Identification of key genes and pathways associated with sex differences in rheumatoid arthritis based on bioinformatics analysis

被引:5
|
作者
Wang, Tingting [1 ]
Zeng, Fanxin [2 ]
Li, Xue [2 ]
Wei, Yuanli [1 ]
Wang, Dongmei [1 ]
Zhang, Weihua [1 ]
Xie, Huanhuan [1 ]
Wei, Lingli [1 ]
Xiong, Siying [1 ]
Liu, Caizhen [1 ]
Li, Shilin [2 ]
Wu, Jianhong [1 ]
机构
[1] Dazhou Cent Hosp, Dept Rheumatol, Dazhou 635000, Sichuan, Peoples R China
[2] Dazhou Cent Hosp, Dept Clin Res Ctr, Dazhou 635000, Sichuan, Peoples R China
关键词
Differentially expressed gene (DEG); MAPK pathway and autophagy; Rheumatoid arthritis (RA); Sex differences; STRESS;
D O I
10.1007/s10067-022-06387-6
中图分类号
R5 [内科学];
学科分类号
1002 ; 100201 ;
摘要
Introduction Women are more likely than men to develop the chronic, progressive autoimmune disease known as rheumatoid arthritis (RA). Although there may be a complex interplay between sex-based differences and autoimmune dysfunction. Their function in RA is largely unknown, though. The purpose of this study was to pinpoint the crucial genes and metabolic pathways that control biological variations in RA between men and women. Methods First, the Gene Expression Omnibus database's gene expression information for GSE39340 and GSE55457 was downloaded (GEO). R software was used to find each of the individually identified differentially expressed genes (DEGs) between the sexes. DEGs that overlapped were found. The interactions between the overlapping DEGs were then further examined using a protein-protein interaction (PPI) network. The Kyoto Encyclopedia of Genes and Genomes and Gene Ontology tools, respectively, were used to perform enrichment analyses. Results According to our findings, there were 1169 DEGs that overlapped between RA males and females, comprising 845 up-regulated genes and 324 down-regulated genes. Ten hub genes, including PIK3R1, RAC1, HRAS, PTPN11, UQCRB, NDUFV1, EGF, UBA1, UBE2G1, and UBE2E1, were discovered in the PPI network. According to a functional enrichment analysis, these genes were primarily enriched in neurodegenerative illnesses, including various disease pathways, MAPK signaling, insulin signaling, and autophagy. Conclusion The current data point to the possibility that the MAPK pathway and autophagy may be significant contributors to sex differences in RA. PTPN11, EGF, and UBA1 may be important genes linked to the gender development of RA and are anticipated to be therapeutic targets for the disease.
引用
收藏
页码:399 / 406
页数:8
相关论文
共 50 条
  • [1] Identification of key genes and pathways associated with sex differences in rheumatoid arthritis based on bioinformatics analysis
    Tingting Wang
    Fanxin Zeng
    Xue Li
    Yuanli Wei
    Dongmei Wang
    Weihua Zhang
    Huanhuan Xie
    Lingli Wei
    Siying Xiong
    Caizhen Liu
    Shilin Li
    Jianhong Wu
    Clinical Rheumatology, 2023, 42 : 399 - 406
  • [2] Identification of Key Genes and Pathways Associated with Sex Differences in Osteoarthritis Based on Bioinformatics Analysis
    Wang, Shiying
    Wang, Huanmei
    Liu, Wei
    Wei, Biaofang
    BIOMED RESEARCH INTERNATIONAL, 2019, 2019
  • [3] Identification of key genes and pathways associated with sex difference in osteoarthritis based on bioinformatics analysis
    Xu, Junchang
    Yan, Zijian
    Wu, Guihua
    Zheng, Yongling
    Liao, Xiaolong
    Zou, Feng
    JOURNAL OF MUSCULOSKELETAL & NEURONAL INTERACTIONS, 2022, 22 (03) : 393 - 400
  • [4] Identification of key genes in rheumatoid arthritis and osteoarthritis based on bioinformatics analysis
    Zhu, Naiqiang
    Hou, Jingyi
    Wu, Yuanhao
    Li, Geng
    Liu, Jinxin
    Ma, GuiYun
    Chen, Bin
    Song, Youxin
    MEDICINE, 2018, 97 (22)
  • [5] Identification of key genes associated with rheumatoid arthritis with bioinformatics approach
    Gang, Xiaokun
    Sun, Yan
    Li, Fei
    Yu, Tong
    Jiang, Zhende
    Zhu, Xiujie
    Jiang, Qiyao
    Wang, Yao
    MEDICINE, 2017, 96 (31)
  • [6] Identification of key genes and pathways in Rheumatoid Arthritis gene expression profile by bioinformatics
    W, Lu
    G, Li
    ACTA REUMATOLOGICA PORTUGUESA, 2018, 43 (02): : 109 - 131
  • [7] Identification of dysregulated genes in rheumatoid arthritis based on bioinformatics analysis
    Hao, Ruihu
    Du, Haiwei
    Guo, Lin
    Tian, Fengde
    An, Ning
    Yang, Tiejun
    Wang, Changcheng
    Wang, Bo
    Zhou, Zihao
    PEERJ, 2017, 5
  • [8] IDENTIFICATION OF HUB GENES AND MOLECULAR PATHWAYS IN PATIENTS WITH RHEUMATOID ARTHRITIS BY BIOINFORMATICS ANALYSIS
    Cheng, L.
    Zhang, S. X.
    Song, S.
    Zheng, C.
    Sun, X.
    Feng, S.
    Kong, T.
    Shi, G.
    Li, X.
    He, P. F.
    Yu, Q.
    ANNALS OF THE RHEUMATIC DISEASES, 2021, 80 : 460 - 460
  • [9] Bioinformatics Analysis and Identification of Genes and Molecular Pathways Involved in Synovial Inflammation in Rheumatoid Arthritis
    Xiong, Yuan
    Mi, Bo-bin
    Liu, Meng-fei
    Xue, Hang
    Wu, Qi-peng
    Liu, Guo-hui
    MEDICAL SCIENCE MONITOR, 2019, 25 : 2246 - 2256
  • [10] The identification of key genes and pathways in glioblastoma by bioinformatics analysis
    Farsi, Zahra
    Allahyari Fard, Najaf
    MOLECULAR & CELLULAR ONCOLOGY, 2023, 10 (01)