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外周血中与阿尔茨海默病前驱期和进展相关的 mRNA 的差异表达。

Differential Expression of mRNAs in Peripheral Blood Related to Prodrome and Progression of Alzheimer's Disease.

机构信息

Department of Neurology, The First Affiliated Hospital of China Medical University, Shenyang, Liaoning 110001, China.

出版信息

Biomed Res Int. 2020 Oct 31;2020:4505720. doi: 10.1155/2020/4505720. eCollection 2020.

Abstract

Alzheimer's disease (AD) is a chronic progressive neurodegenerative disease that affects the quality of life of elderly individuals, while the pathogenesis of AD is still unclear. Based on the bioinformatics analysis of differentially expressed genes (DEGs) in peripheral blood samples, we investigated genes related to mild cognitive impairment (MCI), AD, and late-stage AD that might be used for predicting the conversions. . We obtained the DEGs in MCI, AD, and advanced AD patients from the Gene Expression Omnibus (GEO) database. A Venn diagram was used to identify the intersecting genes. Gene Ontology (GO) and Kyoto Gene and Genomic Encyclopedia (KEGG) were used to analyze the functions and pathways of the intersecting genes. Protein-protein interaction (PPI) networks were constructed to visualize the network of the proteins coded by the related genes. Hub genes were selected based on the PPI network. . Bioinformatics analysis indicated that there were 61 DEGs in both the MCI and AD groups and 27 the same DEGs among the three groups. Using GO and KEGG analyses, we found that these genes were related to the function of mitochondria and ribosome. Hub genes were determined by bioinformatics software based on the PPI network. . Mitochondrial and ribosomal dysfunction in peripheral blood may be early signs in AD patients and related to the disease progression. The identified hub genes may provide the possibility for predicting AD progression or be the possible targets for treatments.

摘要

阿尔茨海默病(AD)是一种慢性进行性神经退行性疾病,影响老年人的生活质量,而 AD 的发病机制尚不清楚。基于外周血样本差异表达基因(DEGs)的生物信息学分析,我们研究了与轻度认知障碍(MCI)、AD 和晚期 AD 相关的基因,这些基因可能用于预测转化。我们从基因表达综合数据库(GEO)中获得了 MCI、AD 和晚期 AD 患者的 DEGs。使用 Venn 图识别交集基因。使用基因本体论(GO)和京都基因与基因组百科全书(KEGG)分析交集基因的功能和途径。构建蛋白质-蛋白质相互作用(PPI)网络以可视化相关基因编码的蛋白质网络。根据 PPI 网络选择枢纽基因。生物信息学分析表明,MCI 和 AD 组中有 61 个 DEG,三组中有 27 个相同的 DEG。通过 GO 和 KEGG 分析,我们发现这些基因与线粒体和核糖体的功能有关。基于 PPI 网络,生物信息学软件确定了枢纽基因。外周血中线粒体和核糖体功能障碍可能是 AD 患者的早期迹象,与疾病进展有关。鉴定的枢纽基因可能为预测 AD 进展提供可能性,也可能成为治疗的潜在靶点。

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