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

HMGB2 promotes smooth muscle cell proliferation through PPAR-γ/PGC-1α pathway-mediated glucose changes in aortic dissection

BACKGROUND AND AIMS

Aortic dissection (AD) is a fatal condition with a complicated pathogenesis. High mobility group protein B2 (HMGB2) is a member of the high mobility group protein family; HMGB2 is involved in innate immunity and inflammatory diseases, but its role in AD remains unclear.

METHODS

HMGB2-/- mice were generated and treated with β-aminopropionitrile and angiotensin II (Ang II) to establish an AD model. An F12 gel containing AAV9-HMGB2 was applied to overexpress HMGB2 in mice. Pathological changes in the aorta were assessed by visualizing vascular collagen deposition and elastic fiber fracture via H&E, Masson and EVG staining. HMGB2 expression was measured by Western blotting and immunohistochemistry. MTS, CCK-8 and EdU assays were used to test cell proliferation.

RESULTS

HMGB2 expression was increased in samples from AD patients, samples from AD mouse modeland human aortic smooth muscle cells (HASMCs). HMGB2 promoted HASMC proliferation. Immunofluorescence staining and plasma membrane protein isolation revealed that HMGB2 decreased GLUT1 expression and promoted GLUT4 translocation. HMGB2 was also found to inhibit the expression of SIRT1/PGC-1α, but blocking the PPAR-γ pathway attenuated this effect. HMGB2-/- significantly reduced the incidence and mortality rates of AD, whereas treatment with AAV9-HMGB2 exacerbated AD.

CONCLUSIONS

This study suggests that HMGB2 promotes HASMC proliferation and vascular remodeling by regulating glucose metabolism through the PPAR-γ/SIRT1/PGC-1α pathway. HMGB2 knockdown reduces, while HMGB2 overexpression promotes, the occurrence of AD in mice. This study may help elucidate the underlying mechanisms and provide a new preventive target for AD.

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.

Angiopoietin-like 4 facilitates human aortic smooth muscle cell phenotype switch and dysfunctions through the PI3K/Akt signaling in aortic dissection

PURPOSE

Vascular smooth muscle cell (VSMC) phenotype switch and dysfunctions have been reported to participate in aortic dissection (AD) progression. This study was aimed to investigate the role of angiopoietin-like 4 (ANGPTL4) in regulating VSMCs phenotype switch.

MATERIALS AND METHODS

Key genes were analyzed in AD using public datasets, and it was found that the central differential gene ANGPTL4 was up-regulated in AD. The KEGG signaling pathway annotation was performed to validate the associated pathways, and the expression of ANGPTL4 was verified using multiple datasets and clinical samples. Furthermore, the specific functions of ANGPTL4 on platelet-derived growth factor-BB (PDGF-BB)-treated human aortic smooth muscle cell (HASMC) phenotypes were investigated. The dynamic effects of ANGPTL4 and core signaling antagonists on HASMC phenotypes were examined.

RESULTS

Hub gene ANGPTL4 was significantly up-regulated in AD. ANGPTL4 was linked to the PI3K/Akt signaling, angiogenesis, and neovascularization and remodeling. ANGPTL4 overexpression further enhanced PDGF-BB effects on HASMC phenotypes, including promoted cell viability and migration, decreased contractile VSMC markers α-SMA and SM22α, elevated ECM degradation markers MMP-2 and MMP-9, and promoted phosphorylation of PI3K and Akt. ANGPTL4 knockdown partially abolished PDGF-BB-induced contractile/synthetic VSMCs imbalance and HASMC dysfunctions. Furthermore, in ANGPTL4-overexpressing HASMCs pre-treated with PDGF-BB, the PI3K/Akt signaling inhibitor LY294002 also partially eliminated the effects caused by the PDGF-BB treatment and ANGPTL4 overexpression.

CONCLUSIONS

ANGPTL4 is significantly up-regulated in AD. ANGPTL4 overexpression further enhanced PDGF-BB effects on HASMC phenotype switch and dysfunctions, which might be involved in the PI3K/Akt signaling.

Comprehensive analysis of gene signatures associated with aging in human aortic dissection

Background

Aortic dissection (AD) is a lethal aortic disease with limited effective therapeutic strategies. Aging increases the risk of AD, yet the underlying mechanisms remain unclear. This study aims to analyze the association of aging-related genes (Args) and AD using bioinformatic analysis. This helps provide novel insights into AD pathogenesis and contributes to developing novel therapeutic strategies.

Methods

mRNA (GSE52093, GSE153434), miRNA (GSE98770) and single-cell RNA-sequencing (scRNA-seq, GSE213740) datasets of AD were downloaded from GEO database. Args were downloaded from Aging Atlas database. Differentially-expressed Args were determined by intersecting Args and differentially-expressed mRNAs of two mRNA datasets. Cytoscape was used to identify hub genes and construct hub gene regulatory networks related to miRNAs. Seurat and clusterProfiler R package were used for investigating expression patterns of hub genes at single-cell level, and functional analysis, respectively. To validate the cellular expression pattern of hub genes, the same analysis was applied to our own scRNA-seq data. Drugs targeting hub Args were determined using the DGIdb database.

Results

HGF, CXCL8, SERPINE1, HIF1A, TIMP1, ESR1 and PLAUR were identified as aging-related hub genes in AD. miR-221-3p was predicted to interact with ESR1. A decreased ESR1 expression in smooth muscle cell subpopulation 4 (SMC4) was observed in AD versus normal aortic tissues, which was validated by sequencing 197,605 aortic cells from 13 AD patients. Additionally, upregulated genes of SMC4 in AD tissues were enriched in the "cellular senescence" pathway. These data indicated that decreased ESR1 might promote SMC4 aging during AD formation. Eleven existing drugs targeting hub genes were identified, including ruxolitinib and filgrastim, which are associated with AD.

Conclusions

By sequencing transcriptomic data, this study revealed aging-related hub genes and regulatory network involved in AD formation. Additionally, this study proposed a noteworthy hypothesis that downregulated ESR1 may exacerbate AD by promoting SMC aging, which requires further investigation.

Epigenomics in aortic dissection: From mechanism to therapeutics

Aortic dissection (AD) has an unfavorable prognosis. It requires early diagnosis, appropriate treatment strategies, and suspicion to recognize symptoms; thus, it is commonly described as an acute aortic emergency. The clinical manifestations of painless AD are complex and variable. However, there is no effective treatment to prevent the progression of AD. Therefore, study of the molecular targets and mechanisms of AD to enable prevention or early intervention is particularly important. Although multiple gene mutations have been proposed as linked to AD development, evidence that multiple epigenetic elements are strongly associated is steadily increasing. These epigenetic processes include DNA methylation, N6-methyladenosine, histone modification, non-histone posttranslational modification, and non-coding RNAs (ncRNAs). Among these processes, resveratrol targeting Sirtuin 1 (SIRT1), 5-azacytidine (5azaC) targeting DNA methyltransferase (DNMT), and vitamin C targeting ten-eleven translocation 2 (Tet2) showed unique advantages in improving AD and vascular dysfunction. Finally, we explored potential epigenetic drugs and diagnostic methods for AD, which might provide options for the future.

Bioinformatics analysis of aging-related genes in thoracic aortic aneurysm and dissection

Objective

Thoracic aortic aneurysm and dissection (TAAD) is a cardiovascular disease with a high mortality rate. Aging is an important risk factor for TAAD. This study explored the relationship between aging and TAAD and investigated the underlying mechanisms, which may contribute to the diagnosis and treatment of TAAD.

Methods

Human aging genes were obtained from the Aging Atlas official website. Various datasets were downloaded from the GEO database:the human TAAD dataset GSE52093 were used for screening differentially expressed genes (DEGs); GSE137869, GSE102397 and GSE153434 were used as validation sets, and GSE9106 was used for diagnostic prediction of receiver operating characteristic (ROC) curves. Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), Gene Set Enrichment Analysis (GSEA), and protein-protein interaction (PPI) network analysis were used to screen differentially co-expressed genes from human aging genes and TAAD. Using five methods of the cytoHubba plugin in Cytoscape software (Degree, Closeness, EPC, MNC, Radiality), hub genes were identified from the differentially co-expressed genes. Single-cell RNA sequencing was used to verify the expression levels of hubgenes in different cell types of aortic tissue. ROC curves were used to further screen for diagnostic genes.

Results

A total of 70 differentially co-expressed genes were screened from human aging genes and DEGs in human TAAD dataset GSE52093. GO enrichment analysis revealed that the DEGs played a major role in regulating DNA metabolism and damaged DNA binding. KEGG enrichment analysis revealed enrichment in the longevity regulating pathway, cellular senescence, and HIF-1 signaling pathway. GSEA indicated that the DEGs were concentrated in the cell cycle and aging-related p53 signaling pathway. The five identified hubgenes were MYC, IL6, HIF1A, ESR1, and PTGS2. Single-cell sequencing of the aging rat aorta showed that hubgenes were expressed differently in different types of cells in aortic tissue. Among these five hubgenes, HIF1A and PTGS2 were validated in the aging dataset GSE102397; MYC, HIF1A and ESR1 were validated in the TAAD dataset GSE153434. The combined area under the diagnostic ROC curve (AUC) values for the five hub genes were >0.7 in the testing and training sets of the dataset GSE9106. The combined AUC values of MYC and ESR1 were equal to the combin ed AUC values of the five hub genes.

Conclusion

The HIF-1 signaling pathway may play an important role in TAAD and aging. MYC and ESR1 may have diagnostic value for aging-related TAAD.

Identification of Immune-Related Gene Signature in Stanford Type A Aortic Dissection

Background: Stanford type A aortic dissection (ATAAD) is a common life-threatening event in the aorta. Recently, immune disorder has been linked to the risk factors that cause ATAAD at the molecular level. However, the specific immune-related gene signature during the progression is unclear.

Methods: The GSE52093 and GSE98770 datasets related to ATAAD from the Gene Expression Omnibus (GEO) database were acquired. The immune gene expression levels were analyzed by single sample gene set enrichment analysis (ssGSEA). The correlations between gene networks and immune scores were determined by weighted gene correlation network analysis (WGCNA). The different immune subgroups were finally divided by consensus clustering. The differentially expressed genes (DEGs) were identified and subsequent functional enrichment analyses were conducted. The hub genes were identified by protein–protein interaction (PPI) network and functional similarities analyses. The immune cell infiltration proportion was determined by the CIBERSORT algorithm.

Results: According to the ssGSEA results, the 13 ATAAD samples from the GEO database were divided into high- and low-immune subgroups according to the ssGSEA, WGCNA, and consensus clustering analysis results. Sixty-eight immune-related DEGs (IRDEGs) between the two subgroups were enriched in inflammatory-immune response biological processes, including leukocyte cell–cell adhesion, mononuclear cell migration, and myeloid leukocyte migration. Among these IRDEGs, 8 genes (CXCR4, LYN, CCL19, CCL3L3, SELL, F11R, DPP4, and VAV3) were identified as hub genes that represented immune-related signatures in ATAAD after the PPI and functional similarities analyses. The proportions of infiltrating CD8 T cells and M1 macrophages were significantly higher in ATAAD patients in the immune-high group than the immune-low group.

Conclusion: Eight immune-related genes were identified as hub genes representing potential biomarkers and therapeutic targets linked to the immune response in ATAAD patients.

Comprehensive Analysis of Key m6A Modification Related Genes and Immune Infiltrates in Human Aortic Dissection

Objective

To identify the feature of N6-methyladenosine (m6A) methylation modification genes in acute aortic dissection (AAD) and explore their relationships with immune infiltration.

Methods

The GSE52093 dataset including gene expression data from patients with AAD and healthy controls was downloaded from Gene Expression Omnibus (GEO) database in order to obtain the differentially expressed genes (DEGs). The differentially methylated m6A genes were obtained from the GSE147027 dataset. The differentially expressed m6A-related genes were obtained based on the intersection results. Meanwhile, the protein-protein interaction (PPI) network of differentially expressed m6A-related genes was constructed, and hub genes with close relationships in the network were selected. Later, hub genes were verified by using the GSE153434 dataset. Thereafter, the relationships between these genes and immune cells infiltration were analyzed.

Results

A total of 279 differentially expressed m6A-related genes were identified in the GSE52093 and GSE147027 datasets. Among them, 94 genes were up-regulated in aortic dissection (AD), while the remaining 185 were down-regulated. As indicated by Gene Ontology (GO) functional enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses, these genes were mainly associated with extracellular matrix (ECM) and smooth muscle cells (SMCs). The seven hub genes, namely, DDX17, CTGF, FLNA, SPP1, MYH11, ITGA5 and CACNA1C, were all confirmed as the potential biomarkers for AD. According to immune infiltration analysis, it was found that hub genes were related to some immune cells. For instance, DDX17, FLNA and MYH11 were correlated with Macrophages M2.

Conclusion

Our study identifies hub genes of AD that may serve as the potential biomarkers, illustrates of the molecular mechanism of AD, and provides support for subsequent research and treatment development.

Potential Clinical Value of Biomarker-Guided Emergency Triage for Thoracic Aortic Dissection

Aim: Thoracic aortic dissection (TAD) is a high-risk vascular disease. The mortality rate of untreated TADs in 24 h was as high as 50%. Thus, rapid diagnosis of TAD in the emergency department would get patients to the right treatments to save their lives. Methods: We profiled the proteome of aortic tissues from TAD patients using a label-free quantification proteomics method. The differentially expressed proteins were screened and subjected to bioinformatics analysis. Candidate biomarkers were selected and validated in independent serum samples using enzyme-linked immunosorbent assays (ELISAs). The diagnostic values were further predicted via receiver operating characteristic (ROC) curve analysis. Results: A total of 1,141 differentially expressed proteins were identified in aortic tissues from 17 TAD patients and eight myocardial infarction (MI) patients. Six proteins were selected as candidate biomarkers for ELISAs in an independent training set of 20 serum samples (TAD = 10, MI = 10). Of these proteins, four with a P-value < 0.01 were further validated in another independent set of 64 serum samples (TAD = 32, MI = 32) via ELISAs. ITGA2, COL2A1, and MIF had P-values < 0.0001, and their areas under the curve (AUCs) were 0.801 (95% CI: 0.691-0.911), 0.773 (95% CI: 0.660-0.887), and 0.701 (95% CI: 0.574-0.828), respectively. Conclusion: ITGA2, COL2A1, and MIF were identified as promising biomarkers for discriminating TAD from emergency patients with severe chest pain. Biomarker-guided emergency triage could further shorten the time for patients to get more effective treatments.