Patterns of immune infiltration in stable and raptured abdominal aortic aneurysms: A gene-expression-based retrospective study.

Abdominal aortic aneurysm (AAA) is a disease characterized by weakening arterial wall and permanent expansion with high mortality once rupture, which was involved with immune system activation. However, owing to technical difficulties, previous research has limited the impact of one or limited immune cells on AAA. We analyzed the composition of immune cells using the CIBERSORT algorithm through transcriptome sequencing data from patients with stable (eAAA) and ruptured aneurysms (rAAA). The whole transcriptome sequencing data, including 17 patients with ruptured AAA and 31 patients with stable AAA were downloaded from Gene Expression Omnibus (GEO, GSE98278). After normalizing and data processing, five rAAA and seventeen eAAA patients entered the follow-up analysis. We performed Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis to identify several pathways that were significantly enriched in rAAA compared to eAAA tissues. We demonstrated that the compositions of infiltrative immune cell in eAAA and rAAA were different. Naïve B cells, both resting and activated CD4+ memory T cells were found significantly higher in ruptured AAA, while memory B cells and activated mast cells were much less in ruptured AAA than that in stable AAA. Besides, PTX3 was significantly highly expressed in rAAA, which might be associated with the complement system and polarization of macrophages. Finally, differentially expressed genes and the related immune cells were mapped in a network to reveal the relationship between gene expression and infiltrative immune cells. We identified the infiltrated immune cell profile of eAAA and rAAA patients, which might be the potential target of AAA treatment.

Lei C ，Yang D ，Chen S ，Chen W ，Sun X ，Wu X ，Chen M ，Li Y ，Zheng Y ... -  《-》

Molecular Fingerprint for Terminal Abdominal Aortic Aneurysm Disease.

Clinical decision making in abdominal aortic aneurysms (AAA) relies completely on diameter. At this point, improved decision tools remain an unmet medical need. Our goal was to identify changes at the molecular level specifically leading up to AAA rupture. Aortic wall tissue specimens were collected during open elective (eAAA; n=31) or emergency repair of ruptured AAA (rAAA; n=17), and gene expression was investigated using microarrays. Identified candidate genes were validated with quantitative real-time polymerase chain reaction in an independent sample set (eAAA: n=46; rAAA: n=18). Two gene sets were identified, 1 set containing 5 genes linked to terminal progression, that is, positively associated with progression of larger AAA, and with rupture (HILPDA, ANGPTL4, LOX, SRPX2, FCGBP), and a second set containing 5 genes exclusively upregulated in rAAA (ADAMTS9, STC1, GFPT2, GAL3ST4, CCL4L1). Genes in both sets essentially associated with processes related to impaired tissue remodeling, such as angiogenesis and adipogenesis. In gene expression experiments we were able to show that upregulated gene expression for identified candidate genes is unique for AAA. Functionally, the selected upregulated factors converge at processes coordinated by the canonical HIF-1α signaling pathway and are highly expressed in fibroblasts but not inflammatory cells of the aneurysmatic wall. Histological quantification of angiogenesis and exploration of the HIF-1α network in rAAA versus eAAA shows enhanced microvessel density but also clear activation of the HIF-1α network in rAAA. Our study shows a specific molecular fingerprint for terminal AAA disease. These changes appear to converge at activation of HIF-1α signaling in mesenchymal cells. Aspects of this cascade might represent targets for rupture risk assessment.

Gäbel G ，Northoff BH ，Weinzierl I ，Ludwig S ，Hinterseher I ，Wilfert W ，Teupser D ，Doderer SA ，Bergert H ，Schönleben F ，Lindeman JHN ，Holdt LM ... -  《-》

A nomoscore of four genes for predicting the rupture risk in abdominal aortic aneurysm patients with osteoarthritis.

Abdominal aortic aneurysm (AAA) represents one of the most life-threatening cardiovascular diseases and is increasingly becoming a significant global public health concern. The aneurysms-osteoarthritis syndrome (AOS) has gained recognition, as patients with this syndrome often exhibit early-stage osteoarthritis (OA) and have a substantially increased risk of rupture, even with mild dilation of the aneurysm. The aim of this study was to discover potential biomarkers that can predict the occurrence of AAA rupture in patients with OA. Two gene expression profile datasets (GSE98278, GSE51588) and two single-cell RNA-seq datasets (GSE164678, GSE152583) were obtained from the GEO database. Functional enrichment analysis, PPI network construction, and machine learning algorithms, including LASSO, Random Forest, and SVM-RFE, were utilized to identify hub genes. In addition, a nomogram and ROC curves were generated to predict the risk of rupture in patients with AAA. Moreover, we analyzed the immune cell infiltration in the AAA tissue microenvironment by CIBERSORT and validated key gene expression in different macrophage subtypes through single-cell analysis. A total of 105 intersecting DEGs that showed consistent changes between rAAA and OA dataset were identified. From these DEGs, four hub genes (PAK1, FCGR1B, LOX and PDPN) were selected by machine learning. High predictive performance was observed for the nomogram based on these hub genes, with an AUC of 0.975 (95 % CI: 0.942-1.000). Abnormal immune cell infiltration was detected in rAAA and correlated significantly with the hub genes. Ruptured AAA cases exhibited higher nomoscore values and lower M2 macrophage infiltration compared to stable AAA. Validation in animal models (PPE+BAPN-induced rAAA) confirmed the significant role of these biomarkers in AAA pathology. The present study successfully identified four potential hub genes (PAK1, FCGR1B, LOX and PDPN) and developed a robust predictive nomogram to assess the risk of AAA rupture. The findings also shed light on the connection between hub genes and immune cell components in the microenvironment of rAAA. These findings support future research on key genes in AAA patients with OA, providing insights for novel management strategies for AAA.

Huang L ，Zhou Z ，Deng T ，Sun Y ，Wang R ，Wu R ，Liu Y ，Ye Y ，Wang K ，Yao C ... -  《-》

Key ferroptosis-related genes in abdominal aortic aneurysm formation and rupture as determined by combining bioinformatics techniques.

Abdominal aortic aneurysm (AAA) is a cardiovascular disease with high mortality and pathogenesis closely related to various cell death types, e.g., autophagy, apoptosis and pyroptosis. However, the association between AAA and ferroptosis is unknown. GSE57691 and GSE98278 dataset were obtained from the Gene Expression Omnibus database, and a ferroptosis-related gene (FRG) set was downloaded from the FerrDb database. These data were normalized, and ferroptosis-related differentially expressed genes (FDEGs, AAA vs. normal samples) were identified using the limma package in R. FRGs expression was analyzed by Gene Set Expression Analysis (GSEA), and FDEGs were analyzed by Gene Ontology (GO) and Kyoto Encyclopedia of Genes (KEGG) pathway enrichment analyses using the clusterProfiler package in R and ClueGO in Cytoscape. Protein-protein interaction networks were assembled using Cytoscape, and crucial FDEGs were identified using CytoHubba. Critical FDEG transcription factors (TFs) were predicted with iRegulon. FDEGs were verified in GSE98278 set, and key FDEGs in AAA (compared with normal samples) and ruptured AAA (RAAA; compared with AAA samples) were identified. Ferroptosis-related immune cell infiltration and correlations with key genes were analyzed by CIBERSORT. Key FEDGs were reverified in Ang II-induced AAA models of ApoE-/- and CD57B/6J mice by immunofluorescence assay. In AAA and normal samples, 40 FDEGs were identified, and the expression of suppressive FRGs was significantly downregulated with GSEA. For FDEGs, the GO terms were response to oxidative stress and cellular response to external stimulus, and the KEGG pathways were the TNF and NOD-like receptor signaling pathways. IL6, ALB, CAV1, PTGS2, NOX4, PRDX6, GPX4, HSPA5, HSPB1, and NCF2 were the most enriched genes in the crucial gene cluster. CEBPG, NFAT5, SOX10, GTF2IRD1, STAT1, and RELA were potential TFs affecting these crucial genes. Ferroptosis-related immune cells involved in AAA formation were CD8+ T, naive CD4+ T, and regulatory T cells (Tregs); M0 and M2 macrophages; and eosinophils. Tregs were also involved in RAAA. GPX4, SLC2A1, and PEBP1 expression was downregulated in both the RAAA and AAA samples. GPX4 and PEBP1 were more important in AAA because they influenced ferroptosis-related immune cell infiltration, and SLC2A1 was more important in RAAA. This is the first study to show that ferroptosis is crucial to AAA/RAAA formation. The TNF and NOD-like signaling pathways and ferroptosis-related immune cell infiltration play key roles in AAA/RAAA. GPX4 is a key ferroptosis-related gene in AAA. Ferroptosis and related genes might be promising targets in the treatment of AAA/RAAA.

Ren J ，Lv Y ，Wu L ，Chen S ，Lei C ，Yang D ，Li F ，Liu C ，Zheng Y ... -  《Frontiers in Cardiovascular Medicine》

Single-Cell RNA Sequencing Deconstructs the Distribution of Immune Cells Within Abdominal Aortic Aneurysms in Mice.

Yuan Z ，Shu L ，Fu J ，Yang P ，Wang Y ，Sun J ，Zheng M ，Liu Z ，Yang J ，Song J ，Song S ，Cai Z ... -  《-》