School of Anesthesiology, Xuzhou Medical University, Xuzhou, Jiangsu Province, 221004, P. R. China.
Department of Anesthesiology, Northern Jiangsu People's Hospital Affiliated to Yangzhou University, 98 Nan Tong Western Road, Yangzhou, Jiangsu Province, 225001, P. R. China.
BMC Neurol. 2024 Nov 25;24(1):459. doi: 10.1186/s12883-024-03965-w.
The role of neurons in central post-stroke pain (CPSP) following thalamic hemorrhage remains unclear. This study aimed to identify key genes associated with post-thalamic hemorrhage pain and to explore their functions in neurons. Single-nucleus RNA sequencing (snRNA-seq) data from a mouse model was used for this analysis.
First, snRNA-seq data were analyzed to identify cell types associated with CPSP induced by thalamic hemorrhage. Differentially expressed genes (DEGs) in neurons were then screened between control and model groups, followed by the construction of a protein-protein interaction (PPI) network for the DEGs. CytoNCA was used to assess node connectivity in the PPI network, and the top 5 key genes were identified. Subsequently, transcription factor (TF)-mRNA and miRNA-mRNA networks were constructed, and small-molecule drugs potentially targeting these key genes were predicted. Finally, the expression differences of key genes in neurons were compared between the model and control groups.
A total of 13 cell clusters were identified, categorized into 8 cell types: T cells, endothelial cells, monocytes, neural progenitor cells (NPCs), microglia, astrocytes, neurons, and oligodendrocytes. A total of 228 DEGs were detected in neurons when comparing the model group with the control group. The PPI network of the DEGs consisted of 126 nodes and 209 edges, identifying the top 5 key genes: Dlgap1, Cacna1c, Gria2, Hsp90ab1, and Gapdh. The miRNA-mRNA network included 68 miRNA-mRNA pairs, 62 miRNAs, and 5 mRNAs, while the TF-mRNA network consisted of 66 TF-mRNA pairs, 56 TFs, and 5 mRNAs. Drug prediction identified 110 small-molecule drugs (e.g., purpurogallin, nifedipine, and novobiocin) potentially targeting these key genes. Additionally, Cacna1c were significantly upregulated in model mice.
This study identified the role of key genes in thalamic hemorrhage-induced CPSP through snRNA-seq, providing a scientific basis for further exploration of the molecular mechanisms underlying CPSP.
神经元在丘脑出血后中枢性卒中后疼痛(CPSP)中的作用尚不清楚。本研究旨在鉴定与丘脑出血后疼痛相关的关键基因,并探讨其在神经元中的功能。该分析使用了来自小鼠模型的单细胞核 RNA 测序(snRNA-seq)数据。
首先,对 snRNA-seq 数据进行分析,以鉴定与丘脑出血引起的 CPSP 相关的细胞类型。然后筛选对照组和模型组神经元中的差异表达基因(DEGs),构建 DEGs 的蛋白质-蛋白质相互作用(PPI)网络。使用 CytoNCA 评估 PPI 网络中的节点连接性,并确定前 5 个关键基因。随后,构建转录因子(TF)-mRNA 和 miRNA-mRNA 网络,并预测潜在针对这些关键基因的小分子药物。最后,比较模型组和对照组神经元中关键基因的表达差异。
共鉴定出 13 个细胞簇,分为 8 种细胞类型:T 细胞、内皮细胞、单核细胞、神经祖细胞(NPCs)、小胶质细胞、星形胶质细胞、神经元和少突胶质细胞。比较模型组和对照组时,神经元中检测到 228 个 DEG。DEGs 的 PPI 网络由 126 个节点和 209 条边组成,确定了前 5 个关键基因:Dlgap1、Cacna1c、Gria2、Hsp90ab1 和 Gapdh。miRNA-mRNA 网络包括 68 个 miRNA-mRNA 对、62 个 miRNA 和 5 个 mRNA,TF-mRNA 网络由 66 个 TF-mRNA 对、56 个 TF 和 5 个 mRNA 组成。药物预测确定了 110 种可能针对这些关键基因的小分子药物(如紫铆因、硝苯地平、新生霉素)。此外,模型小鼠中 Cacna1c 明显上调。
本研究通过 snRNA-seq 鉴定了关键基因在丘脑出血引起的 CPSP 中的作用,为进一步探索 CPSP 的分子机制提供了科学依据。