total, 61 STEMI patients and 50 healthy individuals were included. STEMI patients had higher expression of miR-21-5p, miR-26b-5p, and miR-223-3p and lower expression of miR-150-5p, miR423-5p, and miR-1180-3p than healthy individuals. In STEMI patients, the expression of miR-26b-5p showed the most consistent association with platelet function (all p-values <0.05, Spearman's rho ranging from 0.27 to 0.41), while the expression of miR-150-5p and miR-223-3p showed negative associations with platelet function. No association between miR expression and platelet maturity markers was observed. CONCLUSION: In patients with STEMI, the expression of six miRs was significantly different from healthy individuals. The expression of miR-26b-5p may affect platelet function in acute STEMI patients and potentially influence the effect of antiplatelet therapy.

Stratification of acute myocardial and endothelial cell injury, salvage index and final infarct size by systematic microRNA profiling in acute ST-elevation myocardial infarction.

AIM: Acute injury and subsequent remodelling responses to ST-segment elevation myocardial infarction (STEMI) are major determinants of clinical outcome. Current imaging and plasma biomarkers provide delayed readouts of myocardial injury and recovery. Here, we sought to systematically characterize all microRNAs (miRs) released during the acute phase of STEMI and relate miR release to magnetic resonance imaging (MRI) findings to predict acute and late responses to STEMI, from a single early blood sample. METHODS AND RESULTS: miRs were quantified in blood samples obtained from patients after primary PCI (PPCI) for STEMI. Cardiac MRI (cMRI) was performed to quantify myocardial edema, infarct size and salvage index. Regression models were constructed to predict these outcomes measures, which were then tested with a validation cohort. Transcoronary miR release was quantified from paired measurements of coronary artery and coronary sinus samples. A cell culture model was used to identify endothelial cell-derived miRs.A total of 72 patients undergoing PPCI for acute STEMI underwent miR analysis and cMRI. About >200 miRs were detectable in plasma after STEMI, from which 128 miRs were selected for quantification in all patients. Known myocardial miRs demonstrated a linear correlation with troponin release, and these increased across the transcoronary gradient. We identified novel miRs associated with microvascular injury and myocardial salvage. Regression models were constructed using a training cohort, then tested in a validation cohort, and predicted myocardial oedema, infarct size and salvage index. CONCLUSION: Analysis of miR release after STEMI identifies biomarkers that predict both acute and late outcomes after STEMI. A novel miR-based biomarker score enables the estimation of area at risk, late infarct size and salvage index from a single blood sample 6 hours after PPCI, providing a simple and rapid alternative to serial cMRI characterization of STEMI outcome.

Investigating the expression level of miR-17-3p, miR-101-3p, miR-335-3p, and miR-296-3p in the peripheral blood of patients with acute myocardial infarction.

The role of inflammation has been proven in acute myocardial infarction (AMI) pathogenesis. Due to the effect of NLRP3 gene expression in the inflammation process of MI, we aimed to explore the expression changes and diagnostic power of four inflammation-related miRNAs including miR-17-3p, miR-101-3p, miR-335-3p, miR-296-3p and their potential target, NLRP3, in ST-segment elevation myocardial infarction (STEMI), and non-STEMI (NSTEMI) patients as two major classes of AMI. The expression level of these genes were evaluated in 300 participants equally divided into three groups of STEMI, NSTEMI, and control using quantitative real-time PCR. The expression level of NLRP3 was upregulated in STEMI and NSTEMI patients compared to control subjects. Besides, the expression levels of miR-17-3p, miR-101-3p, and miR-296-3p were significantly downregulated in STEMI and NSTEMI patients compared to controls. The increased expression of NLRP3 had a very strong inverse correlation with miR-17-3p in patients with STEMI and with miR-101-3p in the STEMI and NSTEMI patients. ROC curve analysis showed that the expression level of miR-17-3p had the highest diagnostic power for discrimination between STEMI patients and controls. Remarkably, the combination of all markers resulted in a higher AUC. In summary, there is a significant association between the expression levels of miR-17-3p, miR-101-3p, miR-335-3p, miR-296-3p, and NLRP3 and the incidence of AMI. Although the miR-17-3p expression level has the highest diagnostic power to distinguish between STEMI patients and control subjects, the combination of these miRNAs and NLRP3 could serve as a novel potential diagnostic biomarker of STEMI.

M6A regulator methylation patterns and characteristics of immunity in acute ST-segment elevation myocardial infarction.

M6A methylation is the most prevalent and abundant RNA modification in mammals. Although there are many studies on the regulatory role of m6A methylation in the immune response, the m6A regulators in the pathogenesis of acute ST-segment elevation myocardial infarction (STEMI) remain unclear. We comprehensively analysed the role of m6A regulators in STEMI and built a predictive model, revealing the relationship between m6A methylations and the immune microenvironment. Differential analysis revealed that 18 of 24 m6A regulators were significantly differentially expressed, and there were substantial interactions between the m6A regulator. Then, we established a classifier and nomogram model based on 6 m6A regulators, which can easily distinguish the STEMI and control samples. Finally, two distinct m6A subtypes were obtained and significantly differentially expressed in terms of infiltrating immunocyte abundance, immune reaction activity and human leukocyte antigen genes. Three hub m6A phenotype related genes (RAC2, RELA, and WAS) in the midnightblue module were identified by weighted gene coexpression network analysis, and were associated with immunity. These findings suggest that m6A modification and the immune microenvironment play a key role in the pathogenesis of STEMI.

Elevated Levels of Circulating lncRNAs LIPCAR and MALAT1 Predict an Unfavorable Outcome in Acute Coronary Syndrome Patients.

Coronary artery disease (CAD) is a leading cause of mortality worldwide. In this study, we aimed to assess the potential of plasma long non-coding RNAs (lncRNAs) LIPCAR and MALAT1 and microRNAs (miRNAs) miR-142-3p and miR-155-5p to discriminate unstable CAD patients from stable ones. 23 stable angina (SA), 21 unstable angina (UA), and 50 ST-segment elevation myocardial infarction (STEMI) patients were enrolled; their plasma was collected. ncRNA plasma levels were evaluated using RT-qPCR. All measured ncRNA levels were significantly increased in UA patients' plasma compared to SA patients' plasma and in STEMI-with major adverse cardiovascular event (MACE) patients' plasma vs. STEMI-without MACE patients' plasma. ROC analysis showed that increased levels of LIPCAR and MALAT1 were associated with UA, and the prognostic model improved with the addition of miR-155-5p levels. The assessed lncRNAs discriminated between hyperglycemic (HG) and normoglycemic (NG) UA patients, and they were associated with MACE incidence in STEMI patients; this prediction was improved by the addition of miR-142-3p levels to the ROC multivariate model. We propose LIPCAR and MALAT1 as effective diagnostic markers for vulnerable CAD, their association with HG in UA patients, and as robust predictors for unfavorable evolution of STEMI patients.

Exploring an immune cells-related molecule in STEMI by bioinformatics analysis.

BACKGROUND: ST-elevated myocardial infarction (STEMI) is the leading cause of mortality worldwide. The mortality rate of heart attacks has decreased due to various preventive factors and the development of early diagnostic resuscitation measures, but the long-term prognosis remains poor. The present study aimed to identify novel serum biomarkers in STEMI patients and explored a possible new mechanism of STEMI from an immune molecular angle with bioinformatics analysis. METHODS: Gene expression profiles were obtained from Gene Expression Omnibus (GEO) database. Differential gene analysis, machine learning algorithms, gene set enrichment analysis, and immune cell infiltration analysis were conducted using R software. RESULTS: We identified 146 DEGs (differentially expressed genes) in the integrated dataset between the STEMI and CAD (coronary artery disease) groups. Immune infiltration analysis indicated that eleven cell types were differentially infiltrated. Through correlation analysis, we further screened 25 DEGs that showed a high correlation with monocytes and neutrophils. Afterwards, five genes consistently selected by all three machine learning algorithms were considered candidate genes. Finally, we identified a hub gene (ADM) as a biomarker of STEMI. AUC curves showed that ADM had more than 80% high accuracy in all datasets. CONCLUSIONS: In this study, we explored a potentially new mechanism of STEMI from an immune molecular perspective, which might provide insights into the pathogenesis of STEMI. ADM positively correlated with monocytes and neutrophils, suggesting its potential role in the immune response during STEMI. Additionally, we validated the diagnostic performance of ADM in two external datasets, which could help to develop new diagnostic tools or therapeutic strategies.

Non-invasive STEMI-related biomarkers based on meta-analysis and gene prioritization.

BACKGROUND AND AIMS: Acute ST-Segment Myocardial infarction (STEMI) is a common cardiovascular issue with a considerable burden of the disease. The underlying genetic basis and non-invasive markers were not well-established. METHODS: Here, we implemented a systematic literature review and meta-analyses integration methods on 217 STEMI patients and 72 normal individuals to prioritize and detect the STEMI-related non-invasive markers. Five high-scored genes were experimentally assessed on 10 STEMI patients and 9 healthy controls. Finally, the presence of co-expressed nodes of top-score genes was explored. RESULTS: The differential expression of ARGL, CLEC4E, and EIF3D were significant for Iranian patients. The ROC curve for gene CLEC4E revealed an AUC (95% CI) of 0.786 (0.686-0.886) in the prediction of STEMI. The Cox-PH model was fitted to stratify high/low risk heart failure progression (CI-index = 0.83, Likelihood-Ratio-Test = 3e-10). The SI00AI2 was a common biomarker between STEMI and NSTEMI patients. CONCLUSIONS: In conclusion, the high-scored genes and prognostic model could be applicable for Iranian patients.

Identification of Cx43 variants predisposing to ventricular fibrillation in the acute phase of ST-elevation myocardial infarction.

AIMS: Ventricular fibrillation (VF) occurring in the acute phase of ST-elevation myocardial infarction (STEMI) is the leading cause of sudden cardiac death worldwide. Several studies showed that reduced connexin 43 (Cx43) expression and reduced conduction velocity increase the risk of VF in acute myocardial infarction (MI). Furthermore, genetic background might predispose individuals to primary VF (PVF). The primary objective was to evaluate the presence of GJA1 variants in STEMI patients. The secondary objective was to evaluate the arrhythmogenic impact of GJA1 variants in STEMI patients with VF. METHODS AND RESULTS: The MAP-IDM prospective cohort study included 966 STEMI patients and was designed to identify genetic predisposition to VF. A total of 483 (50.0%) STEMI patients with PVF were included. The presence of GJA1 variants increased the risk of VF in STEMI patients [from 49.1 to 70.8%, P = 0.0423; odds ratio (OR): 0.40; 95% confidence interval: 0.16-0.97; P = 0.04]. The risk of PVF decreased with beta-blocker intake (from 53.5 to 44.8%, P = 0.0085), atrial fibrillation (from 50.7 to 26.4%, P = 0.0022), and with left ventricular ejection fraction >50% (from 60.2 to 41.4%, P < 0.0001). Among 16 GJA1 variants, three novel heterozygous missense variants were identified in three patients: V236I, H248R, and I327M. In vitro studies of these variants showed altered Cx43 localization and decreased cellular communication, mainly during acidosis. CONCLUSION: Connexin 43 variants are associated with increased VF susceptibility in STEMI patients. Restoring Cx43 function may be a potential therapeutic target to prevent PVF in patients with acute MI. CLINICAL TRIAL REGISTRATION: Clinical Trial Registration: https://clinicaltrials.gov/ct2/show/NCT00859300.