基于转录组学数据分析痛风合并动脉粥样硬化的发病机制
DOI:
作者:
作者单位:

(1.天津中医药大学第一附属医院,;2.天津市中药方剂与证候重点实验室,;3.国家中医针灸临床医学研究中心, 天津市 300193;4.成都中医药大学附属医院,四川省成都市 610075)

作者简介:

金玥,硕士,主治医师,研究方向为中西医结合治疗风湿免疫病,E-mail:18002012581@163.com。通信作者刘维,博士,主任医师,教授,研究方向为中西医结合治疗风湿免疫病,E-mail:fengshiliuwei@163.com。

通讯作者:

基金项目:

中国科学技术协会青年人才托举工程(YES20210352);国家自然科学基金面上项目(82074377);天津市科委重大科技成果科普化项目(22KPXMRC00180)


Analysis of the pathogenesis of gout complicated with atherosclerosis based on transcriptome data
Author:
Affiliation:

1.First Teaching Hospital of Tianjin University of Traditional Chinese Medicine, ;2.Tianjin Key Laboratory of Traditional Chinese Medicine Prescription and Syndrome, ;3.National Clinical Research Center for Chinese Medicine Acupuncture and Moxibustion, Tianjin 300193, China;4.Hospital of Chengdu University of Traditional Chinese Medicine, Chengdu, Sichuan 610075, China)

Fund Project:

  • 摘要
  • |
  • 图/表
  • |
  • 访问统计
  • |
  • 参考文献
  • |
  • 相似文献
  • |
  • 引证文献
  • |
  • 资源附件
    摘要:

    目的]采用GEO数据库探讨痛风合并动脉粥样硬化(As)的共同发病机制。 [方法]从GEO数据库中下载痛风(GSE160170)和As(GSE100927)的基因表达矩阵,分析痛风和As的差异表达基因(DEG),并分别进行富集分析。在分析共同差异表达基因(CDEG)后,对其进行功能富集分析、蛋白质-蛋白质相互作用(PPI)网络分析和核心基因(HG)鉴定,并对HG进行共表达分析及验证。最后,分析痛风、As的免疫细胞浸润,同时探索HG与浸润免疫细胞(IIC)之间的相关性。 [结果]GSE160170数据集中获得了1 606个DEG,GSE100927数据集中获得了481个DEG。其中的22个CDEG富集分析结果表明,细胞因子的调控作用可能是痛风合并As的关键机制。通过使用CytoHubba插件识别了6个HG(CCR2、CD2、FCGR3A、FGD3、IL10RA、SIGLEC1),结果显示这些HG尚且可靠。共表达网络显示这些HG可以影响肿瘤坏死因子超家族细胞因子产生的调节作用。免疫细胞浸润分析表明,痛风中的NK细胞表达显著增加,且与CCR2基因呈显著相关;As中的活化肥大细胞表达显著增加,且与CD2基因呈显著相关。 [结论]肿瘤坏死因子超家族细胞因子产生的调节作用很可能是痛风合并As的核心因素。

    Abstract:

    Aim GEO database was used to explore the common pathogenesis of gout complicated with atherosclerosis (As). Methods The gene expression matrices of gout (GSE160170) and As (GSE100927) were downloaded from the GEO database, the differentially expressed genes (DEG) of gout and As were analyzed, and enrichment analysis was performed separately. After analyzing the common differentially expressed genes (CDEG), functional enrichment analysis, protein-protein interaction (PPI) network analysis, and hub genes (HG) identification were performed on them, and co-expression analysis and validation were performed on hub genes. Finally, the immune cell infiltration of gout and As was analyzed, and the correlation between hub genes and infiltrating immune cells (IIC) was explored. Results The GSE160170 dataset obtained 1 606 differentially expressed genes, while the GSE100927 dataset obtained 481 differentially expressed genes. The enrichment analysis of 22 differentially expressed genes showed that the regulation of cytokines may be the key mechanism of gout complicated with As. Six hub genes (CCR2, CD2, FCGR3A, FGD3, IL10RA, SIGLEC1) were identified using the CytoHubba plugin, and the validation results of these hub genes showed that they were still reliable. The co-expression network showed that these hub genes could affect the regulation of tumor necrosis factor superfamily cytokines. Immune cell infiltration analysis showed that the expression of NK cells in gout was significantly increased, and was significantly related to CCR2 gene. The expression of living fertilizer large cells in As was significantly increased, and was significantly related to CD2 gene. Conclusion The regulatory effect of tumor necrosis factor superfamily cytokines may be the core factor of gout complicated with As.

    参考文献
    相似文献
    引证文献
引用本文

金玥,王爱华,樊一桦,刘维.基于转录组学数据分析痛风合并动脉粥样硬化的发病机制[J].中国动脉硬化杂志,2023,31(10):855~864.

复制
分享
文章指标
  • 点击次数:
  • 下载次数:
历史
  • 收稿日期:2023-01-18
  • 最后修改日期:2023-05-04
  • 录用日期:
  • 在线发布日期: 2023-11-08