中国神经再生研究(英文版)

中国神经再生研究(英文版) ›› 2021, Vol. 16 ›› Issue (5): 865-870.doi: 10.4103/1673-5374.297087

• 原著:周围神经损伤修复保护与再生 • 上一篇    下一篇

通过生物信息学数据鉴定的4中急慢性期脊髓损伤差异表达基因

  

  • 出版日期:2021-05-15 发布日期:2020-12-29
  • 基金资助:

    国家自然科学基金项目（31571236）；北京市科学技术计划项目（D161100002816001）；国家重点研究发展计划项目（2016YFC1101604）；教育部创新计划（IRT_16R01）

Identification of four differentially expressed genes associated with acute and chronic spinal cord injury based on bioinformatics data

Su-Ping Niu1, 4, #, Ya-Jun Zhang1, 3, #, Na Han1, 4, Xiao-Feng Yin1, 2, Dian-Ying Zhang1, 2, *, Yu-Hui Kou1, 2, *    

  1. 1 Key Laboratory of Trauma and Neural Regeneration (Peking University), Ministry of Education, Beijing, China;  2 Department of Trauma and Orthopedics, Peking University People’s Hospital, Beijing, China;  3 Trauma Medicine Center, Peking University People’s Hospital, Beijing, China;  4 Office of Academic Research, Peking University People’s Hospital, Beijing, China
  • Online:2021-05-15 Published:2020-12-29
  • Contact: Dian-Ying Zhang, MM, zdy8016@163.com; Yu-Hui Kou, MD, PhD, yuhuikou@bjmu.edu.cn. #Both authors contributed equally to this work.
  • Supported by:
    This study was supported by the National Natural Science Foundation of China, No. 31571236 (to YHK); Science and Technology Planning Project of Beijing of China, No D161100002816001; the National Key Research and Development Program of China, No. 2016YFC1101604 (to DYZ); the Ministry of Education Innovation Program of China, No. IRT_16R01.

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摘要：

考虑到脊髓损伤发展过程中病理变化的复杂性，了解脊髓损伤的潜在分子事件有助于开发潜在的分子靶点或治疗策略。实验以生物信息学方法探索脊髓损伤急慢性期的差异表达基因，从Gene Expression Omnibus数据库下载的基因表达谱GSE45006，GSE93249和GSE45550，鉴定样品中与大鼠脊髓损伤相关的差异表达基因，然后行基因本体论和《京都议定书全书》基因和通路富集分析，并构建蛋白-蛋白相互作用网络。结果得出，(1)脊髓损伤后3-14d，在GSE45550中鉴定出66种差异表达基因，而在脊髓损伤1-56d，在GSE45006中鉴定出2418种差异表达基因。在脊髓损伤后3，8/7和14d时，2个表达谱分别鉴定出1263，195和75种重叠的差异表达基因。(2)损伤后1-14d在GSE45006获得了16种重叠的差异表达基因，包括Pank1，Hn1，Tmem150c，Rgd1309676，Lpl，Mdh1，Nnt，Loc100912219，Large1，Baiap2，Slc24a2，Fundc2，Mrps14，Slc16a7，Obfc1和Alpk3。(3)损伤后1-6个月在GSE93249中得出3882种重叠的差异表达基因，其中包含3316种蛋白编码基因和567种长非编码RNA。(4)对GSE93249和GSE45006富集的1135种重叠的差异表达基因进行比较，发现这些基因主要与对免疫效应过程反应、先天免疫反应、细胞因子产生等有关。(5)重叠的差异表达基因经GO和KEGG分析显示，他们与免疫系统相关通路、破骨细胞分化、NF-κB信号通路和趋化因子信号通路有关。(6)分析GSE93249和GSE45006中急慢性脊髓损伤的重叠差异表达基因，可筛选出四种重叠差异表达基因Slc16a7，Alpk3，Lpl和Nnt。结果有助于揭示脊髓损伤病理生物学过程和制定靶向性干预策略。

https://orcid.org/0000-0002-2576-0028 (Dian-Ying Zhang); 

https://orcid.org/0000-0003-1523-825X (Yu-Hui Kou)

关键词: 脊髓, 损伤, 基因, 差异表达, 蛋白, 因子, 通路, 免疫反应, 生物信息学

Abstract: Complex pathological changes occur during the development of spinal cord injury (SCI), and determining the underlying molecular events that occur during SCI is necessary for the development of promising molecular targets and therapeutic strategies. This study was designed to explore differentially expressed genes (DEGs) associated with the acute and chronic stages of SCI using bioinformatics analysis. Gene expression profiles (GSE45006, GSE93249, and GSE45550) were downloaded from the Gene Expression Omnibus database. SCI-associated DEGs from rat samples were identified, and Gene Ontology and the Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses were performed. In addition, a protein-protein interaction network was constructed. Approximately 66 DEGs were identified in GSE45550 between 3–14 days after SCI, whereas 2418 DEGs were identified in GSE45006 1–56 days after SCI. Moreover, 1263, 195, and 75 overlapping DEGs were identified between these two expression profiles, 3, 7/8, and 14 days after SCI, respectively. Additionally, 16 overlapping DEGs were obtained in GSE45006 1–14 days after SCI, including Pank1, Hn1, Tmem150c, Rgd1309676, Lpl, Mdh1, Nnt, Loc100912219, Large1,  Baiap2, Slc24a2, Fundc2, Mrps14, Slc16a7, Obfc1, and Alpk3. Importantly, 3882 overlapping DEGs were identified in GSE93249 1–6 months after SCI, including 3316 protein-coding genes and 567 long non-coding RNA genes. A comparative analysis between GSE93249 and GSE45006 resulted in the enrichment of 1135 overlapping DEGs. The significant functions of these 1135 genes were correlated with the response to the immune effector process, the innate immune response, and cytokine production. Moreover, the biological processes and KEGG pathways of the overlapping DEGs were significantly enriched in immune system-related pathways, osteoclast differentiation, the nuclear factor-κB signaling pathway, and the chemokine signaling pathway. Finally, an analysis of the overlapping DEGs associated with both acute and chronic SCI, assessed using the expression profiles GSE93249 and GSE45006, identified four overlapping DEGs: Slc16a7, Alpk3, Lpl and Nnt. These findings may be useful for revealing the biological processes associated with SCI and the development of targeted intervention strategies. 

Key words: bioinformatics, differential expression, factor, gene, immune response, injury, pathways, protein, spinal cord