Table4_Identification of Immune-Related Hub Genes in Parkinson’s Disease.DOCX

Background: Parkinson’s disease (PD) is a common, age-related, and progressive neurodegenerative disease. Growing evidence indicates that immune dysfunction plays an essential role in the pathogenic process of PD. The objective of this study was to explore potential immune-related hub genes and immune infiltration patterns of PD.
Method: The microarray expression data of human postmortem substantia nigra samples were downloaded from GSE7621, GSE20141, and GSE49036. Key module genes were screened via weighted gene coexpression network analysis, and immune-related genes were intersected to obtain immune-key genes. Functional enrichment analysis was performed on immune-key genes of PD. In addition to, immune infiltration analysis was applied by a single-sample gene set enrichment analysis algorithm to detect differential immune cell types in the substantia nigra between PD samples and control samples. Least absolute shrinkage and selection operator analysis was performed to further identify immune-related hub genes for PD. Receiver operating characteristic curve analysis of the immune-related hub genes was used to differentiate PD patients from healthy controls. Correlations between immune-related hub genes and differential immune cell types were assessed.
Result: Our findings identified four hub genes (SLC18A2, L1CAM, S100A12, and CXCR4) and seven immune cell types (neutrophils, T follicular helper cells, myeloid-derived suppressor cells, type 1 helper cells, immature B cells, immature dendritic cells, and CD56 bright natural killer cells). The area under the curve (AUC) value of the four-gene-combined model was 0.92. The AUC values of each immune-related hub gene (SLC18A2, L1CAM, S100A12, and CXCR4) were 0.81, 0.78, 0.78, and 0.76, respectively.
Conclusion: In conclusion, SLC18A2, L1CAM, S100A12, and CXCR4 were identified as being associated with the pathogenesis of PD and should be further researched.

背景：帕金森病（Parkinson’s Disease, PD）是一种常见的、与年龄相关的进行性神经退行性疾病。越来越多的研究证据表明，免疫功能异常在帕金森病的致病过程中发挥着关键作用。本研究旨在探讨帕金森病潜在的免疫相关核心基因（hub genes）以及免疫浸润模式。
方法：下载人类死后黑质（substantia nigra）样本的微阵列表达谱数据，数据集来源为GSE7621、GSE20141及GSE49036。通过加权基因共表达网络分析（weighted gene coexpression network analysis）筛选关键模块基因，并与免疫相关基因取交集，得到免疫核心基因。对帕金森病的免疫核心基因开展功能富集分析。此外，采用单样本基因集富集分析（single-sample gene set enrichment analysis）算法进行免疫浸润分析，以检测帕金森病样本与对照样本黑质区域内的差异免疫细胞类型。通过最小绝对收缩和选择算子（least absolute shrinkage and selection operator, LASSO）分析进一步筛选帕金森病的免疫相关核心基因。利用受试者工作特征曲线（receiver operating characteristic curve, ROC）分析免疫相关核心基因的诊断效能，以区分帕金森病患者与健康对照人群。同时评估免疫相关核心基因与差异免疫细胞类型之间的相关性。
结果：本研究共筛选出4个免疫相关核心基因（SLC18A2、L1CAM、S100A12及CXCR4），以及7种差异免疫细胞类型，分别为中性粒细胞、滤泡辅助性T细胞（T follicular helper cells）、髓系来源抑制细胞（myeloid-derived suppressor cells）、1型辅助性T细胞、未成熟B细胞、未成熟树突状细胞及CD56亮型自然杀伤细胞（CD56 bright natural killer cells）。四基因联合模型的曲线下面积（area under the curve, AUC）为0.92。4个免疫相关核心基因单独的AUC值分别为0.81、0.78、0.78及0.76。
结论：综上，本研究证实SLC18A2、L1CAM、S100A12及CXCR4与帕金森病的发病机制密切相关，可作为后续研究的潜在靶点。