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中华老年骨科与康复电子杂志 ›› 2021, Vol. 07 ›› Issue (04) : 193 -200. doi: 10.3877/cma.j.issn.2096-0263.2021.04.001

基础研究

CD8+T细胞、滤泡辅助性T细胞和浆细胞浸润在椎间盘退变中的生物信息学分析
高一诚1, 张广智1, 解琪琪1, 邓亚军1, 任恩惠1, 武作龙1, 贺学岗1, 康学文1,()   
  1. 1. 730030 兰州大学第二医院骨科;730030 甘肃省骨关节疾病研究重点实验室
  • 收稿日期:2020-06-30 出版日期:2021-08-05
  • 通信作者: 康学文
  • 基金资助:
    脊柱疾患疼痛机制研究及治疗甘肃省国际科技合作基地(甘科外[2017]2号-34); 兰州大学创新创业培育项目(cxcy201906); 兰州大学第二医院2019年博士研究生培养专项基金项目(YJS-BD-09)

Bioinformatics analysis of CD8+ T cells, follicular helper T cells and plasma cells infiltration in intervertebral disc degeneration

Yicheng Gao1, Guangzhi Zhang1, Qiqi Xie1, Yajun Deng1, Enhui Ren1, Zuolong Wu1, Xuegang He1, Xuewen Kang1()   

  1. 1. Department of Orthopaedics, Lanzhou University Second Hospital, Lanzhou 730030, China; Key Laboratory of Osteoarthritis of Gansu Province, Lanzhou 730030, China
  • Received:2020-06-30 Published:2021-08-05
  • Corresponding author: Xuewen Kang
引用本文:

高一诚, 张广智, 解琪琪, 邓亚军, 任恩惠, 武作龙, 贺学岗, 康学文. CD8+T细胞、滤泡辅助性T细胞和浆细胞浸润在椎间盘退变中的生物信息学分析[J]. 中华老年骨科与康复电子杂志, 2021, 07(04): 193-200.

Yicheng Gao, Guangzhi Zhang, Qiqi Xie, Yajun Deng, Enhui Ren, Zuolong Wu, Xuegang He, Xuewen Kang. Bioinformatics analysis of CD8+ T cells, follicular helper T cells and plasma cells infiltration in intervertebral disc degeneration[J]. Chinese Journal of Geriatric Orthopaedics and Rehabilitation(Electronic Edition), 2021, 07(04): 193-200.

目的

筛选椎间盘退变(IDD)组织与非退变组织间的关键(hub)基因,并进一步分析IDD组织中免疫细胞浸润情况。

方法

从GEO数据库下载IDD表达谱芯片数据集,利用R软件筛选退变组织与非退变组织中的差异表达基因(DEGs),然后构建蛋白质-蛋白质相互作用网络(PPI),筛选出hub基因。最后首次利用科学的反卷积算法(CIBERSORT)分析IDD组织中免疫细胞的浸润情况,以揭示免疫细胞浸润在IDD中的作用。

结果

共筛选出166个DEGs和10个hub基因。免疫细胞浸润分析发现,IDD组织中单核细胞与调节性T细胞正相关,嗜酸性粒细胞与单核细胞和调节性T细胞负相关;CD8+T细胞、滤泡辅助性T细胞在IDD组织中浸润较少,而浆细胞在IDD组织中浸润则相对较多;静止期树突状细胞、浆细胞、静止期NK细胞调节性T细胞与其他免疫细胞互作较强,而滤泡辅助性T细胞、M2型巨噬细胞与幼稚性B细胞与其它免疫细胞互作较弱。

结论

本结果揭示了IDD中的hub基因,进一步免疫细胞浸润分析表明,CD8+T细胞、滤泡辅助性T细胞和浆细胞与IDD发生发展密切相关,为进一步探讨IDD的分子机制提供新思路。

Objective

To screen the key genes of intervertebral disc degeneration (IDD) tissues and non-degeneration tissues, and to further analyze the infiltration of immune cells.

Methods

Download the IDD expression profile chip dataset from the GEO database, and use R software to screen differentially expressed genes (DEGs) in degenerate and non-degenerate tissues, and then construct a protein-protein interaction network (PPI). Screen out the hub gene. Finally, for the first time, a scientific deconvolution algorithm (CIBERSORT) was used to analyze the infiltration of immune cells in IDD tissues to reveal the role of immune cell infiltration in IDD.

Results

A total of 166 DEGs and 10 hub genes were screened. Immune cell infiltration analysis found that monocytes in IDD tissues were positively correlated with T cells regulatory, and eosinophils were negatively correlated with monocytes and T cells regulatory; CD8+T cells and follicular helper T cells were less infiltrated in IDD. while plasma cells are more infiltrated in IDD tissues; dendritic cells resting, plasma cells, NK cells resting and T cells regulatory interact strongly with other immune cells. T cells follicular helper, Macrophages M2, and B cells na?ve assist weak interaction with other immune cells.

Conclusions

Our results reveal the hub gene in IDD and immune cell infiltration analysis shows that CD8+T cells, follicular helper T cells, and plasma cells are closely related to the development of IDD. To provide a new idea for further exploring the molecular mechanism of IDD.

图1~4 箱式图和PCA图。图1 GSE70362数据集标准化处理之前的箱式图;图2 GSE70362数据集标准化处理之后的箱式图;图3 GSE70362数据集标准化处理之前的二维PCA图;图4 GSE70362数据集标准化处理之后的二维PCA图
表1 10个Hub基因
图6~8 免疫细胞浸润相关性分析。图6免疫细胞浸润的相关性热图;图7调节性T细胞和单核细胞相关性分析;图8单核细胞与嗜酸性粒细胞相关性分析
图9~10 免疫细胞浸润比例的小提琴图及互作网络图分析图。图9 IDD组织与非退变组织中免疫细胞浸润比例的小提琴图,红色标记代表两组样本之间存在浸润差异;图10免疫细胞互作的网络图,圆圈大小代表免疫细胞浸润细胞间的互作强度
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