Zhanying Zhu, Jiani Xu, Haitao Wang, Wei Jin, Miao Liu
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Inflammatory cell model was constructed by treating human cardiac microvascular endothelial cells (HMVEC-Cs) with TNF-α to explore the role of RAC2 in this process.</p><p><strong>Results: </strong>Real time quantitative PCR (RT-qPCR) results showed high-expression of RAC2 in CHD patients, which were reversed after nitric ester drug therapy. The analysis of ROC curves displayed that RAC2 combined with CT-FFR had a higher diagnostic value for CHD (AUC=0.971, 95% CI 0.950-0.992) compared to the single factor, and RAC2 was an independent risk factor for poor prognosis in CHD patients treated with nitric ester drugs (AUC=0.888, 95% CI 0.814-0.961, P<0.001). Overexpression of RAC2 further enhanced the elevated expression levels of NF-κB, NLRP3, IL-1β, and IL-6, induced by TNF-α, and its silence had the opposite effect.</p><p><strong>Conclusions: </strong>RAC2 promoted the inflammatory response of HMVEC-Cs and predicted a poor prognosis in CHD patients. The combination of RAC2 and CT-FFR parameters was a good classifier for diagnosing CHD.</p>","PeriodicalId":18668,"journal":{"name":"Minerva cardiology and angiology","volume":" ","pages":"558-565"},"PeriodicalIF":1.3000,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Diagnostic performance of RAC2 combined with CT-FFR parameters in coronary heart disease.\",\"authors\":\"Zhanying Zhu, Jiani Xu, Haitao Wang, Wei Jin, Miao Liu\",\"doi\":\"10.23736/S2724-5683.24.06618-3\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>The incidence and mortality of coronary heart disease (CHD) are high in the elderly population. CT fractional flow reserve (CT-FFR) is a potential diagnostic technique for cardiovascular diseases. In order to mine valuable biomarkers to combine CT-FFR parameters to improve the diagnostic accuracy of CHD.</p><p><strong>Methods: </strong>In this study, GEO database was used to screen the key genes of CHD. GraphPad software was used to construct receiver operating characteristic (ROC) curve, and SPSS software was used for logistic regression analysis. Inflammatory cell model was constructed by treating human cardiac microvascular endothelial cells (HMVEC-Cs) with TNF-α to explore the role of RAC2 in this process.</p><p><strong>Results: </strong>Real time quantitative PCR (RT-qPCR) results showed high-expression of RAC2 in CHD patients, which were reversed after nitric ester drug therapy. The analysis of ROC curves displayed that RAC2 combined with CT-FFR had a higher diagnostic value for CHD (AUC=0.971, 95% CI 0.950-0.992) compared to the single factor, and RAC2 was an independent risk factor for poor prognosis in CHD patients treated with nitric ester drugs (AUC=0.888, 95% CI 0.814-0.961, P<0.001). Overexpression of RAC2 further enhanced the elevated expression levels of NF-κB, NLRP3, IL-1β, and IL-6, induced by TNF-α, and its silence had the opposite effect.</p><p><strong>Conclusions: </strong>RAC2 promoted the inflammatory response of HMVEC-Cs and predicted a poor prognosis in CHD patients. 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引用次数: 0
摘要
背景:老年人群冠心病(CHD)的发病率和死亡率较高。CT分数血流储备(CT- ffr)是一种有潜力的心血管疾病诊断技术。为了挖掘有价值的生物标志物,结合CT-FFR参数,提高冠心病的诊断准确性。方法:利用GEO数据库对冠心病关键基因进行筛选。采用GraphPad软件构建受试者工作特征(ROC)曲线,采用SPSS软件进行logistic回归分析。通过TNF-α处理人心脏微血管内皮细胞(HMVEC-Cs),构建炎症细胞模型,探讨RAC2在这一过程中的作用。结果:实时定量PCR (RT-qPCR)结果显示,RAC2在冠心病患者体内高表达,经硝酸酯药物治疗后呈逆转。ROC曲线分析显示,RAC2联合CT-FFR对冠心病的诊断价值(AUC=0.971, 95% CI 0.950-0.992)高于单一因素,RAC2是硝酸酯类药物治疗冠心病患者预后不良的独立危险因素(AUC=0.888, 95% CI 0.814-0.961)。结论:RAC2促进hmec - cs的炎症反应,预测冠心病患者预后不良。结合RAC2和CT-FFR参数是诊断冠心病较好的分类器。
Diagnostic performance of RAC2 combined with CT-FFR parameters in coronary heart disease.
Background: The incidence and mortality of coronary heart disease (CHD) are high in the elderly population. CT fractional flow reserve (CT-FFR) is a potential diagnostic technique for cardiovascular diseases. In order to mine valuable biomarkers to combine CT-FFR parameters to improve the diagnostic accuracy of CHD.
Methods: In this study, GEO database was used to screen the key genes of CHD. GraphPad software was used to construct receiver operating characteristic (ROC) curve, and SPSS software was used for logistic regression analysis. Inflammatory cell model was constructed by treating human cardiac microvascular endothelial cells (HMVEC-Cs) with TNF-α to explore the role of RAC2 in this process.
Results: Real time quantitative PCR (RT-qPCR) results showed high-expression of RAC2 in CHD patients, which were reversed after nitric ester drug therapy. The analysis of ROC curves displayed that RAC2 combined with CT-FFR had a higher diagnostic value for CHD (AUC=0.971, 95% CI 0.950-0.992) compared to the single factor, and RAC2 was an independent risk factor for poor prognosis in CHD patients treated with nitric ester drugs (AUC=0.888, 95% CI 0.814-0.961, P<0.001). Overexpression of RAC2 further enhanced the elevated expression levels of NF-κB, NLRP3, IL-1β, and IL-6, induced by TNF-α, and its silence had the opposite effect.
Conclusions: RAC2 promoted the inflammatory response of HMVEC-Cs and predicted a poor prognosis in CHD patients. The combination of RAC2 and CT-FFR parameters was a good classifier for diagnosing CHD.