开发并验证与斯坦福 A 型主动脉夹层免疫渗透相关的有效诊断模型。

IF 3.3 Q2 BIOCHEMISTRY & MOLECULAR BIOLOGY
Xiaoyan Huang, Guoan Zhang, Yangmeng Feng, Xiangrong Zhao, Yaping Li, Fuqiang Liu, Yihan Dong, Jingying Sun, Cuixiang Xu
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引用次数: 0

摘要

背景:斯坦福A型主动脉夹层(TAAD)是一种致命的心血管疾病,发病率和死亡率都很高。该病症病理生理学的一个重要步骤是免疫细胞涌入主动脉中层,导致中层变性。这项工作的目的是研究免疫细胞浸润在 TAAD 中的潜在致病意义,并检测相关的生物标志物:美国国家生物技术信息中心(NCBI)基因表达总库(GEO)数据库提供了RNA测序芯片数据(GSE153434、GPL20795、GSE52093)。使用 ImmuCellAI 预测免疫细胞浸润丰度。使用 GEO2R 挑选差异表达基因(DEG),然后对其进行基因本体(GO)和京都基因组百科全书(KEGG)通路分析。此外,还利用功能和通路富集、最小绝对收缩和选择算子(LASSO)、加权基因共表达网络分析(WGCNA)和差异表达分析找到了与免疫浸润相关的枢纽基因。最后,在微阵列数据集 GSE52093 中使用接收者操作特征曲线(ROC)对中心基因进行了验证和评估。利用动物模型和临床数据证实了中心基因的表达及其与 TAAD 免疫浸润的联系:结果:我们发现了巨噬细胞、T辅助细胞17(Th17)、iTreg细胞、B细胞、自然杀伤细胞与TAAD之间最重要的联系。并筛选出七个与免疫细胞浸润相关的中枢基因:ABCG2、FAM20C、ELL2、MTHFD2、ANKRD6、GLRX 和 CDCP1。该诊断模型在 TAAD 诊断中的 ROC 下面积(AUC)为 0.996,灵敏度为 99.21%,特异度为 98.67%,在验证数据集中显示出惊人的 TAAD 诊断能力。临床样本和动物模型中四个枢纽DEGs(ABCG2、FAM20C、MTHFD2、CDCP1)的表达模式与生物信息学分析相吻合,ABCG2、FAM20C、MTHFD2的上调和CDCP1的下调也与心血管功能不良有关:本研究建立并验证了与TAAD免疫浸润相关的有效诊断模型,为研究TAAD的潜在发病机制和发现新的药物干预靶点提供了新方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Developing and Verifying an Effective Diagnostic Model Linked to Immune Infiltration in Stanford Type A Aortic Dissection.

Background: The deadly cardiovascular condition known as Stanford type A aortic dissection (TAAD) carries a high risk of morbidity and mortality. One important step in the pathophysiology of the condition is the influx of immune cells into the aorta media, which causes medial degeneration. The purpose of this work was to investigate the potential pathogenic significance of immune cell infiltration in TAAD and to test for associated biomarkers.

Methods: The National Center for Biotechnology Information (NCBI) Gene Expression Omnibus (GEO) database provided the RNA sequencing microarray data (GSE153434, GPL20795, GSE52093). Immune cell infiltration abundance was predicted using ImmuCellAI. GEO2R was used to select differentially expressed genes (DEGs), which were then processed for Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses. Additionally, hub genes linked to immune infiltration were found using functional and pathway enrichment, least absolute shrinkage and selection operator (LASSO), weighted gene co-expression network analysis (WGCNA), and differential expression analysis. Lastly, hub genes were validated and assessed using receiver operating characteristic (ROC) curves in the microarray dataset GSE52093. The hub gene expression and its connection to immune infiltration in TAAD were confirmed using both animal models and clinic data.

Results: We identified the most important connections between macrophages, T helper cell 17 (Th17), iTreg cells, B cells, natural killer cells and TAAD. And screened seven hub genes associated with immune cell infiltration: ABCG2, FAM20C, ELL2, MTHFD2, ANKRD6, GLRX, and CDCP1. The diagnostic model in TAAD diagnosis with the area under ROC (AUC) was 0.996, and the sensitivity was 99.21%, the specificity was 98.67%, which demonstrated a surprisingly strong diagnostic power of TAAD in the validation datasets. The expression pattern of four hub DEGs (ABCG2, FAM20C, MTHFD2, CDCP1) in clinic samples and animal models matched bioinformatics analysis, and ABCG2, FAM20C, MTHFD2 up-regulation, and the of CDCP1 down-regulation were also linked to poor cardiovascular function.

Conclusions: This study developed and verified an effective diagnostic model linked to immune infiltration in TAAD, providing new approaches to studying the potential pathogenesis of TAAD and discovering new medication intervention targets.

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