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JAK2-Centered Interactome Hotspot Identified by an Integrative Network Algorithm in Acute Stanford Type A Aortic Dissection

机译:综合网络算法确定的以JAK2为中心的相互作用组热点在斯坦福大学急性A型主动脉夹层中的应用

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摘要

The precise mechanisms underlying dissections, especially those without connective tissue diseases or congenital vascular diseases, are incompletely understood. This study attempted to identify both the expression profile of the dissected ascending aorta and the interactome hotspots associated with the disease, using microarray technology and gene regulatory network analysis. There were 2,737 genes differentially expressed between patients with acute Stanford type A aortic dissection and controls. Eight interactome hotspots significantly associated with aortic dissection were identified by an integrative network algorithm. In particular, we identified a JAK2-centered expression module, which was validated in an independent gene expression microarray data set, and which was characterized by over-expressed cytokines and receptors in acute aortic dissection cases, indicating that JAK2 may play a key role in the inflammatory process, which potentially contributes to the occurrence of acute aortic dissection. Overall, the analytical strategy used in this study offered the possibility to identify functional relevant network modules and subsequently facilitated the biological interpretation in the complicated disease.
机译:解剖的确切机制,尤其是那些没有结缔组织疾病或先天性血管疾病的解剖,尚未得到完全了解。这项研究试图使用微阵列技术和基因调控网络分析来鉴定解剖的升主动脉的表达谱和与该疾病相关的相互作用组热点。急性斯坦福A型主动脉夹层患者与对照组之间存在2737个基因差异表达。通过集成网络算法确定了八个与主动脉夹层显着相关的相互作用组热点。特别是,我们确定了以JAK2为中心的表达模块,该模块已在独立的基因表达微阵列数据集中进行了验证,并且在急性主动脉夹层病例中以过表达的细胞因子和受体为特征,表明JAK2可能在以下方面发挥关键作用炎症过程,可能导致急性主动脉夹层的发生。总体而言,本研究中使用的分析策略为识别功能相关的网络模块提供了可能性,并随后促进了复杂疾病中的生物学解释。

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