The potential role of chemotaxis and the complement system in the formation and progression of thoracic aortic aneurysms inferred from the weighted gene coexpression network analysis

Lei, Chuxiang; Yang, Dan; Chen, Wenlin; Kan, Haoxuan; Xu, Feifei; Zhang, Hui; Wang, Wei; Ji, Lei; Zheng, Yuehong

doi:10.1186/s12967-021-02716-6

Cited by 7 publications

(4 citation statements)

References 50 publications

(50 reference statements)

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“…However, different cells of the immune system (ex. T cells, macrophages) have been observed in human TAA, and several relative inflammatory pathways are reported to be activated [26,27].…”

Section: Discussionmentioning

confidence: 99%

Targeted Proteomic Analysis of Patients with Ascending Thoracic Aortic Aneurysm

et al. 2023

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Background: There is a need for clinical markers to aid in the detection of individuals at risk of harboring an ascending thoracic aneurysm (ATAA) or developing one in the future. Objectives: To our knowledge, ATAA remains without a specific biomarker. This study aims to identify potential biomarkers for ATAA using targeted proteomic analysis. Methods: In this study, 52 patients were divided into three groups depending on their ascending aorta diameter: 4.0–4.5 cm (N = 23), 4.6–5.0 cm (N = 20), and >5.0 cm (N = 9). A total of 30 controls were in-house populations ethnically matched to cases without known or visible ATAA-related symptoms and with no ATAA familial history. Before the debut of our study, all patients provided medical history and underwent physical examination. Diagnosis was confirmed by echocardiography and angio-computed tomography (CT) scans. Targeted-proteomic analysis was conducted to identify possible biomarkers for the diagnosis of ATAA. Results: A Kruskal–Wallis test revealed that C-C motif chemokine ligand 5 (CCL5), defensin beta 1 (HBD1), intracellular adhesion molecule-1 (ICAM1), interleukin-8 (IL8), tumor necrosis factor alpha (TNFα) and transforming growth factor-beta 1 (TGFB1) expressions are significantly increased in ATAA patients in comparison to control subjects with physiological aorta diameter (p < 0.0001). The receiver-operating characteristic analysis showed that the area under the curve values for CCL5 (0.84), HBD1 (0.83) and ICAM1 (0.83) were superior to that of the other analyzed proteins. Conclusions: CCL5, HBD1 and ICAM1 are very promising biomarkers with satisfying sensitivity and specificity that could be helpful in stratifying risk for the development of ATAA. These biomarkers may assist in the diagnosis and follow-up of patients at risk of developing ATAA. This retrospective study is very encouraging; however, further in-depth studies may be worthwhile to investigate the role of these biomarkers in the pathogenesis of ATAA.

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“…However, different cells of the immune system (ex. T cells, macrophages) have been observed in human TAA, and several relative inflammatory pathways are reported to be activated [26,27].…”

Section: Discussionmentioning

confidence: 99%

Targeted Proteomic Analysis of Patients with Ascending Thoracic Aortic Aneurysm

et al. 2023

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“…This suggests that C3AR1 may be a hub between the regulation of inflammation and glucolipid metabolism. In addition, the expression of C3AR1 has been suggested to be associated with the formation of thoracic aortic aneurysms ( 43 ). A study by Propson et al found that mice with C3AR1 knockout in vascular endothelial cells had a significantly diminished tendency toward vascular aging with age, with abnormal activation of peripheral immune cells and reduced inward flow ( 39 ).…”

Section: Discussionmentioning

confidence: 99%

Screening for key genes in circadian regulation in advanced atherosclerosis: A bioinformatic analysis

Yao

Liang

2023

Front. Cardiovasc. Med.

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BackgroundAtherosclerosis (AS) is the most important cardiovascular disease threatening human health, leading to adverse events such as myocardial infarction and stroke. The research on the pathogenesis and causes of AS is being improved step by step, and many factors are associated with AS. However, the relationship between circadian regulation and the pathogenesis of AS is still unclear. Our study identified 2 key genes of circadian regulation in AS by bioinformatics analysis, which provides new perspectives to understand the relationship between circadian rhythm and AS.MethodsWe downloaded samples of early and advanced AS from public databases, screened key genes by weighted gene co-expression network analysis (WGCNA) and Lasso, calculated the immune cell content of the samples using “CIBERSORT,” and analyzed the relationship between key genes and immune cells.ResultsWe obtained the most relevant core modules for advanced AS and analyzed the functions of these modules. Two circadian rhythm-related genes were obtained, which influence the immune infiltration of this late AS. ROC curves demonstrated the efficacy of key genes to differentiate between early and advanced AS.ConclusionWe identified 2 genes most associated with circadian rhythms in advanced AS, whose association with AS has not been elucidated and may become the next therapeutic target.

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“…This structure, known as a co-expression profile, allows for identification and clarification of gene relationships [ 8 ]. WGCNA has been previously used in an attempt to identify genes and pathways relevant to TAA development [ 9 ], but it has not been applied to find the gene expression differences between TAA/BAV and TAA/TAV patients. In this study, we intend to fill in this gap in knowledge by using WGCNA to elucidate those gene expression differences, as well as the underlying molecular mechanisms.…”

Section: Introductionmentioning

confidence: 99%

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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The potential role of chemotaxis and the complement system in the formation and progression of thoracic aortic aneurysms inferred from the weighted gene coexpression network analysis

Cited by 7 publications

References 50 publications

Targeted Proteomic Analysis of Patients with Ascending Thoracic Aortic Aneurysm

Targeted Proteomic Analysis of Patients with Ascending Thoracic Aortic Aneurysm

Screening for key genes in circadian regulation in advanced atherosclerosis: A bioinformatic analysis

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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