Identification of Crucial Genes and Pathways in Human Arrhythmogenic Right Ventricular Cardiomyopathy by Coexpression Analysis

Transcriptome and open chromatin analysis reveals the process of myocardial cell development and key pathogenic target proteins in Long QT syndrome type 7

OBJECTIVE

Long QT syndrome type 7 (Andersen-Tawil syndrome, ATS), which is caused by KCNJ2 gene mutation, often leads to ventricular arrhythmia, periodic paralysis and skeletal malformations. The development, differentiation and electrophysiological maturation of cardiomyocytes (CMs) changes promote the pathophysiology of Long QT syndrome type 7(LQT7). We aimed to specifically reproduce the ATS disease phenotype and study the pathogenic mechanism.

METHODS AND RESULTS

We established a cardiac cell model derived from human induced pluripotent stem cells (hiPSCs) to the phenotypes and electrophysiological function, and the establishment of a human myocardial cell model that specifically reproduces the symptoms of ATS provides a reliable platform for exploring the mechanism of this disease or potential drugs. The spontaneous pulsation rate of myocardial cells in the mutation group was significantly lower than that in the repair CRISPR group, the action potential duration was prolonged, and the Kir2.1 current of the inward rectifier potassium ion channel was decreased, which is consistent with the clinical symptoms of ATS patients. Only ZNF528, a chromatin-accessible TF related to pathogenicity, was continuously regulated beginning from the cardiac mesodermal precursor cell stage (day 4), and continued to be expressed at low levels, which was identified by WGCNA method and verified with ATAC-seq data in the mutation group. Subsequently, it indicated that seven pathways were downregulated (all p < 0.05) by used single sample Gene Set Enrichment Analysis to evaluate the overall regulation of potassium-related pathways enriched in the transcriptome and proteome of late mature CMs. Among them, the three pathways (GO: 0008076, GO: 1990573 and GO: 0030007) containing the mutated gene KCNJ2 is involved that are related to the whole process by which a potassium ion enters the cell via the inward rectifier potassium channel to exert its effect were inhibited. The other four pathways are related to regulation of the potassium transmembrane pathway and sodium:potassium exchange ATPase (p < 0.05). ZNF528 small interfering (si)-RNA was applied to hiPSC-derived cardiomyocytes for CRISPR group to explore changes in potassium ion currents and growth and development related target protein levels that affect disease phenotype. Three consistently downregulated proteins (KCNJ2, CTTN and ATP1B1) associated with pathogenicity were verificated through correlation and intersection analysis.

CONCLUSION

This study uncovers TFs and target proteins related to electrophysiology and developmental pathogenicity in ATS myocardial cells, obtaining novel targets for potential therapeutic candidate development that does not rely on gene editing.

Integrated analysis of WGCNA and machine learning identified diagnostic biomarkers in dilated cardiomyopathy with heart failure

The etiologies and pathogenesis of dilated cardiomyopathy (DCM) with heart failure (HF) remain to be defined. Thus, exploring specific diagnosis biomarkers and mechanisms is urgently needed to improve this situation. In this study, three gene expression profiling datasets (GSE29819, GSE21610, GSE17800) and one single-cell RNA sequencing dataset (GSE95140) were obtained from the Gene Expression Omnibus (GEO) database. GSE29819 and GSE21610 were combined into the training group, while GSE17800 was the test group. We used the weighted gene co-expression network analysis (WGCNA) and identified fifteen driver genes highly associated with DCM with HF in the module. We performed the least absolute shrinkage and selection operator (LASSO) on the driver genes and then constructed five machine learning classifiers (random forest, gradient boosting machine, neural network, eXtreme gradient boosting, and support vector machine). Random forest was the best-performing classifier established on five Lasso-selected genes, which was utilized to select out NPPA, OMD, and PRELP for diagnosing DCM with HF. Moreover, we observed the up-regulation mRNA levels and robust diagnostic accuracies of NPPA, OMD, and PRELP in the training group and test group. Single-cell RNA-seq analysis further demonstrated their stable up-regulation expression patterns in various cardiomyocytes of DCM patients. Besides, through gene set enrichment analysis (GSEA), we found TGF-β signaling pathway, correlated with NPPA, OMD, and PRELP, was the underlying mechanism of DCM with HF. Overall, our study revealed NPPA, OMD, and PRELP serving as diagnostic biomarkers for DCM with HF, deepening the understanding of its pathogenesis.

PRKAR1A and SDCBP Serve as Potential Predictors of Heart Failure Following Acute Myocardial Infarction

Background and Objectives

Early diagnosis of patients with acute myocardial infarction (AMI) who are at a high risk of heart failure (HF) progression remains controversial. This study aimed at identifying new predictive biomarkers of post-AMI HF and at revealing the pathogenesis of HF involving these marker genes.

Methods and Results

A transcriptomic dataset of whole blood cells from AMI patients with HF progression (post-AMI HF, n = 16) and without progression (post-AMI non-HF, n = 16) was analyzed using the weighted gene co-expression network analysis (WGCNA). The results indicated that one module consisting of 720 hub genes was significantly correlated with post-AMI HF. The hub genes were validated in another transcriptomic dataset of peripheral blood mononuclear cells (post-AMI HF, n = 9; post-AMI non-HF, n = 8). PRKAR1A, SDCBP, SPRED2, and VAMP3 were upregulated in the two datasets. Based on a single-cell RNA sequencing dataset of leukocytes from heart tissues of normal and infarcted mice, PRKAR1A was further verified to be upregulated in monocytes/macrophages on day 2, while SDCBP was highly expressed in neutrophils on day 2 and in monocytes/macrophages on day 3 after AMI. Cell-cell communication analysis via the "CellChat" package showed that, based on the interaction of ligand-receptor (L-R) pairs, there were increased autocrine/paracrine cross-talk networks of monocytes/macrophages and neutrophils in the acute stage of MI. Functional enrichment analysis of the abovementioned L-R genes together with PRKAR1A and SDCBP performed through the Metascape platform suggested that PRKAR1A and SDCBP were mainly involved in inflammation, apoptosis, and angiogenesis. The receiver operating characteristic (ROC) curve analysis demonstrated that PRKAR1A and SDCBP, as well as their combination, had a promising prognostic value in the identification of AMI patients who were at a high risk of HF progression.

Conclusion

This study identified that PRKAR1A and SDCBP may serve as novel biomarkers for the early diagnosis of post-AMI HF and also revealed their potentially regulatory mechanism during HF progression.

Identification of IL-6 as a potential mediator of the myocardial fibrosis that occurs in response to surgery with cardiopulmonary bypass in children with Tetralogy of Fallot

BACKGROUND

Tetralogy of Fallot is a common CHD. Studies have shown a close link between heart failure and myocardial fibrosis. Interleukin-6 has been suggested to be a post-independent factor of heart failure. This study aimed to explore the relationship between IL-6 and myocardial fibrosis during cardiopulmonary bypass.

MATERIAL AND METHODS

We downloaded the expression profile dataset GSE132176 from Gene Expression Omnibus. After normalising the raw data, Gene Set Enrichment Analysis and differential gene expression analysis were performed using R. Further, a weighted gene correlation network analysis and a protein-protein interaction network analysis were used to identify HUB genes. Finally, we downloaded single-cell expression data for HUB genes using PanglaoDB.

RESULTS

There were 119 differentially expressed genes in right atrium tissues comparing the post-CPB group with the pre-CPB group. IL-6 was found to be significantly up-regulated in the post-CPB group. Six genes (JUN, FOS, ATF3, EGR1, IL-6, and PTGS2) were identified as HUB genes by a weighted gene correlation network analysis and a protein-protein interaction network analysis. Gene Set Enrichment Analysis showed that IL-6 affects the myocardium during CPB mainly through the JAK/STAT signalling pathway. Finally, we used PanglaoDB data to analyse the single-cell expression of the HUB genes.

CONCLUSION

Our findings suggest that high expression of IL-6 and the activation of the JAK/STAT signalling pathway during CPB maybe the potential mechanism of myocardial fibrosis. We speculate that the high expression of IL-6 might be an important factor leading to heart failure after ToF surgery. We expect that these findings will provide a basis for the development of targeted drugs.

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.

Detecting imperative genes and infiltrating immune cells in chronic Chagas cardiomyopathy by bioinformatics analysis

Chronic Chagas cardiomyopathy (CCC) is an acquired inflammatory cardiomyopathy triggered by the protozoan Trypanosoma cruzi infection. Although microvascular and neurogenic dysfunction and inflammation with persistent parasite presence in the heart may play a major pathogenetic role, little is known about the overall picture of gene co-expression regulating CCC. In this study, we aimed to explore the key biological pathways, hub genes and the landscope of infiltrating immune cells associated with inflammation in chronic Chagas cardiomyopathy. A weighted gene co-expression network analysis (WGCNA) was conducted based on the gene expression profiles from patients with and without chronic Chagas cardiomyopathy (GSE84796). Twelve coexpression modules were identified from the top 25% variant genes. Among them, the turquoise and black module were significantly positively correlated with CCC, which were highly enriched in Th1 and Th2 cell differentiation, the Cytokine-cytokine receptor interaction,NF-kappa B signaling pathway and T cell receptor signaling pathway. In addition, four genes (TBX21, ZAP70,IL2RB and CD69) were selected as candidate hub genes. Gene expression for hub genes were higher in CCC tissues compared to tissues from healthy controls. Additionally, gene set enrichment analysis (GSEA) analysis showed that high expressions of these hub genes were significantly correlated with interferon α response and interferon γ response. The microarray dataset GSE41089 further confirmed that although CD69 was not detected, the expression of TBX21, IL2RB and ZAP70 was also significantly up-regulated in the CCC mice compared to controls. We further studied the immune cells infiltration in CCC patients with CIBERSORT. The fraction of Mast cells activated,T cells CD8 and T cells gamma delta were significantly increased in CCC patients compared with control. Our research provides a more effective understanding of the pathogenesis of CCC and could help in future strategies for new diagnostic and therapeutic approaches for CCC patients.

Pathogenesis of arrhythmogenic cardiomyopathy: role of inflammation

Arrhythmogenic cardiomyopathy (AC) is an inherited disease characterized by progressive breakdown of heart muscle, myocardial tissue death, and fibrofatty replacement. In most cases of AC, the primary lesion occurs in one of the genes encoding desmosomal proteins, disruption of which increases membrane fragility at the intercalated disc. Disrupted, exposed desmosomal proteins also serve as epitopes that can trigger an autoimmune reaction. Damage to cell membranes and autoimmunity provoke myocardial inflammation, a key feature in early stages of the disease. In several preclinical models, targeting inflammation has been shown to blunt disease progression, but translation to the clinic has been sparse. Here we review current understanding of inflammatory pathways and how they interact with injured tissue and the immune system in AC. We further discuss the potential role of immunomodulatory therapies in AC.

Crosstalk between coagulation and complement activation promotes cardiac dysfunction in arrhythmogenic right ventricular cardiomyopathy

Aims: We previously found that complement components are upregulated in the myocardium of patients with arrhythmogenic right ventricular cardiomyopathy (ARVC), and inhibiting the complement receptor C5aR reduces disease severity in desmin knockout (Des-/- ) mice, a model for ARVC. Here, we examined the mechanism underlying complement activation in ARVC, revealing a potential new therapeutic target. Methods: First, immunostaining, RT-PCR and western blot were used to detect the expression levels of complement and coagulation factors. Second, we knocked out the central complement component C3 in Des-/- mice (ARVC model) by crossing Des-/- mice with C3-/- mice to explore whether complement system activation occurs independently of the conventional pathway. Then, we evaluated whether a targeted intervention to coagulation system is effective to reduce myocardium injury. Finally, the plasma sC5b9 level was assessed to investigate the role in predicting adverse cardiac events in the ARVC cohort. Results: The complement system is activated in the myocardium in ARVC. Autoantibodies against myocardial proteins provided a possible mechanism underlying. Moreover, we found increased levels of myocardial C5 and the serum C5a in Des-/-C3-/- mice compared to wild-type mice, indicating that C5 is activated independently from the conventional pathway, presumably via the coagulation system. Crosstalk between the complement and coagulation systems exacerbated the myocardial injury in ARVC mice, and this injury was reduced by using the thrombin inhibitor lepirudin. In addition, we found significantly elevated plasma levels of sC5b9 and thrombin in patients, and this increase was correlated with all-cause mortality. Conclusions: These results suggest that crosstalk between the coagulation and complement systems plays a pathogenic role in cardiac dysfunction in ARVC. Thus, understanding this crosstalk may have important clinical implications with respect to diagnosing and treating ARVC.

Identification of monocyte-associated genes as predictive biomarkers of heart failure after acute myocardial infarction

BACKGROUND

Acute myocardial infarction (AMI) is a major contributor of heart failure (HF). Peripheral blood mononuclear cells (PBMCs), mainly monocytes, are the essential initiators of AMI-induced HF. The powerful biomarkers for early identification of AMI patients at risk of HF remain elusive. We aimed to identify monocyte-related critical genes as predictive biomarkers for post-AMI HF.

METHODS

We performed weighted gene co-expression network analysis (WGCNA) on transcriptomics of PBMCs from AMI patients who developed HF or did not. Functional enrichment analysis of genes in significant modules was performed via Metascape. Then we obtained the single-cell RNA-sequencing data of recruited monocytes/macrophages from AMI and control mice using the Scanpy and screened 381 differentially expressed genes (DEGs) between the two groups. We validated the expression changes of the 25 genes in cardiac macrophages from AMI mice based on bulk RNA-sequencing data and PBMCs data mentioned above.

RESULTS

In our study, the results of WGCNA showed that two modules containing 827 hub genes were most significantly associated with post-AMI HF, which mainly participated in cell migration, inflammation, immunity, and apoptosis. There were 25 common genes between DEGs and hub genes, showing close relationship with inflammation and collagen metabolism. CUX1, CTSD and ADD3 exhibited consistent changes in three independent studies. Receiver operating characteristic curve analysis showed that each of the three genes had excellent performance in recognizing post-AMI HF patients.

CONCLUSION

Our findings provided a set of three monocyte-related biomarkers for the early prediction of HF development after AMI as well as potential therapeutic targets of post-AMI HF.

Systematic analysis of molecular mechanisms of heart failure through the pathway and network-based approach

AIMS

The molecular networks and pathways involved in heart failure (HF) are still largely unknown. The present study aimed to systematically investigate the genes associated with HF, comprehensively explore their interactions and functions, and identify possible regulatory networks involved in HF.

MAIN METHODS

The weighted gene coexpression network analysis (WGCNA), crosstalk analysis, and Pivot analysis were used to identify gene connections, interaction networks, and molecular regulatory mechanisms. Functional analysis and protein-protein interaction (PPI) were performed using DAVID and STRING databases. Gene set variation analysis (GSVA) and receiver operating characteristic (ROC) curve analysis were also performed to evaluate the relationship of the hub genes with HF.

KEY FINDINGS

A total of 5968 HF-related genes were obtained to construct the co-expression networks, and 18 relatively independent and closely linked modules were identified. Pivot analysis suggested that four transcription factors and five noncoding RNAs were involved in regulating the process of HF. The genes in the module with the highest positive correlation to HF was mainly enriched in cardiac remodeling and response to stress. Five upregulated hub genes (ASPN, FMOD, NT5E, LUM, and OGN) were identified and validated. Furthermore, the GSVA scores of the five hub genes for HF had a relatively high areas under the curve (AUC).

SIGNIFICANCE

The results of this study revealed specific molecular networks and their potential regulatory mechanisms involved in HF. These may provide new insight into understanding the mechanisms underlying HF and help to identify more effective therapeutic targets for HF.

Network-Based Approach to Identify the Antiproliferative Mechanisms of Bruceine D in Breast Cancer From the Cancer Genome Atlas

Bruceine D (BD) is a natural compound extracted from a Chinese herb Brucea javanica that has been used for anti-inflammatory and anti-cancer treatment. However, little is reported about BD's effects in breast cancer tumorigenesis. In this paper, we aimed to investigate the effect of BD in breast cancer and elucidate the potential mechanism of BD by integrated multiple databases. Our data suggested BD inhibited MCF-7 and MDA-MB-231 cells proliferation and promoted cells apoptosis. We integrated multiple bioinformatics analysis strategies to identify genes, hub modules and pathways associated with BD treatment. Three key pathways, including AMIT_SERUM_RESPONSE_40_MCF10A, BILD_HRAS_ONCOGENIC_SIGNATURE, and NAGASHIMA_NRG1_SIGNALING_UP were identified to be associated with therapeutic effects of BD in breast cancer. Additionally, we validated the key genes by using quantitative real-time PCR and western blot. In conclusion, these findings revealed potential molecular mechanisms of BD to treat breast cancer by affecting AMIT_SERUM_RESPONSE_40_MCF10A, BILD_HRAS_ONCOGENIC_SIGNATURE, and NAGASHIMA_NRG1_SIGNALING_UP pathways and regulating expression of ZFP36, EGR1, and FOS.

Proteomic and metabolomic characterization of cardiac tissue in acute myocardial ischemia injury rats

The pathological process and mechanism of myocardial ischemia (MI) is very complicated, and remains unclear. An integrated proteomic-metabolomics analysis was applied to comprehensively understand the pathological changes and mechanism of MI. Male Sprague-Dawley rats were randomly divided into a mock surgery (MS) group and an MI group. The MI model was made by ligating the left anterior descending coronary artery, twenty-four hours after which, echocardiography was employed to assess left ventricular (LV) function variables. Blood samples and left ventricular tissues were collected for ELISA, metabolomics and proteomics analysis. The results showed that LV function, including ejection fraction (EF) and fractional shortening (FS), was significantly reduced and the level of cTnT in the serum increased after MI. iTRAQ proteomics showed that a total of 169 proteins were altered including 52 and 117 proteins with increased and decreased expression, respectively, which were mainly involved in the following activities: complement and coagulation cascades, tight junction, regulation of actin cytoskeleton, MAPK signaling pathway, endocytosis, NOD-like receptor signaling pathway, as well as phagosome coupled with vitamin digestion and absorption. Altered metabolomic profiling of this transition was mostly enriched in pathways including ABC transporters, glycerophospholipid metabolism, protein digestion and absorption and aminoacyl-tRNA biosynthesis. The integrated metabolomics and proteomics analysis indicated that myocardial injury after MI is closely related to several metabolic pathways, especially energy metabolism, amino acid metabolism, vascular smooth muscle contraction, gap junction and neuroactive ligand-receptor interaction. These findings may contribute to understanding the mechanism of MI and have implication for new therapeutic targets.

Potentially Critical Roles of NDUFB5, TIMMDC1, and VDAC3 in the Progression of Septic Cardiomyopathy Through Integrated Bioinformatics Analysis

Septic cardiomyopathy (SC) is a rare and harmful cardiovascular disease with decreased left ventricular (LV) output and multiple organ failure, which poses a serious threat to human life. Despite the advances in SC, its diagnostic basis and treatment methods are limited, and the specific diagnostic biomarkers and its candidate regulatory targets have not yet been fully established. In this study, the GSE79962 gene expression profile was retrieved, with 20 patients with SC and 11 healthy donors as control. Weighted gene coexpression network analysis (WGCNA) was employed to investigate gene modules that were strongly correlated with clinical phenotypes. Blue module was found to be most significantly related to SC. Moreover, Gene Ontology (GO) functional enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were performed on the coexpression genes in blue module and showed that it was associated with metabolic pathways, oxidative phosphorylation, and cardiac muscle contraction. Furthermore, a total of 10 hub genes NDUFB5, TIMMDC1, VDAC3, COQ10A, MRPL16 (mitochondrial ribosomal protein L16), C3orf43, TMEM182, DLAT, NDUFA8, and PDHB (pyruvate dehydrogenase E1 beta subunit) in the blue module were identified at transcriptional level and further validated at translational level in myocardium of an lipopolysaccharide-induced septic cardiac dysfunction mouse model. Overall, the results of quantitative real-time polymerase chain reaction were consistent with most of the microarray analysis results. Intriguingly, we observed that the highest change was NDUFB5, TIMMDC1, and VDAC3. These identified and validated genes provided references that would advance the understanding of molecular mechanisms of SC. Taken together, using WGCNA, the hub genes NDUFB5, TIMMDC1, and VDAC3 might serve as potential biomarkers for diagnosis and/or therapeutic targets for precise treatment of SC in the future.