The sdLDL Reduces MRC1 Expression Level and Secretion of Histamin e in Differentiated M2-macrophages from Patients with Coronary Artery Stenosis

Yarnazari, Ameneh; Hassanpour, Parisa; Hosseini‐Fard, Seyed Reza; Amirfarhangi, Abdollah; Najafi, Mohammad

doi:10.2174/1871529x17666170106095554

Cited by 7 publications

(5 citation statements)

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“…consistent with the results of the previous cluster analysis carried out in this stu top 10 differentially expressed genes in macrophages from the normal group wer associated with the complement and immune system, such as C1QA (complemen Chain), C1QB, and C1QC, and the phagocytosis of macrophages, such as MRC1 (M Receptor C-Type 1) [32][33][34]. The results of the volcano plot confirmed the spec these genes (Figure 3B, Table S9).…”

Section: Transcriptome Differences Between Macrophages In the Ad Grou...supporting

confidence: 89%

Single-Cell RNA-Seq Analysis Reveals Macrophages Are Involved in the Pathogenesis of Human Sporadic Acute Type A Aortic Dissection

et al. 2023

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Macrophages play an important role in the progression of sporadic acute type A aortic dissection (ATAAD). The aim of this study was to characterize the cellular heterogeneity of macrophages in ATAAD tissues by scRNA-seq. Ascending aortic wall tissue from six ATAAD patients and three heart transplant donors was assessed by scRNA-seq and then analyzed and validated by various bioinformatic algorithms and histopathology experiments. The results revealed that the proportion of macrophages in ATAAD tissues (24.51%) was significantly higher than that in normal tissues (13.69%). Among the six macrophage subclusters, pro-inflammatory macrophages accounted for 14.96% of macrophages in the AD group and 0.18% in the normal group. Chemokine- and inflammation-related genes (CCL2, CCL20, S100A8, and S100A9) were expressed more intensively in macrophages in ATAAD tissue than in those in normal tissue. Additionally, intercellular communication analysis and transcription factor analysis indicated the activation of inflammation and degradation of the extracellular matrix in ATAAD tissue. Finally, immunohistochemistry, immunofluorescence, and Western blot experiments confirmed the overexpression of macrophage marker genes (CD68 and CD163) and matrix metalloproteinases (MMP9 and MMP2) in ATAAD tissue. Collectively, our study provides a preliminary evaluation of the role of macrophages in ATAAD, and the results could aid in the development of therapeutic options in the future.

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Section: Transcriptome Differences Between Macrophages In the Ad Grou...supporting

confidence: 89%

Single-Cell RNA-Seq Analysis Reveals Macrophages Are Involved in the Pathogenesis of Human Sporadic Acute Type A Aortic Dissection

et al. 2023

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“…HLA-DRA [148], SERPINA1 [149], ABHD12 [150], IMPA2 [151], ARSA (arylsulfatase A) [152], LRFN5 [153], PLXNA4 [154], CHL1 [155], ITPKB (inositol-trisphosphate 3-kinase B) [156], PTN (pleiotrophin) [157], LAMA2 [158], CDH6 [159] and A2M [160] have been shown to have an important role in neurological disorders, but these genes might be associated with progression of T2DM. HLA-F [161], HLA-H [162], FGA (fibrinogen alpha chain) [163], HSPA1B [164], MRC1 [165], DAB2IP [166], KCNJ8 [167], KLKB1 [168], CXCL2 [169], SERPINE2 [170], ADH1C [171], AMBP (alpha-1-microglobulin/bikunin precursor) [172], NR4A2 [173], TYMP (thymidine phosphorylase) [174], TFRC (transferrin receptor) [175], PLAU (plasminogen activator, urokinase) [176], COL6A2 [177], COL15A1 [178], ABI3BP [179], NEXN (nexilin F-actin binding protein) [180], S1PR1 [181], THY1 [182], COL4A1 [183], COL5A2 [184], ADAMTS2 [185], ECM1 [186] and LTBP2 [187] have been found to be differentially expressed in cardiovascular diseases, but these genes might be linked with progression of T2DM. CCL20 [188], CRH (corticotropin releasing hormone) [189], SPP1 [190], LDLR (low density lipoprotein receptor) [191], RORA (RAR related orphan receptor A) [192], LYZ (lysozyme) [193], PTPRN2 [194], DAPK2 [195], OIP5 [196], PON3 [197], NR4A3 [198], VCAN (versican) [199], CNTNAP2 [200], IL1RAP [201], GLI2 [202], CDH13 [203], AEBP1 [204], BGN (biglycan) [205], LOX (lysyl oxidase) [206], IL1RL1 [207] and LUM (lumican) [208] were found to be involved in advancement of obesity, but these genes might be key for development of T2DM.…”

Section: Discussionmentioning

confidence: 99%

Bioinformatics analysis of potential key genes and mechanisms in type 2 diabetes mellitus

Vastrad¹,

Vastrad²

2021

Preprint

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Type 2 diabetes mellitus (T2DM) is etiologically related to metabolic disorder. The aim of our study was to screen out candidate genes of T2DM and to elucidate the underlying molecular mechanisms by bioinformatics methods. Expression profiling by high throughput sequencing data of GSE154126 was downloaded from Gene Expression Omnibus (GEO) database. The differentially expressed genes (DEGs) between T2DM and normal control were identified. And then, functional enrichment analyses of gene ontology (GO) and REACTOME pathway analysis was performed. Protein protein interaction (PPI) network and module analyses were performed based on the DEGs. Additionally, potential miRNAs of hub genes were predicted by miRNet database. Transcription factors (TFs) of hub genes were detected by NetworkAnalyst database. Further, validations were performed by receiver operating characteristic curve (ROC) analysis and real time polymerase chain reaction (RT PCR). In total, 925 DEGs were identified in T2DM, including 447 up regulated genes and 478 down-regulated genes. Functional enrichment analysis results showed that up regulated DEGs were significantly enriched in defense response, neutrophil degranulation, cell adhesion and extracellular matrix organization. The top 10 hub genes, JUN, VCAM1, RELA, U2AF2, ADRB2, FN1, CDK1, TK1, A2M and ACTA2 were identified from the PPI network, modules, miRNA hub gene regulatory network and TF hub gene regulatory network. Furthermore, ROC analysis and RT PCR revealed that JUN, VCAM1, RELA, U2AF2, ADRB2, FN1, CDK1, TK1, A2M and ACTA2 might serve as biomarkers in T2DM. Bioinformatics analysis is a useful tool to explore the molecular mechanism and pathogenesis of T2DM. The identified hub genes may participate in the onset and advancement of T2DM and serve as therapeutic targets.

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“…DEFB1 [136], SLC11A1 [137], SPINK1 [138], CCR1 [139], GLUL (glutamate-ammonia ligase) [140], GPR84 [141], SIGLEC5 [142], SIGLEC7 [143], LGR5 [144], CD38 [145], GRB14 [146], PRDX1 [147], SLC19A2 [148], CADM2 [149], TRPM5 [150], COL1A1 [151], CTRB1 [152], UTS2R [153], CRTC1 [154], MUC5B [155], TMPRSS6 [156], SLC5A2 [157] and KCNJ9 [158] expression were shown to play an important role in diabetes mellitus, but these genes might be novel target for MI. MT1A [159], LYVE1 [160], S100A12 [161], GCKR (glucokinase regulator) [162], TLR8 [163], MRC1 [164], AGTR1 [165], P2RY12 [166], MSR1 [167], NQO1 [168], FKBP5 [169], CMTM5 [170], ADH1C [171], APLNR (apelin receptor) [172], SFRP4 [173], CCL3 [174], COL11A2 [175], EGR3 [176] and IL2RB [177] expression have a role in coronary artery disease. EDN2 [178], SNX10 [179] and KCNN1 [180] were played a predominant role in progression of atrial fibrillation.…”

Section: Discussionmentioning

confidence: 99%

Identification and Interaction Analysis of Molecular Markers in Myocardial Infarction by Integrated Bioinformatics Analysis

Vastrad¹,

Vastrad²

2021

Preprint

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Myocardial infarction (MI) is the leading cardiovascular diseases in worldwide, yet relatively little is known about the genes and signaling pathways involved in MI progression. The present investigation aimed to elucidate potential crucial candidate genes and pathways in MI. expression profiling by high throughput sequencing dataset (GSE132143) was downloaded from the Gene Expression Omnibus (GEO) database, which included data from 20 MI samples and 12 normal control samples. Differentially expressed genes (DEGs) were identified using t-tests in the DESeq2 R package. These DEGs were subsequently investigated by Gene Ontology (GO) and pathway enrichment analysis, a protein-protein interaction (PPI) network, modules, miRNA-hub gene regulatory network and TF-hub gene regulatory network were constructed and analyzed. Hub genes were validated by receiver operating characteristic curve (ROC) analysis. In total, 958 DEGs were identified, of which 480 were up regulated and 478 were down regulated. GO and pathway enrichment analysis results revealed that the DEGs were mainly enriched in, immune system, neuronal system, response to stimulus, and multicellular organismal process. A PPI network, modules, miRNA-hub gene regulatory network and TF-hub gene regulatory network was constructed by using Cytoscape software, and CFTR, CDK1, RPS13, RPS15A, RPS27, NOTCH1, MRPL12, NOS2, CCDC85B and ATN1 were identified as the hub genes. Our results highlight the important roles of the genes including CFTR, CDK1, RPS13, RPS15A, RPS27, NOTCH1, MRPL12, NOS2, CCDC85B and ATN1 in MI pathogenesis or therapeutic management.

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The sdLDL Reduces MRC1 Expression Level and Secretion of Histamin e in Differentiated M2-macrophages from Patients with Coronary Artery Stenosis

Abstract: The results showed that the sdLDL particles reduce the MRC1 gene expression levels in the differentiated M2 macrophages from patients with coronary artery disease. Furthermore, they had high inflammatory capacity for the secretion of histamine.

Cited by 7 publications

References 0 publications

Single-Cell RNA-Seq Analysis Reveals Macrophages Are Involved in the Pathogenesis of Human Sporadic Acute Type A Aortic Dissection

Single-Cell RNA-Seq Analysis Reveals Macrophages Are Involved in the Pathogenesis of Human Sporadic Acute Type A Aortic Dissection

Bioinformatics analysis of potential key genes and mechanisms in type 2 diabetes mellitus

Identification and Interaction Analysis of Molecular Markers in Myocardial Infarction by Integrated Bioinformatics Analysis

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