Exaggerated Autophagy in Stanford Type A Aortic Dissection: A Transcriptome Pilot Analysis of Human Ascending Aortic Tissues

Zhou, Ze-Hua; Liu, Yan; Zhu, Xiyu; Tang, Xingming; Wang, Yali; Wang, Junxia; Xu, Can; Wang, Dongjin; Du, Jie; Zhou, Qing

doi:10.3390/genes11101187

Cited by 23 publications

(18 citation statements)

References 47 publications

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“…The GSE153434 6 and GSE52093 8 dataset was downloaded from GEO ( http://www.ncbi.nlm.nih.gov/geo/ ). Other datasets supporting the conclusions in this article are included within the article and its additional files.…”

Section: Data Sharing Statementmentioning

confidence: 99%

“…This study aims to analyze the infiltration of immune cells in TAAD and explore key immune-related genes in TAAD. The TAAD dataset GSE153434 6 was downloaded from the Gene Expression Omnibus (GEO) database. Immune Cell Abundance Identifier (ImmuCellAI) 7 algorithm was used to quantify the proportions of immune cells in TAAD samples and normal tissues.…”

Section: Introductionmentioning

confidence: 99%

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Patterns of Immune Infiltration and the Key Immune-Related Genes in Acute Type A Aortic Dissection in Bioinformatics Analyses

Chen¹,

Han²,

Tang³

2021

IJGM

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Background Immune-inflammatory mechanisms contribute greatly to the complex process leading to type A aortic dissection (TAAD). This study aims to explore immune infiltration and key immune-related genes in acute TAAD. Methods ImmuCellAI algorithm was applied to analyze patterns of immune infiltration in TAAD samples and normal aortic vessel samples in the GSE153434 dataset. Differentially expressed genes (DEGs) were screened. Immune-related genes were obtained from overlapping DEGs of GSE153434 and immune genes of the ImmPort database. The hub genes were obtained based on the protein–protein interaction (PPI) network. The hub genes in TAAD were validated in the GSE52093 dataset. The correlation between the key immune-related genes and infiltrating immune cells was further analyzed. Results In the study, the abundance of macrophages, neutrophils, natural killer T cells (NKT cells), natural regulatory T cells (nTreg), T-helper 17 cells (Th17 cells) and monocytes was increased in TAAD samples, whereas that of dendritic cells (DCs), CD4 T cells, central memory T cells (Tcm), mucosa associated invariant T cells (MAIT cells) and B cells was decreased. Interleukin 6 (IL-6), C-C motif chemokine ligand 2 (CCL2) and hepatocyte growth factor (HGF) were identified and validated in the GSE52093 dataset as the key immune-related genes. Furthermore, IL-6, CCL2 and HGF were correlated with different types of immune cells. Conclusion In conclusion, several immune cells such as macrophages, neutrophils, NKT cells, and nTreg may be involved in the development of TAAD. IL-6, CCL2 and HGF were identified and validated as the key immune-related genes of TAAD via bioinformatics analyses. The key immune cells and immune-related genes have the potential to be developed as targets of prevention and immunotherapy for patients with TAAD.

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Section: Data Sharing Statementmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Patterns of Immune Infiltration and the Key Immune-Related Genes in Acute Type A Aortic Dissection in Bioinformatics Analyses

Chen¹,

Han²,

Tang³

2021

IJGM

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“…But further evidence is needed to prove that gene expression affected by these RNAm-SNPs was associated with SCAD risk. According to the result of a transcriptome sequencing study (GSE153434), DSP (fold change = 0.327, p = 2.30 × 10 −4 ), MKX (fold change = 0.391, p = 3.83 × 10 −8 ), and SERPINF1 (fold change = 0.066, p = 2.26 × 10 −15 ) were differentially expressed between Stanford type A aortic dissection patients and controls in ascending aortic tissues (Zhou et al, 2020). SERPINF1 expression level was associated with rs11062 (m 6 A-associated SNP locates in the 3 -UTR of SMYD4) in transformed fibroblast cells, left ventricle, subcutaneous adipose, atrial appendage, and esophagus mucosa tissues.…”

Section: Discussionmentioning

confidence: 98%

Genome-Wide Identification of RNA Modifications for Spontaneous Coronary Aortic Dissection

et al. 2021

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RNA modification plays important roles in many biological processes such as gene expression control. Genetic variants that affect RNA modification may have functional roles in aortic dissection. The aim of this study was to identify RNA modifications related to spontaneous coronary artery dissection (SCAD). We examined the association of RNA modification-associated single-nucleotide polymorphisms (RNAm-SNPs) with SCAD in summary data from a genome-wide association study (GWAS) of European descent (270 SCAD cases and 5,263 controls). Furthermore, we performed expression quantitative loci (eQTL) and protein quantitative loci (pQTL) analyses for the RNAm-SNPs using publicly available data. Functional enrichment and protein–protein interaction analyses were performed for the identified proteins. We found 11,464 unique RNAm-SNPs in the SCAD GWAS dataset, and 519 were nominally associated with SCAD. Nine RNAm-SNPs were associated with SCAD at p < 0.001, and among them, seven were N6-methyladenosine (m6A) methylation-related SNPs, one (rs113664950 in HLA-DQB1) was m7G-associated SNP, and one [rs580060 in the 3′-UTR of Mitochondrial Ribosomal Protein S21 (MRPS21)] was A-to-I modification SNP. The genome-wide significant SNP rs3818978 (SCAD association p = 5.74 × 10–10) in the 5′-UTR of MRPS21 was related to m6A modification. These nine SNPs all showed eQTL effects, and six of them were associated with circulating protein or metabolite levels. The related protein-coding genes were enriched in specific Gene Ontology (GO) terms such as extracellular space, extracellular region, defense response, lymphocyte migration, receptor binding and cytokine receptor binding, and so on. The present study found the associations between RNAm-SNPs and SCAD. The findings suggested that RNA modification may play functional roles in SCAD.

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“…Therefore, and additional useful biomarkers are urgently needed. In ammation played a key role in AD initiate and progression [13][14] .…”

Section: Introductionmentioning

confidence: 99%

Neutrophil to lymphocyte ratio and Fibrinogen Values in predicting patients with type B aortic dissection

Yang

Guo

et al. 2020

Preprint

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The aim of this study is to detect the diagnosis value of neutrophil lymphocyte ratio (NLR) and fibrinogen (FIB) in type B aortic dissection (TBAD) patients. This retrospective observation study consisted patients with TBAD, aortic aneurysm and physical examination between January 1, 2016 and December 31, 2019. Demographic and clinical information after the first admission were collected. Multivariate logistic regression analysis was performed to explore the correlational relationship between NLR, FIB and TBAD. Receiver Operating Characteristic Curve (ROC) was performed to evaluate the diagnostic implication of NLR and FIB in TBAD patients. Six hundred and six patients who were first diagnosed with TBAD were included. Control groups were 202 aortic aneurysm and 140 physical examination subjects. The level of NLR and FIB in aortic dissection patients was significantly higher than aortic aneurysm patients and healthy group (P < 0.001). According to the results of multivariate logistic regression analysis, NLR and FIB were independent risk factors of aortic dissection, and the odds ratio (OR) and 95% confidence interval (CI) value of NLR and FIB were 1.499(1.126-1.738) and 1.914(1.475-2.485), respectively. The area under the curve (AUC) was 0.836 of NLR and 0.756 of FIB. NLR and FIB showed high specificity, 89% and 83% respectively. This is the first study provided information on the diagnosis performance of NLR and FIB in TBAD patients. NLR and FIB showed high specificity, which may be a valuable tool for the diagnosis of TBAD.

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Exaggerated Autophagy in Stanford Type A Aortic Dissection: A Transcriptome Pilot Analysis of Human Ascending Aortic Tissues

Cited by 23 publications

References 47 publications

Patterns of Immune Infiltration and the Key Immune-Related Genes in Acute Type A Aortic Dissection in Bioinformatics Analyses

Patterns of Immune Infiltration and the Key Immune-Related Genes in Acute Type A Aortic Dissection in Bioinformatics Analyses

Genome-Wide Identification of RNA Modifications for Spontaneous Coronary Aortic Dissection

Neutrophil to lymphocyte ratio and Fibrinogen Values in predicting patients with type B aortic dissection

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