Department of Neurology, Youjiang Medical University for Nationalities, Affiliated Hospital of Youjiang Medical University for Nationalities, Baise, 533000 Guangxi, China.
Department of Cardiology, Youjiang Medical University for Nationalities, Affiliated Hospital of Youjiang Medical University for Nationalities, Baise, 533000 Guangxi, China.
Biomed Res Int. 2021 Mar 13;2021:6616434. doi: 10.1155/2021/6616434. eCollection 2021.
In this study, we aimed to identify critical genes and pathways for multiple brain regions in Parkinson's disease (PD) by weighted gene coexpression network analysis (WGCNA).
From the GEO database, differentially expressed genes (DEGs) were separately identified between the substantia nigra, putamen, prefrontal cortex area, and cingulate gyrus of PD and normal samples with the screening criteria of value < 0.05 and ∣logfold change (FC) | >0.585. Then, a coexpression network was presented by the WGCNA package. Gene modules related to PD were constructed. Then, PD-related DEGs were used for construction of PPI networks. Hub genes were determined by the cytoHubba plug-in. Functional enrichment analysis was then performed.
DEGs were identified for the substantia nigra (17 upregulated and 52 downregulated genes), putamen (317 upregulated and 317 downregulated genes), prefrontal cortex area (39 upregulated and 72 downregulated genes), and cingulate gyrus (116 upregulated and 292 downregulated genes) of PD compared to normal samples. Gene modules were separately built for the four brain regions of PD. PPI networks revealed hub genes for the substantia nigra (SLC6A3, SLC18A2, and TH), putamen (BMP4 and SNAP25), prefrontal cortex area (SNAP25), and cingulate gyrus (CTGF, CDH1, and COL5A1) of PD. These DEGs in multiple brain regions were involved in distinct biological functions and pathways. GSEA showed that these DEGs were all significantly enriched in electron transport chain, proteasome degradation, and synaptic vesicle pathway.
Our findings revealed critical genes and pathways for multiple brain regions in PD, which deepened the understanding of PD-related molecular mechanisms.
本研究通过加权基因共表达网络分析（WGCNA），旨在鉴定帕金森病（PD）多个脑区的关键基因和通路。
从 GEO 数据库中，分别筛选 PD 患者黑质、壳核、前额叶皮质和扣带回脑区与正常样本之间的差异表达基因（DEGs），筛选标准为 P 值<0.05 和∣logfold change（FC）|>0.585。然后，使用 WGCNA 包构建共表达网络。构建与 PD 相关的基因模块。然后，使用 PD 相关的 DEGs 构建 PPI 网络。使用 cytoHubba 插件确定枢纽基因。然后进行功能富集分析。
与正常样本相比，PD 患者黑质（17 个上调和 52 个下调基因）、壳核（317 个上调和 317 个下调基因）、前额叶皮质（39 个上调和 72 个下调基因）和扣带回（116 个上调和 292 个下调基因）存在 DEGs。分别为 PD 的四个脑区构建了基因模块。PPI 网络揭示了 PD 黑质（SLC6A3、SLC18A2 和 TH）、壳核（BMP4 和 SNAP25）、前额叶皮质（SNAP25）和扣带回（CTGF、CDH1 和 COL5A1）的枢纽基因。这些多脑区的 DEGs 参与了不同的生物学功能和通路。GSEA 表明，这些 DEGs 在电子传递链、蛋白酶体降解和突触小泡途径中均显著富集。
我们的研究结果揭示了 PD 多个脑区的关键基因和通路，加深了对 PD 相关分子机制的理解。
