Bioinformatics and systems biology approach to identify the pathogenetic link of neurological pain and major depressive disorder

被引:0
|
作者
Hu, Jinjing [1 ,2 ]
Fu, Jia [3 ]
Cai, Yuxin [1 ,2 ]
Chen, Shuping [1 ,2 ]
Qu, Mengjian [4 ,5 ]
Zhang, Lisha [6 ,7 ]
Fan, Weichao [1 ]
Wang, Ziyi [8 ]
Zeng, Qing [1 ,2 ]
Zou, Jihua [1 ,2 ,6 ]
机构
[1] Southern Med Univ, Zhujiang Hosp, Dept Rehabil Med, Guangzhou, Peoples R China
[2] Southern Med Univ, Sch Rehabil Med, Guangzhou, Peoples R China
[3] Hong Kong Polytech Univ, Dept Rehabil Sci, Kowloon, Hong Kong, Peoples R China
[4] Univ South China, Affiliated Hosp 1, Hengyang Med Sch, Dept Rehabil, Hengyang, Peoples R China
[5] Univ South China, Affiliated Hosp 1, Hengyang Med Sch, Rehabil Lab, Hengyang, Peoples R China
[6] Hong Kong Polytech Univ, Fac Hlth & Social Sci, Kowloon, Hong Kong, Peoples R China
[7] Suzhou Vocat Hlth Coll, Dept Clin Med, Suzhou, Peoples R China
[8] Southern Med Univ, Sch Clin Med 1, Guangzhou, Peoples R China
关键词
neurological pain; gene expression omnibus (GEO); major depressive disorder (MDD); bioinformatics; receiver operating characteristic (ROC); HEPATOCYTE GROWTH-FACTOR; NEUROPATHIC PAIN; GENE-EXPRESSION; CELLS; METALLOPROTEINASE-9; LANDSCAPE; DISEASES; DATABASE; BURDEN; INNATE;
D O I
10.3389/ebm.2024.10129
中图分类号
R-3 [医学研究方法]; R3 [基础医学];
学科分类号
1001 ;
摘要
Neurological pain (NP) is always accompanied by symptoms of depression, which seriously affects physical and mental health. In this study, we identified the common hub genes (Co-hub genes) and related immune cells of NP and major depressive disorder (MDD) to determine whether they have common pathological and molecular mechanisms. NP and MDD expression data was downloaded from the Gene Expression Omnibus (GEO) database. Common differentially expressed genes (Co-DEGs) for NP and MDD were extracted and the hub genes and hub nodes were mined. Co-DEGs, hub genes, and hub nodes were analyzed for Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment. Finally, the hub nodes, and genes were analyzed to obtain Co-hub genes. We plotted Receiver operating characteristic (ROC) curves to evaluate the diagnostic impact of the Co-hub genes on MDD and NP. We also identified the immune-infiltrating cell component by ssGSEA and analyzed the relationship. For the GO and KEGG enrichment analyses, 93 Co-DEGs were associated with biological processes (BP), such as fibrinolysis, cell composition (CC), such as tertiary granules, and pathways, such as complement, and coagulation cascades. A differential gene expression analysis revealed significant differences between the Co-hub genes ANGPT2, MMP9, PLAU, and TIMP2. There was some accuracy in the diagnosis of NP based on the expression of ANGPT2 and MMP9. Analysis of differences in the immune cell components indicated an abundance of activated dendritic cells, effector memory CD8+ T cells, memory B cells, and regulatory T cells in both groups, which were statistically significant. In summary, we identified 6 Co-hub genes and 4 immune cell types related to NP and MDD. Further studies are needed to determine the role of these genes and immune cells as potential diagnostic markers or therapeutic targets in NP and MDD.
引用
收藏
页数:25
相关论文
共 50 条
  • [31] Quality of life in major depressive disorder: the role of pain and pain catastrophizing cognition
    Chung, Ka-Fai
    Tso, Kwok-Chu
    Yeung, Wing-Fai
    Li, Wei-Hui
    COMPREHENSIVE PSYCHIATRY, 2012, 53 (04) : 387 - 395
  • [32] Pain Inhibition Is Deficient in Chronic Widespread Pain but Normal in Major Depressive Disorder
    Normand, Edith
    Potvin, Stephane
    Gaumond, Isabelle
    Cloutier, Guylaine
    Corbin, Jean-Francois
    Marchand, Serge
    JOURNAL OF CLINICAL PSYCHIATRY, 2011, 72 (02) : 219 - 224
  • [33] Adapting the Goal Attainment Approach for Major Depressive Disorder
    Maggie McCue
    Sagar V. Parikh
    Lisa Mucha
    Sara Sarkey
    Charlie Cao
    Anna Eramo
    Mark Opler
    Briana Webber-Lind
    Clément François
    Neurology and Therapy, 2019, 8 : 167 - 176
  • [34] Adapting the Goal Attainment Approach for Major Depressive Disorder
    McCue, Maggie
    Parikh, Sagar V.
    Mucha, Lisa
    Sarkey, Sara
    Cao, Charlie
    Eramo, Anna
    Opler, Mark
    Webber-Lind, Briana
    Francois, Clement
    NEUROLOGY AND THERAPY, 2019, 8 (02) : 167 - 176
  • [35] Dysregulation of brain dopamine systems in major depressive disorder
    Delva, Nella C.
    Stanwood, Gregg D.
    EXPERIMENTAL BIOLOGY AND MEDICINE, 2021, 246 (09) : 1084 - 1093
  • [36] Bioinformatics and systems biology approaches to identify potential common pathogeneses for sarcopenia and osteoarthritis
    Yang, Jinghong
    Zhong, Jun
    Du, Yimin
    Wang, Zi
    Jiang, Lujun
    Li, Zhong
    Liu, Yanshi
    FRONTIERS IN MEDICINE, 2024, 11
  • [37] Changes in pain during a depressive episode and relationship to cytokine levels in major depressive disorder
    Dahl, Johan
    Ormstad, Heidi
    Aass, Hans Christian D.
    Malt, Ulrik Fredrik
    Andreassen, Ole A.
    NORDIC JOURNAL OF PSYCHIATRY, 2024, : 181 - 188
  • [38] Understanding ayahuasca effects in major depressive disorder treatment through invitro metabolomics and bioinformatics
    Zandonadi, Flavia S.
    Silva, Alex Ap. Rosini
    Melo, Aline A. S.
    Ignarro, Raffaela S.
    Matos, Taynara S.
    Santos, Emerson A. F.
    Barbosa, Luidy D.
    Oliveira, Alexandre L. R.
    Porcari, Andreia M.
    Sussulini, Alessandra
    ANALYTICAL AND BIOANALYTICAL CHEMISTRY, 2023, 415 (18) : 4367 - 4384
  • [39] Identification of Potential Biomarkers for Major Depressive Disorder: Based on Integrated Bioinformatics and Clinical Validation
    Zhong, Xiaogang
    Chen, Yue
    Chen, Weiyi
    Liu, Yiyun
    Gui, Siwen
    Pu, Juncai
    Wang, Dongfang
    He, Yong
    Chen, Xiang
    Chen, Xiaopeng
    Qiao, Renjie
    Xie, Peng
    MOLECULAR NEUROBIOLOGY, 2024, 61 (12) : 10355 - 10364
  • [40] Understanding ayahuasca effects in major depressive disorder treatment through invitro metabolomics and bioinformatics
    Flávia S. Zandonadi
    Alex Ap. Rosini Silva
    Aline A. S. Melo
    Raffaela S. Ignarro
    Taynara S. Matos
    Emerson A. F. Santos
    Luidy D. Barbosa
    Alexandre L. R. Oliveira
    Andréia M. Porcari
    Alessandra Sussulini
    Analytical and Bioanalytical Chemistry, 2023, 415 : 4367 - 4384