急性主动脉夹层患者住院死亡的预测因素和候选诊断生物标志物
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摘要
目的：A型急性主动脉夹层(AAD)是较常见的主动脉急症,A型AAD患者比B型患者面临更高的住院死亡率。已有许多研究报道了D二聚体浓度对AAD的辅助性鉴别诊断意义,但D二聚体浓度对住院死亡的预测价值存在争议,本研究探索血浆D二聚体浓度与A型AAD患者住院死亡的关系,并分析可能对住院死亡提供预测价值的因素。
方法：本研究为前瞻性观察性研究,入选2012-02到2013-05期间就诊我院急诊科疑诊为AAD的连续病例,对患者进行常规实验室及影像学检查,同时检测入院时血浆D二聚体浓度。A型AAD的诊断由多层主动脉计算机断层扫描(CT)血管成像确诊。为识别住院死亡的预测因素,收集患者的人口统计学资料、相关病史、体格检查、实验室检查、影像学检查及入院治疗措施。主要研究终点为住院死亡,死亡原因包括：主动脉破裂、围术期死亡、主动脉夹层相关的器官缺血。记录住院期间的主要终点事件及其发生时间。根据住院期间是否死亡将患者分为死亡组和存活组。住院死亡预测因素通过单因素和多因素Cox比例风险模型分析确定。
结果：共入选194例经CT血管成像确诊的A型AAD患者,男134例,平均年龄(51.7±11.1)岁,平均住院时间为(13±10)天。住院期间,院内死亡率为13.9%(27/194)。基线资料分析显示,与存活组患者比较,死亡组患者血浆D二聚体浓度明显升高(13.9±7.6μg/ml vs.8.5±6.8μg/ml, P=0.000),血小板计数明显降低(125±68×109/Lvs.187±74×109/L,P=0.000),血肌酐浓度显著升高,而入院时收缩压／舒张压显著降低(118/64mmHg vs.140/75mmHg, P<0.01);死亡组患者接受外科手术的比例明显低于存活组(7.2%vs.72.5%,P<0.001)。单因素Cox回归分析显示入院D二聚体浓度、收缩压、血小板计数、血肌酐浓度以及外科手术治疗均与住院死亡相关。对血浆D二聚体浓度预测住院死亡的阈值分析显示：D二聚体浓度≥20μg/ml组的住院死亡率明显高于D二聚体浓度<20μg/ml组(34.2%vs.9.0%,logrank P<0.001)。D二聚体浓度≥20μg/ml显著增加住院死亡风险(HR,3.964；95%CI,1.830～8.588；P=0.000)；由于本组AAD患者发生住院死亡的例数较少,为保持多元回归方程的稳定,进行多元回归分析时,仅纳入有显著性差异的客观基线变量。为探讨D二聚体浓度分组对住院死亡的预测价值建立模型1,经调整年龄,收缩压,血肌酐浓度,入院血小板计数,结果显示：D二聚体浓度≥20μg/ml和住院死亡相关HR：3.709,95%CI(1.558～8.827)。考虑到手术治疗是影响预后的关键治疗措施,所以在模型1的基础上纳入手术干预(模型2),结果显示：高D二聚体浓度不再和住院死亡独立相关,入院血小板计数HR：0.993；95%CI(0.987-0.999),收缩压HR：0.979,95%CI(0.965～0.992)和手术干预HR：0.033；95%CI(0.008～0.146)均与住院死亡独立相关。相关性分析显示入院D二聚体浓度与血小板计数呈负相关关系(r=-0.442,P<0.001)。未接受外科手术治疗的AAD患者,D二聚体浓度≥20ug/ml组的住院死亡率显著高于D二聚体浓度<20ug/ml(P<0.05),但接受手术治疗后,两组差异不明显。
结论：A型AAD患者住院死亡率仍较高。入院时收缩压降低、血小板计数下降以及不施行手术治疗是A型AAD发生住院死亡的独立预测因素。升高的血浆D二聚体浓度和A型AAD患者发生住院死亡相关,此类A型AAD患者更需要紧急外科手术治疗。
目的：早期准确诊断是改善急性主动脉夹层(AAD)患者预后的关键环节。应用生物标志物可以帮助临床医生对疾病做出诊断,并启动早期正确治疗。但寻找AAD的理想生物标志物是一项很有挑战性的工作。本实验从转录组学出发寻找AAD特异性的血浆生物标志物。
方法：采用标准的组织收集技术分别收集8例男性AAD患者和8例正常器官捐献者的升主动脉标本。各选取4例AAD患者(平均年龄,49.1±4.9岁)和正常对照者(平均年龄,47.9±6.7岁)的主动脉标本,从直接的病灶组织出发,应用基因表达谱芯片初筛mRNA表达谱。通过比较AAD患者撕裂血管组织和正常人血管组织的mRNA表达谱,利用生物信息学分析,确定差异最显著且分泌表达的基因。为了确认芯片的结果,扩大组织样本,分别选取8例AAD和8例正常对照主动脉组织标本,用quantitative real-time PCR和western blot分别在aRNA和蛋白水平验证差异基因表达,确定组织差异表达基因与AAD的关系。按年龄和性别匹配的原则,收集两个独立的病例对照人群的血浆样本,第一个病例对照人群包含20例A型AAD患者和18例健康对照,第二个验证人群包含65例A型AAD患者,32例B型AAD患者以及44例正常对照。然后应用ELISA方法检测差异蛋白的血浆浓度,确定该蛋白可以作为辅助诊断AAD的血浆生物标志物。应用t检验或非参数检验评估组间差异显著性,应用ROC曲线检验生物标志物诊断AAD的能力。
结果：我们设定了严格的差异基因挑选阈值(Foldchange>3并且p<0.01),满足条件时才认为该基因在AAD和正常对照之间有差异。基因表达谱芯片分析显示18个基因在AAD中表达上调,28个基因表达下调。聚类分析表明,46个差异表达的基因显著聚集于黏着斑和肌动蛋白细胞骨架调节信号通路(p<0.001)。综合运用多种生物信息学分析工具(Gene Ontology, UniProt, and Human Plasma Proteome)并结合Pubmed文献检索,分析差异基因的特性。结果发现三个候选基因,即/(?)NGPT2(芯片检测表达升高4倍)、CCL3(表达升高3.7倍)和FN1(表达升高3.7倍)。扩大样本量至8例AAD和8例正常对照主动脉组织标本,用quantitative real-timePCR法检测了三个候选基因的(?)RNA表达改变,发现AAD患者血管组织中ANGPT2的mRNA表达水平升高为对照的2.4倍(P<0.01),CCL3升高为对照的3.6倍(P=0.02),FN1没有显著差异。Western blot检测进一步证实,ANGPT2基因的蛋白水平在AAD患者血管组织中升高了4.2倍(P=0.033)。在第一个ELISA检测人群,发现AAD患者的血浆ANGPT2浓度升高为对照组的1.8倍(P=0.002),但CCL3没有明显改变(P=0.51)。在第二个验证ELISA检测人群,AAD患者血浆ANGPT2浓度仍显著高于对照组(中位数4.1ng/mL和1.4ng/mL, P=6.9E-9)。ROC曲线分析表明,血浆ANGPT2浓度具有较高的AAD鉴别诊断价值(曲线下面积,0.81,P<0.0001)。在切点2.46ng/mL的敏感性和特异性分别是72%和80%。
结论：我们发现主动脉夹层患者的病变血管组织基因表达谱存在明显改变,主要集中在黏着斑和肌动蛋白细胞骨架调节两条信号通路。另外,发现ANGPT2基因与AAD相关,血浆ANGPT2浓度可以作为AAD诊断的新的生物标志物。
Objective:Type A acute aortic dissection (AAD) confers higher in-hospital mortality. It is controversial that plasma D-dimer can predict in-hospital mortality of AAD. Our study aims to investigate the correlation of plasma D-dimer with in-hospital mortality and analyze risk factors of in-hospital mortality in patients with type A AAD.
Methods:The study designed as a prospectively observational study. From2012-2to2013-5, a series of consecutive patients with suspect AAD presented to our emergency department was enrolled, and plasma D-dimer level was measured (stago-evolution, France) immediately following admission. The diagnosis of type A AAD was confirmed by aorta angiography with multi-detector computed tomography for each patient. To define risk factors of in-hospital mortality, patient's clinical characteristics were collected. All patients were followed up during hospitalization. Patients were divided into two groups:the deceased group, who died during hospitalization, and the survival group. The risk factors for in-hospital mortality were determined by using univariate and multivariate Cox proportional hazards analyses.
Results:A total of194patients with type A AAD were included,134males, average age (51.7±11.1years). During a mean of13days hospitalization, death occurred in27(13.9%) patients. The plasma D-dimer level of the deceased group was significantly higher than that of the survival group (13.9±7.6μg/ml vs.8.5±6.8μg/ml, P=0.000). The platelet counts of the deceased group was significantly lower than that of the survival group (125±68×109/L vs.187±74×109/L, P=0.000). The plasma Scr level of the deceased group was higher. Admission blood pressure levels of the deceased group were lower than the survial group (118/64mmHg vs.140/75mmHg, P<0.01). More patients in the survival group undergone surgery(72.5%). On univariate Cox regression analysis, admission D-dimer level≥20μg/ml was associated with increased risk of in-hospital death(HR,3.964;95%CI,1.830～8.588; P=0.000). The in-hospital mortality was significantly higher in patients with plasma D-dimer level≥20μg/ml than in those with plasma D-dimer level<20μg/ml (34.2%vs.9.0%, log rank P<0.001). In model1, after adjustment for age, systolic blood pressure, platelet counts, Scr level, a high admission D-dimer level (≥20μg/ml) was still a powerful independent predictor of in-hospital mortality (HR:3.709,95%CI (1.558-8.827)). Given that surgical intervention is key treatment measure to improve the prognosis, so we constructed Cox regression model2which include model1and surgical intervention. The results showed that high admission D-dimer level did not independently correlate with in-hospital mortality any more. Meanwhile admission platelet counts (HR:0.993;95%CI (0.987～0.999)), systolic blood pressure (HR:0.979,95%CI (0.965-0.992)) and surgery (HR:0.033;95%CI(0.008-0.146)) independently correlated with in-hospital mortality. Correlation analysis indicated a negative correlation between admission D-dimer level and platelet counts(r=-0.442, P<0.001). Type A AAD patients who did not undergone surgery with a higher admission D-dimer≥20ug/ml confers higher in-hospital mortality. However when these patients undergone surgery, their in-hopital mortality were similar.
Conclusions:Our results suggest admission lower systolic blood pressure, lower platelet counts and conservative treatment are independent predictors for in-hospital mortality of AAD. A high admission D-dimer level might be a powerful predictor for increased in-hospital mortality in patients with type A AAD, these patients may benefit more from surgery.
Objective:The excessive mortality associated with acute aortic dissection (AAD) makes the need for accurate diagnosis critical. Biomarker-assisted diagnosis of acute aortic dissection is important for initiation of treatment and improved survival. However, identification of biomarkers for AAD in blood is a challenging task. The present study aims to discover the potential AAD biomarkers using a transcriptomic strategy.
Methods:Ascending aortic tissue was collected from eight male patients with Stanford Type A aortic dissection and eight healthy male organ donors. Array based genome-wide gene expression profiling were performed on a panel of aortic tissues from4AAD patients (mean age,49.1±4.9years) and4controls (mean age,47.9±6.7years). The differentially expressed genes were validated using quantitative reverse transcriptase PCR (qRT-PCR) and westen blot in the whole tissue panel. The plasma levels of potential biomarker were determined in two independent case-control cohorts by enzyme linked immunosorbent assay. Twenty type A AAD patients and eighteen normal controls were enrolled in the pilot cohort. Sixty five type A AAD patients, thirty two type B AAD patients and forty four normal controls were included in the second validation cohort. Difference between groups was evaluated using Student's t test or Mann-Whitney test. Sensitivity and specificity were calculated in relation to the final diagnosis. Receiver operating characteristics (ROC) curves were constructed by plotting sensitivity (true-positive fraction) vs.1-specificity (false-positive fraction) for discrimination between controls and patients with AAD. The area under the curve was calculated.
Results:Transcriptome data demonstrated that a total of18genes were significantly up-regulated and28genes were significantly down-regulated among AAD tissues (FDR-adjusted p<0.01, foldchange>3.0). The differentially expressed gene set was highly enriched among functional categories involved in Focal adhesion and Regulation of actin cytoskeleton pathways (p<0.001). By using literature data (Gene Ontology, UniProt, and Human Plasma Proteome), we identified three proteins (angiopoietin2(ANGPT2), chemokine (C-C motif) ligand3(CCL3) and FN1), as candidate biomarkers for blood-based detection of AAD. The qRT-PCR assay demonstrated that ANGPT2and CCL3increased2.4-fold (P<0.01) and3.6-fold (P=0.02) in the entire patient group, compared with control specimens, respectively. The western-blot analysis indicated that ANGPT2in AAD group increased4.2-fold (P=0.033). In the pilot study, although the plasma concentrations of CCL3were unchanged(P=0.51), ANGPT2levels were significantly1.8-fold higher in AAD patients than in controls(P=0.002). In the validation study, ANGPT2was also significantly elevated in AAD patients as compared with controls (medians4.1ng/mL vs.1.4ng/mL, p=6.9E-9). ROC curve analysis showed that ANGPT2was highly predictive of a diagnosis of acute aortic dissection (area under ROC curve0.81, p<0.0001). Sensitivity and specificity were72%and80%, respectively, at the cutoff value of2.46ng/mL.
Conclusions:Our study indicate that Focal adhesion and Regulation of actin cytoskeleton pathways are probably invoved in pathogenesis of AAD. Moreover, our preliminary study offers the first evidence that ANGPT2is associated with AAD and could be a promising biomarker for early detection of AAD. Future studies with a larger sample size of normal and AAD patient samples should be pursued.
方法：本研究为前瞻性观察性研究,入选2012-02到2013-05期间就诊我院急诊科疑诊为AAD的连续病例,对患者进行常规实验室及影像学检查,同时检测入院时血浆D二聚体浓度。A型AAD的诊断由多层主动脉计算机断层扫描(CT)血管成像确诊。为识别住院死亡的预测因素,收集患者的人口统计学资料、相关病史、体格检查、实验室检查、影像学检查及入院治疗措施。主要研究终点为住院死亡,死亡原因包括：主动脉破裂、围术期死亡、主动脉夹层相关的器官缺血。记录住院期间的主要终点事件及其发生时间。根据住院期间是否死亡将患者分为死亡组和存活组。住院死亡预测因素通过单因素和多因素Cox比例风险模型分析确定。
结果：共入选194例经CT血管成像确诊的A型AAD患者,男134例,平均年龄(51.7±11.1)岁,平均住院时间为(13±10)天。住院期间,院内死亡率为13.9%(27/194)。基线资料分析显示,与存活组患者比较,死亡组患者血浆D二聚体浓度明显升高(13.9±7.6μg/ml vs.8.5±6.8μg/ml, P=0.000),血小板计数明显降低(125±68×109/Lvs.187±74×109/L,P=0.000),血肌酐浓度显著升高,而入院时收缩压／舒张压显著降低(118/64mmHg vs.140/75mmHg, P<0.01);死亡组患者接受外科手术的比例明显低于存活组(7.2%vs.72.5%,P<0.001)。单因素Cox回归分析显示入院D二聚体浓度、收缩压、血小板计数、血肌酐浓度以及外科手术治疗均与住院死亡相关。对血浆D二聚体浓度预测住院死亡的阈值分析显示：D二聚体浓度≥20μg/ml组的住院死亡率明显高于D二聚体浓度<20μg/ml组(34.2%vs.9.0%,logrank P<0.001)。D二聚体浓度≥20μg/ml显著增加住院死亡风险(HR,3.964；95%CI,1.830～8.588；P=0.000)；由于本组AAD患者发生住院死亡的例数较少,为保持多元回归方程的稳定,进行多元回归分析时,仅纳入有显著性差异的客观基线变量。为探讨D二聚体浓度分组对住院死亡的预测价值建立模型1,经调整年龄,收缩压,血肌酐浓度,入院血小板计数,结果显示：D二聚体浓度≥20μg/ml和住院死亡相关HR：3.709,95%CI(1.558～8.827)。考虑到手术治疗是影响预后的关键治疗措施,所以在模型1的基础上纳入手术干预(模型2),结果显示：高D二聚体浓度不再和住院死亡独立相关,入院血小板计数HR：0.993；95%CI(0.987-0.999),收缩压HR：0.979,95%CI(0.965～0.992)和手术干预HR：0.033；95%CI(0.008～0.146)均与住院死亡独立相关。相关性分析显示入院D二聚体浓度与血小板计数呈负相关关系(r=-0.442,P<0.001)。未接受外科手术治疗的AAD患者,D二聚体浓度≥20ug/ml组的住院死亡率显著高于D二聚体浓度<20ug/ml(P<0.05),但接受手术治疗后,两组差异不明显。
结论：A型AAD患者住院死亡率仍较高。入院时收缩压降低、血小板计数下降以及不施行手术治疗是A型AAD发生住院死亡的独立预测因素。升高的血浆D二聚体浓度和A型AAD患者发生住院死亡相关,此类A型AAD患者更需要紧急外科手术治疗。
目的：早期准确诊断是改善急性主动脉夹层(AAD)患者预后的关键环节。应用生物标志物可以帮助临床医生对疾病做出诊断,并启动早期正确治疗。但寻找AAD的理想生物标志物是一项很有挑战性的工作。本实验从转录组学出发寻找AAD特异性的血浆生物标志物。
方法：采用标准的组织收集技术分别收集8例男性AAD患者和8例正常器官捐献者的升主动脉标本。各选取4例AAD患者(平均年龄,49.1±4.9岁)和正常对照者(平均年龄,47.9±6.7岁)的主动脉标本,从直接的病灶组织出发,应用基因表达谱芯片初筛mRNA表达谱。通过比较AAD患者撕裂血管组织和正常人血管组织的mRNA表达谱,利用生物信息学分析,确定差异最显著且分泌表达的基因。为了确认芯片的结果,扩大组织样本,分别选取8例AAD和8例正常对照主动脉组织标本,用quantitative real-time PCR和western blot分别在aRNA和蛋白水平验证差异基因表达,确定组织差异表达基因与AAD的关系。按年龄和性别匹配的原则,收集两个独立的病例对照人群的血浆样本,第一个病例对照人群包含20例A型AAD患者和18例健康对照,第二个验证人群包含65例A型AAD患者,32例B型AAD患者以及44例正常对照。然后应用ELISA方法检测差异蛋白的血浆浓度,确定该蛋白可以作为辅助诊断AAD的血浆生物标志物。应用t检验或非参数检验评估组间差异显著性,应用ROC曲线检验生物标志物诊断AAD的能力。
结果：我们设定了严格的差异基因挑选阈值(Foldchange>3并且p<0.01),满足条件时才认为该基因在AAD和正常对照之间有差异。基因表达谱芯片分析显示18个基因在AAD中表达上调,28个基因表达下调。聚类分析表明,46个差异表达的基因显著聚集于黏着斑和肌动蛋白细胞骨架调节信号通路(p<0.001)。综合运用多种生物信息学分析工具(Gene Ontology, UniProt, and Human Plasma Proteome)并结合Pubmed文献检索,分析差异基因的特性。结果发现三个候选基因,即/(?)NGPT2(芯片检测表达升高4倍)、CCL3(表达升高3.7倍)和FN1(表达升高3.7倍)。扩大样本量至8例AAD和8例正常对照主动脉组织标本,用quantitative real-timePCR法检测了三个候选基因的(?)RNA表达改变,发现AAD患者血管组织中ANGPT2的mRNA表达水平升高为对照的2.4倍(P<0.01),CCL3升高为对照的3.6倍(P=0.02),FN1没有显著差异。Western blot检测进一步证实,ANGPT2基因的蛋白水平在AAD患者血管组织中升高了4.2倍(P=0.033)。在第一个ELISA检测人群,发现AAD患者的血浆ANGPT2浓度升高为对照组的1.8倍(P=0.002),但CCL3没有明显改变(P=0.51)。在第二个验证ELISA检测人群,AAD患者血浆ANGPT2浓度仍显著高于对照组(中位数4.1ng/mL和1.4ng/mL, P=6.9E-9)。ROC曲线分析表明,血浆ANGPT2浓度具有较高的AAD鉴别诊断价值(曲线下面积,0.81,P<0.0001)。在切点2.46ng/mL的敏感性和特异性分别是72%和80%。
结论：我们发现主动脉夹层患者的病变血管组织基因表达谱存在明显改变,主要集中在黏着斑和肌动蛋白细胞骨架调节两条信号通路。另外,发现ANGPT2基因与AAD相关,血浆ANGPT2浓度可以作为AAD诊断的新的生物标志物。
Objective:Type A acute aortic dissection (AAD) confers higher in-hospital mortality. It is controversial that plasma D-dimer can predict in-hospital mortality of AAD. Our study aims to investigate the correlation of plasma D-dimer with in-hospital mortality and analyze risk factors of in-hospital mortality in patients with type A AAD.
Methods:The study designed as a prospectively observational study. From2012-2to2013-5, a series of consecutive patients with suspect AAD presented to our emergency department was enrolled, and plasma D-dimer level was measured (stago-evolution, France) immediately following admission. The diagnosis of type A AAD was confirmed by aorta angiography with multi-detector computed tomography for each patient. To define risk factors of in-hospital mortality, patient's clinical characteristics were collected. All patients were followed up during hospitalization. Patients were divided into two groups:the deceased group, who died during hospitalization, and the survival group. The risk factors for in-hospital mortality were determined by using univariate and multivariate Cox proportional hazards analyses.
Results:A total of194patients with type A AAD were included,134males, average age (51.7±11.1years). During a mean of13days hospitalization, death occurred in27(13.9%) patients. The plasma D-dimer level of the deceased group was significantly higher than that of the survival group (13.9±7.6μg/ml vs.8.5±6.8μg/ml, P=0.000). The platelet counts of the deceased group was significantly lower than that of the survival group (125±68×109/L vs.187±74×109/L, P=0.000). The plasma Scr level of the deceased group was higher. Admission blood pressure levels of the deceased group were lower than the survial group (118/64mmHg vs.140/75mmHg, P<0.01). More patients in the survival group undergone surgery(72.5%). On univariate Cox regression analysis, admission D-dimer level≥20μg/ml was associated with increased risk of in-hospital death(HR,3.964;95%CI,1.830～8.588; P=0.000). The in-hospital mortality was significantly higher in patients with plasma D-dimer level≥20μg/ml than in those with plasma D-dimer level<20μg/ml (34.2%vs.9.0%, log rank P<0.001). In model1, after adjustment for age, systolic blood pressure, platelet counts, Scr level, a high admission D-dimer level (≥20μg/ml) was still a powerful independent predictor of in-hospital mortality (HR:3.709,95%CI (1.558-8.827)). Given that surgical intervention is key treatment measure to improve the prognosis, so we constructed Cox regression model2which include model1and surgical intervention. The results showed that high admission D-dimer level did not independently correlate with in-hospital mortality any more. Meanwhile admission platelet counts (HR:0.993;95%CI (0.987～0.999)), systolic blood pressure (HR:0.979,95%CI (0.965-0.992)) and surgery (HR:0.033;95%CI(0.008-0.146)) independently correlated with in-hospital mortality. Correlation analysis indicated a negative correlation between admission D-dimer level and platelet counts(r=-0.442, P<0.001). Type A AAD patients who did not undergone surgery with a higher admission D-dimer≥20ug/ml confers higher in-hospital mortality. However when these patients undergone surgery, their in-hopital mortality were similar.
Conclusions:Our results suggest admission lower systolic blood pressure, lower platelet counts and conservative treatment are independent predictors for in-hospital mortality of AAD. A high admission D-dimer level might be a powerful predictor for increased in-hospital mortality in patients with type A AAD, these patients may benefit more from surgery.
Objective:The excessive mortality associated with acute aortic dissection (AAD) makes the need for accurate diagnosis critical. Biomarker-assisted diagnosis of acute aortic dissection is important for initiation of treatment and improved survival. However, identification of biomarkers for AAD in blood is a challenging task. The present study aims to discover the potential AAD biomarkers using a transcriptomic strategy.
Methods:Ascending aortic tissue was collected from eight male patients with Stanford Type A aortic dissection and eight healthy male organ donors. Array based genome-wide gene expression profiling were performed on a panel of aortic tissues from4AAD patients (mean age,49.1±4.9years) and4controls (mean age,47.9±6.7years). The differentially expressed genes were validated using quantitative reverse transcriptase PCR (qRT-PCR) and westen blot in the whole tissue panel. The plasma levels of potential biomarker were determined in two independent case-control cohorts by enzyme linked immunosorbent assay. Twenty type A AAD patients and eighteen normal controls were enrolled in the pilot cohort. Sixty five type A AAD patients, thirty two type B AAD patients and forty four normal controls were included in the second validation cohort. Difference between groups was evaluated using Student's t test or Mann-Whitney test. Sensitivity and specificity were calculated in relation to the final diagnosis. Receiver operating characteristics (ROC) curves were constructed by plotting sensitivity (true-positive fraction) vs.1-specificity (false-positive fraction) for discrimination between controls and patients with AAD. The area under the curve was calculated.
Results:Transcriptome data demonstrated that a total of18genes were significantly up-regulated and28genes were significantly down-regulated among AAD tissues (FDR-adjusted p<0.01, foldchange>3.0). The differentially expressed gene set was highly enriched among functional categories involved in Focal adhesion and Regulation of actin cytoskeleton pathways (p<0.001). By using literature data (Gene Ontology, UniProt, and Human Plasma Proteome), we identified three proteins (angiopoietin2(ANGPT2), chemokine (C-C motif) ligand3(CCL3) and FN1), as candidate biomarkers for blood-based detection of AAD. The qRT-PCR assay demonstrated that ANGPT2and CCL3increased2.4-fold (P<0.01) and3.6-fold (P=0.02) in the entire patient group, compared with control specimens, respectively. The western-blot analysis indicated that ANGPT2in AAD group increased4.2-fold (P=0.033). In the pilot study, although the plasma concentrations of CCL3were unchanged(P=0.51), ANGPT2levels were significantly1.8-fold higher in AAD patients than in controls(P=0.002). In the validation study, ANGPT2was also significantly elevated in AAD patients as compared with controls (medians4.1ng/mL vs.1.4ng/mL, p=6.9E-9). ROC curve analysis showed that ANGPT2was highly predictive of a diagnosis of acute aortic dissection (area under ROC curve0.81, p<0.0001). Sensitivity and specificity were72%and80%, respectively, at the cutoff value of2.46ng/mL.
Conclusions:Our study indicate that Focal adhesion and Regulation of actin cytoskeleton pathways are probably invoved in pathogenesis of AAD. Moreover, our preliminary study offers the first evidence that ANGPT2is associated with AAD and could be a promising biomarker for early detection of AAD. Future studies with a larger sample size of normal and AAD patient samples should be pursued.
引文
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