Identification of Candidate Genes Associated With Development of Vascular Cognitive Impairment by Integrated Bioinformatics Analysis Combined With Biological Experiments.

Yajing Cheng, Ying Liu, Rong Wu, Yiyuan Xu, Meiyue Sun, Feng Wang, Xin Geng, Fei Wang
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Abstract

The morbidity and mortality associated with vascular cognitive impairment (VCI) generally increase steeply, and health systems will face increasing demand for services. The present study aims to screen key genes to give new insight into the mechanisms and treatment of VCI based on bioinformatic approaches combined with biological experiments in rats. The gene expression data of VCI patients contained in the GSE122063 data set were downloaded from the Gene Expression Omnibus. We performed a weighted gene co-expression network analysis to identify a hub module and 44 hub genes. Two hundred and seventy-seven differentially expressed genes (DEGs) were analyzed using R software by the "limma" package. STRING database was used to construct protein-protein interaction (PPI) network, after which 36 hub genes were identified through Cytoscape. Functional enrichment analysis revealed that these genes from the yellow module and 277 DEGs were mainly associated with these pathways, such as Staphylococcus aureus infection, complement, and coagulation cascades. These biological functions are related to inflammatory cell activation and inflammatory response. The key genes of VCI were the overlapping hub genes from the yellow module and the PPI network. The expressions of hub genes in rats were determined by quantitative reverse transcription-polymerase chain reaction, Western blot, immunohistochemistry, and immunofluorescence. In conclusion, C1QA, C1QB, C1QC, CD163, and FCGR2A were highly expressed in the hippocampus of VCI rats, and they can serve as candidate biomarkers for the diagnosis and prognosis of VCI. Finally, molecular docking results suggested that 5 genes interact with Bisphenol A. These findings open a new avenue to investigate molecular mechanisms for preventing or treating VCI.

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综合生物信息学分析与生物实验相结合鉴定血管性认知障碍相关候选基因。
与血管性认知障碍(VCI)相关的发病率和死亡率普遍急剧增加,卫生系统将面临越来越多的服务需求。本研究旨在基于生物信息学方法结合大鼠生物学实验,筛选关键基因,为VCI的机制和治疗提供新的思路。从GEO下载GSE122063数据集中VCI患者的基因表达数据。我们进行了加权基因共表达网络分析(WGCNA)来鉴定一个枢纽模块和44个枢纽基因。采用R软件“limma”软件包对277个差异表达基因(deg)进行分析。利用STRING数据库构建蛋白-蛋白相互作用(protein-protein interaction, PPI)网络,通过Cytoscape鉴定出36个枢纽基因。功能富集分析显示,来自黄色模块和277个DEGs的这些基因主要与金黄色葡萄球菌感染、补体和凝血级联等途径相关。这些生物学功能与炎症细胞活化和炎症反应有关。VCI的关键基因是黄色模块和PPI网络中重叠的枢纽基因。采用qRT-PCR、western blot、免疫组化、免疫荧光检测大鼠中枢基因的表达。综上所述,C1QA、C1QB、C1QC、CD163、FCGR2A在VCI大鼠海马中高表达,可作为VCI诊断和预后的候选生物标志物。最后,分子对接结果提示5个基因与双酚a相互作用,这些发现为研究预防或治疗血管性认知障碍的分子机制开辟了新的途径。
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