Exaggerated Autophagy in Stanford Type A Aortic Dissection: A Transcriptome Pilot Analysis of Human Ascending Aortic Tissues

Key gene screening and diagnostic model establishment for acute type a aortic dissection

Background

Aortic dissection, particularly acute type A aortic dissection (ATAAD), is a life-threatening cardiovascular emergency with alarmingly high mortality rates globally. Despite advancements in imaging techniques like computed tomography angiography (CTA), delayed diagnosis and incomplete understanding of molecular mechanisms persist, contributing to poor outcomes. Recent studies highlight the role of immune dysregulation, vascular smooth muscle cell (VSMC) apoptosis, and metabolic-epigenetic interactions in AD pathogenesis, underscoring the need for novel biomarkers and therapeutic targets.

Objective

This study aims to identify critical genes and molecular pathways associated with ATAAD, develop a multi-omics diagnostic model, and evaluate potential therapeutic interventions to improve clinical outcomes.

Methods

Transcriptome datasets from the Gene Expression Omnibus (GEO) database were analyzed using differential expression analysis, weighted gene co-expression network analysis (WGCNA), and machine learning algorithms (SVM, Random Forest, LASSO regression). Functional enrichment and immunoinfiltration analyses were performed to explore biological pathways and immune cell interactions. External dataset validation and PCR testing of clinical samples (n = 9) were conducted to confirm gene expression differences. A nomogram diagnostic model was constructed and evaluated for predictive accuracy.

Results

Six core genes were identified: Ccl2, Cdh8, Hk2, Tph1, Npy1r, and Slc24a4, with four (Ccl2, Hk2, Tph1, and Npy1r) showing significant differential expression in clinical validation. Functional enrichment revealed associations with immune cell migration, vascular development regulation, extracellular matrix pathways, and the PI3K-Akt signaling pathway. Immunoinfiltration analysis demonstrated increased infiltration of B cell precursors, resting NK cells, and M2 macrophages in ATAAD tissues, negatively correlating with core gene expression. The nomogram model exhibited high diagnostic precision (AUC=0.935, 95% CI: 0.908-0.963), supported by calibration and decision curve analyses.

Conclusion

This study identifies key molecular markers and pathways in ATAAD pathogenesis, emphasizing the role of immune dysregulation and extracellular matrix remodeling. The multi-omics diagnostic model provides a novel tool for early screening, potentially reducing mortality through timely intervention. These findings advance the understanding of aortic dissection mechanisms and offer actionable targets for future research and clinical applications.

Lactate Dehydrogenase A Is a Novel Positive Regulator of Vascular Smooth Muscle Cell Ferroptosis During Aortic Dissection

Aims: Vascular smooth muscle cell (VSMC) ferroptosis is a pivotal event in the process of aortic dissection (AD), and a number of agents have a protective role against AD by inhibiting VSMC ferroptosis. While glycolysis is an ancient pathway related to almost all biological processes, its precise involvement in VSMC ferroptosis and AD remains unclear. Results: In this study, bioinformatics analysis revealed that glycolysis-related molecules and pathways were involved in VSMC ferroptosis and AD. We focused on the key enzyme of glycolysis, lactate dehydrogenase A (LDHA), and found that LDHA overexpression promoted ferroptosis and lipid peroxidation in cystine deprivation- or imidazole ketone erastin-treated VSMCs and vice versa. Clinical specimens showed a negative correlation between elevated LDHA levels in dissected aortae and ferroptosis-related molecules glutathione peroxidase 4 (GPX4), solute carrier family 7 member 11 (SLC7A11), and ferroptosis suppressor protein 1 (FSP1). In VSMC ferroptosis, LDHA overexpression led to the suppression of GPX4, SLC7A11, and FSP1. Furthermore, the interaction between LDHA and nuclear factor (erythroid-derived 2)-like 2 (NRF2) was identified, and the overexpression or agonist of NRF2 reversed the contribution of LDHA on VSMC ferroptosis and lipid peroxidation. Innovation and Conclusion: These results highlight a significant association between LDHA and VSMC ferroptosis in AD development mediated through NRF2. These findings present LDHA as a potential target for AD intervention by inhibiting its expression. Antioxid. Redox Signal. 42, 378-392.

Identification of the Hub Gene LDB3 in Stanford Type A Aortic Dissection Based on Comprehensive Bioinformatics Analysis

Stanford type A aortic dissection (TAAD) is a life-threatening disease. This study explored the role of LIM domain binding 3 (LDB3) in TAAD progression. Four datasets from the Gene Expression Omnibus were analyzed to identify TAAD-related hub genes. LDB3 single nucleotide polymorphisms (SNPs) were assessed in the UK Biobank. Western blotting and immunofluorescence detected LDB3 expression in angiotensin II (Ang II) stimulated human aortic vascular smooth muscle cells (HA-VSMC), human samples, and a murine model. Bioinformatics identified tissue inhibitor of metalloproteinase-1 (TIMP1) and LDB3 as TAAD hub genes. TIMP1 was expressed in macrophages, mesenchymal cells, and smooth muscle cells, while LDB3 was mostly expressed in smooth muscle cells. Validation showed TIMP1 was upregulated and LDB3 downregulated in TAAD. Six LDB3 SNPs were associated with aortic aneurysm and dissection in the UK Biobank. In human and murine samples, LDB3 expression was reduced in diseased tissues and co-localized with smooth muscle. Ang II-stimulated HA-VSMC exhibited LDB3 reduction and altered intercellular connections. The aforementioned findings suggest that the newly identified gene LDB3 is crucial in the progression of TAAD.

GMRSP encoded by lncRNA H19 regulates metabolic reprogramming and alleviates aortic dissection

Metabolic disturbances are hallmarks of vascular smooth muscle cell (VSMC) phenotypic transitions, which play a critical role in the pathogenesis of aortic dissection (AD). In this study, we identify and characterize glucose metabolism regulatory protein (GMRSP), a protein encoded by lncRNA H19. Using VSMC-specific GMRSP induction in knock-in mice, adeno-associated virus-mediated GMRSP overexpression, and exosomal GMRSP delivery, we demonstrate significant improvements in AD and mitochondrial dysfunction. Mechanistically, GMRSP inhibits heterogeneous nuclear ribonucleoprotein (hnRNP) A2B1-mediated alternative splicing of pyruvate kinase M (PKM) pre-mRNA, leading to reduced PKM2 production and glycolysis. This reprogramming preserves the contractile phenotype of VSMCs and prevents their transition to a proliferative state. Importantly, pharmacological activation of PKM2 via TEPP-46 abrogates the protective effects of GMRSP in vivo and in vitro. Clinical relevance is shown by elevated plasma PKM2 levels in AD patients, which correlate with poor prognosis. Collectively, these findings indicate GMRSP as a key regulator of VSMC metabolism and phenotypic stability, highlighting its potential as a therapeutic target for AD.

FABP5+ macrophages contribute to lipid metabolism dysregulation in type A aortic dissection

Type A aortic dissection (TAAD) is an acute onset disease with a high mortality rate. TAAD is caused by a tear in the aortic intima and subsequent blood infiltration. The most prominent characteristics of TAAD are aortic media degeneration and inflammatory cell infiltration, which disturb the structural integrity and function of nonimmune and immune cells in the aortic wall. However, to date, there is no systematic evaluation of the interactions between nonimmune cells and immune cells and their effects on metabolism in the context of aortic dissection. Here, multiomics, including bulk RNA-seq, single-cell RNA-seq, and lipid metabolomics, was applied to elucidate the comprehensive TAAD lipid metabolism landscape. Normally, monocytes in the stress response state secrete a variety of cytokines. Injured fibroblasts lack the ability to degrade lipids, which is suspected to contribute to a high lipid environment. Macrophages differentiate into fatty acid binding protein 5-positive (FABP5+) macrophages under the stimulation of metabolic substrates. Moreover, the upregulation of Fabp5+ macrophages were retrospectively validated in TAAD model mice and TAAD patients. Finally, Fabp5+ macrophages can generate a wide range of proinflammatory cytokines, which possibly contribute to TAAD pathogenesis.

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.

Development and validation of a 6-gene signature derived from RNA modification-associated genes for the diagnosis of Acute Stanford Type A Aortic Dissection

Background

Acute Stanford Type A Aortic Dissection (ATAAD) is a critical medical emergency characterized by significant morbidity and mortality. This study aims to identify specific gene expression patterns and RNA modification associated with ATAAD.

Methods

The GSE153434 dataset was obtained from the Gene Expression Omnibus (GEO) database. Differential expression analysis was conducted to identify differential expression genes (DEGs) associated with ATAAD. To validate the involvement of RNA modification in ATAAD, RNA modification-related genes (M6A, M1A, M5C, APA, A-to-I) were acquired from GeneCards, following by Least Absolute Shrinkage and Selection Operator (LASSO) regression analysis. A gene prediction signature consisting of key genes was established, and Real-time PCR was used to validate the gene expression in clinical samples. The patients were then divided into high and low-risk groups, and subsequent enrichment analysis, including Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), Gene Set Enrichment Analysis (GSEA), Gene Set Variation Analysis (GSVA), and assessments of immune infiltration. A co-expression network analysis (WGCNA) was performed to explore gene-phenotype relationships and identify key genes.

Results

A total of 45 RNA modification genes were acquired. Six gene signatures (YTHDC1, WTAP, CFI, ADARB1, ADARB2, TET3) were developed for ATAAD diagnosis and risk stratification. Enrichment analysis suggested the potential involvement of inflammation and extracellular matrix pathways in the progression of ATAAD. The incorporation of pertinent genes from the GSE147026 dataset into the six-gene signature further validated the model's effectiveness. A significant upregulation in WTAP, ADARB2, and TET3 expression, whereas YTHDC1 exhibited a noteworthy downregulation in the ATAAD group.

Conclusion

Six-gene signature could serve as an efficient model for predicting the diagnosis of ATAAD.

Developing and Verifying an Effective Diagnostic Model Linked to Immune Infiltration in Stanford Type A Aortic Dissection

BACKGROUND

The deadly cardiovascular condition known as Stanford type A aortic dissection (TAAD) carries a high risk of morbidity and mortality. One important step in the pathophysiology of the condition is the influx of immune cells into the aorta media, which causes medial degeneration. The purpose of this work was to investigate the potential pathogenic significance of immune cell infiltration in TAAD and to test for associated biomarkers.

METHODS

The National Center for Biotechnology Information (NCBI) Gene Expression Omnibus (GEO) database provided the RNA sequencing microarray data (GSE153434, GPL20795, GSE52093). Immune cell infiltration abundance was predicted using ImmuCellAI. GEO2R was used to select differentially expressed genes (DEGs), which were then processed for Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses. Additionally, hub genes linked to immune infiltration were found using functional and pathway enrichment, least absolute shrinkage and selection operator (LASSO), weighted gene co-expression network analysis (WGCNA), and differential expression analysis. Lastly, hub genes were validated and assessed using receiver operating characteristic (ROC) curves in the microarray dataset GSE52093. The hub gene expression and its connection to immune infiltration in TAAD were confirmed using both animal models and clinic data.

RESULTS

We identified the most important connections between macrophages, T helper cell 17 (Th17), iTreg cells, B cells, natural killer cells and TAAD. And screened seven hub genes associated with immune cell infiltration: ABCG2, FAM20C, ELL2, MTHFD2, ANKRD6, GLRX, and CDCP1. The diagnostic model in TAAD diagnosis with the area under ROC (AUC) was 0.996, and the sensitivity was 99.21%, the specificity was 98.67%, which demonstrated a surprisingly strong diagnostic power of TAAD in the validation datasets. The expression pattern of four hub DEGs (ABCG2, FAM20C, MTHFD2, CDCP1) in clinic samples and animal models matched bioinformatics analysis, and ABCG2, FAM20C, MTHFD2 up-regulation, and the of CDCP1 down-regulation were also linked to poor cardiovascular function.

CONCLUSIONS

This study developed and verified an effective diagnostic model linked to immune infiltration in TAAD, providing new approaches to studying the potential pathogenesis of TAAD and discovering new medication intervention targets.

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.

Analysis of Inflammation-Related Genes in Patients with Stanford Type A Aortic Dissection

Background: Aortic dissection (AD) is a life-threatening cardiovascular disease. Pathophysiologically, it has been shown that aortic wall inflammation promotes the occurrence and development of aortic dissection. Thus, the aim of the current research was to determine the inflammation-related biomarkers in AD. Methods: In this study, we conducted differentially expressed genes (DEGs) analysis using the GSE153434 dataset containing 10 type A aortic dissection (TAAD) and 10 normal samples downloaded from the Gene Expression Omnibus (GEO) database. The intersection of DEGs and inflammation-related genes was identified as differential expressed inflammation-related genes (DEIRGs). Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses were performed for DEIRGs. We then constructed the protein-protein interaction (PPI) network using the Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) database and identified hub genes using the Cytoscape plugin MCODE. Finally, least absolute shrinkage and selection operator (LASSO) logistic regression was used to construct a diagnostic model. Results: A total of 1728 DEGs were identified between the TAAD and normal samples. Thereafter, 61 DEIRGs are obtained by taking the intersection of DEGs and inflammation-related genes. The GO indicated that DEIRGs were mainly enriched in response to lipopolysaccharide, in response to molecules of bacterial origin, secretory granule membrane, external side of plasma, receptor ligand activity, and signaling receptor activator activity. KEGG analysis indicated that DEIRGs were mainly enriched in cytokine-cytokine receptor interaction, TNF signaling pathway, and proteoglycans in cancer. We identified MYC, SELL, HIF1A, EDN1, SERPINE1, CCL20, IL1R1, NOD2, TLR2, CD69, PLAUR, MMP14, and HBEGF as hub genes using the MCODE plug-in. The ROC indicated these genes had a good diagnostic performance for TAAD. Conclusion: In conclusion, our study identified 13 hub genes in the TAAD. This study will be of significance for the future development of a preventive therapy 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.

Targeting autophagy in aortic aneurysm and dissection

Autophagy is a well-conserved biological process that maintains homeostasis. Accumulating evidence has revealed that autophagy plays an important role in various cardiovascular diseases, such as aneurysm, aortic dissection, atherosclerosis, and myocardial ischemia-reperfusion injury. Here, we summarize the current experimental evidence on the function of autophagy and autophagy proteins in aortic aneurysm and dissection (AAD). AAD is a very serious aortic disease, and there are currently no effective drug treatment options. Studies have shown that autophagy is activated during AAD. However, the role of autophagy in AAD is still controversial. For example, knocking out autophagy related 5 (ATG5) or ATG7 to inhibit autophagy and excessive autophagy activation can promote the occurrence of AAD. Recently, multiple studies have demonstrated that rapamycin and metformin, which are autophagy activators, can delay the progression of AAD. Thus, targeting autophagy has the potential to become a new therapeutic strategy for AAD. In addition, we discuss the recent research progress on AAD from the perspective of single-cell RNA sequencing. Moreover, we offer our perspective on current challenges and barriers in this research field.

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.

Targeting Ferroptosis as a Novel Approach to Alleviate Aortic Dissection

A variety of programmed cell death types have been shown to participate in the loss of smooth muscle cells (SMCs) during the development of aortic dissection (AD), but it is still largely unclear whether ferroptosis is involved in the development of AD. In the present study, we found that the expression of key ferroptosis regulatory proteins, solute carrier family 7 member 11 (SLC7A11), ferroptosis suppressor protein 1 (FSP1) and glutathione peroxidase 4 (GPX4) were downregulated in aortas of Stanford type A AD (TAAD) patients, and liproxstatin-1, a specific inhibitor of ferroptosis, obviously abolished the β-aminopropionitrile (BAPN)-induced development and rupture of AD in mice. Furthermore, the expression of methyltransferase-like 3 (METTL3), a major methyltransferase of RNA m6A, was remarkably upregulated in the aortas of TAAD patients, and the protein levels of METTL3 were negatively correlated with SLC7A11 and FSP1 levels in human aortas. Overexpression of METTL3 in human aortic SMCs (HASMCs) inhibited, while METTL3 knockdown promoted SLC7A11 and FSP1 expression. More importantly, overexpression of METTL3 facilitated imidazole ketone erastin- and cystine deprivation-induced ferroptosis, while knockdown of METTL3 repressed ferroptosis of HASMCs. Overexpression of either SLC7A11 or FSP1 largely abrogated the effect of METTL3 on HASMC ferroptosis. Therefore, we have revealed that ferroptosis is a critical cause of AD in both humans and mice and that METTL3 promotes ferroptosis of HASMCs by inhibiting the expression of SLC7A11 and FSP1. Thus, targeting ferroptosis or m6A RNA methylation is a potential novel strategy for the treatment of AD.

Role of Necroptosis and Immune Infiltration in Human Stanford Type A Aortic Dissection: Novel Insights from Bioinformatics Analyses

Background

Stanford type A aortic dissection (TAAD) is one of the most life-threatening cardiovascular emergencies with high mortality and morbidity, and necroptosis is a newly identified type of programmed cell death and contributes to the pathogenesis of various cardiovascular diseases. However, the role of necroptosis in TAAD has not been elucidated. This study was aimed at determining the role of necroptosis in TAAD using bioinformatics analyses.

Methods

The RNA sequencing dataset GSE153434 and the microarray dataset GSE52093 were obtained from Gene Expression Omnibus (GEO) database. Differentially expressed genes of necroptosis (NRDEGs) were identified based on differentially expressed genes (DEGs) and necroptosis gene set. Gene set enrichment analysis (GSEA) was applied to evaluate the gene enrichment signaling pathway in TAAD. The STRING database and Cytoscape software were used to establish and visualize protein-protein interaction (PPI) networks and identify the key functional modules of NRDEGs. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses of NRDEGs were also performed. Additionally, Spearman correlations were used to construct the necroptosis-related transcription factor-target genes regulatory network, immune infiltration patterns were analyzed using the ImmuCellAI algorithm, and the correlation between immune cell-type abundance and NRDEGs expression was investigated. The expression levels of NRDEGs and immune infiltration were additionally verified in the GSE52093 dataset.

Results

We found that the necroptosis pathway was considerably enriched and activated in TAAD samples. Overall, 25 NRDEGs were identified including MLKL, RIPK1, and FADD, and among them, 18 were verified in the validation set. Moreover, GO and KEGG enrichment analyses found that NRDEGs were primarily involved in the tumor necrosis factor signaling pathway, nucleotide-binding oligomerization domain-like receptor signaling pathway, and interleukin-17 signaling pathway. The imbalance of Th17/Treg cells was identified in the TAAD samples. Furthermore, correlation analysis indicated that expression of NRDEGs was positively associated with proinflammatory immune-cell infiltrations and negatively associated with anti-inflammatory or regulatory immune-cell infiltrations.

Conclusions

The present findings suggest that necroptosis phenomenon exists in TAAD and correlates with immune cell infiltration, which indicate necroptosis may promote the development of TAAD through activating immune infiltration and immune response. This study paves a new road to future investigation of the pathogenic mechanisms and therapeutic strategies for TAAD.

Bioinformatics Analysis Reveals Cell Cycle-Related Gene Upregulation in Ascending Aortic Tissues From Murine Models

Thoracic aortic aneurysm and dissection (TAAD) is a high-risk aortic disease. Mouse models are usually used to explore the pathological progression of TAAD. In our studies, we performed bioinformatics analysis on a microarray dataset (GSE36778) and verified experiments to define the integrated hub genes of TAAD in three different mouse models. Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) and protein-protein interaction (PPI) network analyses, and histological and quantitative reverse transcription-PCR (qRT-PCR) experiments were used in our study. First, differentially expressed genes (DEGs) were identified, and twelve common differentially expressed genes were found. Second, genes related to the cell cycle and inflammation were enriched by using GO and PPI. We focused on filtering and validating eighteen hub genes that were upregulated. Then, expression data from human ascending aortic tissues in the GSE153434 dataset were also used to verify our findings. These results indicated that cell cycle-related genes participate in the pathological mechanism of TAAD and provide new insight into the molecular mechanisms of TAAD.

Role of ferroptosis-related genes in Stanford type a aortic dissection and identification of key genes: new insights from bioinformatic analysis

Stanford type A aortic dissection (TAAD) is one of the most dangerous vascular diseases worldwide, and the mechanisms of its development remain unclear. Further molecular pathology studies may contribute to a comprehensive understanding of TAAD and provide new insights into diagnostic markers and potential therapeutic targets. Recent studies have identified that ferroptosis, a form of cell death, may play a previously unrecognized role in influencing the development of TAAD. In this study, we explored the pathological role of ferroptosis in TAAD by performing bioinformatics analyses. Gene set enrichment analysis (GSEA) showed that the ferroptosis-related gene (FRG) set was significantly different between normal and TAAD aortic samples at an overall level (p < 0.001). Further Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses explored the potential functions and pathways of FRG in TAAD. We further identified six key genes (CA9, HMOX1, IL6, CDKN1A, HIF1A, MYC) from differentially expressed FRGs in TAAD by constructing a protein-protein interaction (PPI) network, all key genes were upregulated in TAAD. Four of the key genes (CA9, IL6, CDKN1A, and HIF1A) were demonstrated to be correlated with cigarette smoke extract-induced ferroptosis in aortic vascular smooth muscle cells. These results suggest that ferroptosis is one of the essential pathological processes in the development of TAAD, and some FRGs affect TAAD development by mediating cellular ferroptosis, which provides deepening insights into the molecular mechanisms and potential therapeutic targets of TAAD.

Genome-Wide Identification of RNA Modifications for Spontaneous Coronary Aortic Dissection

RNA modification plays important roles in many biological processes such as gene expression control. Genetic variants that affect RNA modification may have functional roles in aortic dissection. The aim of this study was to identify RNA modifications related to spontaneous coronary artery dissection (SCAD). We examined the association of RNA modification-associated single-nucleotide polymorphisms (RNAm-SNPs) with SCAD in summary data from a genome-wide association study (GWAS) of European descent (270 SCAD cases and 5,263 controls). Furthermore, we performed expression quantitative loci (eQTL) and protein quantitative loci (pQTL) analyses for the RNAm-SNPs using publicly available data. Functional enrichment and protein–protein interaction analyses were performed for the identified proteins. We found 11,464 unique RNAm-SNPs in the SCAD GWAS dataset, and 519 were nominally associated with SCAD. Nine RNAm-SNPs were associated with SCAD at p < 0.001, and among them, seven were N⁶-methyladenosine (m⁶A) methylation-related SNPs, one (rs113664950 in HLA-DQB1) was m⁷G-associated SNP, and one [rs580060 in the 3′-UTR of Mitochondrial Ribosomal Protein S21 (MRPS21)] was A-to-I modification SNP. The genome-wide significant SNP rs3818978 (SCAD association p = 5.74 × 10^–10) in the 5′-UTR of MRPS21 was related to m⁶A modification. These nine SNPs all showed eQTL effects, and six of them were associated with circulating protein or metabolite levels. The related protein-coding genes were enriched in specific Gene Ontology (GO) terms such as extracellular space, extracellular region, defense response, lymphocyte migration, receptor binding and cytokine receptor binding, and so on. The present study found the associations between RNAm-SNPs and SCAD. The findings suggested that RNA modification may play functional roles in SCAD.

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.

Neutrophil to lymphocyte ratio and fibrinogen values in predicting patients with type B aortic dissection

The aim of this study is to detect the diagnosis value of neutrophil lymphocyte ratio (NLR) and fibrinogen (FIB) in type B aortic dissection (TBAD) patients. This retrospective observation study consisted patients with TBAD, aortic aneurysm and physical examination between January 1, 2016 and December 31, 2019. Demographic and clinical information after the first admission were collected. Multivariate logistic regression analysis was performed to explore the correlational relationship between NLR, FIB and TBAD. Receiver Operating Characteristic Curve (ROC) was performed to evaluate the diagnostic implication of NLR and FIB in TBAD patients. Six hundred and six patients who were first diagnosed with TBAD were included. Control groups were 202 aortic aneurysm and 140 physical examination subjects. The level of NLR and FIB in aortic dissection patients was significantly higher than aortic aneurysm patients and healthy group (P < 0.001). According to the results of multivariate logistic regression analysis, NLR and FIB were independent risk factors of aortic dissection, and the odds ratio (OR) and 95% confidence interval (CI) value of NLR and FIB were 1.499 (1.126–1.738) and 1.914 (1.475–2.485), respectively. The area under the curve (AUC) was 0.836 of NLR and 0.756 of FIB. NLR and FIB showed high specificity, 89% and 83% respectively. This is the first study provided information on the diagnosis performance of NLR and FIB in TBAD patients. NLR and FIB showed high specificity, which may be a valuable tool for the diagnosis of TBAD.