Weighted Gene Co-expression Network Analysis Identifies Crucial Genes Mediating Progression of Carotid Plaque.
Weighted Gene Co-expression Network Analysis Identifies Crucial Genes Mediating Progression of Carotid Plaque.
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DOI：
10.3389/fphys.2021.601952
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发表时间：
2021
影响因子：
4
通讯作者：
Zheng Y
中科院分区：
文献类型：
--
作者：
Chen M;Chen S;Yang D;Zhou J;Liu B;Chen Y;Ye W;Zhang H;Ji L;Zheng Y
颈动脉斑块表面破裂可引起严重的脑血管疾病，包括短暂性脑缺血发作和中风。本研究的目的是阐明控制颈动脉斑块进展的分子机制，并为颈动脉粥样硬化提供候选治疗靶点。我们的分析中使用了微阵列数据集 GSE28829 和 RNA-seq 数据集 GSE104140，其中包含晚期斑块和早期斑块样本。使用“limma”R 包筛选差异表达基因 (DEG)。根据加权基因共表达网络分析（WGCNA）构建的共表达网络，鉴定了早期和晚期斑块的基因模块。每个模块都采用了基因本体论（GO）和京都基因基因组百科全书（KEGG）分析。此外，还鉴定了每个模块的中心基因。通过基于 DEG 共表达网络的分子复合物检测 (MCODE) 来鉴定关键基因，并通过 GSE43292 数据集进行验证。对关键基因进行基因集富集分析（GSEA）。进行敏感性分析来评估我们构建的网络的稳健性。共筛选出436个DEG，其中上调335个，下调81个。确定与炎症和免疫反应相关的通路集中在高级斑块的黑色模块中。黑色模块的中心基因是 ARHGAP18（Rho GTPase 激活蛋白 18）。 NCF2（中性粒细胞胞质因子2）、IQGAP2（含有GTPase激活蛋白2的IQ基序）和CD86（CD86分子）在关键基因中具有最高的连接性。所有关键基因均已成功验证，敏感性分析表明我们的结果是可靠的。据我们所知，该研究首次将DEGs和WGCNA结合起来，在颈动脉斑块中建立DEG共表达网络，并提出了颈动脉粥样硬化的潜在治疗靶点。
Surface rupture of carotid plaque can cause severe cerebrovascular disease, including transient ischemic attack and stroke. The aim of this study was to elucidate the molecular mechanism governing carotid plaque progression and to provide candidate treatment targets for carotid atherosclerosis. The microarray dataset GSE28829 and the RNA-seq dataset GSE104140, which contain advanced plaque and early plaque samples, were utilized in our analysis. Differentially expressed genes (DEGs) were screened using the “limma” R package. Gene modules for both early and advanced plaques were identified based on co-expression networks constructed by weighted gene co-expression network analysis (WGCNA). Gene Ontology (GO) and Kyoto Encyclopedia of Genes Genomes (KEGG) analyses were employed in each module. In addition, hub genes for each module were identified. Crucial genes were identified by molecular complex detection (MCODE) based on the DEG co-expression network and were validated by the GSE43292 dataset. Gene set enrichment analysis (GSEA) for crucial genes was performed. Sensitivity analysis was performed to evaluate the robustness of the networks that we constructed. A total of 436 DEGs were screened, of which 335 were up-regulated and 81 were down-regulated. The pathways related to inflammation and immune response were determined to be concentrated in the black module of the advanced plaques. The hub gene of the black module was ARHGAP18 (Rho GTPase activating protein 18). NCF2 (neutrophil cytosolic factor 2), IQGAP2 (IQ motif containing GTPase activating protein 2) and CD86 (CD86 molecule) had the highest connectivity among the crucial genes. All crucial genes were validated successfully, and sensitivity analysis demonstrated that our results were reliable. To the best of our knowledge, this study is the first to combine DEGs and WGCNA to establish a DEG co-expression network in carotid plaques, and it proposes potential therapeutic targets for carotid atherosclerosis.
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NADPH 氧化酶相关基因与血压变化和高血压事件的关联：GenSalt 研究
影响因子：
2.7
作者：
Li H;Han X;Hu Z;Huang J;Chen J;Hixson JE;Rao DC;He J;Gu D;Chen S
通讯作者：
Chen S
影响因子：
3.7
作者：
Ghaleb AM;Bialkowska AB;Snider AJ;Gnatenko DV;Hannun YA;Yang VW;Schmidt VA
通讯作者：
Schmidt VA
DOI：
10.1253/circj.cj-16-0924
发表时间：
2016-10-25
期刊：
Circulation journal : official journal of the Japanese Circulation Society
影响因子：
--
作者：
Linton MF;Babaev VR;Huang J;Linton EF;Tao H;Yancey PG
通讯作者：
Yancey PG
影响因子：
30.8
作者：
Nelson, Christopher P.;Goel, Anuj;Deloukas, Panos
通讯作者：
Deloukas, Panos
影响因子：
3.5
作者：
Ewing, M. M.;Karper, J. C.;Quax, P. H. A.
通讯作者：
Quax, P. H. A.