Identification of genomic differences among peripheral arterial beds in atherosclerotic and healthy arteries

Significance of neutrophil extracellular traps-related gene in the diagnosis and classification of atherosclerosis

Atherosclerosis (AS) is a pathological process associated with various cardiovascular diseases. Upon different stimuli, neutrophils release reticular complexes known as neutrophil extracellular traps (NETs). Numerous researches have indicated a strong correlation between NETs and AS. However, its role in cardiovascular disease requires further investigation. By utilizing a machine learning algorithm, we examined the genes associated with NETs that were expressed differently in individuals with AS compared to normal controls. As a result, we identified four distinct genes. A nomogram model was built to forecast the incidence of AS. Additionally, we conducted analysis on immune infiltration, functional enrichment and consensus clustering in AS samples. The findings indicated that individuals with AS could be categorized into two groups, exhibiting notable variations in immune infiltration traits among the groups. Furthermore, to measure the NETs model, the principal component analysis algorithm was developed and cluster B outperformed cluster A in terms of NETs. Additionally, there were variations in the expression of multiple chemokines between the two subtypes. By studying AS NETs, we acquired fresh knowledge about the molecular patterns and immune mechanisms implicated, which could open up new possibilities for AS immunotherapy.

Small nucleolar RNA host gene 18 controls vascular smooth muscle cell contractile phenotype and neointimal hyperplasia

AIMS

Long non-coding RNA (LncRNA) small nucleolar RNA host gene 18 (SNHG18) has been widely implicated in cancers. However, little is known about its functional involvement in vascular diseases. Herein, we attempted to explore a role for SNHG18 in modulating vascular smooth muscle cell (VSMC) contractile phenotype and injury-induced neointima formation.

METHODS AND RESULTS

Analysis of single-cell RNA sequencing and transcriptomic datasets showed decreased levels of SNHG18 in injured and atherosclerotic murine and human arteries, which is positively associated with VSMC contractile genes. SNHG18 was upregulated in VSMCs by TGFβ1 through transcription factors Sp1 and SMAD3. SNHG18 gene gain/loss-of-function studies revealed that VSMC contractile phenotype was positively regulated by SNHG18. Mechanistic studies showed that SNHG18 promotes a contractile VSMC phenotype by up-regulating miR-22-3p. SNHG18 up-regulates miR-22 biogenesis and miR-22-3p production by competitive binding with the A-to-I RNA editing enzyme, adenosine deaminase acting on RNA-2 (ADAR2). Surprisingly, we observed that ADAR2 inhibited miR-22 biogenesis not through increasing A-to-I editing within primary miR-22, but by interfering with the binding of microprocessor complex subunit DGCR8 to primary miR-22. Importantly, perivascular SNHG18 overexpression in the injured vessels dramatically up-regulated the expression levels of miR-22-3p and VSMC contractile genes, and prevented injury-induced neointimal hyperplasia. Such modulatory effects were reverted by miR-22-3p inhibition in the injured arteries. Finally, we observed a similar regulator role for SNHG18 in human VSMCs and a decreased expression level of both SNHG18 and miR-22-3p in diseased human arteries; and we found that the expression level of SNHG18 was positively associated with that of miR-22-3p in both healthy and diseased human arteries.

CONCLUSION

We demonstrate that SNHG18 is a novel regulator in governing VSMC contractile phenotype and preventing injury-induced neointimal hyperplasia. Our findings have important implications for therapeutic targeting snhg18/miR-22-3p signalling in vascular diseases.

Deciphering smooth muscle cell heterogeneity in atherosclerotic plaques and constructing model: a multi-omics approach with focus on KLF15/IGFBP4 axis

BACKGROUND

Ruptured atherosclerotic plaques often precipitate severe ischemic events, such as stroke and myocardial infarction. Unraveling the intricate molecular mechanisms governing vascular smooth muscle cell (VSMC) behavior in plaque stabilization remains a formidable challenge.

METHODS

In this study, we leveraged single-cell and transcriptomic datasets from atherosclerotic plaques retrieved from the gene expression omnibus (GEO) database. Employing a combination of single-cell population differential analysis, weighted gene co-expression network analysis (WGCNA), and transcriptome differential analysis techniques, we identified specific genes steering the transformation of VSMCs in atherosclerotic plaques. Diagnostic models were developed and validated through gene intersection, utilizing the least absolute shrinkage and selection operator (LASSO) and random forest (RF) methods. Nomograms for plaque assessment were constructed. Tissue localization and expression validation were performed on specimens from animal models, utilizing immunofluorescence co-localization, western blot, and reverse-transcription quantitative-polymerase chain reaction (RT-qPCR). Various online databases were harnessed to predict transcription factors (TFs) and their interacting compounds, with determination of the cell-specific localization of TF expression using single-cell data.

RESULTS

Following rigorous quality control procedures, we obtained a total of 40,953 cells, with 6,261 representing VSMCs. The VSMC population was subsequently clustered into 5 distinct subpopulations. Analyzing inter-subpopulation cellular communication, we focused on the SMC2 and SMC5 subpopulations. Single-cell subpopulation and WGCNA analyses revealed significant module enrichments, notably in collagen-containing extracellular matrix and cell-substrate junctions. Insulin-like growth factor binding protein 4 (IGFBP4), apolipoprotein E (APOE), and cathepsin C (CTSC) were identified as potential diagnostic markers for early and advanced plaques. Notably, gene expression pattern analysis suggested that IGFBP4 might serve as a protective gene, a hypothesis validated through tissue localization and expression analysis. Finally, we predicted TFs capable of binding to IGFBP4, with Krüppel-like family 15 (KLF15) emerging as a prominent candidate showing relative specificity within smooth muscle cells. Predictions about compounds associated with affecting KLF15 expression were also made.

CONCLUSION

Our study established a plaque diagnostic and assessment model and analyzed the molecular interaction mechanisms of smooth muscle cells within plaques. Further analysis revealed that the transcription factor KLF15 may regulate the biological behaviors of smooth muscle cells through the KLF15/IGFBP4 axis, thereby influencing the stability of advanced plaques via modulation of the PI3K-AKT signaling pathway. This could potentially serve as a target for plaque stability assessment and therapy, thus driving advancements in the management and treatment of atherosclerotic plaques.

Transcriptomic analysis reveals Cilostazol's role in ameliorating cardiovascular disease: Inhibition of monocyte-to-macrophage differentiation and reduction of endothelial cell reactive oxygen species production

Background

Cardiovascular diseases (CVDs) are the leading global cause of death, with atherosclerosis as the primary cause. Chronic inflammation, endothelial dysfunction, and the role of molecules like nitric oxide and reactive oxygen species are crucial in this context. Our previous research indicated that cilostazol and ginkgo biloba extract could enhance the ability of endothelial cells to dissolve blood clots, but the effects of cilostazol on monocytes remain unexplored.

Method

This study utilized peripheral blood mononuclear cells from 10 healthy donors, treated ex vivo with cilostazol. RNA-sequencing, over-representation analysis, xCell stromal cell analysis, and Gene Set Enrichment Analysis were employed to investigate the gene expression changes and biological pathways affected by cilostazol treatment.

Results

The study identified specific gene sets and pathways that were enriched or reduced in response to cilostazol treatment, providing insights into its effects on monocytes and potential therapeutic applications in CVD. The analysis also revealed the potential impact of cilostazol on the stromal cell compartment, further broadening our understanding of its multifaceted role.

Conclusion

The findings offer a nuanced understanding of the advantages and mechanisms of cilostazol in CVD, uncovering novel therapeutic targets and strategies to enhance the clinical application of cilostazol and contributing to the broader implications of this therapy in cardiovascular health.

Omics Approaches Unveiling the Biology of Human Atherosclerotic Plaques

Atherosclerosis is a chronic inflammatory disease of the arterial wall, characterized by the buildup of plaques with the accumulation and transformation of lipids, immune cells, vascular smooth muscle cells, and necrotic cell debris. Plaques with collagen-poor thin fibrous caps infiltrated by macrophages and lymphocytes are considered unstable because they are at the greatest risk of rupture and clinical events. However, the current histologic definition of plaque types may not fully capture the complex molecular nature of atherosclerotic plaque biology and the underlying mechanisms contributing to plaque progression, rupture, and erosion. The advances in omics technologies have changed the understanding of atherosclerosis plaque biology, offering new possibilities to improve risk prediction and discover novel therapeutic targets. Genomic studies have shed light on the genetic predisposition to atherosclerosis, and integrative genomic analyses expedite the translation of genomic discoveries. Transcriptomic, proteomic, metabolomic, and lipidomic studies have refined the understanding of the molecular signature of atherosclerotic plaques, aiding in data-driven hypothesis generation for mechanistic studies and offering new prospects for biomarker discovery. Furthermore, advancements in single-cell technologies and emerging spatial analysis techniques have unveiled the heterogeneity and plasticity of plaque cells. This review discusses key omics-based discoveries that have advanced the understanding of human atherosclerotic plaque biology, focusing on insights derived from omics profiling of human atherosclerotic vascular specimens.

Identification of key genes for atherosclerosis in different arterial beds

Atherosclerosis (AS) is the pathologic basis of various cardiovascular and cerebrovascular events, with a high degree of heterogeneity among different arterial beds. However, mechanistic differences between arterial beds remain unexplored. The aim of this study was to explore key genes and potential mechanistic differences between AS in different arterial beds through bioinformatics analysis. Carotid atherosclerosis (CAS), femoral atherosclerosis (FAS), infrapopliteal atherosclerosis (IPAS), abdominal aortic atherosclerosis (AAS), and AS-specific differentially expressed genes (DEGs) were screened from the GSE100927 and GSE57691 datasets. Immune infiltration analysis was used to identify AS immune cell infiltration differences. Unsupervised cluster analysis of AS samples from different regions based on macrophage polarization gene expression profiles. Weighted gene co-expression network analysis (WGCNA) was performed to identify the most relevant module genes with AS. Hub genes were then screened by LASSO regression, SVM-REF, and single-gene differential analysis, and a nomogram was constructed to predict the risk of AS development. The results showed that differential expression analysis identified 5, 4, 121, and 62 CAS, FAS, IPAS, AAS-specific DEGs, and 42 AS-common DEGs, respectively. Immune infiltration analysis demonstrated that the degree of macrophage and mast cell enrichment differed significantly in different regions of AS. The CAS, FAS, IPAS, and AAS could be distinguished into two different biologically functional and stable molecular clusters based on macrophage polarization gene expression profiles, especially for cardiomyopathy and glycolipid metabolic processes. Hub genes for 6 AS (ADAP2, CSF3R, FABP5, ITGAX, MYOC, and SPP1), 4 IPAS (CLECL1, DIO2, F2RL2, and GUCY1A2), and 3 AAS (RPL21, RPL26, and RPL10A) were obtained based on module gene, gender stratification, machine learning algorithms, and single-gene difference analysis, respectively, and these genes were effective in differentiating between different regions of AS. This study demonstrates that there are similarities and heterogeneities in the pathogenesis of AS between different arterial beds.

Below-the-Knee Endovascular Revascularization: A Position Statement

Patients with chronic limb-threatening ischemia, the terminal stage of peripheral artery disease, are frequently afflicted by below-the-knee disease. Although all patients should receive guideline-directed medical therapy, restoration of inline flow is oftentimes necessary to avoid limb loss. Proper patient selection and proficiency in endovascular techniques for below-the-knee revascularization are intended to prevent major amputation and promote wound healing. This review, a consensus among an international panel of experienced operators, provides guidance on these challenges from an endovascular perspective and offers techniques to navigate this complex disease process.

Two ferroptosis-specific expressed genes NOX4 and PARP14 are considered as potential biomarkers for the diagnosis and treatment of diabetic retinopathy and atherosclerosis

OBJECTIVES

Both Diabetic retinopathy (DR) and Atherosclerosis (AS) are common complications in patients with diabetes, and they share major pathophysiological similarities and have a common pathogenesis. Studies performed to date have demonstrated that ferroptosis plays a vital part in the occurrence and development of DR and AS, but its mechanism in the two diseases remains poorly understood.

METHODS

DR Chip data (GSE60436 and GSE102485) and AS chip data (GSE100927 and GSE57691) were obtained from the Gene Expression Omnibus (GEO) database. The screening of the differential expression genes (DEGs) was analyzed using the limma package, and the genes related to ferroptosis were obtained from the FerrDb V2 database. Two key genes (NOX4 and PARP14) were identified through external datasets validation and receiver operating characteristic (ROC) curve analysis. Gene Ontology (GO) and Gene Set Enrichment Analysis (GSEA) were used to conduct a functional enrichment analysis, and miRNA-mRNA networks were established. The CIBERSORT algorithm was applied to identify the immune cell infiltration between the disease group and control group. Next, the correlations between key genes and infiltrating immune cells were investigated by the Spearman method. Finally, the correlation between 2 key genes and ferroptosis markers was confirmed.

RESULTS

Nine ferroptosis differentially expressed genes (DE-FRGs) between DR and AS were identified in this study. NOX4 and PARP14 were selected as key genes for further analysis by external datasets and ROC curve analysis. The key genes NOX4, PARP14 and their correlated genes (such as CYBA, NOX1, NOX3, CYBB, PARP9, PARP10, and PARP15) are mainly enriched in oxidoreductase activity, protein ADP-ribosylation, superoxide metabolic process, reactive oxygen species metabolic process, PID pathway, and VEGFA-VEGFR2 pathway. A miRNA-mRNA network was constructed, and we got 12 miRNAs correlated with the target gene NOX4, 38 miRNAs correlated with the target gene PARP14. Three common miRNAs (hsa-miR-1-3p, hsa-miR-129-2-3p, and hsa-miR-155-5p) were observed in the network. Immune infiltration analysis displayed that activated B cell, MDSC, and Type 17 T helper cell are the common immune cells involved in the immune infiltration process of DR and AS. The results revealed that there are significant correlations between two key genes and most ferroptosis marker genes no matter in DR or AS.

CONCLUSION

Ferroptosis-related genes NOX4 and PARP14 may be common biomarkers of DR and AS. Both were associated with immune infiltration in patients with DR and AS. Our data provide a theoretical basis for the early diagnosis and immunotherapy of the two diseases.

Identification of M2 Macrophage-Related Key Genes in Advanced Atherosclerotic Plaques by Network-Based Analysis

ABSTRACT

Atherosclerotic plaque accounts for major adverse cardiovascular events because of its vulnerability. The classically activated macrophage (M1) and alternatively activated macrophage (M2) are implicated in the progression and regression of plaque, respectively. However, the therapeutic targets related to M2 macrophages still remain largely elusive. In this study, cell-type identification by estimating relative subsets of RNA transcripts and weighted gene coexpression network analysis algorithms were used to establish a weighted gene coexpression network for identifying M2 macrophage-related hub genes using GSE43292 data set. The results showed that genes were classified into 7 modules, with the blue module (Cor = 0.67, P = 3e-05) being the one that was most related to M2 macrophage infiltration in advanced plaques, and then 99 hub genes were identified from blue module. Meanwhile, 1289 differentially expressed genes were produced in GSE43292 data set. Subsequently, the intersection genes of hub genes and differentially expressed genes, including AKTIP , ASPN , FAM26E , RAB23 , PLS3 , and PLSCR4 , were obtained by Venn diagrams and named as key genes. Further validation using data sets GSE100927 and GSE41571 showed that 6 key genes all downregulated in advanced and vulnerable plaques compared with early and stable plaque samples (|Log2 (fold change)| > 0.5, P < 0.05 or 0.001), respectively. Receiver operator characteristic curve analysis indicated that the 6 key genes might have potential diagnostic value. The validation of key genes in the model in vitro and in vivo also demonstrated decreased mRNA expressions of AKTIP , ASPN , FAM26E , RAB23 , PLS3 , and PLSCR4 ( P < 0.05 or 0.001). Collectively, we identified AKTIP, ASPN, FAM26E, RAB23, PLS3, and PLSCR4 as M2 macrophage-related key genes during atherosclerotic progression, proposing potential intervention targets for advanced atherosclerotic plaques.

Macrophage profiling in atherosclerosis: understanding the unstable plaque

The development and rupture of atherosclerotic plaques is a major contributor to myocardial infarctions and ischemic strokes. The dynamic evolution of the plaque is largely attributed to monocyte/macrophage functions, which respond to various stimuli in the plaque microenvironment. To this end, macrophages play a central role in atherosclerotic lesions through the uptake of oxidized low-density lipoprotein that gets trapped in the artery wall, and the induction of an inflammatory response that can differentially affect the stability of the plaque in men and women. In this environment, macrophages can polarize towards pro-inflammatory M1 or anti-inflammatory M2 phenotypes, which represent the extremes of the polarization spectrum that include Mhem, M(Hb), Mox, and M4 populations. However, this traditional macrophage model paradigm has been redefined to include numerous immune and nonimmune cell clusters based on in-depth unbiased single-cell approaches. The goal of this review is to highlight (1) the phenotypic and functional properties of monocyte subsets in the circulation, and macrophage populations in atherosclerotic plaques, as well as their contribution towards stable or unstable phenotypes in men and women, and (2) single-cell RNA sequencing studies that have advanced our knowledge of immune, particularly macrophage signatures present in the atherosclerotic niche. We discuss the importance of performing high-dimensional approaches to facilitate the development of novel sex-specific immunotherapies that aim to reduce the risk of cardiovascular events.

Integrated genetic analysis of diabetic complications: Bioinformatics insights into foot ulcers, neuropathy and peripheral artery disease

Diabetic foot ulcers (DFU), diabetic peripheral neuropathy (DPN) and peripheral arterial disease (PAD) are common complications of diabetes mellitus, while diabetic peripheral neuropathy and peripheral arterial disease contribute to the pathogenesis of diabetic foot ulcers, and the pathogenic mechanisms between these three diseases still need further investigation. The keywords 'diabetic foot ulcer', 'diabetic peripheral neuropathy' and 'atherosclerosis' were used to search for related gene sets in the GEO database. Differentially expressed genes (DEGs) were screened and analysed for GO, KEGG and enrichR functional enrichment. Potential three disease biomarkers were identified by SVM-SVM-RFE and LASSO regression analysis. The results were also validated using external datasets and discriminability was measured by area under the ROC curve (AUC). Finally, biomarkers and co-upregulated genes were analysed through the GSEA and Attie Laboratories diabetes databases. A total of 11 shared genes (KRT16, CD24, SAMD9L, SRGAP2, FGL2, GPR34, DDIT4, NFE2L3, FBLN5, ANXA3 and CPA3), two biomarkers (SAMD9L and FGL2) and one co-upregulated gene (CD24) were screened. GO and KEGG pathway analysis of DEGs, enrichr enrichment analysis of shared differential genes and GSEA analysis of biomarkers showed that these significant genes were mainly focused on vasoregulatory, inflammatory-oxidative stress and immunomodulatory pathways. In this study, we used bioinformatics to investigate the intrinsic relationship and potential mechanisms of three common lower extremity complications of diabetes and identified two pivotal genes using the LASSO model and the SVM-RFE algorithm, which will further help clinicians to understand the relationship between diabetic complications, improve the diagnosis and treatment of diabetic foot problems and help doctors to identify the potential risk factors of diabetic foot.

Construction of a novel lower-extremity peripheral artery disease subtype prediction model using unsupervised machine learning and neutrophil-related biomarkers

Lower-extremity peripheral artery disease (LE-PAD) is a prevalent circulatory disorder with risks of critical limb ischemia and amputation. This study aimed to develop a prediction model for a novel LE-PAD subtype to predict the severity of the disease and guide personalized interventions. Additionally, LE-PAD pathogenesis involves altered immune microenvironment, we examined the immune differences to elucidate LE-PAD pathogenesis. A total of 460 patients with LE-PAD were enrolled and clustered using unsupervised machine learning algorithms (UMLAs). Logistic regression analyses were performed to screen and identify predictive factors for the novel subtype of LE-PAD and a prediction model was built. We performed a comparative analysis regarding neutrophil levels in different subgroups of patients and an immune cell infiltration analysis to explore the associations between neutrophil levels and LE-PAD. Through hematoxylin and eosin (H&E) staining of lower-extremity arteries, neutrophil infiltration in patients with and without LE-PAD was compared. We found that UMLAs can helped in constructing a prediction model for patients with novel LE-PAD subtypes which enabled risk stratification for patients with LE-PAD using routinely available clinical data to assist clinical decision-making and improve personalized management for patients with LE-PAD. Additionally, the results indicated the critical role of neutrophil infiltration in LE-PAD pathogenesis.

Constructing a competitive endogenous RNA network of EndMT-related atherosclerosis through weighted gene co-expression network analysis

Atherosclerosis is a chronic inflammatory disease characterized by endothelial dysfunction and plaque formation. Under pro-inflammatory conditions, endothelial cells can undergo endothelial-to-mesenchymal transition (EndMT), contributing to atherosclerosis development. However, the specific regulatory mechanisms by which EndMT contributes to atherosclerosis remain unclear and require further investigation. Dan-Shen-Yin (DSY), a traditional Chinese herbal formula, is commonly used for cardiovascular diseases, but its molecular mechanisms remain elusive. Emerging evidence indicates that competing endogenous RNA (ceRNA) networks play critical roles in atherosclerosis pathogenesis. In this study, we constructed an EndMT-associated ceRNA network during atherosclerosis progression by integrating gene expression profiles from the Gene Expression Omnibus (GEO) database and weighted gene co-expression network analysis. Functional enrichment analysis revealed this EndMT-related ceRNA network is predominantly involved in inflammatory responses. ROC curve analysis showed the identified hub genes can effectively distinguish between normal vasculature and atherosclerotic lesions. Furthermore, Kaplan-Meier analysis demonstrated that high expression of IL1B significantly predicts ischemic events in atherosclerosis. Molecular docking revealed most DSY bioactive components can bind key EndMT-related lncRNAs, including AC003092.1, MIR181A1HG, MIR155HG, WEE2-AS1, and MIR137HG, suggesting DSY may mitigate EndMT in atherosclerosis by modulating the ceRNA network.

M6A plays a potential role in carotid atherosclerosis by modulating immune cell modification and regulating aging-related genes

RNA N6-methyladenosine (m6A) regulators play essential roles in diverse biological processes, including immune responses. Mounting evidence suggests that their dysregulation is intricately linked to numerous diseases. However, the role of m6A-associated genes in carotid atherosclerosis and their relationship with aging and immune cells remain unclear. Analyze the expression profiles of m6A-related genes in carotid atherosclerosis-related datasets. Based on the expression patterns of m6A-related genes, perform consistent clustering analysis of carotid atherosclerosis samples and investigate associated immune cell infiltration patterns and aging characteristics. Develop an m6A prediction model specific to carotid atherosclerosis and analyze the relationships between immune cells infiltration and aging features. The m6A methylation modification level exhibited a substantial decrease in early-stage carotid atherosclerosis samples compared to late-stage carotid atherosclerosis samples. Subsequently, two distinct m6A subtypes were defined through consensus clustering analysis, with the lower m6A modification level group showing associations with heightened immune cell infiltration and increased expression of aging-related genes. A model composed of five m6A-related genes was formulated, and the results indicated that this model possesses effective predictive and therapeutic capabilities for carotid atherosclerosis. Furthermore, the downregulation of YTHDC1 expression resulted in elevated expression of inflammatory factors and a decrease in the expression of the aging-related gene RGN. Single-cell data analysis suggests that the reduced expression of YTHDC1 may decrease the degradation of inflammation-related factors in macrophages, leading to a highly inflammatory state in the carotid artery wall. Furthermore, the sustained release of inflammatory factors may increase the expression of the aging-related gene RGN in vascular smooth muscle cells, further exacerbating the progression of atherosclerosis. A reduced level of m6A methylation modification could enhance inflammation and expedite cellular aging, thereby contributing to the development of carotid atherosclerosis.

Identification of key pyroptosis-related genes and microimmune environment among peripheral arterial beds in atherosclerotic arteries

Atherosclerosis is a chronic inflammatory disease characterized with innate and adaptive immunity but also involves pyroptosis. Few studies have explored the role of pyroptosis in advanced atherosclerotic plaques from different vascular beds. Here we try to identify the different underlying function of pyroptosis in the progression of atherosclerosis between carotid arteries and femoral. arteries. We extracted gene expression levels from 55 advanced carotid or femoral atherosclerotic plaques. The pyroptosis score of each sample was calculated by single-sample-gene-set enrichment analysis (ssGSEA). We then divided the samples into two clusters: high pyroptosis scores cluster (PyroptosisScoreH cluster) and low pyroptosis scores cluster (PyroptosisScoreL cluster), and assessed functional enrichment and immune cell infiltration in the two clusters. Key pyroptosis related genes were identified by the intersection between results of Cytoscape and LASSO (Least Absolute Shrinkage and Selection Operator) regression analysis. Finally, all key pyroptosis related genes were validated in vitro. We found all but one of the 29 carotid plaque samples belonged to the PyroptosisScoreH cluster and the majority (19 out of 26) of femoral plaques were part of the PyroptosisScoreL cluster. Atheromatous plaque samples in the PyroptosisScoreL cluster had higher proportions of gamma delta T cells, M2 macrophages, myeloid dendritic cells (DCs), and cytotoxic lymphocytes (CTLs), but lower proportions of endothelial cells (ECs). Immune full-activation pathways (e.g., NOD-like receptor signaling pathway and NF-kappa B signaling pathway) were highly enriched in the PyroptosisScoreH cluster. The key pyroptosis related genes GSDMD, CASP1, NLRC4, AIM2, and IL18 were upregulated in advanced carotid atherosclerotic plaques. We concluded that compared to advanced femoral atheromatous plaques, advanced carotid atheromatous plaques were of higher grade of pyroptosis. GSDMD, CASP1, NLRC4, AIM2, and IL18 were the key pyroptosis related genes, which might provide a new sight in the prevention of fatal strokes in advanced carotid atherosclerosis.

An integrative analysis of single-cell and bulk transcriptome and bidirectional mendelian randomization analysis identified C1Q as a novel stimulated risk gene for Atherosclerosis

Background

The role of complement component 1q (C1Q) related genes on human atherosclerotic plaques (HAP) is less known. Our aim is to establish C1Q associated hub genes using single-cell RNA sequencing (scRNA-seq) and bulk RNA analysis to diagnose and predict HAP patients more effectively and investigate the association between C1Q and HAP (ischemic stroke) using bidirectional Mendelian randomization (MR) analysis.

Methods

HAP scRNA-seq and bulk-RNA data were download from the Gene Expression Omnibus (GEO) database. The C1Q-related hub genes was screened using the GBM, LASSO and XGBoost algorithms. We built machine learning models to diagnose and distinguish between types of atherosclerosis using generalized linear models and receiver operating characteristics (ROC) analyses. Further, we scored the HALLMARK_COMPLEMENT signaling pathway using ssGSEA and confirmed hub gene expression through qRT-PCR in RAW264.7 macrophages and apoE-/- mice. Furthermore, the risk association between C1Q and HAP was assessed through bidirectional MR analysis, with C1Q as exposure and ischemic stroke (IS, large artery atherosclerosis) as outcomes. Inverse variance weighting (IVW) was used as the main method.

Results

We utilized scRNA-seq dataset (GSE159677) to identify 24 cell clusters and 12 cell types, and revealed seven C1Q associated DEGs in both the scRNA-seq and GEO datasets. We then used GBM, LASSO and XGBoost to select C1QA and C1QC from the seven DEGs. Our findings indicated that both training and validation cohorts had satisfactory diagnostic accuracy for identifying patients with HPAs. Additionally, we confirmed SPI1 as a potential TF responsible for regulating the two hub genes in HAP. Our analysis further revealed that the HALLMARK_COMPLEMENT signaling pathway was correlated and activated with C1QA and C1QC. We confirmed high expression levels of C1QA, C1QC and SPI1 in ox-LDL-treated RAW264.7 macrophages and apoE-/- mice using qPCR. The results of MR indicated that there was a positive association between the genetic risk of C1Q and IS, as evidenced by an odds ratio (OR) of 1.118 (95%CI: 1.013-1.234, P = 0.027).

Conclusion

The authors have effectively developed and validated a novel diagnostic signature comprising two genes for HAP, while MR analysis has provided evidence supporting a favorable association of C1Q on IS.

In silico based analysis to explore genetic linkage between atherosclerosis and its potential risk factors

Atherosclerosis (ATH) is a chronic cardiovascular disease characterized by plaque formation in arteries, and it is a major cause of illness and death. Although therapeutic advances have significantly improved the prognosis of ATH, missing therapeutic targets pose a significant residual threat. This research used a systems biology approach to identify the molecular biomarkers involved in the onset and progression of ATH, analysing microarray gene expression datasets from ATH and tissues impacted by risk factors such as high cholesterol, adipose tissue, smoking, obesity, sedentary lifestyle, stress, alcohol consumption, hypertension, hyperlipidaemia, high fat, diabetes to find the differentially expressed genes (DEGs). Bioinformatic analyses of Protein-Protein Interaction (PPI), Gene Ontology (GO), and Kyoto Encyclopedia of Genes and Genomes (KEGG) were conducted on differentially expressed genes, revealing metabolic and signaling pathways (the chemokine signaling pathway, cytokine-cytokine receptor interaction, the cytosolic DNA-sensing pathway, the peroxisome proliferator-activated receptors signaling pathway, and the nuclear factor-kappa B signaling pathway), ten hubs proteins (CCL5, CCR1, TLR1, CCR2, FCGR2A, IL1B, CD163, AIF1, CXCL-1 and TNF), five transcription factors (YY1, FOXL1, FOXC1, SRF, and GATA2), and five miRNAs (mir-27a-3p, mir-124-3p, mir-16-5p, mir-129-2-3p, mir-1-3p). These findings identify potential biomarkers that may increase knowledge of the mechanisms underlying ATH and their connection to risk factors, aiding in the development of new therapies.

Exploring biomarkers for autophagy-mediated macrophage pyroptosis in atherosclerosis

This study tried to investigate the macrophage autophagy-related pyroptosis in atherosclerosis. The gene expression omnibus (GEO) dataset of GSE100927 was used for differentially expressed genes (DEG) screening, gene ontology (GO) and kyoto encyclopedia of genes and genomes (KEGG), CIBERSORT, weighted correlation network analysis (WGCNA), receiver operating characteristic (ROC), gene set enrichment analysis (GSEA), and correlation analysis, and GSE159677 was used for single-cell analysis, all conducted in R software. Protein-protein interaction (PPI) was constructed in STRING and analyzed in Cytoscape. Transcription factors, drugs, and tissue co-expression network were explored in NetworkAnalyst. A total of 110 autophagy-related DEG (DEATG) were identified, and GO/KEGG revealed the top items enriched in autophagy, phagosome and lysosome. CIBERSORT showed 11 cell types were markedly differentially expressed (p < .05). WGCNA found the turquoise and yellow module were positively correlated with macrophage M0 (corr = 0.5, P = 6e-6) and M2 (corr = 0.54, P = 1e-6), respectively. Then 35 immune-related DEATG were identified, and functional analysis showed immune effector process, interleukin-6 and myeloid cell activation were enriched besides autophagy. PPI and MCC algorithm identified 6 hub genes in regulating macrophage-related autophagy, and ROC indicated high prediction value (area under curve = 0.961). GSEA enriched 6 common pathways associated with autophagy and atherosclerosis pathogenesis, and immune correlation suggested these hub genes were correlated with macrophages M0/M1, monocytes and T cells. Then venn plot found 3 central genes in mediating macrophage autophagy-associated pyroptosis in atherosclerosis, and single-cell analysis demonstrated cell distribution, then validated in THPA human samples. Our data discovered hub genes responsible for macrophage autophagy-mediated pyroptosis in atherosclerosis, and functional analysis with immune cell distribution evidenced their high phenotype-trait prediction value.

Transcriptomics Analysis Revealed Key Genes Associated with Macrophage Autophagolysosome in Male ApoE-/- Mice Aortic Atherosclerosis

Purpose

Atherosclerosis (AS) is the most common cause of cardiovascular and cerebrovascular diseases. However, the mechanisms underlying atherosclerotic plaque progression remain unclear. This study aimed to investigate the genes associated with the development of atherosclerosis in the aorta of ApoE-/- male mice, which could serve as novel biomarkers and therapeutic targets in interventions to halt plaque progression.

Methods

Eight-week-old ApoE-/- mice were fed a normal purified laboratory diet or a Western Diet (WD) for 6 or 22 weeks. High-throughput sequencing technology was used to analyze the transcriptomes of the aortas of four groups of mice that were exposed to different dietary conditions. We retrieved and downloaded the human Arteriosclerosis Disease Chip dataset GSE100927 from the Gene Expression Omnibus (GEO) database and selected 29 cases of carotid atherosclerotic lesions and 12 cases of normal carotid tissues as the experimental and control groups, respectively, to further verify our dataset. In addition, we used quantitative reverse transcription polymerase chain reaction (QT-PCR) to verify the expression levels of the core genes in an atherosclerosis mouse model.

Results

There were 265 differentially expressed genes (DEGs) between the ApoE-/- Male mice AS22W group and Sham22W group. In addition to the well-known activation of inflammation and immune response, t the autophagy-lysosome system is also an important factor that affects the development of atherosclerosis. We identified five core genes (Atp6ap2, Atp6v0b, Atp6v0d2, Atp6v1a, and Atp6v1d) in the protein-protein interaction (PPI) network that were closely related to autophagosomes. Hub genes were highly expressed in the carotid atherosclerosis group in the GSE100927 dataset (P < 0.001). QT-PCR showed that the RNA level of Atp6v0d2 increased significantly during the development of atherosclerotic plaque in ApoE-/- male mice.

Conclusion

Five core genes which affect the development of aortic atherosclerosis through the autophagy-lysosome system, especially Atp6v0d2, were screened and identified using bioinformatic techniques.

Glut10 restrains neointima formation by promoting SMCs mtDNA demethylation and improving mitochondrial function

Neointimal hyperplasia is a major clinical complication of coronary artery bypass graft and percutaneous coronary intervention. Smooth muscle cells (SMCs) play a vital roles in neointimal hyperplasia development and undergo complex phenotype switching. Previous studies have linked glucose transporter member 10(Glut10) to the phenotypic transformation of SMCs. In this research, we reported that Glut10 helps maintain the contractile phenotype of SMCs. The Glut10-TET2/3 signaling axis can arrest neointimal hyperplasia progression by improving mitochondrial function via promotion of mtDNA demethylation in SMCs. Glut10 is significantly downregulated in both human and mouse restenotic arteries. Global Glut10 deletion or SMC-specific Glut10 ablation in the carotid artery of mice accelerated neointimal hyperplasia, while Glut10 overexpression in the carotid artery triggered the opposite effects. All of these changes were accompanied by a significant increase in vascular SMCs migration and proliferation. Mechanistically, Glut10 is expressed primarily in the mitochondria after platelet-derived growth factor-BB (PDGF-BB) treatment. Glut10 ablation induced a reduction in ascorbic acid (VitC) concentrations in mitochondria and mitochondrial DNA (mtDNA) hypermethylation by decreasing the activity and expression of the Ten-eleven translocation (TET) protein family. We also observed that Glut10 deficiency aggravated mitochondrial dysfunction and decreased the adenosinetriphosphate (ATP) content and the oxygen consumption rate, which also caused SMCs to switch their phenotype from contractile to synthetic phenotype. Furthermore, mitochondria-specific TET family inhibition partially reversed these effects. These results suggested that Glut10 helps maintain the contractile phenotype of SMCs. The Glut10-TET2/3 signaling axis can arrest neointimal hyperplasia progression by improving mitochondrial function via the promotion of mtDNA demethylation in SMCs.

Single-cell profiling reveals inflammatory polarization of human carotid versus femoral plaque leukocytes

Femoral atherosclerotic plaques are less inflammatory than carotid plaques histologically, but limited cell-level data exist regarding comparative immune landscapes and polarization at these sites. We investigated intraplaque leukocyte phenotypes and transcriptional polarization in 49 patients undergoing femoral (n = 23) or carotid (n = 26) endarterectomy using single-cell RNA-Seq (scRNA-Seq; n = 13), flow cytometry (n = 24), and IHC (n = 12). Comparative scRNA-Seq of CD45+-selected leukocytes from femoral (n = 9; 35,265 cells) and carotid (n = 4; 30,655 cells) plaque revealed distinct transcriptional profiles. Inflammatory foam cell-like macrophages and monocytes comprised higher proportions of myeloid cells in carotid plaques, whereas noninflammatory foam cell-like macrophages and LYVE1-overexpressing macrophages comprised higher proportions of myeloid cells in femoral plaque (P < 0.001 for all). A significant comparative excess of CCR2+ macrophages in carotid versus plaque was observed by flow cytometry in a separate validation cohort. B cells were more prevalent and exhibited a comparatively antiinflammatory profile in femoral plaque, whereas cytotoxic CD8+ T cells were more prevalent in carotid plaque. In conclusion, human femoral plaques exhibit distinct macrophage phenotypic and transcriptional profiles as well as diminished CD8+ T cell populations compared with human carotid plaques.

Uncovering the shared molecule and mechanism between ulcerative colitis and atherosclerosis: an integrative genomic analysis

Background

Ulcerative colitis (UC) and atherosclerosis (AS) are closely related. However, the pathologic mechanisms underlying the co-occurrence of UC and AS are not well understood.

Objects

To reveal the hub molecule and mechanism involved in the co-occurrence of UC and AS.

Methods

Differentially expressed genes (DEGs) of UC and AS were obtained, and the shared DEGs of UC and AS were explored for biological function. Next, the hub genes were explored using the cytoHubba plugin. The predictive ability of the hub genes was measured by constructing the receiver operating characteristic curve. Analyses of immune infiltration and the single-gene gene set enrichment analysis (GSEA) for the hub genes were further carried out.

Results

Identification of 59 DEGs (55 were upregulated and four were downregulated) shared by both UC and AS was performed. Enriched pathways of the shared DEGs were mainly related to immunity and inflammation. Protein tyrosine phosphatase, receptor type, C (PTPRC) was identified as the hub crosstalk gene for the comorbidity of UC and AS. The upregulation of PTPRC was correlated with mast cells resting, T cells CD4 memory resting, macrophages M0, and macrophages M1. Pathways of immune and inflammatory processes, including NF-kappa B, viral protein interaction with cytokine and cytokine receptor, and cytokine-cytokine receptor interaction, were significantly correlated with high expression of PTPRC in UC and AS.

Conclusion

At the transcriptional level, our study reveals that imbalanced inflammatory and immune responses are the key pathological mechanisms underlying the comorbidity of UC and AS and that PTPRC is a key biomarker for the comorbidity of UC and AS.

Identification of lipid metabolism-related biomarkers for diagnosis and molecular classification of atherosclerosis

BACKGROUND

Atherosclerosis is now the main cause of cardiac-cerebral vascular diseases around the world. Disturbances in lipid metabolism have an essential role in the development and progression of atherosclerosis. Thus, we aimed to investigate lipid metabolism-related molecular clusters and develop a diagnostic model for atherosclerosis.

METHODS

First, we used the GSE100927 and GSE43292 datasets to screen differentially expressed lipid metabolism-related genes (LMRGs). Subsequent enrichment analysis of these key genes was performed using the Metascape database. Using 101 atherosclerosis samples, we investigated the LMRG-based molecular clusters and the corresponding immune cell infiltration. After that, a diagnostic model for atherosclerosis was constructed using the least absolute shrinkage and selection operator (LASSO) and multivariate logistic regression. Finally, a series of bioinformatics techniques, including CIBERSORT, gene set variation analysis, and single-cell data analysis, were used to analyze the potential mechanisms of the model genes in atherosclerosis.

RESULTS

A total of 29 LMRGs were found to be differentially expressed between atherosclerosis and normal samples. Functional and DisGeNET enrichment analyses indicated that 29 LMRGs are primarily engaged in cholesterol and lipid metabolism, the PPAR signaling pathway, and regulation of the inflammatory response and are also closely associated with atherosclerotic lesions. Two LMRG-related molecular clusters with significant biological functional differences are defined in atherosclerosis. A three-gene diagnostic model containing ADCY7, SCD, and CD36 was subsequently constructed. Receiver operating characteristic curves, decision curves, and an external validation dataset showed that our model exhibits good predictive performance. In addition, three model genes were found to be closely associated with immune cell infiltration, especially macrophage infiltration.

CONCLUSIONS

Our study comprehensively highlighted the intricate association between lipid metabolism and atherosclerosis and created a three-gene model for future clinical diagnosis.

Identification of necroptosis-related gene TRAF5 as potential target of diagnosing atherosclerosis and assessing its stability

BACKGROUND

Atherosclerosis (AS) is a leading cause of morbidity and mortality in older patients and features progressive formation of plaques in vascular tissues. With the progression of atherosclerosis, plaque rupture may occur and cause stroke, myocardial infarction, etc. Different forms of cell death promote the formation of a necrotic core of the plaque, leading to rupture. Necroptosis is a type of programmed cell death that contributes to the development of cardiovascular disease. However, the role of necroptosis in AS has not yet been investigated.

METHODS

The Gene Expression Omnibus (GEO) database was used to obtain gene expression profiles. Differentially expressed genes (DEGs) and necroptosis gene sets were used to identify necroptosis-related differentially expressed genes (NRDEGs). The NRDEGs were used to construct a diagnostic model and were further screened using least absolute shrinkage selection operator (LASSO) regression and random forest (RF) analysis. The discriminatory capacity of the NRDEGs was evaluated using receiver operating characteristic (ROC) curves. Immune infiltration levels were estimated based on CIBERSORTx analysis. The GSE21545 dataset, containing survival information, was used to determine prognosis-associated genes. Univariate and multivariate Cox regression analyses combined with survival analysis determined gene prognostic values. RNA and protein levels were detected by RT-qPCR and western blotting in arteriosclerosis obliterans(ASO) and normal vascular tissues. Vascular smooth muscle cells (VSMCs) were treated with oxidized low-density lipoprotein (ox-LDL) to develop cell models of advanced AS. The effects of protein knockdown on necroptosis were assessed by western blotting and flow cytometry. EdU and Cell Counting Kit-8 assays were used to examine cell proliferation.

RESULTS

TNF Receptor Associated Factor 5 (TRAF5) was identified as a diagnostic marker for AS based on the AUC value in both the GSE20129 and GSE43292 datasets. According to differential expression analysis, LASSO regression analysis, RF analysis, univariate analysis, multivariate analysis, and gene-level survival analysis, TRAF5 was markedly associated with necroptosis in AS. Silencing TRAF5 promotes necroptosis and attenuates the proliferation of ox-LDL-induced cell models of advanced AS.

CONCLUSIONS

This study identified a diagnostic marker of necroptosis-related atherosclerosis, TRAF5, which can also be used to diagnose and assess atherosclerotic plaque stability. This novel finding has important implications in the diagnosis and assessment of plaque stability in atherosclerosis.

Imaging Early Life Cardiovascular Phenotype

The growing epidemics of obesity, hypertension, and diabetes, in addition to worsening environmental factors such as air pollution, water scarcity, and climate change, have fueled the continuously increasing prevalence of cardiovascular diseases (CVDs). This has caused a markedly increasing burden of CVDs that includes mortality and morbidity worldwide. Identification of subclinical CVD before overt symptoms can lead to earlier deployment of preventative pharmacological and nonpharmacologic strategies. In this regard, noninvasive imaging techniques play a significant role in identifying early CVD phenotypes. An armamentarium of imaging techniques including vascular ultrasound, echocardiography, magnetic resonance imaging, computed tomography, noninvasive computed tomography angiography, positron emission tomography, and nuclear imaging, with intrinsic strengths and limitations can be utilized to delineate incipient CVD for both clinical and research purposes. In this article, we review the various imaging modalities used for the evaluation, characterization, and quantification of early subclinical cardiovascular diseases.

Nonnegative matrix factorization analysis and multiple machine learning methods identified IL17C and ACOXL as novel diagnostic biomarkers for atherosclerosis

BACKGROUND

Atherosclerosis is the common pathological basis for many cardiovascular and cerebrovascular diseases. The purpose of this study is to identify the diagnostic biomarkers related to atherosclerosis through machine learning algorithm.

METHODS

Clinicopathological parameters and transcriptomics data were obtained from 4 datasets (GSE21545, GSE20129, GSE43292, GSE100927). A nonnegative matrix factorization algorithm was used to classify arteriosclerosis patients in GSE21545 dataset. Then, we identified prognosis-related differentially expressed genes (DEGs) between the subtypes. Multiple machine learning methods to detect pivotal markers. Discrimination, calibration and clinical usefulness of the predicting model were assessed using area under curve, calibration plot and decision curve analysis respectively. The expression level of the feature genes was validated in GSE20129, GSE43292, GSE100927.

RESULTS

2 molecular subtypes of atherosclerosis was identified, and 223 prognosis-related DEGs between the 2 subtypes were identified. These genes are not only related to epithelial cell proliferation, mitochondrial dysfunction, but also to immune related pathways. Least absolute shrinkage and selection operator, random forest, support vector machine- recursive feature elimination show that IL17C and ACOXL were identified as diagnostic markers of atherosclerosis. The prediction model displayed good discrimination and good calibration. Decision curve analysis showed that this model was clinically useful. Moreover, IL17C and ACOXL were verified in other 3 GEO datasets, and also have good predictive performance.

CONCLUSION

IL17C and ACOXL were diagnostic genes of atherosclerosis and associated with higher incidence of ischemic events.

Bulk and single-cell characterisation of the immune heterogeneity of atherosclerosis identifies novel targets for immunotherapy

BACKGROUND

Immune cells that infiltrate lesions are important for atherosclerosis progression and immunotherapies. This study was aimed at gaining important new insights into the heterogeneity of these cells by integrating the sequencing results of multiple samples and using an enhanced single-cell sequencing workflow to overcome the limitations of a single study.

RESULTS

Integrative analyses identified 28 distinct subpopulations based on gene expression profiles. Further analysis demonstrated that these cells manifested high heterogeneity at the levels of tissue preferences, genetic perturbations, functional variations, immune dynamics, transcriptional regulators, metabolic changes, and communication patterns. Of the T cells, interferon-induced CD8⁺ T cells were involved in the progression of atherosclerosis. In contrast, proinflammatory CD4⁺ CD28^null T cells predicted a poor outcome in atherosclerosis. Notably, we identified two subpopulations of foamy macrophages that exhibit contrasting phenotypes. Among them, TREM2^- SPP1⁺ foamy macrophages were preferentially distributed in the hypoxic core of plaques. These glycolytic metabolism-enriched cells, with impaired cholesterol metabolism and robust pro-angiogenic capacity, were phenotypically regulated by CSF1 secreted by co-localised mast cells. Moreover, combined with deconvolution of the bulk datasets, we revealed that these dysfunctional cells had a higher proportion of ruptured and haemorrhagic lesions and were significantly associated with poor atherosclerosis prognoses.

CONCLUSIONS

We systematically explored atherosclerotic immune heterogeneity and identified cell populations underlying atherosclerosis progression and poor prognosis, which may be valuable for developing new and precise immunotherapies.

Analysis of the Genetic Relationship between Atherosclerosis and Non-Alcoholic Fatty Liver Disease through Biological Interaction Networks

Non-alcoholic fatty liver disease (NAFLD) seems to have some molecular links with atherosclerosis (ATH); however, the molecular pathways which connect both pathologies remain unexplored to date. The identification of common factors is of great interest to explore some therapeutic strategies to improve the outcomes for those affected patients. Differentially expressed genes (DEGs) for NAFLD and ATH were extracted from the GSE89632 and GSE100927 datasets, and common up- and downregulated DEGs were identified. Subsequently, a protein-protein interaction (PPI) network based on the common DEGs was performed. Functional modules were identified, and the hub genes were extracted. Then, a Gene Ontology (GO) and pathway analysis of common DEGs was performed. DEGs analysis in NAFLD and ATH showed 21 genes that were regulated similarly in both pathologies. The common DEGs with high centrality scores were ADAMTS1 and CEBPA which appeared to be down- and up-regulated in both disorders, respectively. For the analysis of functional modules, two modules were identified. The first one was oriented to post-translational protein modification, where ADAMTS1 and ADAMTS4 were identified, and the second one mainly related to the immune response, where CSF3 was identified. These factors could be key proteins with an important role in the NAFLD/ATH axis.

Specialty Balloons for Vessel Preparation During Infrainguinal Endovascular Revascularization Procedures: A Review of Literature

Balloon angioplasty with/without utilizing drug eluting technology or stenting constitutes the treatment of choice for a significant percentage of patients with peripheral artery disease requiring an intervention. However, in cases of diffuse disease and plaque complexity, angioplasty may lead to dissection, recoil, and/or early restenosis, making vessel preparation a key component for successful and durable endovascular revascularization outcome. This review of literature aims to present contemporary data for several commercially available specialty balloons that have been designed to minimize the arterial wall stress of conventional balloon angioplasty and facilitate technical success, as well as long-term patency.

Identification of crucial genes for predicting the risk of atherosclerosis with system lupus erythematosus based on comprehensive bioinformatics analysis and machine learning

BACKGROUND

Systemic lupus erythematosus (SLE) has become a major public health problem over the years, and atherosclerosis (AS) is one of the main complications of SLE associated with serious cardiovascular consequences in this patient population. The present study aimed to identify potential biomarkers for SLE patients with AS.

METHODS

Five microarray datasets (GSE50772, GSE81622, GSE100927, GSE28829, GSE37356) were downloaded from the NCBI Gene Expression Omnibus database. The Limma package was used to identify differentially expressed genes (DEGs) in AS. Weighted gene coexpression network analysis (WGCNA) was used to identify significant module genes associated with SLE. Functional enrichment analysis, protein-protein interaction (PPI) network construction, and machine learning algorithms (least absolute shrinkage and selection operator (Lasso, Support Vector Machine-Recursive Feature Elimination (SVM-RFE), and random forest) were applied to identify hub genes. Subsequently, we generated a nomogram and receiver operating characteristic curve (ROC) for predicting the risk of AS in SLE patients. Finally, immune cell infiltrations were analyzed, and Consensus Cluster Analysis was conducted based on Single Sample Gene Set Enrichment Analysis (ssGSEA) scores.

RESULTS

Five hub genes (SPI1, MMP9, C1QA, CX3CR1, and MNDA) were identified and used to establish a nomogram that yielded a high predictive performance (area under the curve 0.900-0.981). Dysregulated immune cell infiltrations were found in AS, with positive correlations with the five hub genes. Consensus clustering showed that the optimal number of subtypes was 3. Compared to subtypes A and B, subtype C presented higher expression of the five hub genes, immune cell infiltration levels and immune checkpoint expression.

CONCLUSION

Our study systematically identified five candidate hub genes (SPI1, MMP9, C1QA, CX3CR1, MNDA) and established a nomogram that could predict the risk of AS with SLE using various bioinformatic analyses and machine learning algorithms. Our findings provide the foothold for future studies on potential crucial genes for AS in SLE patients. Additionally, the dysregulated immune cell proportions and immune checkpoint expressions in AS with SLE were identified.

Novel immune cell infiltration-related biomarkers in atherosclerosis diagnosis

Background

Immune cell infiltration (ICI) has a close relationship with the progression of atherosclerosis (AS). Therefore, the current study was aimed to explore the role of genes related to ICI and to investigate potential mechanisms in AS.

Methods

Single-sample gene set enrichment analysis (ssGSEA) was applied to explore immune infiltration in AS and controls. Genes related to immune infitration were mined by weighted gene co-expression network analysis (WGCNA). The function of those genes were analyzed by enrichment analyses of the Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO). The interactions among those genes were visualized in the protein-protein interaction (PPI) network, followed by identification of hub genes through Cytoscape software. A receiver operating characteristic (ROC) plot was generated to assess the performance of hub genes in AS diagnosis. The expressions of hub genes were measured by reverse transcription quantitative real-time PCR (RT-qPCR) in human leukemia monocyticcell line (THP-1) derived foam cells and macrophages, which mimic AS and control, respectively.

Results

We observed that the proportions of 27 immune cells were significantly elevated in AS. Subsequent integrative analyses of differential expression and WGCNA identified 99 immune cell-related differentially expressed genes (DEGs) between AS and control. Those DEGs were associated with tryptophan metabolism and extracellular matrix (ECM)-related functions. Moreover, by constructing the PPI network, we found 11 hub immune cell-related genes in AS. The expression pattern and receiver ROC analyses in two independent datasets showed that calsequestrin 2 (CASQ2), nexilin F-Actin binding protein (NEXN), matrix metallopeptidase 12 (MMP12), C-X-C motif chemokine ligand 10 (CXCL10), phospholamban (PLN), heme oxygenase 1 (HMOX1), ryanodine receptor 2 (RYR2), chitinase 3 like 1 (CHI3L1), matrix metallopeptidase 9 (MMP9), actin alpha cardiac muscle 1 (ACTC1) had good performance in distinguishing AS from control samples. Furthermore, those biomarkers were shown to be correlated with angiogenesis and immune checkpoints. In addition, we found 239 miRNAs and 47 transcription factor s (TFs), which may target those biomarkers and regulate their expressions. Finally, we found that RT-qPCR results were consistent with sequencing results.

The commonness in immune infiltration of rheumatoid arthritis and atherosclerosis: Screening for central targets via microarray data analysis

Background

Although increasing evidence has reported an increased risk of atherosclerosis (AS) in rheumatoid arthritis (RA), the communal molecular mechanism of this phenomenon is still far from being fully elucidated. Hence, this article aimed to explore the pathogenesis of RA complicated with AS.

Methods

Based on the strict inclusion/exclusion criteria, four gene datasets were downloaded from the Gene Expression Omnibus (GEO) database. After identifying the communal differentially expressed genes (DEGs) and hub genes, comprehensive bioinformatics analysis, including functional annotation, co-expression analysis, expression validation, drug-gene prediction, and TF-mRNA-miRNA regulatory network construction, was conducted. Moreover, the immune infiltration of RA and AS was analyzed and compared based on the CIBERSORT algorithm, and the correlation between hub genes and infiltrating immune cells was evaluated in RA and AS respectively.

Results

A total of 54 upregulated and 12 downregulated communal DEGs were screened between GSE100927 and GSE55457, and functional analysis of these genes indicated that the potential pathogenesis lies in immune terms. After the protein-protein interaction (PPI) network construction, a total of six hub genes (CCR5, CCR7, IL7R, PTPRC, CD2, and CD3D) were determined as hub genes, and the subsequent comprehensive bioinformatics analysis of the hub genes re-emphasized the importance of the immune system in RA and AS. Additionally, three overlapping infiltrating immune cells were found between RA and AS based on the CIBERSORT algorithm, including upregulated memory B cells, follicular helper T cells and γδT cells.

Conclusions

Our study uncover the communal central genes and commonness in immune infiltration between RA and AS, and the analysis of six hub genes and three immune cells profile might provide new insights into potential pathogenesis therapeutic direction of RA complicated with AS.

Distinct role of mitochondrial function and protein kinase C in intimal and medial calcification in vitro

Introduction

Vascular calcification (VC) is a major risk factor for cardiovascular morbidity and mortality. Depending on the location of mineral deposition within the arterial wall, VC is classified as intimal and medial calcification. Using in vitro mineralization assays, we developed protocols triggering both types of calcification in vascular smooth muscle cells (SMCs) following diverging molecular pathways.

Materials and methods and results

Human coronary artery SMCs were cultured in osteogenic medium (OM) or high calcium phosphate medium (CaP) to induce a mineralized extracellular matrix. OM induces osteoblast-like differentiation of SMCs–a key process in intimal calcification during atherosclerotic plaque remodeling. CaP mimics hyperphosphatemia, associated with chronic kidney disease–a risk factor for medial calcification. Transcriptomic analysis revealed distinct gene expression profiles of OM and CaP-calcifying SMCs. OM and CaP-treated SMCs shared 107 differentially regulated genes related to SMC contraction and metabolism. Real-time extracellular efflux analysis demonstrated decreased mitochondrial respiration and glycolysis in CaP-treated SMCs compared to increased mitochondrial respiration without altered glycolysis in OM-treated SMCs. Subsequent kinome and in silico drug repurposing analysis (Connectivity Map) suggested a distinct role of protein kinase C (PKC). In vitro validation experiments demonstrated that the PKC activators prostratin and ingenol reduced calcification triggered by OM and promoted calcification triggered by CaP.

Conclusion

Our direct comparison results of two in vitro calcification models strengthen previous observations of distinct intracellular mechanisms that trigger OM and CaP-induced SMC calcification in vitro. We found a differential role of PKC in OM and CaP-calcified SMCs providing new potential cellular and molecular targets for pharmacological intervention in VC. Our data suggest that the field should limit the generalization of results found in in vitro studies using different calcification protocols.

Identifying potential signatures for atherosclerosis in the context of predictive, preventive, and personalized medicine using integrative bioinformatics approaches and machine-learning strategies

Background

Atherosclerosis is a major contributor to morbidity and mortality worldwide. Although several molecular markers associated with atherosclerosis have been developed in recent years, the lack of robust evidence hinders their clinical applications. For these reasons, identification of novel and robust biomarkers will directly contribute to atherosclerosis management in the context of predictive, preventive, and personalized medicine (PPPM). This integrative analysis aimed to identify critical genetic markers of atherosclerosis and further explore the underlying molecular immune mechanism attributing to the altered biomarkers.

Methods

Gene Expression Omnibus (GEO) series datasets were downloaded from GEO. Firstly, differential expression analysis and functional analysis were conducted. Multiple machine-learning strategies were then employed to screen and determine key genetic markers, and receiver operating characteristic (ROC) analysis was used to assess diagnostic value. Subsequently, cell-type identification by estimating relative subsets of RNA transcript (CIBERSORT) and a single-cell RNA sequencing (scRNA-seq) data were performed to explore relationships between signatures and immune cells. Lastly, we validated the biomarkers' expression in human and mice experiments.

Results

A total of 611 overlapping differentially expressed genes (DEGs) included 361 upregulated and 250 downregulated genes. Based on the enrichment analysis, DEGs were mapped in terms related to immune cell involvements, immune activating process, and inflaming signals. After using multiple machine-learning strategies, dehydrogenase/reductase 9 (DHRS9) and protein tyrosine phosphatase receptor type J (PTPRJ) were identified as critical biomarkers and presented their high diagnostic accuracy for atherosclerosis. From CIBERSORT analysis, both DHRS9 and PTPRJ were significantly related to diverse immune cells, such as macrophages and mast cells. Further scRNA-seq analysis indicated DHRS9 was specifically upregulated in macrophages of atherosclerotic lesions, which was confirmed in atherosclerotic patients and mice.

Conclusions

Our findings are the first to report the involvement of DHRS9 in the atherogenesis, and the proatherogenic effect of DHRS9 is mediated by immune mechanism. In addition, we confirm that DHRS9 is localized in macrophages within atherosclerotic plaques. Therefore, upregulated DHRS9 could be a novel potential target for the future predictive diagnostics, targeted prevention, patient stratification, and personalization of medical services in atherosclerosis.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13167-022-00289-y.

Role of PCK2 in the proliferation of vascular smooth muscle cells in neointimal hyperplasia

Vascular smooth muscle cell (VSMC) proliferation is a hallmark of neointimal hyperplasia (NIH) in atherosclerosis and restenosis post-balloon angioplasty and stent insertion. Although numerous cytotoxic and cytostatic therapeutics have been developed to reduce NIH, it is improbable that a multifactorial disease can be successfully treated by focusing on a preconceived hypothesis. We, therefore, aimed to identify key molecules involved in NIH via a hypothesis-free approach. We analyzed four datasets (GSE28829, GSE43292, GSE100927, and GSE120521), evaluated differentially expressed genes (DEGs) in wire-injured femoral arteries of mice, and determined their association with VSMC proliferation in vitro. Moreover, we performed RNA sequencing on platelet-derived growth factor (PDGF)-stimulated human VSMCs (hVSMCs) post-phosphoenolpyruvate carboxykinase 2 (PCK2) knockdown and investigated pathways associated with PCK2. Finally, we assessed NIH formation in Pck2 knockout (KO) mice by wire injury and identified PCK2 expression in human femoral artery atheroma. Among six DEGs, only PCK2 and RGS1 showed identical expression patterns between wire-injured femoral arteries of mice and gene expression datasets. PDGF-induced VSMC proliferation was attenuated when hVSMCs were transfected with PCK2 siRNA. RNA sequencing of PCK2 siRNA-treated hVSMCs revealed the involvement of the Akt-FoxO-PCK2 pathway in VSMC proliferation via Akt2, Akt3, FoxO1, and FoxO3. Additionally, NIH was attenuated in the wire-injured femoral artery of Pck2-KO mice and PCK2 was expressed in human femoral atheroma. PCK2 regulates VSMC proliferation in response to vascular injury via the Akt-FoxO-PCK2 pathway. Targeting PCK2, a downstream signaling mediator of VSMC proliferation, may be a novel therapeutic approach to modulate VSMC proliferation in atherosclerosis.

Data mining reveal the association between diabetic foot ulcer and peripheral artery disease

Background

Diabetic foot ulcer (DFU) and peripheral artery disease (PAD) are common diseases that seriously affect the quality of life and bring a huge economic burden to society. Although mounting evidence supports a close link between the two disorders, the mechanisms of comorbidity remain to be fully elucidated.

Methods

The gene expression profiles of DFU (GSE80178) and PAD (GSE100927) were downloaded from the Gene Expression Omnibus (GEO) database. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) performed pathway enrichment analysis for common differentially expressed genes (DEGs) present in DFU and PAD. Subsequently, we constructed a protein-protein interaction (PPI) network using the STRING database and detected core modules and hub genes in the network. Finally, we analyzed the co-expression network and the TF-miRNA-mRNA regulatory network of hub genes.

Results

A total of 167 common DEGs (91 up-regulated genes and 76 down-regulated genes) was selected for subsequent analyses. Functional analysis emphasizes the important role of chemokines and cytokines in these two diseases. Finally, six hub genes were identified using cytoHubba, including CXCL8, IL1RN, MMP1, CD68, CCR7 and CCL3.

Conclusions

The hub genes and signaling pathways involved can regulate both diseases simultaneously, suggesting a close relationship between the molecular mechanisms of the two diseases and possible targets for drugs that intervene in both diseases.

Exploration of the Crucial Genes and Molecular Mechanisms Mediating Atherosclerosis and Abnormal Endothelial Shear Stress

Background

Abnormal endothelial shear stress (ESS) is a significant risk factor for atherosclerosis (AS); however, the genes and pathways between ESS and AS are poorly understood. Here, we screened hub genes and potential regulatory targets linked to the progression of AS induced by abnormal ESS.

Methods

The microarray data of ESS and AS were downloaded from the Gene Expression Omnibus (GEO) database. The coexpression modules related to shear stress and AS were identified with weighted gene coexpression network analysis (WGCNA). Coexpression genes in modules obtained from GSE28829 and GSE160611 were considered as SET1. The results were validated in validation set by differential gene analysis. The limma package in R was used to identify differentially expressed genes (DEGs). The common DEGs of GSE100927 and GSE103672 were regarded as SET2. Next, Gene Ontology (GO) annotation and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis was conducted. Protein-protein interaction (PPI) enrichment analysis was assembled, and hub genes were identified using MCODE and ClueGO in Cytoscape. ROC curve analyses were conducted to assess the ability of common hub genes to distinguish samples of atherosclerotic plaque from normal arterial. The expression of common hub gene was verified in ox-LDL-induced foam cells and GSE41571.

Results

We identified three gene modules (the blue, tan, and cyan modules) related to AS and three shear stress-related modules (the brown, red, and pink modules). A total of 129 genes in SET1 and 476 genes in SET2 were identified. CCRL2, LGALS9, and PLCB2 were identified as common hub genes and validated in the GSE100927, GSE28829, and GSE41571. ROC analysis indicates the expression of CCRL2, LGALS9, and PLCB2 could effectively distinguish the atherosclerotic plaque and normal arterial. The expression level of CCRL2, LGALS9, and PLCB2 increases with the accumulation of lipid increased.

Conclusion

We identified CCRL2, LGALS9, and PLCB2 as key genes associated with abnormal ESS and AS and may provide potential prevention and treatment target of AS induced by abnormal ESS.

Analyzing the pathogenesis of systemic lupus erythematosus complicated by atherosclerosis using transcriptome data

Background

Accumulating evidence supports the predisposition of systemic lupus erythematosus (SLE) to atherosclerosis (AS). However, the common pathogenesis of these two diseases remains unclear. This study aimed to explore the mechanisms of SLE complicated by AS.

Methods

Gene expression profiles of SLE (GSE50772) and AS (GSE100927) were downloaded from the Gene Expression Omnibus. We analyzed differentially expressed genes (DEGs) of SLE and AS and performed enrichment analyses separately. After analyzing the common DEGs (CDEGs), we performed functional enrichment analysis, protein-protein interaction (PPI) network analysis, and hub genes (HGs) identification of CDEGs. Then, we performed a co-expression analysis of HGs and verified their expression and diagnostic value. We further explored immune cell infiltration and analyzed the correlation between HGs and infiltrating immune cells (IICs). Finally, we verified the reliability of the screening pathway.

Results

We obtained 530 DEGs from the GSE50772 dataset and 448 DEGs from the GSE100927 dataset. The results of the enrichment analysis showed that there were many similar immune- and inflammation-related processes between the two diseases. We analyzed 26 CDEGs (two downregulated genes and 24 upregulated genes) and enrichment analysis highlighted the important role of the IL-17 signaling pathway. We identified five HGs (CCR1, CD163, IL1RN, MMP9, and SIGLEC1) using the CytoHubba plugin and HGs validation showed that the five HGs screened were reliable. Co-expression networks showed that five HGs can affect mononuclear cell migration. Immune cell infiltration analysis indicated monocytes in SLE and M0 macrophages in AS accounted for a high proportion of all IICs, and the difference in infiltration was obvious. We also found a significant positive correlation between CCR1, CD163, IL1RN, and MMP9 and monocytes in SLE, and a significant positive correlation between CCR1, IL1RN, MMP9, and SIGLEC1 and M0 macrophages in AS. Pathway validation also demonstrated that the IL-17 signaling pathway was a key pathway for the differentiation of monocytes into macrophages.

Conclusions

The five HGs may promote the differentiation of monocytes into macrophages by influencing the IL-17 signaling pathway, leading to SLE complicated by AS. Our study provides insights into the mechanisms of SLE complicated by AS.

Pyroptosis-Related Gene Signature and Expression Patterns in the Deterioration of Atherosclerosis

Background

Pyroptosis has been shown to be involved in the overall process of atherosclerosis. This study was aimed at investigating pyroptosis-related gene expression patterns in atherosclerosis and their diagnostic significance.

Methods and Results

In GSE100927, fifty-four pyroptosis-related genes were identified. Between atherosclerotic plaques and normal samples, the expression patterns of pyroptosis-related genes were significantly different. In order to construct a pyroptosis-related risk score signature (PRSS), the least absolute shrinkage and selection operator (LASSO) was combined with multivariate logistic regression to screen twelve genes. The diagnostic efficiency of the PRSS performed well in GSE43292, as shown by the results of receiver-operating characteristics (ROCs). Consensus clustering identified two expression patterns of pyroptosis-related genes in different statuses of atherosclerotic plaque in GSE163154. The biological behavior of the different clusters was examined by the gene set variation analysis (GSVA). The Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) enrichment analyses revealed that the differentially expressed genes (DEGs) in the two clusters were enriched in the immune response. The Cytoscape software was used to construct protein-protein interaction (PPI) networks for hub gene screening. Following that, the Drug Gene Interaction Database (DGIdb) was utilized to find 47 possible medicines and chemical compounds that interact with hub genes in atherosclerotic plaques.

Conclusion

The results of this study showed that pyroptosis-related genes contribute to the progression of atherosclerosis and may serve as biomarkers in clinical diagnosis as well as novel therapeutic targets for the treatment of AS.

Analysis of Immune and Inflammation Characteristics of Atherosclerosis from Different Sample Sources

Background

Atherosclerosis is the predominant cause of cardiovascular diseases. Existing studies suggest that the development of atherosclerosis is closely related to inflammation and immunity, but whether there are differences and similarities between atherosclerosis occurring at different sites is still unknown. We elucidated the pathological characteristics of peripheral vascular diseases by using bioinformatic analyses on immune cells and inflammation-related gene expression in atherosclerotic arteries and plaques.

Methods

Eight data sets regarding atherosclerosis were downloaded from the Gene Expression Omnibus database. Human immune genes were obtained from the IMMPORT website. The samples were scored and divided into high- and low-immune groups. Then the samples were analysed using weighted gene co-expression network analysis, while the modules were analysed using functional enrichment. The protein–protein interaction network was constructed using the STRING and Cytoscape databases. The hub immune genes were screened, and the correlation between hub immune genes and immune cells was analysed.

Results

Immune cells and their functions were significantly different during atherosclerosis development. The infiltration proportion of immune cells was approximately similar in samples from different sources of patients with carotid atherosclerosis. However, the sensitivity of lower extremity atherosclerosis samples to immune cells is lower than that of carotid atherosclerosis samples.The samples from the plaque and artery were mainly infiltrated by macrophages, T cells and mast cells. After immune cells were assessed, resting NK cells, activated mast cells and M0 macrophages were found to be key immune cells in atherosclerosis and plaque formation. In addition, CCL4, TLR2, IL1B and PTPRC were considered to be immune marker genes in atherosclerosis development. Conclusion. Bioinformatic data analysis confirms the essential role of immune cells in cardiovascular diseases, and also indicates some differences of immune and inflammation characteristics of atherosclerosis between carotid and lower extremity arteries.

Endothelial Intracellular ANG (Angiogenin) Protects Against Atherosclerosis by Decreasing Endoplasmic Reticulum Stress

BACKGROUND

ANG (angiogenin) is essential for cellular adaptation to endoplasmic reticulum (ER) stress, a process closely associated with cardiovascular diseases, including atherosclerosis. We aimed to investigate the role of ANG in the progression of atherosclerosis and elucidate its underlying molecular mechanisms.

METHODS

We constructed adenoassociated virus 9 ANG overexpression vectors and endothelial ANG- and ApoE (apolipoprotein E)-deficient mice to determine the effects of ANG on ER stress and atherosclerotic lesions. RNA sequencing of endothelial ANG- and ApoE-deficient mice identified ANG-dependent downregulation of ST3GAL5 (ST3 beta-galactoside alpha-2,3-sialyltransferase 5) expression, and the direct regulation of ST3GAL5 by ANG was verified by chromatin immunoprecipitation sequencing and luciferase reporter assay results.

RESULTS

Reanalysis of expression profiling datasets indicated decreased ANG levels in patients' atherosclerotic lesions, and these data were validated in aortas from ApoE^-/- mice. ER stress marker and adhesion molecule levels, aortic root lesions and macrophage deposition were substantially reduced in ApoE^-/- mice injected with an adenoassociated virus 9 ANG without signal peptide (ANG-ΔSP) overexpression vector compared with empty and full-length ANG overexpression vectors. Endothelial ANG deficiency significantly elevated ER stress and increased adhesion molecule expression, which aggravated atherosclerotic lesions and enhanced THP-1 monocyte adhesion to endothelial cells in vivo and in vitro, respectively. Furthermore, ANG-ΔSP overexpression significantly attenuated oxidized low-density lipoprotein-induced ER stress and THP-1 monocyte adhesion to endothelial cells, which were reversed by ST3GAL5 inhibition.

CONCLUSIONS

These results suggest that endothelial intracellular ANG is a novel therapeutic against atherosclerosis and exerts atheroprotective effects via ST3GAL5-mediated ER stress suppression.

Analysis of differentially expressed genes and signaling pathways involved in atherosclerosis and chronic obstructive pulmonary disease

Atherosclerosis is an important medical and social problem, and the keys to solving this problem are still largely unknown. A common situation in real clinical practice is the comorbid course of atherosclerosis with chronic obstructive pulmonary disease (COPD). Diseases share some common risk factors and may be closely linked pathogenetically.

METHODS

Bioinformatics analysis of datasets from Gene Expression Omnibus (GEO) was performed to examine the gene ontology (GO) of common differentially expressed genes (DEGs) in COPD and peripheral arterial atherosclerosis. DEGs were identified using the limma R package with the settings p < 0.05, corrected using the Benjamini & Hochberg algorithm and ǀlog 2FCǀ > 1.0. The GO, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment, and the protein-protein interaction (PPI) network analysis were performed with the detected DEGs.

RESULTS

The biological processes and signaling pathways involving common DEGs from airway epithelial datasets in COPD and tissue in peripheral atherosclerosis were identified. A total of 15 DEGs were identified, comprising 12 upregulated and 3 downregulated DEGs. The GO enrichment analysis demonstrated that the upregulated hub genes were mainly involved in the inflammatory response, reactive oxygen species metabolic process, cell adhesion, lipid metabolic process, regulation of angiogenesis, icosanoid biosynthetic process, and cellular response to a chemical stimulus. The KEGG pathway enrichment analysis demonstrated that the common pathways were Toll-like receptor signaling pathway, NF-kappa B signaling pathway, lipid and atherosclerosis, and cytokine-cytokine receptor interaction.

CONCLUSIONS

Biological processes and signaling pathways associated with the immune response may link the development and progression of COPD and atherosclerosis.

Identification of Potential Targets Linked to the Cardiovascular/Alzheimer’s Axis through Bioinformatics Approaches

The identification of common targets in Alzheimer’s disease (AD) and cardiovascular disease (CVD) in recent years makes the study of the CVD/AD axis a research topic of great interest. Besides aging, other links between CVD and AD have been described, suggesting the existence of common molecular mechanisms. Our study aimed to identify common targets in the CVD/AD axis. For this purpose, genomic data from calcified and healthy femoral artery samples were used to identify differentially expressed genes (DEGs), which were used to generate a protein–protein interaction network, where a module related to AD was identified. This module was enriched with the functionally closest proteins and analyzed using different centrality algorithms to determine the main targets in the CVD/AD axis. Validation was performed by proteomic and data mining analyses. The proteins identified with an important role in both pathologies were apolipoprotein E and haptoglobin as DEGs, with a fold change about +2 and −2, in calcified femoral artery vs healthy artery, respectively, and clusterin and alpha-2-macroglobulin as close interactors that matched in our proteomic analysis. However, further studies are needed to elucidate the specific role of these proteins, and to evaluate its function as biomarkers or therapeutic targets.

Analysis of ABC Transporter Gene Expression in Atherosclerosis

ABC transporters are a large family of membrane proteins that transport chemically diverse substrates across the cell membrane. Disruption of transport mechanisms mediated by ABC transporters causes the development of various diseases, including atherosclerosis. Methods: A bioinformatic analysis of a dataset from Gene Expression Omnibus (GEO) was performed. A GEO dataset containing data on gene expression levels in samples of atherosclerotic lesions and control arteries without atherosclerotic lesions from carotid, femoral, and infrapopliteal arteries was used for analysis. To evaluate differentially expressed genes, a bioinformatic analysis was performed in comparison groups using the limma package in R (v. 4.0.2) and the GEO2R and Phantasus tools (v. 1.11.0). Results: The obtained data indicate the differential expression of many ABC transporters belonging to different subfamilies. The differential expressions of ABC transporter genes involved in lipid transport, mechanisms of multidrug resistance, and mechanisms of ion exchange are shown. Differences in the expression of transporters in tissue samples from different arteries are established. Conclusions: The expression of ABC transporter genes demonstrates differences in atherosclerotic samples and normal arteries, which may indicate the involvement of transporters in the pathogenesis of atherosclerosis.

Two-faced Janus: The dual role of macrophages in atherosclerotic calcification

Calcification is an independent predictor of atherosclerosis-related cardiovascular events. Microcalcification is linked to inflamed, unstable lesions, in comparison to the fibrotic stable plaque phenotype generally associated with advanced calcification. This paradox relates to recognition that calcification presents in a wide spectrum of manifestations that differentially impact plaque’s fate. Macrophages, the main inflammatory cells in atherosclerotic plaque, have a multifaceted role in disease progression. They crucially control the mineralization process, from microcalcification to the osteoid metaplasia of bone-like tissue. It is a bilateral interaction that weighs heavily on the overall plaque fate but remains rather unexplored. This review highlights current knowledge about macrophage phenotypic changes in relation to and interaction with the calcifying environment. On the one hand, macrophage-led inflammation kickstarts microcalcification through a multitude of interlinked mechanisms, which in turn stimulates phenotypic changes in vascular cell types to drive microcalcification. Macrophages may also modulate the expression/activity of calcification inhibitors and inducers, or eliminate hydroxyapatite nucleation points. Contrarily, direct exposure of macrophages to an early calcifying milieu impacts macrophage phenotype, with repercussions for plaque progression and/or stability. Macrophages surrounding macrocalcification deposits show a more reparative phenotype, modulating extracellular matrix, and expressing osteoclast genes. This phenotypic shift favours gradual displacement of the pro-inflammatory hubs; the lipid necrotic core, by macrocalcification. Parallels to bone metabolism may explain many of these changes to macrophage phenotype, with advanced calcification able to show homeostatic osteoid metaplasia. As the targeted treatment of vascular calcification developing in atherosclerosis is thus far severely lacking, it is crucial to better understand its mechanisms of development.

MicroRNA profiles of human peripheral arteries and abdominal aorta in normal conditions: MicroRNAs-27a-5p, -139-5p and -155-5p emerge and in atheroma too

Atherosclerosis may starts early in life and each artery has peculiar characteristics likely affecting atherogenesis. The primary objective of the work was to underpin the microRNA (miR)-profiling differences in human normal femoral, abdominal aortic, and carotid arteries. The secondary aim was to investigate if those identified miRs, differently expressed in normal conditions, may also have a role in atherosclerotic arteries at adult ages. MiR-profiles were performed on normal tissues, revealing that aorta and carotid arteries are more similar than femoral arteries. MiRs emerging from profiling comparisons, i.e., miR-155-5p, -27a-5p, and -139-5p, were subjected to validation by RT-qPCR in normal arteries and also in pathological/atheroma counterparts, considering all the available 20 artery specimens. The three miRs were confirmed to be differentially expressed in normal femoral vs aorta/carotid arteries. Differential expression of those miRs was also observed in atherosclerotic arteries, together with some miR-target proteins, such as vimentin, CD44, E-cadherin and an additional marker SLUG. The different expression of miRs and targets/markers suggests that aorta/carotid and femoral arteries differently activate molecular drivers of pathological condition, thus conditioning the morphology of atheroma in adult life and likely suggesting the future use of artery-specific treatment to counteract atherosclerosis.

ETS-Related Gene Expression in Healthy Femoral Arteries With Focal Calcifications

Bone development-related genes are enriched in healthy femoral arteries, which are more prone to calcification, as documented by the predominance of fibrocalcific plaques at the femoral location. We undertook a prospective histological study on the presence of calcifications in normal femoral arteries collected from donors. Since endothelial-to-mesenchymal transition (EndMT) participates in vascular remodeling, immunohistochemical (IHC) and molecular markers of EndMT and chondro-osteogenic differentiation were assessed. Transmission electron microscopy (TEM) was used to describe calcification at its inception. Two hundred and fourteen femoral arteries were enrolled. The mean age of the donors was 39.9 ± 12.9 years; male gender prevailed (M: 128). Histology showed a normal architecture; calcifications were found in 52 (24.3%) cases, without correlations with cardiovascular risk factors. Calcifications were seen on or just beneath the inner elastic lamina (IEL). At IHC, SLUG was increasingly expressed in the wall of focally calcified femoral arteries (FCFA). ETS-related gene (ERG), SLUG, CD44, and SOX-9 were positive in calcifications. RT-PCR showed increased levels of BPM-2, RUNX-2, alkaline phosphatase, and osteocalcin osteogenic transcripts and increased expression of the chondrogenic marker, SOX-9, in FCFA. TEM documented osteoblast-like cells adjacent to the IEL, releasing calcifying vesicles from the cell membrane. The vesicles were embedded in a proteoglycan-rich matrix and were entrapped in IEL fenestrations. In this study, ERG- and CD44-positive cell populations were found in the context of increased SLUG expression, thus supporting the participation of EndMT in FCFA; the increased transcript expression of osteochondrogenic markers, particularly SOX-9, reinforced the view that EndMT, osteochondrogenesis, and neoangiogenesis interact in the process of arterial calcification. Given its role as a transcription factor in the regulation of endothelial homeostasis, arterial ERG expression can be a clue of endothelial dysregulation and changes in IEL organization which can ultimately hinder calcifying vesicle diffusion through the IEL fenestrae. These results may have a broader implication for understanding arterial calcification within a disease context.

Identification of potential therapeutic targets for atherosclerosis by analysing the gene signature related to different immune cells and immune regulators in atheromatous plaques

Background

Atherosclerosis is a chronic inflammatory disease that affects multiple arteries. Numerous studies have shown the inherent immune diversity in atheromatous plaques and suggest that the dysfunction of different immune cells plays an important role in atherosclerosis. However, few comprehensive bioinformatics analyses have investigated the potential coordinators that might orchestrate different immune cells to exacerbate atherosclerosis.

Methods

Immune infiltration of 69 atheromatous plaques from different arterial beds in GSE100927 were explored by single-sample-gene-set enrichment analysis (presented as ssGSEA scores), ESTIMATE algorithm (presented as immune scores) and CIBERSORT algorithm (presented as relative fractions of 22 types of immune cells) to divide these plaques into ImmuneScoreL cluster (of low immune infiltration) and ImmuneScoreH cluster (of high immune infiltration). Subsequently, comprehensive bioinformatics analyses including differentially-expressed-genes (DEGs) analysis, protein–protein interaction networks analysis, hub genes analysis, Gene-Ontology-terms and KEGG pathway enrichment analysis, gene set enrichment analysis, analysis of expression profiles of immune-related genes, correlation analysis between DEGs and hub genes and immune cells were conducted. GSE28829 was analysed to cross-validate the results in GSE100927.

Results

Immune-related pathways, including interferon-related pathways and PD-1 signalling, were highly enriched in the ImmuneScoreH cluster. HLA-related (except for HLA-DRB6) and immune checkpoint genes (IDO1, PDCD-1, CD274(PD-L1), CD47), RORC, IFNGR1, STAT1 and JAK2 were upregulated in the ImmuneScoreH cluster, whereas FTO, CRY1, RORB, and PER1 were downregulated. Atheromatous plaques in the ImmuneScoreH cluster had higher proportions of M0 macrophages and gamma delta T cells but lower proportions of plasma cells and monocytes (p < 0.05). CAPG, CECR1, IL18, IGSF6, FBP1, HLA-DPA1 and MMP7 were commonly related to these immune cells. In addition, the advanced-stage carotid plaques in GSE28829 exhibited higher immune infiltration than early-stage carotid plaques.

Conclusions

Atheromatous plaques with higher immune scores were likely at a more clinically advanced stage. The progression of atherosclerosis might be related to CAPG, IGSF6, IL18, CECR1, FBP1, MMP7, FTO, CRY1, RORB, RORC, PER1, HLA-DPA1 and immune-related pathways (IFN-γ pathway and PD-1 signalling pathway). These genes and pathways might play important roles in regulating immune cells such as M0 macrophages, gamma delta T cells, plasma cells and monocytes and might serve as potential therapeutic targets for atherosclerosis.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12920-021-00991-2.

Exploring the Pathogenesis of Psoriasis Complicated With Atherosclerosis via Microarray Data Analysis

Background

Although more and more evidence has supported psoriasis is prone to atherosclerosis, the common mechanism of its occurrence is still not fully elucidated. The purpose of this study is to further explore the molecular mechanism of the occurrence of this complication.

Methods

The gene expression profiles of psoriasis (GSE30999) and atherosclerosis (GSE28829) were downloaded from the Gene Expression Omnibus (GEO) database. After identifying the common differentially expressed genes (DEGs) of psoriasis and atherosclerosis, three kinds of analyses were performed, namely functional annotation, protein‐protein interaction (PPI) network and module construction, and hub gene identification and co-expression analysis.

Results

A total of 94 common DEGs (24 downregulated genes and 70 upregulated genes) was selected for subsequent analyses. Functional analysis emphasizes the important role of chemokines and cytokines in these two diseases. In addition, lipopolysaccharide-mediated signaling pathway is closely related to both. Finally, 16 important hub genes were identified using cytoHubba, including LYN, CSF2RB, IL1RN, RAC2, CCL5, IRF8, C1QB, MMP9, PLEK, PTPRC, FYB, BCL2A1, LCP2, CD53, NCF2 and TLR2.

Conclusions

Our study reveals the common pathogenesis of psoriasis and atherosclerosis. These common pathways and hub genes may provide new ideas for further mechanism research.