Integrated analysis of immunocyte infiltration and differential gene expression in tricuspid aortic valve-associated thoracic aortic aneurysms

Fan, Xiaoping; Peng, Jihai; Lei, Liming; He, Jie; Huang, Jinsong; Zheng, Dandan; Xü, Wei; Cai, Shihao; Chen, Jimei

doi:10.21037/atm.2020.03.05

Cited by 4 publications

(1 citation statement)

References 32 publications

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“…AS is a chronic inflammatory disease in which all stages of sterile inflammation are accompanied by extensive immune cell infiltration (e.g. macrophages, T cells and mast cells) [George 1998;Wu 2007;Carità 2016;Kostyunin 2019;Fan 2020;Goody 2020; Kostyunin 2020]. The pathology of AS is complex, and its main processes include calcification of the valve stroma and involve genetic factors, lipoprotein deposition and oxidation, chronic inflammation, osteogenic transition of cardiac valve interstitial cells, and active valve calcification [Ghaisas 2000; Lindman 2016].…”

Section: Discussionmentioning

confidence: 99%

Bioinformatic-based Identification of Genes Associated with Aortic Valve Stenosis

Song¹,

Jiang²,

Wei³

et al. 2022

HSF

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Background: Aortic valve stenosis (AS) disease is the most common valvular disease in developed countries. The pathology of AS is complex, and its main processes include calcification of the valve stroma and involve genetic factors, lipoprotein deposition and oxidation, chronic inflammation, osteogenic transition of cardiac valve interstitial cells, and active valve calcification. The aim of this study was to identify potential genes associated with AS. Methods: Three original gene expression profiles (GSE153555, GSE12644, and GSE51472) were downloaded from the Gene Expression Omnibus (GEO) database and analyzed by GEO2R tool or ‘limma’ in R to identify differentially expressed genes (DEGs). Functional enrichment was analyzed using the ClusterProfiler package in R Bioconductor. STRING was utilized for the Protein–Protein Interaction (PPI) Network construct, and tissue-specific gene expression were identified using BioGPS database. The hub genes were screened out using the Cytoscape software. Related miRNAs were predicted in Targetscan, miWalk, miRDB, Hoctar, and TarBase. Results: A total of 58 upregulated genes and 20 downregulated genes were screened out, which were mostly enriched in matrix remodeling and the immune system process. A module was thus clustered into by PPI network analysis, which mainly involved in Fc gamma R-mediated phagocytosis, Osteoclast differentiation. Ten genes (IBSP, NCAM1, MMP9, FCGR3B, COL4A3, FCGR1A, THY1, RUNX2, ITGA4, and COL10A1) with the highest degree scores were subsequently identified as the hub genes for AS by applying the CytoHubba plugin. And hsa-miR-1276 was finally identified as potential miRNA and miRNA-gene regulatory network was constructed using NetworkAnalyst. Conclusions: Our analysis suggested that IBSP, NCAM1, MMP9, FCGR3B, COL4A3, FCGR1A, THY1, RUNX2, ITGA4, and COL10A1 might be hub genes associated with AS, and hsa-miR-1276 was potential miRNA. This result could provide novel insight into pathology and therapy of AS in the future.

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Section: Discussionmentioning

confidence: 99%

Bioinformatic-based Identification of Genes Associated with Aortic Valve Stenosis

Song¹,

Jiang²,

Wei³

et al. 2022

HSF

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The causal relationship between thoracic aortic aneurysm and immune cells: a mendelian randomization study

Liu,

Pan,

Xia

et al. 2024

BMC Cardiovasc Disord

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One of the pathogenic causes of thoracic aortic aneurysm (TAA), a dangerous vascular condition that can cause aortic rupture, is autoimmune disorders. Currently, immune cell clustering is becoming more and more refined, and the specific immune cell phenotypes involved are yet unknown. Here, we want to clarify the causal link between TAA risk and 731 immune cell traits. There was a Mendelian randomization analysis (MR). We discovered that the presence of TAA led to an increase in CD45 on CD33− HLA-DR− myeloid cells, an increase in CD45 on natural killer cells, and a decrease in FSC-A on granulocytes after applying FDR correction. Our research also revealed a strong correlation between the incidence of TAA and an increase in immune cells with CD3 on CD39+ CD4+, and CD25 on IgD− CD27− phenotypes. Through genetic techniques, our research has shown the intimate relationship between immune cells and TAA, offering direction for future clinical investigations.

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Identification of immune-related signatures and pathogenesis differences between thoracic aortic aneurysm patients with bicuspid versus tricuspid valves via weighted gene co-expression network analysis

Huang,

Guan,

Qiu

et al. 2023

PLoS ONE

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Background Thoracic aortic aneurysm (TAA) occurs due to pathological aortal dilation, and both individuals with normal tricuspid aortic valves (TAV) or abnormal bicuspid aortic valves (BAV), the latter being a congenital condition, are at risk. However, some differences are present between TAA/BAV and TAA/TAV with respect to their pathophysiological processes and molecular mechanisms, but their exact nature is still mostly unknown. Therefore, it is necessary to elucidate TAA developmental differences among BAV vs. TAV patients. Methods Publically-available gene expression datasets, aortic tissue derived from TAA/BAV and TAA/TAV individuals, were analyzed by weighted gene co-expression network analysis (WGCNA) to identify gene modules associated with those conditions. Gene Ontology (GO) enrichment analysis was performed on those modules to identify the enriched genes within those modules, which were verified by Gene Set Variation Analysis (GSVA) on a dataset derived from aortic smooth muscle cell gene expression between TAA/TAV and TAV/BAV patients. Immune cell infiltration patterns were then analyzed by CIBERSORT, and a protein-protein interaction (PPI) network was constructed based on WGCNA and enrichment analysis results to identify hub genes, followed by validation via stepwise regression analysis. Three signatures most strongly associated with TAA/TAV were confirmed by receiver operating characteristic (ROC) and decision curve analyses (DCA) between prior-established training and testing gene sets. Results WGCNA delineated 2 gene modules being associated with TAA/TAV vs. TAA/BAV; both were enriched for immune-associated genes, such as those relating to immune responses, etc., under enrichment analysis. TAA/TAV and TAA/BAV tissues also had differing infiltrating immune cell proportions, particularly with respect to dendritic, mast and CD4 memory T cells. Identified three signatures, CD86, integrin beta 2 (ITGB2) and alpha M (ITGAM), as yielding the strongest associations with TAA/TAV onset, which was verified by areas under the curve (AUC) at levels approximating 0.8 or above under ROC analysis, indicating their predictive value for TAA/TAV onset. However, we did not examine possible confounding variables, so there are many alternative explanations for this association. Conclusions TAA/TAV pathogenesis was found to be more associated with immune-related gene expression compared to TAA/BAV, and the identification of three strongly-associated genes could facilitate their usage as future biomarkers for diagnosing the likelihood of TAA/TAV onset vs. TAA/BAV, as well as for developing future treatments.

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Integrated analysis of immunocyte infiltration and differential gene expression in tricuspid aortic valve-associated thoracic aortic aneurysms

Cited by 4 publications

References 32 publications

Bioinformatic-based Identification of Genes Associated with Aortic Valve Stenosis

Bioinformatic-based Identification of Genes Associated with Aortic Valve Stenosis

The causal relationship between thoracic aortic aneurysm and immune cells: a mendelian randomization study

Identification of immune-related signatures and pathogenesis differences between thoracic aortic aneurysm patients with bicuspid versus tricuspid valves via weighted gene co-expression network analysis

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