Liu Chunjiang, Zhou Yufei, Zhao Di, Yu Luchen, Zhou Yue, Xu Miaojun, Tang Liming
Department of General Surgery, Vascular Surgery Division, Shaoxing People's Hospital (Shaoxing Hospital of Zhejiang University), Shaoxing, China.
Department of Cardiology, Shanghai Institute of Cardiovascular Diseases, Zhongshan Hospital and Institutes of Biomedical Sciences, Fudan University, Shanghai, China.
Front Genet. 2022 Aug 11;13:950613. doi: 10.3389/fgene.2022.950613. eCollection 2022.
Aortic dissection (AD) is a life-threatening disease. Chromatin regulators (CRs) are indispensable epigenetic regulators. We aimed to identify differentially expressed chromatin regulators (DECRs) for AD diagnosis. We downloaded the GSE52093 and GSE190635 datasets from the Gene Expression Omnibus database. Following the merging and processing of datasets, bioinformatics analysis was applied to select candidate DECRs for AD diagnosis: CRs exertion; DECR identification using the "Limma" package; analyses of enrichment of function and signaling pathways; construction of protein-protein interaction (PPI) networks; application of machine-learning algorithms; evaluation of receiver operating characteristic (ROC) curves. GSE98770 served as the validation dataset to filter DECRs. Moreover, we collected peripheral-blood samples to further validate expression of DECRs by real-time reverse transcription-quantitative polymerase chain reaction (RT-qPCR). Finally, a nomogram was built for clinical use. A total of 841 CRs were extracted from the merged dataset. Analyses of functional enrichment of 23 DECRs identified using Limma showed that DECRs were enriched mainly in epigenetic-regulation processes. From the PPI network, 17 DECRs were selected as node DECRs. After machine-learning calculations, eight DECRs were chosen from the intersection of 13 DECRs identified using support vector machine recursive feature elimination (SVM-RFE) and the top-10 DECRs selected using random forest. DECR expression between the control group and AD group were considerably different. Moreover, the area under the ROC curve (AUC) of each DECR was >0.75, and four DECRs (tumor protein 53 (TP53), chromobox protein homolog 7 (CBX7), Janus kinase 2 (JAK2) and cyclin-dependent kinase 5 (CDK5)) were selected as candidate biomarkers after validation using the external dataset and clinical samples. Furthermore, a nomogram with robust diagnostic value was established (AUC = 0.960). TP53, CBX7, JAK2, and CDK5 might serve as diagnostic DECRs for AD diagnosis. These DECRs were enriched predominantly in regulating epigenetic processes.
主动脉夹层（AD）是一种危及生命的疾病。染色质调节因子（CRs）是不可或缺的表观遗传调节因子。我们旨在鉴定用于AD诊断的差异表达染色质调节因子（DECRs）。我们从基因表达综合数据库下载了GSE52093和GSE190635数据集。在对数据集进行合并和处理后，应用生物信息学分析来选择用于AD诊断的候选DECRs：CRs发挥作用；使用“Limma”软件包鉴定DECRs；对功能和信号通路的富集进行分析；构建蛋白质-蛋白质相互作用（PPI）网络；应用机器学习算法；评估受试者工作特征（ROC）曲线。GSE98770用作验证数据集以筛选DECRs。此外，我们收集外周血样本，通过实时逆转录定量聚合酶链反应（RT-qPCR）进一步验证DECRs的表达。最后，构建了一个用于临床的列线图。从合并数据集中总共提取了841个CRs。使用Limma鉴定的23个DECRs的功能富集分析表明，DECRs主要富集于表观遗传调控过程。从PPI网络中，选择了17个DECRs作为节点DECRs。经过机器学习计算，从使用支持向量机递归特征消除（SVM-RFE）鉴定的13个DECRs与使用随机森林选择的前10个DECRs的交集中选择了8个DECRs。对照组和AD组之间的DECR表达有显著差异。此外，每个DECR的ROC曲线下面积（AUC）>0.75，在使用外部数据集和临床样本进行验证后，选择了四个DECRs（肿瘤蛋白53（TP53）、染色质盒蛋白同源物7（CBX7）、Janus激酶2（JAK2）和细胞周期蛋白依赖性激酶5（CDK5））作为候选生物标志物。此外，建立了具有强大诊断价值的列线图（AUC = 0.960）。TP53、CBX7、JAK2和CDK5可能作为AD诊断的诊断性DECRs。这些DECRs主要富集于调节表观遗传过程。
