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Tetrachlorobisphenol A (TCBPA) and Tetrabromobisphenol S (TBBPS) are organic compounds widely used in industrial production, including in plastic and textile manufacturing. Presently, residual TCBPA is commonly detected in the environment as well as in human and animal sera. Therefore, it is imperative to assess the potential toxicological effects of TCBPA on organismal health. A series of biochemical experiments, including indirect immunofluorescence, ELISA, Western blot, MTT, etc, were conducted to analyze the effects of TCBPA on vascular smooth muscle cells. In this study, the biological impact of TCBPA on arterial smooth muscle cells (ASMCs) was investigated. CCK8 and EdU assays demonstrated significant proliferation of ASMCs following TCBPA treatment. Furthermore, TCBPA induced an inflammatory response in smooth muscle cells, as evidenced by the upregulated expression of inflammatory cytokines including IL-6, IL-1ß, and MCP1. Additionally, we observed that TCBPA triggered an oxidative stress response in ASMCs by measuring ROS levels. To elucidate the underlying molecular mechanism of TCBPA-induced ASMC proliferation, we found that NLRP3 was essential for this process. Further investigation revealed that NLRP3 activation was mediated by NF-κB (which was activated by ROS). In summary, our findings suggest that TCBPA promotes the proliferation of ASMCs through the ROS/NF-κB/NLRP3 signaling cascade. This work indicates that TCBPA may represent a potential risk factor for the development of atherosclerosis, highlighting the need for judicious control of TCBPA usage.
Subject(s)
NF-kappa B , NLR Family, Pyrin Domain-Containing 3 Protein , Animals , Humans , NF-kappa B/metabolism , NLR Family, Pyrin Domain-Containing 3 Protein/metabolism , Reactive Oxygen Species/metabolism , Signal Transduction , Myocytes, Smooth MuscleABSTRACT
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.
Subject(s)
Atherosclerosis , Plaque, Atherosclerotic , Humans , Plaque, Atherosclerotic/genetics , Plaque, Atherosclerotic/metabolism , Pyroptosis/genetics , Endothelial Cells/metabolism , Interleukin-18 , Atherosclerosis/genetics , Atherosclerosis/metabolism , Carotid Arteries/metabolismABSTRACT
Introduction: Immune-mediated inflammatory diseases (IMIDs) have been associated with an increased risk of venous thromboembolism (VTE) in multiple observational studies. However, a direct causally relation between IMIDs and VTE remains unclear to date. Here, we used Mendelian randomization (MR) analysis to investigate causal associations between IMIDs and VTE. Methods: We collected genetic data from published genome-wide association studies (GWAS) for six common IMIDs, specifically inflammatory bowel disease (IBD), Crohn's disease (CD), ulcerative colitis (UC), rheumatoid arthritis (RA), psoriasis (PSO), and systemic lupus erythematosus (SLE); and summary-level data for VTE, pulmonary embolism (PE), and deep vein thrombosis (DVT) from the FinnGen database. Two-sample MR analysis using inverse variance weighting (IVW) was performed to identify causal associations between IMIDs and VTE/DVT/PE, and sensitivity analyses were implemented for robustness. Results: IVW analysis showed a causal relationship between genetically predicted UC (one type of IBD) and the risk of VTE (OR = 1.043, 95% CI: 1.013-1.073, p = 0.004) and DVT (OR = 1.088, 95% CI: 1.043-1.136, p < 0.001), but we found no evidence of causality between UC and PE (OR = 1.029, 95% CI: 0.986-1.074, p = 0.19). In addition, no associations were observed between total IBD, CD, RA, SLE, or PSO and VTE/DVT/PE. Sensitivity analysis found no evidence for horizontal pleiotropy. Conclusion: This MR study provides new genetic evidence for the causal relationship between IMIDs and the risk of VTE. Our findings highlight the importance of active intervention and monitoring to mitigate VTE risk in patients with IBD, in particular those presenting with UC.
Subject(s)
Arthritis, Rheumatoid , Colitis, Ulcerative , Crohn Disease , Inflammatory Bowel Diseases , Lupus Erythematosus, Systemic , Pulmonary Embolism , Venous Thromboembolism , Humans , Venous Thromboembolism/etiology , Venous Thromboembolism/genetics , Genome-Wide Association Study , Mendelian Randomization Analysis , Immunomodulating Agents , Inflammatory Bowel Diseases/genetics , Inflammatory Bowel Diseases/complications , Pulmonary Embolism/epidemiology , Pulmonary Embolism/genetics , Colitis, Ulcerative/genetics , Colitis, Ulcerative/complications , Crohn Disease/genetics , Crohn Disease/complications , Arthritis, Rheumatoid/etiology , Lupus Erythematosus, Systemic/geneticsABSTRACT
Background: The present study is aimed at identifying the differentially expressed genes (DEGs) and relevant biological processes and pathways associated with epicardial adipose tissue (EAT) from patients with coronary artery disease (CAD). We also explored potential biomarkers using two machine-learning algorithms and calculated the immune cell infiltration in EAT. Materials and Methods: Three datasets (GSE120774, GSE64554, and GSE24425) were obtained from the Gene Expression Omnibus (GEO) database. The GSE120774 dataset was used to evaluate DEGs between EAT of CAD patients and the control group. Functional enrichment analyses were conducted to study associated biological functions and mechanisms using the Kyoto Encyclopedia of Genes and Genomes (KEGG), Gene Ontology (GO), and Gene Set Enrichment Analysis (GSEA). After this, the least absolute shrinkage and selection operator (LASSO) and support vector machine recursive feature elimination (SVM-RFE) were performed to identify the feature genes related to CAD. The expression level of the feature genes was validated in GSE64554 and GSE24425. Finally, we calculated the immune cell infiltration and evaluated the correlation between the feature genes and immune cells using CIBERSORT. Results: We identified a total of 130 upregulated and 107 downregulated genes in GSE120774. Functional enrichment analysis revealed that DEGs are associated with several pathways, including the calcium signaling pathway, complement and coagulation cascades, ferroptosis, fluid shear stress and atherosclerosis, lipid and atherosclerosis, and regulation of lipolysis in adipocytes. TCF21, CDH19, XG, and NNAT were identified as feature genes and validated in the GSE64554 and GSE24425 datasets. Immune cell infiltration analysis showed plasma cells are significantly more numerous in EAT than in the control group (p = 0.001), whereas macrophage M0 (p = 0.024) and resting mast cells (p = 0.036) were significantly less numerous. TCF21, CDH19, XG, and NNAT were correlated with immune cells, including plasma cells, M0 macrophages, and resting mast cells. Conclusion: TCF21, CDH19, XG, and NNAT might serve as feature genes for CAD, providing new insights for future research on the pathogenesis of cardiovascular diseases.
Subject(s)
Atherosclerosis , Coronary Artery Disease , Humans , Coronary Artery Disease/genetics , Gene Ontology , Biomarkers/metabolism , Adipose Tissue/metabolism , Basic Helix-Loop-Helix Transcription FactorsABSTRACT
Background: Intraplaque hemorrhage (IPH) is an important feature of unstable plaques and an independent risk factor for cardiovascular events. However, the molecular mechanisms contributing to IPH are incompletely characterized. We aimed to identify novel biomarkers and interventional targets for IPH and to characterize the role of immune cells in IPH pathogenesis. Methods: The microarray dataset GSE163154 which contain IPH and non-IPH plaque samples was obtained from the Gene Expression Omnibus (GEO). R software was adopted for identifying differentially expressed genes (DEGs) and conducting functional investigation. The hub genes were carried by protein-protein interaction (PPI) network and were validated by the GSE120521 dataset. CIBERSORT deconvolution was used to determine differential immune cell infiltration and the relationship of immune cells and hub genes. We confirmed expression of proteins encoded by the hub genes by immunohistochemistry and western blotting in 8 human carotid endarterectomy samples with IPH and 8 samples without IPH (non-IPH). Results: We detected a total of 438 differentially expressed genes (DEGs), of which 248 were upregulated and 190 were downregulated. DEGs were mainly involved in inflammatory related pathways, including neutrophil activation, neutrophil degranulation, neutrophil-mediated immunity, leukocyte chemotaxis, and lysosomes. The hub genes found through the method of degree in the PPI network showed that ITGB2 and ITGAM might play an important role in IPH. Receiver operating characteristic (ROC) results also showed a good performance of these two genes in the test and validation dataset. We found that the proportions of infiltrating immune cells in IPH and non-IPH samples differed, especially in terms of M0 and M2 macrophages. Immunohistochemistry and western blotting analysis showed that expression levels of ITGB2 and ITGAM increased significantly in carotid atherosclerotic plaques with IPH. Conclusion: ITGB2 and ITGAM are key hub genes of IPH and may play an important role in the biological process of IPH. Our findings advance our understanding of the underlying mechanisms of IPH pathogenesis and provide valuable information and directions for future research into novel targets for IPH diagnosis and immunotherapy.
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Identifying biomarkers for abdominal aortic aneurysms (AAA) is key to understanding their pathogenesis, developing novel targeted therapeutics, and possibly improving patients outcomes and risk of rupture. Here, we identified AAA biomarkers from public databases using single-cell RNA-sequencing, weighted co-expression network (WGCNA), and differential expression analyses. Additionally, we used the multiple machine learning methods to identify biomarkers that differentiated large AAA from small AAA. Biomarkers were validated using GEO datasets. CIBERSORT was used to assess immune cell infiltration into AAA tissues and investigate the relationship between biomarkers and infiltrating immune cells. Therefore, 288 differentially expressed genes (DEGs) were screened for AAA and normal samples. The identified DEGs were mostly related to inflammatory responses, lipids, and atherosclerosis. For the large and small AAA samples, 17 DEGs, mostly related to necroptosis, were screened. As biomarkers for AAA, G0/G1 switch 2 (G0S2) (Area under the curve [AUC] = 0.861, 0.875, and 0.911, in GSE57691, GSE47472, and GSE7284, respectively) and for large AAA, heparinase (HPSE) (AUC = 0.669 and 0.754, in GSE57691 and GSE98278, respectively) were identified and further verified by qRT-PCR. Immune cell infiltration analysis revealed that the AAA process may be mediated by T follicular helper (Tfh) cells and the large AAA process may also be mediated by Tfh cells, M1, and M2 macrophages. Additionally, G0S2 expression was associated with neutrophils, activated and resting mast cells, M0 and M1 macrophages, regulatory T cells (Tregs), resting dendritic cells, and resting CD4 memory T cells. Moreover, HPSE expression was associated with M0 and M1 macrophages, activated and resting mast cells, Tregs, and resting CD4 memory T cells. Additional, G0S2 may be an effective diagnostic biomarker for AAA, whereas HPSE may be used to confer risk of rupture in large AAAs. Immune cells play a role in the onset and progression of AAA, which may improve its diagnosis and treatment.
Subject(s)
Aortic Aneurysm, Abdominal , Cell Cycle Proteins , Glucuronidase , Machine Learning , Aortic Aneurysm, Abdominal/diagnosis , Aortic Aneurysm, Abdominal/metabolism , Biomarkers/metabolism , Cell Cycle Proteins/metabolism , Glucuronidase/metabolism , Heparin Lyase/metabolism , Humans , Macrophages/metabolismABSTRACT
Background: Calcific aortic valve disease (CAVD) is the most common valvular heart disease in the aging population, resulting in a significant health and economic burden worldwide, but its underlying diagnostic biomarkers and pathophysiological mechanisms are not fully understood. Methods: Three publicly available gene expression profiles (GSE12644, GSE51472, and GSE77287) from human Calcific aortic valve disease (CAVD) and normal aortic valve samples were downloaded from the Gene Expression Omnibus database for combined analysis. R software was used to identify differentially expressed genes (DEGs) and conduct functional investigations. Two machine learning algorithms, least absolute shrinkage and selection operator (LASSO) and support vector machine-recursive feature elimination (SVM-RFE), were applied to identify key feature genes as potential biomarkers for Calcific aortic valve disease (CAVD). Receiver operating characteristic (ROC) curves were used to evaluate the discriminatory ability of key genes. The CIBERSORT deconvolution algorithm was used to determine differential immune cell infiltration and the relationship between key genes and immune cell types. Finally, the Expression level and diagnostic ability of the identified biomarkers were further validated in an external dataset (GSE83453), a single-cell sequencing dataset (SRP222100), and immunohistochemical staining of human clinical tissue samples, respectively. Results: In total, 34 identified DEGs included 21 upregulated and 13 downregulated genes. DEGs were mainly involved in immune-related pathways such as leukocyte migration, granulocyte chemotaxis, cytokine activity, and IL-17 signaling. The machine learning algorithm identified SCG2 and CCL19 as key feature genes [area under the ROC curve (AUC) = 0.940 and 0.913, respectively; validation AUC = 0.917 and 0.903, respectively]. CIBERSORT analysis indicated that the proportion of immune cells in Calcific aortic valve disease (CAVD) was different from that in normal aortic valve tissues, specifically M2 and M0 macrophages. Key genes SCG2 and CCL19 were significantly positively correlated with M0 macrophages. Single-cell sequencing analysis and immunohistochemical staining of human aortic valve tissue samples showed that SCG2 and CCL19 were increased in Calcific aortic valve disease (CAVD) valves. Conclusion: SCG2 and CCL19 are potential novel biomarkers of Calcific aortic valve disease (CAVD) and may play important roles in the biological process of Calcific aortic valve disease (CAVD). Our findings advance understanding of the underlying mechanisms of Calcific aortic valve disease (CAVD) pathogenesis and provide valuable information for future research into novel diagnostic and immunotherapeutic targets for Calcific aortic valve disease (CAVD).
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Objective: Chronic thromboembolic pulmonary hypertension (CTEPH) is characterized by thrombofibrotic obstruction of the proximal pulmonary arteries, which result in vascular remodeling of the distal pulmonary artery. While the cellular and molecular mechanisms underlying CTEPH pathogenesis remain incompletely understood, recent evidence implicates vascular remodeling. Here, we identify the molecular mechanisms that contribute to vascular remodeling in CTEPH. Methods: Microarray data (GSE130391) for patients with CTEPH and healthy controls were downloaded from the Gene Expression Omnibus (GEO) and screened for differentially expressed genes (DEGs). DEGs were functionally annotated using Gene Ontology (GO) functional analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis. A protein-protein interaction (PPI) network was constructed to identify hub genes. Finally, pulmonary artery samples were harvested from patients with CTEPH (n = 10) and from controls (n = 10) and primary vascular smooth muscle cells (VSMCs) were cultured. Effects of the proto-oncogene FOS on VSMC proliferation and migration were assessed using expression and knockdown studies. Results: We detected a total of 292 DEGs, including 151 upregulated and 141 downregulated genes. GO analysis revealed enrichment of DEGs in biological processes of signal transduction, response to lipopolysaccharide, signal transduction, and myeloid dendritic cell differentiation. Molecular function analysis revealed enrichment in tumor necrosis factor (TNF)-activated receptor activity, transcriptional activator activity, and protein homodimerization activity. The expression of TNF-α and its receptor (sTNFR1 and sTNFR2) were significantly higher in CTEPH group, compared with control group. KEGG pathway analysis revealed enrichment in salmonella infection, pathways in cancer, osteoclast differentiation, and cytokine-cytokine receptor interaction. Hub genes in the PPI included FOS, suggesting an important role for this gene in vascular remodeling in CTEPH. Primary VSMCs derived from patients with CTEPH showed increased FOS expression and high proliferation and migration, which was attenuated by FOS inhibition. In control VSMCs, TNF-α treatment increased proliferation and migration, which FOS inhibition likewise attenuated. Conclusion: TNF-α drives CTEPH pathogenesis by promoting VSMC proliferation and migration via increased FOS expression. These results advance our understanding of the molecular mechanisms of vascular remodeling in CTEPH, and may inform the development of new therapeutic targets.
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BACKGROUND: Esophageal squamous cell carcinoma (ESCC) is one of the most fatal cancers in the world. The 5-year survival rate of ESCC is <30%. However, few biomarkers can accurately predict the prognosis of patients with ESCC. We aimed to identify potential survival-associated biomarkers for ESCC to improve its poor prognosis. METHODS: ImmuneAI analysis was first used to access the immune cell abundance of ESCC. Then, ESTIMATE analysis was performed to explore the tumor microenvironment (TME), and differential analysis was used for the selection of immune-related differentially expressed genes (DEGs). Weighted gene coexpression network analysis (WGCNA) was used for selecting the candidate DEGs. Least absolute shrinkage and selection operator (LASSO) Cox regression was used to build the immune-cell-associated prognostic model (ICPM). Kaplan-Meier curve of survival analysis was performed to evaluate the efficacy of the ICPM. RESULTS: Based on the ESTIMATE and ImmuneAI analysis, we obtained 24 immune cells' abundance. Next, we identified six coexpression module that was associated with the abundance. Then, LASSO regression models were constructed by selecting the genes in the module that is most relevant to immune cells. Two test dataset was used to testify the model, and we finally, obtained a seven-genes survival model that performed an excellent prognostic efficacy. CONCLUSION: In the current study, we filtered seven key genes that may be potential prognostic biomarkers of ESCC, and they may be used as new factors to improve the prognosis of cancer.
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Atherosclerosis and its complications diseases remain leading causes of cardiovascular morbidity and mortality, bringing a massive burden on public health worldwide. Atherosclerosis is recognized as chronic inflammation, and involves several highly correlated processes, including lipid metabolism dysfunction, endothelial cell dysfunction, inflammation, oxidative stress, vascular smooth muscle cell activation, platelet activation, thrombosis, altered matrix metabolism, and vascular remodeling. Within the past few decades, accumulating evidence has shown that the Yes-associated protein (YAP), the major effector of the Hippo pathway, can play a crucial role in pathogenesis and development of atherosclerosis. Activation of YAP-related pathways, which are induced by alerting flow pattern and matrix stiffness among others, can regulate processes including vascular endothelial cell dysfunction, monocyte infiltration, and smooth muscle cell migration, which contribute to atherosclerotic lesion formation. Further, YAP potentially modulates atherosclerotic complications such as vascular calcification and intraplaque hemorrhage, which require further investigation. Here, we summarized the relevant literature to outline current findings detailing the relationship between of YAP and atherosclerosis and highlight areas for future research.
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OBJECTIVES: Carotid artery geometry influences blood flow disturbances and is thus an important risk factor for carotid atherosclerosis. Extracellular matrix (ECM) and yes-associated protein (YAP) expression may play essential roles in the pathophysiology of carotid artery stenosis, but the effect of blood flow disturbances of carotid bifurcation location on the ECM is unknown. We hypothesized that carotid artery anatomy and geometry are independently associated with the ECM and YAP expression. METHODS: In this cross-sectional study, 193 patients were divided into two groups: an asymptomatic group (n = 111) and a symptomatic group (n = 82), symptomatic patients presenting with ischemic attack, amaurosis fugax, or minor non-disabling stroke. For all subjects before surgery, carotid bifurcation angle and internal artery angle were measured with computed tomography angiography (CTA), and laminar shear stress was measured with ultrasonography. After surgery, pathology of all plaque specimens was analyzed using hematoxylin and eosin (HE) staining and Movat special staining. Immunohistochemistry was performed to detect expression of YAP in a subset of 30 specimens. RESULTS: Symptomatic patients had increased carotid bifurcation angle and laminar shear stress compared to asymptomatic patients (P < 0.05), although asymptomatic patients had increased internal carotid angle compared to symptomatic patients (P < 0.001). Relative higher bifurcation angles were correlated with increased carotid bifurcation, decreased internal angle, and decreased laminar shear stress. For each change in intervertebral space or one-third of vertebral body height, carotid bifurcation angle changed 4.76°, internal carotid angle changed 6.91°, and laminar shear stress changed 0.57 dynes/cm2. Pathology showed that average fibrous cap thickness and average narrowest fibrous cap thickness were greater in asymptomatic patients than symptomatic patients (P < 0.05). Expression of proteoglycan and YAP protein in symptomatic patients was higher than in asymptomatic patients (P < 0.001), while collagen expression was lower in symptomatic patients than asymptomatic patients (P < 0.05). CONCLUSION: Geometry of the carotid artery and position relative to cervical spine might be associated with ECM and YAP protein expression, which could contribute to carotid artery stenosis.