Purpose. Alzheimer’s disease (AD) is considered to be the most common neurodegenerative disease and also one of the major fatal diseases affecting the elderly, thus bringing a huge burden to society. Therefore, identifying AD-related hub genes is extremely important for developing novel strategies against AD. Materials and Methods. Here, we extracted the gene expression profile GSE63061 from the National Center for Biotechnology Information (NCBI) GEO database. Once the unverified gene chip was removed, we standardized the microarray data after quality control. We utilized the Limma software package to screen the differentially expressed genes (DEGs). We conducted Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses of DEGs. Subsequently, we constructed a protein-protein interaction (PPI) network using the STRING database. Result. We screened 2169 DEGs, comprising 1313 DEGs with upregulation and 856 DEGs with downregulation. Functional enrichment analysis showed that the response of immune, the degranulation of neutrophils, lysosome, and the differentiation of osteoclast were greatly enriched in DEGs with upregulation; peptide biosynthetic process, translation, ribosome, and oxidative phosphorylation were dramatically enriched in DEGs with downregulation. 379 nodes and 1149 PPI edges were demonstrated in the PPI network constructed by upregulated DEGs; 202 nodes and 1963 PPI edges were shown in the PPI network constructed by downregulated DEGs. Four hub genes, including GAPDH, RHOA, RPS29, and RPS27A, were identified to be the newly produced candidates involved in AD pathology. Conclusion. GAPDH, RHOA, RPS29, and RPS27A are expected to be key candidates for AD progression. The results of this study can provide comprehensive insight into understanding AD’s pathogenesis and potential new therapeutic targets.

中文翻译：

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鉴定阿尔茨海默病中的枢纽基因

目的。阿尔茨海默病（Alzheimer's disease，AD）被认为是最常见的神经退行性疾病，也是影响老年人的主要致命疾病之一，给社会带来了巨大的负担。因此，识别与 AD 相关的中枢基因对于开发针对 AD 的新策略极为重要。材料和方法. 在这里，我们从国家生物技术信息中心 (NCBI) GEO 数据库中提取了基因表达谱 GSE63061。一旦移除未经验证的基因芯片，我们在质量控制后标准化微阵列数据。我们利用 Limma 软件包筛选差异表达基因 (DEG)。我们对 DEG 进行了基因本体论 (GO) 和京都基因和基因组百科全书 (KEGG) 分析。随后，我们使用 STRING 数据库构建了蛋白质-蛋白质相互作用 (PPI) 网络。结果. 我们筛选了2169个DEGs，其中上调的1313个DEGs和下调的856个DEGs。功能富集分析表明，免疫反应、中性粒细胞脱粒、溶酶体和破骨细胞分化在DEGs中显着富集，且上调；肽生物合成过程、翻译、核糖体和氧化磷酸化在 DEGs 中显着富集并下调。在上调的DEGs构建的PPI网络中，展示了379个节点和1149条PPI边；在由下调的 DEG 构建的 PPI 网络中显示了 202 个节点和 1963 个 PPI 边缘。四个中心基因，包括 GAPDH、RHOA、RPS29 和 RPS27A，被确定为参与 AD 病理学的新产生的候选基因。结论. GAPDH、RHOA、RPS29 和 RPS27A 有望成为 AD 进展的关键候选者。这项研究的结果可以为了解 AD 的发病机制和潜在的新治疗靶点提供全面的见解。