Department of Neurology, Minhang Branch, Zhongshan Hospital, Fudan University, 170 Xinsong Road, 201199 Shanghai, China.
State Key Laboratory of Genetic Engineering, School of Life Sciences, Fudan University, Shanghai 200438, China.
Comput Math Methods Med. 2021 Jul 15;2021:6329041. doi: 10.1155/2021/6329041. eCollection 2021.
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.
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.
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.
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.
阿尔茨海默病（AD）被认为是最常见的神经退行性疾病之一，也是影响老年人的主要致命疾病之一，因此给社会带来了巨大的负担。因此，鉴定 AD 相关的枢纽基因对于开发针对 AD 的新策略非常重要。
在这里，我们从美国国立生物技术信息中心（NCBI）GEO 数据库中提取了基因表达谱 GSE63061。去除未经证实的基因芯片后，我们对质量控制后的微阵列数据进行了标准化。我们利用 Limma 软件包筛选差异表达基因（DEGs）。我们对 DEGs 进行了基因本体论（GO）和京都基因与基因组百科全书（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。
我们筛选出 2169 个 DEGs，其中包括 1313 个上调的 DEGs 和 856 个下调的 DEGs。功能富集分析表明，上调的 DEGs 中，免疫反应、中性粒细胞脱颗粒、溶酶体和破骨细胞分化显著富集；下调的 DEGs 中，肽生物合成过程、翻译、核糖体和氧化磷酸化显著富集。上调的 DEGs 构建的 PPI 网络中显示出 379 个节点和 1149 个 PPI 边；下调的 DEGs 构建的 PPI 网络中显示出 202 个节点和 1963 个 PPI 边。在由上调的 DEGs 构建的 PPI 网络中，鉴定出 4 个枢纽基因，包括 GAPDH、RHOA、RPS29 和 RPS27A，它们被认为是参与 AD 病理的新候选基因。
GAPDH、RHOA、RPS29 和 RPS27A 有望成为 AD 进展的关键候选基因。本研究的结果可以为深入了解 AD 的发病机制和潜在的新治疗靶点提供全面的认识。
