JAK2-centered interactome hotspot identified by an integrative network algorithm in acute Stanford type A aortic dissection

Identifying HIF1A and HGF as two hub genes in aortic dissection and function analysis by integrating RNA sequencing and single-cell RNA sequencing data

Objective

Aortic dissection (AD) is a severe aortic disease with high mortality, and its pathogenesis remains elusive. To explore the regulatory mechanisms of AD, we integrated public RNA sequencing (RNA-seq) and single-cell RNA sequencing (scRNA-seq) datasets to screen the hub genes of AD and further analyzed their functions, which may provide references to the diagnosis and treatment of AD.

Methods

Four AD-related datasets were obtained from the Gene Expression Omnibus (GEO) database. Weighted gene co-expression network analysis and differential expression analysis were applied to identify overlapping genes in dataset GSE153434. Protein-protein interaction (PPI) network was constructed based on overlapping genes. Five methods (closeness, degree, EPC, MCC, and MNN) were used to pick hub genes. The receiver operating characteristic curve was used to evaluate the diagnostic efficiency of the hub genes in extra datasets GSE98770 and GSE52093. scRNA-seq dataset GSE213740 was used to explore the expression and function of the hub genes at the single-cell level. Quantitative real-time polymerase chain reaction was used to verify the expression of hub genes in beta-aminopropionitrile (BAPN)-induced mouse thoracic aortic aneurysm and dissection (TAAD) model.

Results

A total of 71 overlapping genes were screened by intersecting the significant genes in the pink module and the differentially expressed genes. A PPI network with 45 nodes and 74 edges was generated, and five top hub genes (HIF1A, HGF, HMOX1, ITGA5, and ITGB3) were identified. All the hub genes had area under the curve values above 0.55. scRNA-seq data analysis showed that HIF1A was significantly upregulated in macrophages and HGF was significantly upregulated in vascular smooth muscle cells (SMCs) of the ascending aortas in AD patients. HIF1A may transcriptionally regulate multiple downstream target genes involving inflammation (TLR2, ALOX5AP, and MIF), glycolysis (ENO1, LDHA, and GAPDH), tissue remodeling (PLAU), and angiogenesis (SERPIN and VEGFA). HGF may participate in the signaling among SMCs, fibroblasts, and endothelial cells through binding to different receptors (MET, EGFR, IGF1R, and KDR). The mRNA expression of Hif1a, Hgf, and their target genes, including Alox5ap, Serpine1, Tlr2, Plau, Egfr, and Igf1r, was significantly upregulated in aortic tissues of BAPN-treated mice.

Conclusion

By integrating RNA-seq and scRNA-seq data, we identified HIF1A and HGF as two hub genes with good diagnostic efficiency for AD. HIF1A in macrophages may promote AD formation by promoting inflammation, glycolysis, tissue remodeling, and angiogenesis, and HGF may mediate signaling among SMCs, fibroblasts, and endothelial cells in the development of AD.

Preoperative clinical characteristics and risk assessment in Sun's modified classification of Stanford type A acute aortic dissection

OBJECTIVES

This study aims to retrospectively analyze the clinical features of Stanford type A acute aortic dissection (TAAAD) based on Sun's modified classification, and to investigate whether the Sun's modified classification can be used to assess the risk of preoperative rupture.

METHODS

Clinical data was collected between January 2018 and June 2019. Data included patient demographics, history of disease, type of dissection according to the Sun's modified classification, time of onset, biochemical tests, and preoperative rupture.

RESULTS

A total of 387 patients with TAAAD who met the inclusion criteria of Sun's modified classification were included. There were more complex types, with 75, 151 and 140 patients in the type A1C, A2C and A3C groups, respectively. The age of the entire group of patients was 51.46 ± 12.65 years and 283 (73.1%) were male. The time from onset to the emergency room was 25.37 ± 30.78 h. There were a few cases of TAAAD combined with stroke, pericardial effusion, pleural effusion, and lower extremity and organ ischemia in the complex type group. The white blood cell count (WBC), neutrophil count (NEC) and blood amylase differed significantly between the groups. Three independent risk factors for preoperative rupture were identified: neutrophil count, blood potassium ion level, and platelet count. Binary logistic regression analysis showed that the Sun's modified classification could not be used to assess the risk of preoperative rupture in TAAAD.

CONCLUSION

TAAAD was classified as the complex type in most patients. WBC, NEC and blood amylase were significantly different between the groups. NEC and serum potassium ion level were independent risk factors for preoperative rupture of TAAAD, while platelet count was its protective factor. More samples are needed to determine whether Sun's modified classification can be used to evaluate the risk of preoperative rupture.

Somatic Variants Acquired Later in Life Associated with Thoracic Aortic Aneurysms: JAK2 V617F

The JAK2 V617F somatic variant is a well-known driver of myeloproliferative neoplasms (MPN) associated with an increased risk for athero-thrombotic cardiovascular disease. Recent studies have demonstrated its role in the development of thoracic aortic aneurysm (TAA). However, limited clinical information and level of JAK2 V617F burden have been provided for a comprehensive evaluation of potential confounders. A retrospective genotype-first study was conducted to identify carriers of the JAK2 V617F variant from an internal exome sequencing database in Yale DNA Diagnostics Lab. Additionally, the overall incidence of somatic variants in the JAK2 gene across various tissue types in the healthy population was carried out based on reanalysis of SomaMutDB and data from the UK Biobank (UKBB) cohort to compare our dataset to the population prevalence of the variant. In our database of 12,439 exomes, 594 (4.8%) were found to have a thoracic aortic aneurysm (TAA), and 12 (0.049%) were found to have a JAK2 V617F variant. Among the 12 JAK2 V617F variant carriers, five had a TAA (42%), among whom four had an ascending TAA and one had a descending TAA, with a variant allele fraction ranging from 11.2% to 20%. Among these five patients, 60% were female, and average age at diagnosis was 70 (49-79). The mean ascending aneurysm size was 5.05 cm (range 4.6-5.5 cm), and four patients had undergone surgical aortic replacement or repair. UKBB data revealed a positive correlation between the JAK2 V617F somatic variant and aortic valve disease (effect size 0.0086, p = 0.85) and TAA (effect size = 0.004, p = 0.92), although not statistically significant. An unexpectedly high prevalence of TAA in our dataset (5/594, 0.84%) is greater than the prevalence reported before for the general population, supporting its association with TAA. JAK2 V617F may contribute a meaningful proportion of otherwise unexplained aneurysm patients. Additionally, it may imply a potential JAK2-specific disease mechanism in the developmental of TAA, which suggests a possible target of therapy that warrants further investigation.

Innovative target mining stratagems to navigate drug repurposing endeavours

The conventional theory linking a single gene with a particular disease and a specific drug contributes to the dwindling success rates of traditional drug discovery. This requires a substantial shift focussing on contemporary drug design or drug repurposing, which entails linking multiple genes to diverse physiological or pathological pathways and drugs. Lately, drug repurposing, the art of discovering new/unlabelled indications for existing drugs or candidates in clinical trials, is gaining attention owing to its success rates. The rate-limiting phase of this strategy lies in target identification, which is generally driven through disease-centric and/or drug-centric approaches. The disease-centric approach is based on exploration of crucial biomolecules such as genes or proteins underlying pathological cascades of the disease of interest. Investigating these pathological interplays aids in the identification of potential drug targets that can be leveraged for novel therapeutic interventions. The drug-centric approach involves various strategies such as exploring the mechanism of adverse drug reactions that can unearth potential targets, as these untoward reactions might be considered desirable therapeutic actions in other disease conditions. Currently, artificial intelligence is an emerging robust tool that can be used to translate the aforementioned intricate biological networks to render interpretable data for extracting precise molecular targets. Integration of multiple approaches, big data analytics, and clinical corroboration are essential for successful target mining. This chapter highlights the contemporary strategies steering target identification and diverse frameworks for drug repurposing. These strategies are illustrated through case studies curated from recent drug repurposing research inclined towards neurodegenerative diseases, cancer, infections, immunological, and cardiovascular disorders.

Comprehensive Analysis of Key Endoplasmic Reticulum Stress-Related Genes and Immune Infiltrates in Stanford Type A Aortic Dissection

BACKGROUND

Type A aortic dissection is a fatal disease. However, the role of endoplasmic reticulum stress-related genes (ERSRGs) in type A aortic dissection has not yet been fully clarified.

METHODS

Differentially expressed genes in the aorta of type A aortic dissection patients were analyzed based on the GSE52093 database. The ERSRGs were downloaded from the GeneCards website. Functional enrichment analysis and protein-protein interaction analysis were performed on the acquired differentially expressed ERSRGs. The mRNA expression of the 5 top key differentially expressed ERSRGs was further explored in GSE153434 and clinical samples. Immune infiltration correlation analysis was performed on the validated key genes. Finally, we constructed regulatory networks of transcription factors, miRNAs, and chemicals.

RESULTS

Twelve differentially expressed ERSRGs were identified, of which 8 genes were downregulated and 4 genes were upregulated. GeneMANIA was adopted to analyze these genes and their interacting proteins, and the results showed that the main function was calcium ion transport. Four key genes, ACTC1, CASQ2, SPP1, and REEP1, were validated in GSE153434 and clinical samples. The area under the ROC curve values for ACTC1, CASQ2, SPP1, and REEP1 were 0.92, 0.96, 0.89, and 1.00, respectively. ACTC1 and REEP1 correlated with multiple immune cells. Many transcription factors, microRNAs, and chemicals were identified with the potential to regulate these 4 key genes.

CONCLUSION

In this study, we identified 12 differentially expressed ERSRGs by analyzing the Gene Expression Omnibus database. Four key genes may influence the development of type A aortic dissection by regulating endoplasmic reticulum stress. These results expand our understanding of type A aortic dissection, and the 4 key genes are expected to be diagnostic markers and potential therapeutic targets.

Integrative analysis reveals chemokines CCL2 and CXCL5 mediated shear stress-induced aortic dissection formation

Background

Aortic dissection (AD) is a critical emergency in cardiovascular disease. AD occurs only in specific sites of the aorta, and the variation of shear stress in different aortic segments is a possible cause not reported. This study investigated the key molecules involved in shear stress-induced AD through quantitative bioinformatic analysis of a public RNA sequencing database and clinical tissue sample validation.

Methods

Gene expression data from the GSE153434, GSE147026, and GSE52093 datasets were downloaded from the Gene Expression Omnibus. Next, differently expressed genes (DEGs) in each dataset were identified and integrated to identify common AD DEGs. STRING, Cytoscape, and MCODE were used to identify hub genes and crucial clustering modules, and Connectivity Map (CMap) was used to identify positive and negative agents. The same procedure was performed for the GSE160611 dataset to obtain shear stress-induced human aortic endothelial cell (HAEC) DEGs. After the integration of these two DEGs sets to identify shear stress-associated hub DEGs in AD, Gene Ontology Enrichment Analysis was performed. The common chemokine receptors and ligands in AD were identified by analyzing AD's three RNA sequencing datasets. Their origin was verified by analyzing AD single-cell sequencing data and validated by immunoblotting and immunofluorescence.

Results

We identified 100 down-regulated and 50 up-regulated AD common DEGs. Enrichment results showed that common DEGs were closely related to blood vessel morphogenesis, muscle structure development, muscle tissue development, and chemotaxis. Among those DEGs, MYC, CCL2, and SPP1 are the three molecules with the highest degree. A crucial cluster of 15 genes was identified using MCODE, which contained inflammation-related genes with elevated expression and muscle cell-related genes with decreased expression, and CCL2 is central to immune-related genes. CMap confirmed MEK inhibitors and ALK inhibitors as possible therapeutic agents for AD. Moreover, 366 shear stress-associated DEGs in HAEC were identified in the GSE160611 dataset. After taking the intersection, we identified five shear stress-associated hub DEGs in AD (ANGPTL4, SNAI2, CCL2, GADD45B, and PROM1), and the enrichment analysis indicated they were related to the endothelial cell apoptotic process. Chemokine CCL2 was the molecule with a high degree in both DEG sets. Besides CCL2, CXCL5 was the only chemokine ligand differentially expressed in the three datasets. Additionally, immunoblotting confirmed the increased expression of CCL2 and CXCL5 in clinical tissue samples. Further research at the single-cell level revealed that CCL2 has multiple origins, and CXCL5 is macrophage-derived.

Conclusion

Through integrative analysis, we identified core common AD DEGs and possible therapeutic agents based on these DEGs. We elucidated that the chemokine CCL2 and CXCL5-mediated "Endothelial-Monocyte-Neutrophil" axis may contribute to the development of shear stress-induced AD. These findings provide possible therapeutic targets for the prevention and treatment of AD.

Transcriptomic Analysis of Tight Junction Proteins Demonstrates the Aberrant Expression and Function of Zona Occludens 2 (ZO-2) Protein in Stanford Type A Aortic Dissection

OBJECTIVE

Thoracic aortic aneurysm dissection (TAAD) represents a cardiac surgery emergency characterized by the disrupted integrity of the aortic wall and is associated with poor prognosis. In this context, the identification of biomarkers implicated in the pathobiology of TAAD is crucial. Our aim in the present original in silico study is to assess the differential gene expression profile of the tight junction proteins (TJPs) in patients with TAAD and to propose novel biomarkers for the diagnosis and prognosis of this disease.

METHODS

We implemented bioinformatics methodology in order to construct the gene network of the TJPs family, identify the differentially expressed genes (DEGs) in pathologic aortic tissue excised from patients with TAAD as compared to healthy aortic tissue, and assess the related biological functions and the associated miRNA families.

RESULTS

Data regarding the transcriptomic profile of selected genes were retrieved and incorporated from three microarray datasets, including 23 TAAD and 20 healthy control samples. A total of 32 TJPs were assessed. The zona occludens 2 (ZO-2) protein encoded by the gene TJP2 was significantly under-expressed in patients with TAAD compared to the control group (p = 0.009). ZO-2 was associated with fair discrimination and calibration traits in predicting the TAAD presentation. CpG islands of ZO-2 were demonstrated. No important difference was found regarding ZO-2 expression between aneurysmal non-dissected and healthy control aortic tissue. Finally, we performed gene set enrichment analysis (GSEA) and uncovered the major biological functions and miRNA families (hsa-miR-155-5p, hsa-miR-1-3p, hsa-miR-2118-5p, hsa-miR-4691-3p, and hsa-miR-1229-3p) relevant to ZO-2.

CONCLUSIONS

These outcomes demonstrated the important role of ZO-2 in the pathobiology of TAAD.

Identification and Analysis of Hub Genes and Immune Cells Associated with the Formation of Acute Aortic Dissection

Background

Acute type A aortic dissection (AAD) is a catastrophic disease with high mortality, but the pathogenesis has not been fully elucidated. This study is aimed at identifying hub genes and immune cells associated with the pathogenesis of AAD.

Methods

The datasets were downloaded from Gene Expression Omnibus (GEO). Gene Set Enrichment Analysis (GSEA), gene set variation analysis (GSVA), and differential analysis were performed. The differentially expressed genes (DEGs) were intersected with specific genes collected from MSigDB. The gene function and pathway enrichment analysis were also performed on intersecting genes. The key modules were selected by weighted gene coexpression network analysis (WGCNA). Hub genes were identified by least absolute shrinkage and selection operator (LASSO) analysis and were verified in the metadataset. The immune cell infiltration was analyzed by CIBERSORT, and the relationship between hub genes and immune cells was performed by Pearson's correlation analysis. The single-cell RNA sequencing (scRNA-seq) dataset was used to verify the differences in DNA damage and repair signaling pathways and hub genes in different cell types.

Results

The results of GSEA and GSVA indicated that DNA damage and repair processes were activated in the occurrence of AAD. The gene function and pathway enrichment analysis on differentially expressed DNA damage- and repair-related genes showed that these genes were mainly involved in the regulation of the cell cycle process, cellular response to DNA damage stimulus, response to wounding, p53 signaling pathway, and cellular senescence. Three key modules were identified by WGCNA. Five genes were screened as hub genes, including CDK2, EIF4A1, GLRX, NNMT, and SLCO2A1. Naive B cells and Gamma delta T cells (γδ T cells) were decreased in AAD, but monocytes and M0 macrophages were increased. scRNA-seq analysis included that DNA damage and repair processes were activated in smooth muscle cells (SMCs), tissue stem cells, and monocytes in the aortic wall of patients with AAD.

Conclusions

Our results suggested that DNA damage- and repair-related genes may be involved in the occurrence of AAD by regulating many biological processes. The hub genes and immune cells reported in this study also increase the understanding of AAD.

Applying multi-omics techniques to the discovery of biomarkers for acute aortic dissection

Acute aortic dissection (AAD) is a cardiovascular disease that manifests suddenly and fatally. Due to the lack of specific early symptoms, many patients with AAD are often overlooked or misdiagnosed, which is undoubtedly catastrophic for patients. The particular pathogenic mechanism of AAD is yet unknown, which makes clinical pharmacological therapy extremely difficult. Therefore, it is necessary and crucial to find and employ unique biomarkers for Acute aortic dissection (AAD) as soon as possible in clinical practice and research. This will aid in the early detection of AAD and give clear guidelines for the creation of focused treatment agents. This goal has been made attainable over the past 20 years by the quick advancement of omics technologies and the development of high-throughput tissue specimen biomarker screening. The primary histology data support and add to one another to create a more thorough and three-dimensional picture of the disease. Based on the introduction of the main histology technologies, in this review, we summarize the current situation and most recent developments in the application of multi-omics technologies to AAD biomarker discovery and emphasize the significance of concentrating on integration concepts for integrating multi-omics data. In this context, we seek to offer fresh concepts and recommendations for fundamental investigation, perspective innovation, and therapeutic development in AAD.

The Genetics and Typical Traits of Thoracic Aortic Aneurysm and Dissection

Genetic predisposition and risk factors such as hypertension and smoking can instigate the development of thoracic aortic aneurysm (TAA), which can lead to highly lethal aortic wall dissection and/or rupture. Monogenic defects in multiple genes involved in the elastin-contractile unit and the TGFβ signaling pathway have been associated with TAA in recent years, along with several genetic modifiers and risk-conferring polymorphisms. Advances in omics technology have also provided significant insights into the processes behind aortic wall degeneration: inflammation, epigenetics, vascular smooth muscle phenotype change and depletion, reactive oxygen species generation, mitochondrial dysfunction, and angiotensin signaling dysregulation. These recent advances and findings might pave the way for a therapy that is capable of stopping and perhaps even reversing aneurysm progression.

Identification and validation of differentially expressed chromatin regulators for diagnosis of aortic dissection using integrated bioinformatics analysis and machine-learning algorithms

Background: Aortic dissection (AD) is a life-threatening disease. Chromatin regulators (CRs) are indispensable epigenetic regulators. We aimed to identify differentially expressed chromatin regulators (DECRs) for AD diagnosis.

Methods: We downloaded the GSE52093 and GSE190635 datasets from the Gene Expression Omnibus database. Following the merging and processing of datasets, bioinformatics analysis was applied to select candidate DECRs for AD diagnosis: CRs exertion; DECR identification using the “Limma” package; analyses of enrichment of function and signaling pathways; construction of protein–protein interaction (PPI) networks; application of machine-learning algorithms; evaluation of receiver operating characteristic (ROC) curves. GSE98770 served as the validation dataset to filter DECRs. Moreover, we collected peripheral-blood samples to further validate expression of DECRs by real-time reverse transcription-quantitative polymerase chain reaction (RT-qPCR). Finally, a nomogram was built for clinical use.

Results: A total of 841 CRs were extracted from the merged dataset. Analyses of functional enrichment of 23 DECRs identified using Limma showed that DECRs were enriched mainly in epigenetic-regulation processes. From the PPI network, 17 DECRs were selected as node DECRs. After machine-learning calculations, eight DECRs were chosen from the intersection of 13 DECRs identified using support vector machine recursive feature elimination (SVM-RFE) and the top-10 DECRs selected using random forest. DECR expression between the control group and AD group were considerably different. Moreover, the area under the ROC curve (AUC) of each DECR was >0.75, and four DECRs (tumor protein 53 (TP53), chromobox protein homolog 7 (CBX7), Janus kinase 2 (JAK2) and cyclin-dependent kinase 5 (CDK5)) were selected as candidate biomarkers after validation using the external dataset and clinical samples. Furthermore, a nomogram with robust diagnostic value was established (AUC = 0.960).

Conclusion: TP53, CBX7, JAK2, and CDK5 might serve as diagnostic DECRs for AD diagnosis. These DECRs were enriched predominantly in regulating epigenetic processes.

Patterns of Immune Infiltration and the Key Immune-Related Genes in Acute Type A Aortic Dissection in Bioinformatics Analyses

Background

Immune-inflammatory mechanisms contribute greatly to the complex process leading to type A aortic dissection (TAAD). This study aims to explore immune infiltration and key immune-related genes in acute TAAD.

Methods

ImmuCellAI algorithm was applied to analyze patterns of immune infiltration in TAAD samples and normal aortic vessel samples in the GSE153434 dataset. Differentially expressed genes (DEGs) were screened. Immune-related genes were obtained from overlapping DEGs of GSE153434 and immune genes of the ImmPort database. The hub genes were obtained based on the protein–protein interaction (PPI) network. The hub genes in TAAD were validated in the GSE52093 dataset. The correlation between the key immune-related genes and infiltrating immune cells was further analyzed.

Results

In the study, the abundance of macrophages, neutrophils, natural killer T cells (NKT cells), natural regulatory T cells (nTreg), T-helper 17 cells (Th17 cells) and monocytes was increased in TAAD samples, whereas that of dendritic cells (DCs), CD4 T cells, central memory T cells (Tcm), mucosa associated invariant T cells (MAIT cells) and B cells was decreased. Interleukin 6 (IL-6), C-C motif chemokine ligand 2 (CCL2) and hepatocyte growth factor (HGF) were identified and validated in the GSE52093 dataset as the key immune-related genes. Furthermore, IL-6, CCL2 and HGF were correlated with different types of immune cells.

Conclusion

In conclusion, several immune cells such as macrophages, neutrophils, NKT cells, and nTreg may be involved in the development of TAAD. IL-6, CCL2 and HGF were identified and validated as the key immune-related genes of TAAD via bioinformatics analyses. The key immune cells and immune-related genes have the potential to be developed as targets of prevention and immunotherapy for patients with TAAD.

Identification of Molecular Regulatory Features and Markers for Acute Type A Aortic Dissection

BACKGROUND

Acute type A aortic dissection (ATAAD) is one of the most lethal cardiovascular diseases, and its molecular mechanism remains unclear.

METHODS

Differentially expressed genes (DEGs) between ATAAD and control were detected by limma R package in GSE52093, GSE153434, GSE98770, and GSE84827, respectively. The coexpression network of DEGs was identified by the WGCNA package. Enrichment analysis was performed for module genes that were positively correlated with ATAAD using clusterProfiler R package. In addition, differentially methylated markers between aortic dissection and control were identified by ChAMP package. After comparing with ATAAD-related genes, a protein-protein interaction (PPI) network was established based on the STRING database. The genes with the highest connectivity were identified as hub genes. Finally, differential immune cell infiltration between ATAAD and control was identified by ssGSEA.

RESULTS

From GSE52093 and GSE153434, 268 module genes were obtained with consistent direction of differential expression and high correlation with ATAAD. They were significantly enriched in T cell activation, HIF-1 signaling pathway, and cell cycle. In addition, 2060 differentially methylated markers were obtained from GSE84827. Among them, 77 methylation markers were ATAAD-related DEGs. Using the PPI network, we identified MYC, ITGA2, RND3, BCL2, and PHLPP2 as hub genes. Finally, we identified significantly differentially infiltrated immune cells in ATAAD.

CONCLUSION

The hub genes we identified may be regulated by methylation and participate in the development of ATAAD through immune inflammation and oxidative stress response. The findings may provide new insights into the molecular mechanisms and therapeutic targets for ATAAD.

Regulatory Master Genes Identification and Drug Repositioning by Integrative mRNA-miRNA Network Analysis for Acute Type A Aortic Dissection

Acute type A aortic dissection (ATAAD) is a life-threatening disease. The understanding of its pathogenesis and treatment approaches remains unclear. In the present work, differentially expressed genes (DEGs) from two ATAAD datasets GSE52093 and GSE98770 were filtered. Transcription factor TEAD4 was predicted as a key modulator in protein-protein interaction (PPI) network. Weighted correlation network analysis (WGCNA) identified five modules in GSE52093 and four modules in GSE98770 were highly correlated with ATAAD. 71 consensus DEGs of highly correlated modules were defined and functionally annotated. L1000CDS² was executed to predict drug for drug repositioning in ATAAD treatment. Eight compounds were filtered as potential drugs. Integrative analysis revealed the interaction network of five differentially expressed miRNA and 16 targeted DEGs. Finally, master DEGs were validated in human ATAAD samples and AD cell model in vitro. TIMP3 and SORBS1 were downregulated in ATAAD samples and AD cell model, while PRUNE2 only decreased in vitro. Calcium channel blocker and glucocorticoid receptor agonist might be potential drugs for ATAAD. The present study offers potential targets and underlying molecular mechanisms ATAAD pathogenesis, prevention and drug discovery.

Genetic Deletion of Socs3 in Smooth Muscle Cells Ameliorates Aortic Dissection in Mice

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Stat3, a major signaling molecule for proinflammatory cytokines including IL-6, was activated both in inflammatory cells and in SMC in the aortic walls of human AD and mouse AD model.

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SMC-specific deletion of Socs3 enhanced Stat3 activation in SMC, induced moderate proinflammatory response in the aortic walls, and ameliorated AD in mice.

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SmSocs3-KO aortas showed increases in fibroblasts, adventitial collagen fibers, and tensile strength of the aortic walls.

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IL-6-stimulated SMC in culture secreted humoral factor(s) that promoted proliferative response of fibroblasts.

Aortic dissection (AD) is the acute destruction of aortic wall and is reportedly induced by inflammatory response. Here we investigated the role of smooth muscle Socs3 (a negative regulator of Janus kinases/signal transducer and activator of transcription signaling) in AD pathogenesis using a mouse model generated via β-aminopropionitrile and angiotensin II infusion. Socs3 deletion specifically in smooth muscle cells yielded a chronic inflammatory response of the aortic wall, which was associated with increased fibroblasts, reinforced aortic tensile strength, and less-severe tissue destruction. Although an acute inflammatory response is detrimental in AD, smooth muscle-regulated inflammatory response seemed protective against AD.

Identification of the molecular mechanisms associated with acute type A aortic dissection through bioinformatics methods

Aortic dissection is characterized by the redirection of blood flow, which flows through an intimal tear into the aortic media. The purpose of this study was to find potential acute type A aortic dissection (AAAD)-related genes and molecular mechanisms by bioinformatics. The gene expression profiles of GSE52093 were obtained from Gene Expression Omnibus (GEO) database, including 7 AAAD samples and 5 normal samples. The differentially expressed genes (DEGs) were detected between AAAD and normal samples. The functional annotation and pathway enrichment analysis were conducted through the Database for Annotation, Visualization and Integration Discovery (DAVID). A protein-protein interaction network was established by the Search Tool for the Retrieval of Interacting Genes (STRING) software. The microRNAs (miRNAs) of these differentially expressed genes were predicted using <microRNA.org> database. Moreover, DEGs were analyzed in the comparative toxicogenomics (CTD) database to screen out the potential therapeutic small molecules. As a result, there were 172 DEGs identified in patients with AAAD. These DEGs were significantly enriched in 6 pathways, including cell cycle, oocyte meiosis, DNA replication, extracellular matrix-receptor interaction, and mineral absorption pathway. Notably, CDC20, CDK1, CHEK1, KIF20A, MCM10, PBK, PTTG1, RACGAP, and TOP2A were crucial genes with a high degree in the protein-protein interaction network. Furthermore, potential miRNAs (miR-301, miR-302 family, and miR-130 family) were identified. In addition, small molecules like azathioprine and zoledronic acid were identified to be potential drugs for AAAD.

STAT3 Activation Correlates with Adventitial Neutrophil Infiltration in Human Aortic Dissection

Objective: Aortic dissection (AD) is a fatal disease that is caused by the rapid destruction of the aortic wall. Although recent studies in animal models indicate an important relationship between inflammation and tissue destruction, activation status of inflammatory signaling and its relation to the inflammatory cell infiltration are poorly characterized in human AD.

Materials and Methods: We examined the activation of inflammatory signaling molecules NFκB and STAT3, and neutrophil infiltration in AD tissue samples that were obtained during the surgical repair within 24 h after AD onset.

Results: Activation of NFκB was observed mainly in the intima both in AD samples and in aortic samples without AD. Activation of STAT3 was observed in AD samples, but not in the aortic sample without AD. Neutrophil infiltration was observed predominantly in the adventitial layer of AD samples. Histological analysis revealed that STAT3 was activated in cells other than neutrophils. Notably, STAT3 activation and neutrophil infiltration showed positive correlation in adventitial layer of AD tissue.

Conclusion: These findings demonstrated that adventitial STAT3 activation was associated with neutrophil infiltration, suggesting their importance in AD pathogenesis.

Abnormal Ribosome Biogenesis Partly Induced p53-Dependent Aortic Medial Smooth Muscle Cell Apoptosis and Oxidative Stress

Ribosome biogenesis is a crucial biological process related to cell proliferation, redox balance, and muscle contractility. Aortic smooth muscle cells (ASMCs) show inhibition of proliferation and apoptosis, along with high levels of oxidative stress in aortic dissection (AD). Theoretically, ribosome biogenesis should be enhanced in the ASMCs at its proliferative state but suppressed during apoptosis and oxidative stress. However, the exact status and role of ribosome biogenesis in AD are unknown. We therefore analyzed the expression levels of BOP1, a component of the PeBoW complex which is crucial to ribosome biogenesis, in AD patients and a murine AD model and its influence on the ASMCs. BOP1 was downregulated in the aortic tissues of AD patients compared to healthy donors. In addition, overexpression of BOP1 in human aortic smooth muscle cells (HASMCs) inhibited apoptosis and accumulation of p53 under hypoxic conditions, while knockdown of BOP1 decreased the protein synthesis rate and motility of HASMCs. The RNA polymerase I inhibitor cx-5461 induced apoptosis, ROS production, and proliferative inhibition in the HASMCs, which was partly attenuated by p53 knockout. Furthermore, cx-5461 aggravated the severity of AD in vivo, but a p53-/- background extended the life-span and lowered AD incidence in the mice. Taken together, decreased ribosome biogenesis in ASMCs resulting in p53-dependent proliferative inhibition, oxidative stress, and apoptosis is one of the underlying mechanisms of AD.

Gene expression profiling of acute type A aortic dissection combined with in vitro assessment

OBJECTIVES

The mechanisms underlying aortic dissection remain to be fully elucidated. We aimed to identify key molecules driving dissection through gene expression profiling achieved by microarray analysis and subsequent in vitro experiments using human aortic endothelial cells (HAECs) and aortic vascular smooth muscle cells (AoSMCs).

METHODS

Total RNA, including microRNA (miRNA), was isolated from the intima-media layer of dissected ascending aorta obtained intraoperatively from acute type A aortic dissection (ATAAD) patients without familial thoracic aortic disease (n = 8) and that of non-dissected ascending aorta obtained from transplant donors (n = 9). Gene expression profiling was performed with mRNA and miRNA microarrays, and results were confirmed by quantitative polymerase chain reaction (qPCR). Target genes and miRNA were identified by gene ontology analysis and a literature search. To reproduce the in silico results, HAECs and AoSMCs were stimulated in vitro by upstream cytokines, and expression of target genes was assessed by qPCR.

RESULTS

Microarray analysis revealed 1536 genes (3.6%, 1536/42 545 probes) and 41 miRNAs (3.0%, 41/1368 probes) that were differentially expressed in the ATAAD group (versus donor group). The top 15 related pathways included regulation of inflammatory response, growth factor activity and extracellular matrix. Gene ontology analysis identified JAK2 (regulation of inflammatory response), PDGFA, TGFB1, VEGFA (growth factor activity) and TIMP3, TIMP4, SERPINE1 (extracellular matrix) as the target genes and miR-21-5p, a TIMP3 repressor, as target miRNA that interacts with the target genes. Validation qPCR confirmed the altered expression of all 7 target genes and miR-21-5p in dissected aorta specimens (all genes, P < 0.05). Ingenuity pathway analysis showed TNF-α and TGF-β to be upstream cytokines for the target genes. In vitro experiments showed these cytokines inhibit TIMP3 expression (P < 0.05) and enhance VEGFA expression (P < 0.01) in AoSMCs but not HAECs. miR-21-5p expression increases in AoSMCs under TNF-α and TGF-β stimulation (fold change: 1.36; P = 0.011).

CONCLUSIONS

Results of our novel approach, integrating in vitro assessment into gene expression profiling, implicated chronic inflammation characterized by MMP-TIMP dysregulation, increased VEGFA expression, and TGF-β signalling in the development of dissection. Further investigation may reveal novel diagnostic biomarkers and uncover the mechanism(s) underlying ATAAD.

DNA methylome analysis reveals distinct epigenetic patterns of ascending aortic dissection and bicuspid aortic valve

Aims

Epigenetics may mediate the effects of environmental risk factors on disease, including heart disease. Thus, measuring the DNA methylome offers the opportunity to identify novel disease biomarkers and novel insights into disease mechanisms. The DNA methylation landscape of ascending aortic dissection (AD) and bicuspid aortic valve (BAV) with aortic aneurysmal dilatation remain uncharacterized. The present study aimed to explore the genome-wide DNA methylation landscape underpinning these two diseases.

Methods and results

We used Illumina 450k DNA methylation beadarrays to analyse 21 ascending aorta samples, including 10 cases with AD, 5 with BAV and 6 healthy controls. We adjusted for intra-sample cellular heterogeneity, providing the first unbiased genome-wide exploration of the DNA methylation landscape underpinning these two diseases. We discover that both diseases are characterized by loss of DNA methylation at non-CpG sites. We validate this non-CpG hypomethylation signature with pyrosequencing. In contrast to non-CpGs, AD and BAV exhibit distinct DNA methylation landscapes at CpG sites, with BAV characterized mainly by hypermethylation of EZH2 targets. In the case of AD, integrative DNA methylation gene expression analysis reveals that AD is characterized by a dedifferentiated smooth muscle cell phenotype. Our integrative analysis further reveals hypomethylation associated overexpression of RARA in AD, a pattern which is also seen in cells exposed to smoke toxins.

Conclusion

Our data supports a model in which increased cellular proliferation in AD and BAV underpins loss of methylation at non-CpG sites. Our data further supports a model, in which AD is associated with an inflammatory vascular remodeling process, possibly mediated by the epigenome and linked to environmental risk factors such as smoking.

Role of Macrophage Socs3 in the Pathogenesis of Aortic Dissection

BACKGROUND

Aortic dissection (AD) is a life-threatening medical emergency caused by the abrupt destruction of the intimomedial layer of the aortic walls. Given that previous studies have reported the involvement of proinflammatory cytokine interleukin-6 in AD pathogenesis, we investigated the role of signal transduction and activator of transcription 3 signaling, a downstream pathway of interleukin-6 in macrophages in pathogenesis of AD.

METHODS AND RESULTS

We characterized the pathological and molecular events triggered by aortic stress, which can lead to AD. Aortic stress on the suprarenal aorta because of infrarenal aorta stiffening and angiotensin II infusion for 1 week caused focal medial rupture at the branching point of the celiac trunk and superior mesenteric artery. This focal medial rupture healed in 6 weeks in wild-type (WT) mice, but progressed to AD in mice with macrophage-specific deletion of Socs3 gene (mSocs3-KO). mSocs3-KO mice showed premature activation of cell proliferation, an inflammatory response, and skewed differentiation of macrophages toward the tissue-destructive phenotype. Concomitantly, they showed aberrant phenotypic modulation of smooth muscle cells and transforming growth factor beta signaling, which are likely to participate in tissue repair. Human AD samples revealed signal transduction and activator of transcription 3 activation in adventitial macrophages adjacent to the site of tissue destruction.

CONCLUSIONS

These findings suggest that AD development is preceded by focal medial rupture, in which macrophage Socs3 maintains proper inflammatory response and differentiation of SMCs, thus promoting fibrotic healing to prevent tissue destruction and AD development. Understanding the sequence of the pathological and molecular events preceding AD development will help predict and prevent AD development and progression.

Weighted Gene Co-expression Network Analysis Identifies FKBP11 as a Key Regulator in Acute Aortic Dissection through a NF-kB Dependent Pathway

Acute aortic dissection (AAD) is a life-threatening disease. Despite the higher risk of mortality, currently there are no effective therapies that can ameliorate AAD development or progression. Identification of meaningful clusters of co-expressed genes or representative biomarkers for AAD may help to identify new pathomechanisms and foster development of new therapies. To this end, we performed a weighted gene co-expression network analysis (WGCNA) and calculated module-trait correlations based on a public microarray dataset (GSE 52093) and discovered 9 modules were found to be related to AAD. The module which has the strongest positive correlation with AAD was further analyzed and the top 10 hub genes SLC20A1, GINS2, CNN1, FAM198B, MAD2L2, UBE2T, FKBP11, SLMAP, CCDC34, and GALK1 were identified. Furthermore, we validated the data by qRT-PCR in an independent sample set originated from our study center. Overall, the qRT-PCR results were consistent with the results of the microarray analysis. Intriguingly, the highest change was found for FKBP11, a protein belongs to the FKBP family of peptidyl-prolyl cis/trans isomerases, which catalyze the folding of proline-containing polypeptides. In congruent with the gene expression analysis, FKBP11 expression was induced in cultured endothelial cells by angiotensin II treatment and endothelium of the dissected aorta. More importantly we show that FKBP11 provokes inflammation in endothelial cells by interacting with NF-kB p65 subunit, resulting in pro-inflammatory cytokines production. Accordingly, siRNA mediated knockdown of FKBP11 in cultured endothelial cells suppressed angiotensin II induced monocyte transmigration through the endothelial monolayer. Based on these data, we hypothesize that pro-inflammatory cytokines elicited by FKBP11 overexpression in the endothelium under AAD condition could facilitate transendothelial migration of the circulating monocytes into the aorta, where they differentiate into active macrophages and secrete MMPs and other extracellular matrix (ECM) degrading proteins, contributing to sustained inflammation and AAD. Taken together, our data identify important role of FKBP11 which can serve as biomarker and/or therapeutic target for AAD.

Pathway mapping and development of disease-specific biomarkers: protein-based network biomarkers

It is known that a disease is rarely a consequence of an abnormality of a single gene, but reflects the interactions of various processes in a complex network. Annotated molecular networks offer new opportunities to understand diseases within a systems biology framework and provide an excellent substrate for network-based identification of biomarkers. The network biomarkers and dynamic network biomarkers (DNBs) represent new types of biomarkers with protein-protein or gene-gene interactions that can be monitored and evaluated at different stages and time-points during development of disease. Clinical bioinformatics as a new way to combine clinical measurements and signs with human tissue-generated bioinformatics is crucial to translate biomarkers into clinical application, validate the disease specificity, and understand the role of biomarkers in clinical settings. In this article, the recent advances and developments on network biomarkers and DNBs are comprehensively reviewed. How network biomarkers help a better understanding of molecular mechanism of diseases, the advantages and constraints of network biomarkers for clinical application, clinical bioinformatics as a bridge to the development of diseases-specific, stage-specific, severity-specific and therapy predictive biomarkers, and the potentials of network biomarkers are also discussed.