Identification of hub biomarkers and immune-related pathways participating in the progression of Kawasaki disease by integrated bioinformatics analysis

被引:3
|
作者
Gao, Yang [1 ,2 ]
Tang, Xuan [1 ,3 ]
Qian, Guanghui [1 ]
Huang, Hongbiao [1 ]
Wang, Nana [1 ]
Wang, Yan [1 ]
Zhuo, Wenyu [1 ]
Jiang, Jiaqi [1 ]
Zheng, Yiming [1 ]
Li, Wenjie [1 ]
Liu, Zhiheng [1 ,4 ]
Li, Xuan [1 ,4 ]
Xu, Lei [1 ]
Zhang, Jiaying [1 ]
Huang, Li [1 ]
Liu, Ying [1 ,5 ]
Lv, Haitao [1 ,4 ,5 ]
机构
[1] Soochow Univ, Childrens Hosp, Inst Pediat Res, Dept Pediat, Suzhou, Jiangsu, Peoples R China
[2] First Peoples Hosp Lianyungang, Dept Pediat, Lianyungang, Jiangsu, Peoples R China
[3] Nantong Univ, Jiangyin Peoples Hosp, Dept Pediat, Wuxi, Jiangsu, Peoples R China
[4] Soochow Univ, Childrens Hosp, Dept Cardiol, Suzhou, Jiangsu, Peoples R China
[5] Soochow Univ, Childrens Hosp, 92 Zhongnan St,Suzhou Ind Pk Suzhou, Suzhou 215025, Jiangsu, Peoples R China
基金
中国国家自然科学基金;
关键词
Biomarkers; Kawasaki disease; LASSO regression model; Weighted gene correlation network analysis; NEUTROPHIL EXTRACELLULAR TRAPS; S100A12; MATRIX-METALLOPROTEINASE-9; PATHOGENESIS; INSIGHTS; GENE; INFLAMMATION; MYD88; TLR2; KEGG;
D O I
10.1016/j.imbio.2023.152750
中图分类号
R392 [医学免疫学]; Q939.91 [免疫学];
学科分类号
100102 ;
摘要
Background: Kawasaki disease (KD) is a systemic vasculitis that commonly affects children and its etiology remains unknown. Growing evidence suggests that immune-mediated inflammation and immune cells in the peripheral blood play crucial roles in the pathophysiology of KD. The objective of this research was to find important biomarkers and immune-related mechanisms implicated in KD, along with their correlation with immune cells in the peripheral blood. Material/Methods: Gene microarray data from the Gene Expression Omnibus (GEO) was utilized in this study. Three datasets, namely GSE63881 (341 samples), GSE73463 (233 samples), and GSE73461 (279 samples), were obtained. To find intersecting genes, we employed differentially expressed genes (DEGs) analysis and weighted gene co-expression network analysis (WGCNA). Subsequently, functional annotation, construction of protein-protein interaction (PPI) networks, and Least Absolute Shrinkage and Selection Operator (LASSO) regression were performed to identify hub genes. The accuracy of these hub genes in identifying KD was evaluated using the receiver operating characteristic curve (ROC). Furthermore, Gene Set Variation Analysis (GSVA) was employed to explore the composition of circulating immune cells within the assessed datasets and their relationship with the hub gene markers. Results: WGCNA yielded eight co-expression modules, with one hub module (MEblue module) exhibiting the strongest association with acute KD. 425 distinct genes were identified. Integrating WGCNA and DEGs yielded a total of 277 intersecting genes. By conducting LASSO analysis, five hub genes (S100A12, MMP9, TLR2, NLRC4 and ARG1) were identified as potential biomarkers for KD. The diagnostic value of these five hub genes was demonstrated through ROC curve analysis, indicating their high accuracy in diagnosing KD. Analysis of the circulating immune cell composition within the assessed datasets revealed a significant association between KD and various immune cell types, including activated dendritic cells, neutrophils, immature dendritic cells, macrophages, and activated CD8 T cells. Importantly, all five hub genes exhibited strong correlations with immune cells. Conclusion: Activated dendritic cells, neutrophils, and macrophages were closely associated with the pathogenesis of KD. Furthermore, the hub genes (S100A12, MMP9, TLR2, NLRC4, and ARG1) are likely to participate in the pathogenic mechanisms of KD through immune-related signaling pathways.
引用
收藏
页数:13
相关论文
共 50 条
  • [1] Bioinformatics analysis reveals the landscape of immune cell infiltration and immune-related pathways participating in the progression of carotid atherosclerotic plaques
    Tan, Liao
    Xu, Qian
    Shi, Ruizheng
    Zhang, Guogang
    ARTIFICIAL CELLS NANOMEDICINE AND BIOTECHNOLOGY, 2021, 49 (01) : 96 - 107
  • [2] Bioinformatics analysis reveals the landscape of immune cell infiltration and novel immune-related biomarkers in moyamoya disease
    Cao, Lei
    Ai, Yunzheng
    Dong, Yang
    Li, Dongpeng
    Wang, Hao
    Sun, Kaiwen
    Wang, Chenchao
    Zhang, Manxia
    Yan, Dongming
    Li, Hongwei
    Liang, Guobiao
    Yang, Bo
    FRONTIERS IN GENETICS, 2023, 14
  • [3] Bioinformatics analysis and identification of hub genes of neutrophils in Kawasaki disease: a pivotal study
    Tang, Yunjia
    Yang, Daoping
    Ma, Jin
    Wang, Nana
    Qian, Weiguo
    Wang, Bo
    Qin, Yiming
    Lu, Meihua
    Lv, Haitao
    CLINICAL RHEUMATOLOGY, 2023, 42 (11) : 3089 - 3096
  • [4] Identification of the immune-related biomarkers in Behcet's disease by plasma proteomic analysis
    Liu, Huan
    Zhang, Panpan
    Li, Fuzhen
    Xiao, Xiao
    Zhang, Yinan
    Li, Na
    Du, Liping
    Yang, Peizeng
    ARTHRITIS RESEARCH & THERAPY, 2023, 25 (01)
  • [5] Identification of hub genes and pathogenesis in Kawasaki disease based on bioinformatics analysis
    Cao, Min
    Zhang, Zhenhu
    Liu, Qian
    Zhang, Yuda
    INDIAN JOURNAL OF PATHOLOGY AND MICROBIOLOGY, 2024, 67 (02) : 297 - 305
  • [6] Identification of novel immune-related biomarker and therapeutic drugs in Parkinson disease via integrated bioinformatics analysis
    Yang, Xiaoxia
    Wang, Zhiyun
    MEDICINE, 2023, 102 (31) : E34456
  • [7] Bioinformatics analysis and identification of hub genes of neutrophils in Kawasaki disease: a pivotal study
    Yunjia Tang
    Daoping Yang
    Jin Ma
    Nana Wang
    Weiguo Qian
    Bo Wang
    Yiming Qin
    Meihua Lu
    Haitao Lv
    Clinical Rheumatology, 2023, 42 : 3089 - 3096
  • [8] Identification of hub proteins in cerebrospinal fluid as potential biomarkers of Alzheimer's disease by integrated bioinformatics
    Li, Yang
    Chen, Zuolong
    Wang, Qiong
    Lv, Xinyi
    Cheng, Zhaozhao
    Wu, Yan
    Tang, Fang
    Shen, Yong
    Gao, Feng
    JOURNAL OF NEUROLOGY, 2023, 270 (03) : 1487 - 1500
  • [9] Bioinformatics-based identification of lipid- and immune-related biomarkers in abdominal aortic aneurysms
    Li, Yuejin
    Li, Rougang
    Guo, Shikui
    Li, Yu
    Wang, Yongzhi
    Wen, Xin
    Lan, Tian
    Gong, Kunmei
    HELIYON, 2023, 9 (02)
  • [10] Identification of Disease-Specific Hub Biomarkers and Immune Infiltration in Osteoarthritis and Rheumatoid Arthritis Synovial Tissues by Bioinformatics Analysis
    Sun, Fei
    Zhou, Jian Lin
    Peng, Pu Ji
    Qiu, Chen
    Cao, Jia Rui
    Peng, Hao
    DISEASE MARKERS, 2021, 2021