Dong Xiaolin, Li Yanping, Li Qingyun, Li Wenhao, Wu Gang
Department of Neurology, The Affiliated Yan'An Hospital of Kunming Medical University, Kunming, Yunnan, China.
Front Genet. 2023 Jan 17;14:1090382. doi: 10.3389/fgene.2023.1090382. eCollection 2023.
Parkinson's disease (PD) is a common neurodegenerative disease in middle-aged and elderly people, and there is less research on the relationship between immunity and PD. In this study, the protein-protein interaction networks (PPI) data, 2747 human immune-related genes (HIRGs), 2078 PD-related genes (PDRGs), and PD-related datasets (GSE49036 and GSE20292) were downloaded from the Human Protein Reference Database (HPRD), Amigo 2, DisGeNET, and Gene Expression Omnibus (GEO) databases, respectively. An immune- or PD-directed neighbor co-expressed network construction (IOPDNC) was drawn based on the GSE49036 dataset and HPRD database. Furthermore, a PD-directed neighbor co-expressed network was constructed. Modular clustering analysis was performed on the genes of the gene interaction network obtained in the first step to obtain the central core genes using the GraphWeb online website. The modules with the top 5 functional scores and the number of core genes greater than six were selected as PD-related gene modules. The Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses of different module genes were performed. The single sample Gene Set Enrichment Analysis (ssGSEA) algorithm was used to calculate the immune cell infiltration of the PD and the normal samples. The quantitative Reverse Transcription Polymerase Chain Reaction (qRT-PCR) was performed to investigate the expression of module genes. An IOPDNC and PD-directed neighbor co-expressed network (PDNC network) were constructed. Furthermore, a total of 5 immune-PD modules were identified which could distinguish between PD and normal samples, and these module genes were strongly related to PD in protein interaction level or gene expression level. In addition, functional analysis indicated that module genes were involved in various neurodegenerative diseases, such as Alzheimer disease, Huntington disease, Parkinson disease, and Long-term depression. In addition, the genes of the 6 modules were significantly associated with these 4 differential immune cells (aDC cells, eosinophils, neutrophils, and Th2 cells). Finally, the result of qRT-PCR manifested that the expression of 6 module genes was significantly higher in normal samples than in PD samples. In our study, the immune-related genes were found to be strongly related to PD and might play key roles in PD.
帕金森病（PD）是中老年人群中常见的神经退行性疾病，关于免疫与PD之间关系的研究较少。在本研究中，分别从人类蛋白质参考数据库（HPRD）、Amigo 2、DisGeNET和基因表达综合数据库（GEO）下载了蛋白质-蛋白质相互作用网络（PPI）数据、2747个人类免疫相关基因（HIRGs）、2078个PD相关基因（PDRGs）以及PD相关数据集（GSE49036和GSE20292）。基于GSE49036数据集和HPRD数据库绘制了免疫或PD导向的邻居共表达网络构建（IOPDNC）。此外，构建了PD导向的邻居共表达网络。对第一步获得的基因相互作用网络的基因进行模块聚类分析，使用GraphWeb在线网站获得核心基因。选择功能得分排名前5且核心基因数量大于6的模块作为PD相关基因模块。对不同模块基因进行基因本体论（GO）和京都基因与基因组百科全书（KEGG）富集分析。使用单样本基因集富集分析（ssGSEA）算法计算PD样本和正常样本的免疫细胞浸润情况。进行定量逆转录聚合酶链反应（qRT-PCR）以研究模块基因的表达。构建了IOPDNC和PD导向的邻居共表达网络（PDNC网络）。此外，共鉴定出5个免疫-PD模块，这些模块能够区分PD样本和正常样本，并且这些模块基因在蛋白质相互作用水平或基因表达水平上与PD密切相关。此外，功能分析表明模块基因参与了多种神经退行性疾病，如阿尔茨海默病、亨廷顿病、帕金森病和长期抑郁。此外，6个模块的基因与这4种差异免疫细胞（活化树突状细胞、嗜酸性粒细胞、中性粒细胞和Th2细胞）显著相关。最后，qRT-PCR结果表明，6个模块基因在正常样本中的表达明显高于PD样本。在我们的研究中，发现免疫相关基因与PD密切相关，可能在PD中起关键作用。
