The Association and Pathogenesis of SERPINA3 in Coronary Artery Disease

Lei, Zhijun; Wu, You; Li, Bingyu; Zhai, Mengen; Zhong, Yuan; Ju, Peinan; Kou, Wenxin; Shi, Yefei; Zhang, Xianling; Peng, Wenhui

doi:10.3389/fcvm.2021.756889

Cited by 22 publications

(18 citation statements)

References 35 publications

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“…Next, the 5 potential biomarkers were analyzed and discussed for their association with ICM along with the literature. SERPINA3 belonging to the superfamily of serine protease inhibitors plays a significant role in the pathogenesis of atherosclerosis ( 35 ). SERPINA3 not only was a novel diagnostic and pharmacological target for HF but also associated with major adverse cardiovascular events in patients with acute myocardial infarction ( 36 , 37 ).…”

Section: Discussionmentioning

confidence: 99%

Identification of potential biomarkers of inflammation-related genes for ischemic cardiomyopathy

Wang

Xie

Cheng

et al. 2022

Front. Cardiovasc. Med.

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ObjectiveInflammation plays an important role in the pathophysiology of ischemic cardiomyopathy (ICM). We aimed to identify potential biomarkers of inflammation-related genes for ICM and build a model based on the potential biomarkers for the diagnosis of ICM.Materials and methodsThe microarray datasets and RNA-Sequencing datasets of human ICM were downloaded from the Gene Expression Omnibus database. We integrated 8 microarray datasets via the SVA package to screen the differentially expressed genes (DEGs) between ICM and non-failing control samples, then the differentially expressed inflammation-related genes (DEIRGs) were identified. The least absolute shrinkage and selection operator, support vector machine recursive feature elimination, and random forest were utilized to screen the potential diagnostic biomarkers from the DEIRGs. The potential biomarkers were validated in the RNA-Sequencing datasets and the functional experiment of the ICM rat, respectively. A nomogram was established based on the potential biomarkers and evaluated via the area under the receiver operating characteristic curve (AUC), calibration curve, decision curve analysis (DCA), and Clinical impact curve (CIC).Results64 DEGs and 19 DEIRGs were identified, respectively. 5 potential biomarkers (SERPINA3, FCN3, PTN, CD163, and SCUBE2) were ultimately selected. The validation results showed that each of these five potential biomarkers showed good discriminant power for ICM, and their expression trends were consistent with the bioinformatics results. The results of AUC, calibration curve, DCA, and CIC showed that the nomogram demonstrated good performance, calibration, and clinical utility.ConclusionSERPINA3, FCN3, PTN, CD163, and SCUBE2 were identified as potential biomarkers associated with the inflammatory response to ICM. The proposed nomogram could potentially provide clinicians with a helpful tool to the diagnosis and treatment of ICM from an inflammatory perspective.

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Section: Discussionmentioning

confidence: 99%

Identification of potential biomarkers of inflammation-related genes for ischemic cardiomyopathy

Wang

Xie

Cheng

et al. 2022

Front. Cardiovasc. Med.

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“…Overexpression of SERPINA3 can enhance the expression of inflammatory markers in human umbilical vein endothelial cells (HUVEC), proving its important role in CAD. 31 In the present study, three SERPINA3 gene isoforms (serpina3n, serpina3m, and ser-pina3g), in three microarray datasets, were up-regulated in ALI compared to those in control groups. Additionally, our results also confirmed that SERPINA3 protein was increased in BEAS-2B cells treated with LPS, and these results further demonstrated that SERPINA3 could be associated with ALI.…”

Section: Discussionmentioning

confidence: 44%

Identification of biomarkers and candidate small-molecule drugs in lipopolysaccharide (LPS)-induced acute lung injury by bioinformatics analysis

Wang

Chen

2023

Allergol Immunopathol

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Background/objective: Acute lung injury (ALI) is a critical clinical syndrome with high rates of incidence and mortality. However, its molecular mechanism remains unclear. The current work aimed to explore the molecular mechanisms of ALI by identifying different expression genes (DEGs) and candidate drugs using a combination of chip analysis and experimental validation. Methods: Three microarray datasets were downloaded from Gene Expression Omnibus (GEO) database to obtain DEGs. We conducted a Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway-enrichment analyses of overlapping DEGs among three databases. The expression level of key gene was verified by Western blotting analysis in LPS-treated ALI cell models. Finally, we predicted the candidate drugs targeting the key gene that might be effective for ALI treatment, and the role of candidate drug in treating ALI was verified by investigation. Results: A total 29 overlapping DEGs were up-regulated in LPS-induced ALI groups. They were enriched in inflammation and inflammation-related pathways. Serpin family A member 3 (SERPINA3) was defined as a key gene because it was associated with inflammation pathway and up-regulated in microarray datasets in LPS-induced ALI. In LPS-induced human bronchial epithelial cells transformed with Ad12-SV40-2B (BEAS-2B) cells, SERPINA3 was enhanced. Pyridoxal phosphate as an upstream drug of SERPINA3 could improve cell viability and reduce expression inflammatory factors in LPS-treated BEAS-2B cells. Conclusion: Our study suggested that pyridoxal phosphate could be a candidate drug targeting SERPINA3 gene in LPS-induced ALI. It has protective and anti-inflammatory effects in BEAS-2B cells, and may become a potential novel treatment for ALI.

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“…Most studies of SERPINA3 have focused on tumors, and few have investigated NALFD and AS, whereas the mouse homologue SERPINA3C is related to two diseases in more studies. Plasma levels of the acute-phase protein SERPINA3 increase substantially during inflammation ( 34 ). However, we found obviously diminished SERPINA3 expression in patients compared with controls in the NAFLD and AS datasets, suggesting that SERPINA3 has an anti-NAFLD ( 35 ) and anti-AS ( 36 ) effects.…”

Section: Discussionmentioning

confidence: 99%

Potential diagnostic markers shared between non-alcoholic fatty liver disease and atherosclerosis determined by machine learning and bioinformatic analysis

Wang,

He,

Wang

et al. 2024

Front. Med.

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BackgroundEvidence indicates that chronic non-alcoholic fatty liver disease (NAFLD) can increase the risk of atherosclerosis (AS), but the underlying mechanism remains unclear.ObjectiveThis study is intended for confirming key genes shared between NAFLD and AS, and their clinical diagnostic value to establish a foundation for searching novel therapeutic targets.MethodsWe downloaded the Gene Expression Omnibus (GEO) datasets, GSE48452 and GSE89632 for NAFLD and GSE100927, GSE40231 and GSE28829 for AS. The progression of NAFLD co-expression gene modules were recognized via weighted gene co-expression network analysis (WGCNA). We screened for differentially expressed genes (DEGs) associated with AS and identified common genes associated with NAFLD and AS using Venn diagrams. We investigated the most significant core genes between NAFLD and AS using machine learning algorithms. We then constructed a diagnostic model by creating a nomogram and evaluating its performance using ROC curves. Furthermore, the CIBERSORT algorithm was utilized to explore the immune cell infiltration between the two diseases, and evaluate the relationship between diagnostic genes and immune cells.ResultsThe WGCNA findings associated 1,129 key genes with NAFLD, and the difference analysis results identified 625 DEGs in AS, and 47 genes that were common to both diseases. We screened the core RPS6KA1 and SERPINA3 genes associated with NAFLD and AS using three machine learning algorithms. A nomogram and ROC curves demonstrated that these genes had great clinical meaning. We found differential expression of RPS6KA1 in patients with steatosis and NASH, and of SERPINA3 only in those with NASH compared with normal individuals. Immune infiltration findings revealed that macrophage and mast cell infiltration play important roles in the development of NAFLD and AS. Notably, SERPINA3 correlated negatively, whereas RPS6KA1 correlated positively with macrophages and mast cells.ConclusionWe identified RPS6KA1 and SERPINA3 as potential diagnostic markers for NAFLD and AS. The most promising marker for a diagnosis of NAFLD and AS might be RPS6KA1, whereas SERPINA3 is the most closely related gene for NASH and AS. We believe that further exploration of these core genes will reveal the etiology and a pathological relationship between NAFLD and AS.

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The Association and Pathogenesis of SERPINA3 in Coronary Artery Disease

Cited by 22 publications

References 35 publications

Identification of potential biomarkers of inflammation-related genes for ischemic cardiomyopathy

Identification of potential biomarkers of inflammation-related genes for ischemic cardiomyopathy

Identification of biomarkers and candidate small-molecule drugs in lipopolysaccharide (LPS)-induced acute lung injury by bioinformatics analysis

Potential diagnostic markers shared between non-alcoholic fatty liver disease and atherosclerosis determined by machine learning and bioinformatic analysis

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