Identification of the common differentially expressed genes and pathogenesis between neuropathic pain and aging

被引:9
|
作者
Ye, Qingqing [1 ]
Huang, Zhensheng [1 ]
Lu, Weicheng [1 ]
Yan, Fang [1 ]
Zeng, Weian [1 ]
Xie, Jingdun [1 ]
Zhong, Weiqiang [1 ]
机构
[1] Sun Yat sen Univ Canc Ctr, Dept Anesthesiol, State Key Lab Oncol Southern China, Collaborat Innovat Canc Med, Guangzhou, Peoples R China
基金
中国国家自然科学基金;
关键词
neuropathic pain; aging; co-DEGs; immune infiltration; regulation network; IMMUNE CELLS; ASSOCIATION; MECHANISMS; RECEPTOR; NEURONS; DISEASE; MODELS; CORTEX;
D O I
10.3389/fnins.2022.994575
中图分类号
Q189 [神经科学];
学科分类号
071006 ;
摘要
BackgroundNeuropathic pain is a debilitating disease caused by damage or diseases of the somatosensory nervous system. Previous research has indicated potential associations between neuropathic pain and aging. However, the mechanisms by which they are interconnected remain unclear. In this study, we aim to identify the common differentially expressed genes (co-DEGs) between neuropathic pain and aging through integrated bioinformatics methods and further explore the underlying molecular mechanisms. MethodsThe microarray datasets GSE24982, GSE63442, and GSE63651 were downloaded from Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) and co-DEGs were first identified. Functional enrichment analyses, protein-protein Interaction (PPI) network, module construction and hub genes identification were performed. Immune infiltration analysis was conducted. Targeted transcription factors (TFs), microRNAs (miRNAs) and potential effective drug compounds for hub genes were also predicted. ResultsA total of 563 and 1,250 DEGs of neuropathic pain and aging were screened, respectively. 16 genes were further identified as co-DEGs. The functional analysis emphasizes the vital roles of the humoral immune response and complement and coagulation cascades in these two diseases. Cxcl14, Fblim1, RT1-Da, Serping1, Cfd, and Fcgr2b were identified as hub genes. Activated B cell, mast cell, activated dendritic cell, CD56 bright natural killer cell, effector memory CD8 + T cell, and type 2 T helper cell were significantly up-regulated in the pain and aging condition. Importantly, hub genes were found to correlate with the activated B cell, activated dendritic cell, Gamma delta T cell, central memory CD4 + T cell and mast cell in pain and aging diseases. Finally, Spic, miR-883-5p, and miR-363-5p et al. were predicted as the potential vital regulators for hub genes. Aldesleukin, Valziflocept, MGD-010, Cinryze, and Rhucin were the potential effective drugs in neuropathic pain and aging. ConclusionThis study identified co-DEGs, revealed molecular mechanisms, demonstrated the immune microenvironment, and predicted the possible TFs, miRNAs regulation networks and new drug targets for neuropathic pain and aging, providing novel insights into further research.
引用
收藏
页数:16
相关论文
共 50 条
  • [11] Identification of differentially expressed genes in primary Sjogren's syndrome
    Zhang, Lei
    Xu, Poshi
    Wang, Xiaoyu
    Zhang, Zongshan
    Zhao, Wenxin
    Li, Zhengmin
    Yang, Guangxia
    Liu, Panpan
    JOURNAL OF CELLULAR BIOCHEMISTRY, 2019, 120 (10) : 17368 - 17377
  • [12] Identification of differentially expressed genes, pathways, and immune infiltration in diabetes
    Liang, Ying
    Wei, Shuxiang
    Peng, Xing
    Feng, Qiling
    Li, Lingling
    Liang, Diefei
    Wu, Hongshi
    Zhang, Xiaoyun
    Huang, Chulin
    Lin, Yongqing
    CLINICS, 2024, 79
  • [13] Identification of Differentially Expressed Genes Associated with Papillary Thyroid Carcinoma
    Cui, Hongyuan
    Zhu, Mingwei
    Zhang, Junhua
    Li, Wenqin
    Zou, Lihui
    Wang, Yan
    COMBINATORIAL CHEMISTRY & HIGH THROUGHPUT SCREENING, 2020, 23 (06) : 546 - 553
  • [14] Identification of the Hub Genes Related to Nerve Injury-Induced Neuropathic Pain
    Wang, Kai
    Yi, Duan
    Yu, Zhuoyin
    Zhu, Bin
    Li, Shuiqing
    Liu, Xiaoguang
    FRONTIERS IN NEUROSCIENCE, 2020, 14
  • [15] Differentially expressed genes between systemic sclerosis and rheumatoid arthritis
    Sun, Zhenyu
    Wang, Wenjuan
    Yu, Degang
    Mao, Yuanqing
    HEREDITAS, 2019, 156 (1)
  • [16] Identification of differentially expressed genes in the kidneys of growth hormone transgenic mice
    Coschigano, K. T.
    Wetzel, A. N.
    Obichere, N.
    Sharma, A.
    Lee, S.
    Rasch, R.
    Guigneaux, M. M.
    Flyvbjerg, A.
    Wood, T. G.
    Kopchick, J. J.
    GROWTH HORMONE & IGF RESEARCH, 2010, 20 (05) : 345 - 355
  • [17] Identification of differentially expressed genes in human testis biopsies with defective spermatogenesis
    Kothalawala, Shashika D.
    Guenther, Stefan
    Schuppe, Hans-Christian
    Pilatz, Adrian
    Wagenlehner, Florian
    Kliesch, Sabine
    O'Donnell, Liza
    Fietz, Daniela
    REPRODUCTIVE MEDICINE AND BIOLOGY, 2024, 23 (01)
  • [18] Identification and Functional Analysis of Differentially Expressed Genes Related to Metastatic Osteosarcoma
    Niu, Feng
    Zhao, Song
    Xu, Chang-Yan
    Chen, Lin
    Ye, Long
    Bi, Gui-Bin
    Tian, Gang
    Gong, Ping
    Nie, Tian-Hong
    ASIAN PACIFIC JOURNAL OF CANCER PREVENTION, 2014, 15 (24) : 10797 - 10801
  • [19] Identification of Differentially Expressed Genes between Original Breast Cancer and Xenograft Using Machine Learning Algorithms
    Wang, Deling
    Li, Jia-Rui
    Zhang, Yu-Hang
    Chen, Lei
    Huang, Tao
    Cai, Yu-Dong
    GENES, 2018, 9 (03)
  • [20] Sexual Dimorphism and Aging in the Human Hyppocampus: Identification, Validation, and Impact of Differentially Expressed Genes by Factorial Microarray and Network Analysis
    Guebel, Daniel V.
    Torres, Nestor V.
    FRONTIERS IN AGING NEUROSCIENCE, 2016, 8