Crucial Genes in Aortic Dissection Identified by Weighted Gene Coexpression Network Analysis

Identification of a novel immune infiltration-related gene signature, MCEMP1, for coronary artery disease

Background

This study aims to identify a novel gene signature for coronary artery disease (CAD), explore the role of immune cell infiltration in CAD pathogenesis, and assess the cell function of mast cell-expressed membrane protein 1 (MCEMP1) in human umbilical vein endothelial cells (HUVECs) treated with oxidized low-density lipoprotein (ox-LDL).

Methods

To identify differentially expressed genes (DEGs) of CAD, datasets GSE24519 and GSE61145 were downloaded from the Gene Expression Omnibus (GEO) database using the R "limma" package with p < 0.05 and |log2 FC| > 1. Gene ontology (GO) and pathway analyses were conducted to determine the biological functions of DEGs. Hub genes were identified using support vector machine-recursive feature elimination (SVM-RFE) and least absolute shrinkage and selection operator (LASSO). The expression levels of these hub genes in CAD were validated using the GSE113079 dataset. CIBERSORT program was used to quantify the proportion of immune cell infiltration. Western blot assay and qRT-PCR were used to detect the expression of hub genes in ox-LDL-treated HUVECs to validate the bioinformatics results. Knockdown interference sequences for MCEMP1 were synthesized, and cell proliferation and apoptosis were examined using a CCK8 kit and Muse® Cell Analyzer, respectively. The concentrations of IL-1β, IL-6, and TNF-α were measured with respective enzyme-linked immunosorbent assay (ELISA) kits.

Results

A total of 73 DEGs (four down-regulated genes and 69 up-regulated genes) were identified in the metadata (GSE24519 and GSE61145) cohort. GO and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis results indicated that these DEGs might be associated with the regulation of platelet aggregation, defense response or response to bacterium, NF-kappa B signaling pathway, and lipid and atherosclerosis. Using SVM-RFE and LASSO, seven hub genes were obtained from the metadata. The upregulated expression of DIRC2 and MCEMP1 in CAD was confirmed in the GSE113079 dataset and in ox-LDL-treated HUVECs. The associations between the two hub genes (DIRC2 and MCEMP1) and the 22 types of immune cell infiltrates in CAD were found. MCEMP1 knockdown accelerated cell proliferation and suppressed cell apoptosis for ox-LDL-treated HUVECs. Additionally, MCEMP1 knockdown appeared to decrease the expression of inflammatory factors IL-1β, IL-6, and TNF-α.

Conclusions

The results of this study indicate that MCEMP1 may play an important role in CAD pathophysiology.

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.

Weekend Effect and Mortality Outcomes in Aortic Dissection: A Prospective Analysis

Background

Aortic dissection (AD) is a critical heart condition with potentially severe outcomes. Our study aimed to investigate the existence of a "weekend effect" in AD by examining the correlation between patient outcomes and whether their treatment occurred on weekdays versus weekends.

Methods

Specifically, we prospectively analysed the effect of weekday and weekend treatment on acute AD patient outcomes, both before surgical intervention and during hospitalization, for 124 patients treated from 2019-2021, as well as during 6 months of follow-up.

Results

The mean age of the study population was 62.5 years, and patient age exhibited a high degree of variability. We recorded a mortality rate before surgery of 8.65% for the weekend group and 15% for the weekday group, but this difference was not statistically significant. During hospitalization, mortality was 50% in the weekend group and 25% in the weekday group, but this difference was not statistically significant. Discharge mortality was 9.61% in the weekend group and 5% in the weekday group.

Conclusions

Our findings suggest that there was no significant difference in mortality rates between patients admitted to the hospital on weekends versus weekdays. Therefore, the period of the week when a patient presents to the hospital with AD appears not to affect their mortality.

Downregulation of LILRB4 Promotes Human Aortic Smooth Muscle Cell Contractile Phenotypic Switch and Apoptosis in Aortic Dissection

Aortic dissection (AD) is a severe vascular disease with high rates of mortality and morbidity. However, the underlying molecular mechanisms of AD remain unclear. Differentially expressed genes (DEGs) were screened by bioinformatics methods. Alterations of histopathology and inflammatory factor levels in β-aminopropionitrile (BAPN)-induced AD mouse model were evaluated through Hematoxylin-Eosin (HE) staining and Enzyme-linked immunosorbent assay (ELISA), respectively. Reverse transcription quantitative real-time polymerase chain reaction was performed to detect DEGs expression. Furthermore, the role of LILRB4 in AD was investigated through Cell Counting Kit-8 (CCK-8), wound healing, and flow cytometry. Western blotting was employed to assess the phenotypic switch and extracellular matrix (ECM)-associated protein expressions in platelet-derived growth factor-BB (PDGF-BB)-stimulated in vitro model of AD. In the AD mouse model, distinct dissection formation was observed. TNF-α, IL-1β, IL-8, and IL-6 levels were higher in the AD mouse model than in the controls. Six hub genes were identified, including LILRB4, TIMP1, CCR5, CCL7, MSR1, and CLEC4D, all of which were highly expressed. Further exploration revealed that LILRB4 knockdown inhibited the cell vitality and migration of PDGF-BB-induced HASMCs while promoting apoptosis and G0/G1 phase ratio. More importantly, LILRB4 knockdown promoted the protein expression of α-SMA and SM22α, while decreasing the expression of Co1, MMP2, and CTGF, which suggested that LILRB4 silencing promoted contractile phenotypic transition and ECM stability. LILRB4 knockdown inhibits the progression of AD. Our study provides a new potential target for the clinical treatment of AD.

Comparison of Transcriptomic Signatures between Monkeypox-Infected Monkey and Human Cell Lines

Monkeypox virus (MPV) is a smallpox-like virus belonging to the genus Orthopoxvirus of the family Poxviridae. Unlike smallpox with no animal reservoir identified and patients suffering from milder symptoms with less mortality, several animals were confirmed to serve as natural hosts of MPV. The reemergence of a recently reported monkeypox epidemic outbreak in nonendemic countries has raised concerns about a global outburst. Since the underlying mechanism of animal-to-human transmission remains largely unknown, comprehensive analyses to discover principal differences in gene signatures during disease progression have become ever more critical. In this study, two MPV-infected in vitro models, including human immortal epithelial cancer (HeLa) cells and rhesus monkey (Macaca mulatta) kidney epithelial (MK2) cells, were chosen as the two subjects to identify alterations in gene expression profiles, together with co-regulated genes and pathways that are affected during monkeypox disease progression. Using Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and MetaCore analyses, we discovered that elevated expression of genes associated with interleukins (ILs), G protein-coupled receptors (GPCRs), heat shock proteins (HSPs), Toll-like receptors (TLRs), and metabolic-related pathways play major roles in disease progression of both monkeypox-infected monkey MK2 and human HeLa cell lines. Interestingly, our analytical results also revealed that a cluster of differentiation 40 (CD40), plasmin, and histamine served as major regulators in the monkeypox-infected monkey MK2 cell line model, while interferons (IFNs), macrophages, and neutrophil-related signaling pathways dominated the monkeypox-infected human HeLa cell line model. Among immune pathways of interest, apart from traditional monkeypox-regulated signaling pathways such as nuclear factor- (NF-κB), mitogen-activated protein kinases (MAPKs), and tumor necrosis factors (TNFs), we also identified highly significantly expressed genes in both monkey and human models that played pivotal roles during the progression of monkeypox infection, including CXCL1, TNFAIP3, BIRC3, IL6, CCL2, ZC3H12A, IL11, CSF2, LIF, PTX3, IER3, EGR1, ADORA2A, and DUOX1, together with several epigenetic regulators, such as histone cluster family gene members, HIST1H3D, HIST1H2BJ, etc. These findings might contribute to specific underlying mechanisms related to the pathophysiology and provide suggestions regarding modes of transmission, post-infectious sequelae, and vaccine development for monkeypox in the future.

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.