Cui Chun-Yan, Liu Xiao, Peng Ming-Hui, Liu Qing, Zhang Ying
Department of Pain, Hospital (T.C.M) Affiliated to Southwest Medical University, Luzhou, 646000, Sichuan, China; Department of Anesthesiology, Hospital (T.C.M) Affiliated to Southwest Medical University, Luzhou, 646000, Sichuan, China.
Department of Pain, Hospital (T.C.M) Affiliated to Southwest Medical University, Luzhou, 646000, Sichuan, China; Department of Anesthesiology, Hospital (T.C.M) Affiliated to Southwest Medical University, Luzhou, 646000, Sichuan, China; Hejiang Traditional Chinese Medicine Hospital, Luzhou, 646000, Sichuan, China.
Comput Biol Med. 2022 Nov;150:106135. doi: 10.1016/j.compbiomed.2022.106135. Epub 2022 Sep 22.
Neuropathic pain is a common chronic pain, characterized by spontaneous pain and mechanical allodynia. The incidence of neuropathic pain is on the rise due to infections, higher rates of diabetes and stroke, and increased use of chemotherapy drugs in cancer patients. At present, due to its pathophysiological process and molecular mechanism remaining unclear, there is a lack of effective treatment and prevention methods in clinical practice. Now, we use bioinformatics technology to integrate and filter hub genes that may be related to the pathogenesis of neuropathic pain, and explore their possible molecular mechanism by functional annotation and pathway enrichment analysis.
The expression profiles of GSE24982, GSE2884, GSE2636 and GSE30691 were downloaded from the Gene Expression Omnibus(GEO)database, and these datasets include 93 neuropathic pain Rattus norvegicus and 59 shame controls. After the four datasets were all standardized by quantiles, the differentially expressed genes (DEGs) between NPP Rattus norvegicus and the shame controls were finally identified by the robust rank aggregation (RRA) analysis method. In order to reveal the possible underlying biological function of DEGs, the Gene Ontology (GO) functional annotation and Kyoto Encyclopedia of Genes and Genomes (KEGG) Pathway enrichment analysis of DEGs were performed. In addition, a Protein-protein Interaction (PPI) network was also established. At the end of our study, a high throughput sequencing dataset GSE117526 was used to corroborate our calculation results.
Through RRA analysis of the above four datasets GSE24982, GSE2884, GSE2636, and GSE30691, we finally obtained 231 DEGs, including 183 up-regulated genes and 47 down-regulated genes. Arranging 231 DEGs in descending order according to |log2 fold change (FC)|, we found that the top 20 key genes include 14 up-regulated genes and 6 down-regulated genes. The most down-regulated hub gene abnormal expressed in NPP was Egf17 (P-value = 0.008), Camk2n2 (P-value = 0.002), and Lep (P-value = 0.02), and the most up-regulated hub gene abnormal expressed in NPP was Nefm (P-value = 1.08E-06), Prx (P-value = 2.68E-07), and Stip1 (P-value = 4.40E-07). In GO functional annotation analysis results, regulation of ion transmembrane transport (GO:0034765; P-value = 1.45E-09) was the most remarkable enriched for biological process, synaptic membrane (GO:0097060; P-value = 2.95E-08) was the most significantly enriched for cellular component, channel activity (GO:0015267; P-value = 2.44E-06) was the most prominent enriched for molecular function. In KEGG pathway enrichment analysis results, the top three notable enrichment pathways were Neuroactive ligand-receptor interaction (rno04080; P-value = 3.46E-08), Calcium signaling pathway (rno04020; P-value = 5.37E-05), and Osteoclast differentiation (rno04380; P-value = 0.000459927). Cav1 and Lep appeared in the top 20 genes in both RRA analysis and PPI analysis, while Nefm appeared in RRA analysis and datasets GSE117526 validation analysis, so we finally identified these three genes as hub genes.
Our research identified the hub genes and signal pathways of neuropathic pain, enriched the pathophysiological mechanism of neuropathic pain to some extent, and provided a possible basis for the targeted therapy of neuropathic pain.
神经性疼痛是一种常见的慢性疼痛,其特征为自发性疼痛和机械性痛觉过敏。由于感染、糖尿病和中风发病率上升以及癌症患者化疗药物使用增加,神经性疼痛的发病率正在上升。目前,由于其病理生理过程和分子机制尚不清楚,临床实践中缺乏有效的治疗和预防方法。现在,我们利用生物信息学技术整合并筛选出可能与神经性疼痛发病机制相关的枢纽基因,并通过功能注释和通路富集分析探索其可能的分子机制。
从基因表达综合数据库(GEO)下载GSE24982、GSE2884、GSE2636和GSE30691的表达谱,这些数据集包括93只神经性疼痛大鼠和59只对照大鼠。对这四个数据集进行分位数标准化后,最终通过稳健秩聚合(RRA)分析方法确定神经性疼痛大鼠与对照大鼠之间的差异表达基因(DEG)。为了揭示DEG可能的潜在生物学功能,对DEG进行了基因本体论(GO)功能注释和京都基因与基因组百科全书(KEGG)通路富集分析。此外,还建立了蛋白质-蛋白质相互作用(PPI)网络。在研究结束时,使用高通量测序数据集GSE117526来证实我们的计算结果。
通过对上述四个数据集GSE24982、GSE2884、GSE2636和GSE30691进行RRA分析,我们最终获得了231个DEG,其中包括183个上调基因和47个下调基因。根据|log2倍数变化(FC)|对231个DEG进行降序排列,我们发现前20个关键基因包括14个上调基因和6个下调基因。在神经性疼痛中异常表达的下调程度最大的枢纽基因是Egf17(P值 = 0.008)、Camk2n2(P值 = 0.002)和Lep(P值 = 0.02),上调程度最大的枢纽基因是Nefm(P值 = 1.08E - 06)、Prx(P值 = 2.68E - 07)和Stip1(P值 = 4.40E - 07)。在GO功能注释分析结果中,离子跨膜运输调控(GO:0034765;P值 = 1.45E - 09)在生物过程中富集最为显著,突触膜(GO:0097060;P值 = 2.95E - 08)在细胞成分中富集最为显著,通道活性(GO:0015267;P值 = 2.44E - 06)在分子功能中富集最为突出。在KEGG通路富集分析结果中,最显著的三个富集通路是神经活性配体 - 受体相互作用(rno04080;P值 = 3.46E - 08)、钙信号通路(rno04020;P值 = 5.37E - 05)和破骨细胞分化(rno04380;P值 = 0.000459927)。Cav1和Lep在RRA分析和PPI分析的前20个基因中均出现,而Nefm出现在RRA分析和数据集GSE117526验证分析中,因此我们最终确定这三个基因是枢纽基因。
我们的研究确定了神经性疼痛的枢纽基因和信号通路,在一定程度上丰富了神经性疼痛的病理生理机制,并为神经性疼痛的靶向治疗提供了可能的依据。