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Network-Based Integrated Analysis of Transcriptomic Studies in Dissecting Gene Signatures for LPS-Induced Acute Lung Injury
Inflammation ( IF 5.1 ) Pub Date : 2021-08-30 , DOI: 10.1007/s10753-021-01518-8
Fang Cao 1 , Chunyan Wang 2 , Danling Long 3 , Yujuan Deng 4 , Kaimin Mao 5 , Hua Zhong 6
Affiliation  

Acute lung injury (ALI) is a type of serious clinical syndrome leading to morbidity and mortality. However, the precise pathogenesis of ALI remains elusive. Here, we implemented an integrative meta-analysis of six GEO microarray studies with 76 samples in the ALI mouse model. A total of 958 differentially expressed genes (DEGs) were identified in LPS relative to normal samples. Then, a network-based meta-analysis was used to mine core DEGs and to unfold the interactions among these genes. We found that Ebi3 was the top upregulated genes in the LPS-induced ALI. GO, KEGG, and GSEA analyses were performed for functional annotation. qRT-PCR revealed augmented expression of six candidate genes (Stat1, Syk, Jak3, Rac2, Ripk1, and Traf6) in the established ALI mouse model with LPS exposure. Taken together, our study investigated comprehensively hub DEGs and their networks for LPS-stimulated ALI, which might afford an additional approach to determine biomarkers and therapeutic targets and explore the molecular pathophysiology toward ALI.



中文翻译:

基于网络的转录组学研究解析 LPS 诱导的急性肺损伤基因特征的综合分析

急性肺损伤(ALI)是一种导致发病和死亡的严重临床综合征。然而,ALI 的确切发病机制仍不清楚。在这里,我们对 ALI 小鼠模型中的 76 个样本的六项 GEO 微阵列研究进行了综合荟萃分析。相对于正常样本,LPS 中总共鉴定出 958 个差异表达基因 (DEG)。然后,使用基于网络的荟萃分析来挖掘核心DEG并揭示这些基因之间的相互作用。我们发现Ebi3是 LPS 诱导的 ALI 中最上调的基因。进行 GO、KEGG 和 GSEA 分析以进行功能注释。qRT-PCR 显示,在暴露于 LPS 的 ALI 小鼠模型中,六个候选基因(Stat1SykJak3Rac2Ripk1Traf6 )的表达增强。总而言之,我们的研究全面调查了 LPS 刺激的 ALI 的中心 DEG 及其网络,这可能提供一种额外的方法来确定生物标志物和治疗靶点,并探索 ALI 的分子病理生理学。

更新日期:2021-09-01
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