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中华移植杂志(电子版) ›› 2022, Vol. 16 ›› Issue (04) : 201 -209. doi: 10.3877/cma.j.issn.1674-3903.2022.04.002

论著

肾移植术后BK病毒相关性肾病核心基因及免疫微环境的生物信息学分析
董博清1, 豆猛1, 张静1, 冯新顺1, 郑瑾1, 李潇1, 丁小明1, 薛武军1, 李杨1,()   
  1. 1. 710061 西安交通大学第一附属医院肾移植科 西安交通大学器官移植研究所
  • 收稿日期:2022-05-07 出版日期:2022-08-25
  • 通信作者: 李杨
  • 基金资助:
    陕西省重点研发计划(2022SF-148); 西安交通大学基本科研业务基金(xzy012021060); 中国器官移植发展基金课题

Bioinformatics analysis of the hub genes and immune microenvironment in BK virus-associated nephropathy after renal transplantation

Boqing Dong1, Meng Dou1, Jing Zhang1, Xinshun Feng1, Jin Zheng1, Xiao Li1, Xiaoming Ding1, Wujun Xue1, Yang Li1,()   

  1. 1. Department of Kidney Transplantation, First Affiliated Hospital & Institute of Organ Transplantation, Xi′an Jiaotong University, Xi′an 710061, China
  • Received:2022-05-07 Published:2022-08-25
  • Corresponding author: Yang Li
引用本文:

董博清, 豆猛, 张静, 冯新顺, 郑瑾, 李潇, 丁小明, 薛武军, 李杨. 肾移植术后BK病毒相关性肾病核心基因及免疫微环境的生物信息学分析[J/OL]. 中华移植杂志(电子版), 2022, 16(04): 201-209.

Boqing Dong, Meng Dou, Jing Zhang, Xinshun Feng, Jin Zheng, Xiao Li, Xiaoming Ding, Wujun Xue, Yang Li. Bioinformatics analysis of the hub genes and immune microenvironment in BK virus-associated nephropathy after renal transplantation[J/OL]. Chinese Journal of Transplantation(Electronic Edition), 2022, 16(04): 201-209.

目的

通过生物信息学方法分析肾移植术后BK病毒相关性肾病(BKVAN)的核心基因及其与浸润的免疫细胞相关性。

方法

从美国国立生物技术信息中心基因表达综合数据库下载BKVAN相关数据集GSE75693和GSE72925,BK病毒(BKV)血症相关数据集GSE47199。合并GSE75693和GSE72925后筛选差异表达基因(DEGs),然后进行基因本体生物过程(GOBP)以及京都基因与基因组百科全书(KEGG)通路分析,并通过蛋白-蛋白相互作用(PPI)网络进一步筛选核心基因。使用CIBERSORT进行免疫浸润分析,然后计算差异的免疫细胞和核心基因的相关性。最后,在GSE47199数据集筛选BKV血症和BKVAN共同的核心基因,使用基因集富集分析(GSEA)鉴定共同的核心基因分别在BKVAN和BKV血症中的生物过程。所有统计分析及可视化均基于R语言(4.0.2)。P<0.05为差异有统计学意义。

结果

在合并数据中共筛选出175个上调及70个下调DEGs。在PPI网络中,通过5种方法交集得到9个核心基因,核心基因主要富集在免疫细胞活化与功能相关的进程;在KEGG分析中,核心基因主要富集在病毒蛋白与细胞因子和细胞因子受体间相互作用、细胞因子-细胞因子受体间相互作用以及趋化因子信号通路等。免疫浸润分析表明PTPRC、CCL5、TYROBP、CXCL10、CD2和CXCL9与BKVAN中浸润的免疫细胞相关。CD2是BKVAN和BKV血症的共同核心基因。

结论

通过生物信息学方法筛选出BKVAN的核心基因,其中PTPRC、CCL5、TYROBP、CXCL10、CD2和CXCL9与BKVAN中浸润的免疫细胞相关,CD2是BKVAN和BKV血症的共同核心基因,这些标志物为肾移植术后BKVAN的诊治提供依据。

Objective

To analyze hub genes in BK virus-associated nephropathy (BKVAN) after renal transplantation and its relationship with infiltrating immune cells by bioinformatics methods.

Methods

GSE75693 and GSE72925 (BKVAN-related datasets) and GSE47199 (a BK viremia-related dataset) were downloaded from GEO database. Then GSE75693 and GSE72925 were combined to screen for differential expression genes (DEGs), followed by gene ontology biological process (BPGO), Kyoto encyclopedia of genes and genomes (KEGG) pathway and protein-protein interaction (PPI) network analysis to further screen hub genes. Immune infiltration analysis was performed using CIBERSORT, and then correlations between differential immune cells and hub genes were calculated. Finally, common hub genes in both BK viremia and BKVAN were screened in the GSE47199 dataset, and the biological process of common hub genes in BKVAN and BK viremia were identified using gene set enrichment analysis (GSEA). All statistical analysis and visualizations were based on R language (4.0.2). P<0.05 was considered statistically significant.

Results

A total of 175 up-regulated and 70 down-regulated DEGs were screened from the combined dataset. Nine hub genes were obtained from the PPI network by five methods of intersection, and the hub genes were mainly enriched in the processes related to immune cell activation and function; in the KEGG analysis, the hub genes were mainly enriched in viral proteins, cytokine and cytokine receptor interactions, cytokine-cytokine receptor interactions and chemokine signaling pathways. Immune infiltration analysis showed that PTPRC, CCL5, TYROBP, CXCL10, CD2 and CXCL9 were associated with infiltrating immune cells in BKVAN. CD2 was the common hub gene for both BKVAN and BK viremia.

Conclusions

In this study, the hub genes of BKVAN were screened by bioinformatics, among which PTPRC, CCL5, TYROBP, CXCL10, CD2 and CXCL9 were associated with immune cells infiltration in BKVAN, and CD2 was the common hub gene of BKVAN and BK viremia.

图1 BKVAN DEGs可视化 注:BKVAN. BK病毒相关性肾病;DEGs.差异表达基因;a.火山图,展示|差异倍数(log2FC)|>1的基因,此外|差异倍数(log2FC)|>1.5的基因在图中标记并列出基因名;b.热图,展示前25个上调以及下调DEGs
图2 BKVAN DEGs富集分析 注:BKVAN. BK病毒相关性肾病;DEGs.差异表达基因;a.245个DEGs基因本体生物学过程分析结果;b.DEGs京都基因与基因组百科全书通路分析结果
图3 构建蛋白质-蛋白质相互作用网络与筛选核心基因 注:DEGs.差异表达基因;a. MCODE中得分最高的子网络(11.471分); b.通过MNC、Degree、Stress、Radiality和Closeness交集筛选出9个核心基因;c. 9个核心基因的基因本体生物过程分析结果;d. 9个核心基因的KEGG通分析结果
图4 GSE75693和GSE72925合并数据集中免疫细胞分布及差异浸润的免疫细胞与核心基因的Pearson相关性分析 注:BKVAN. BK病毒相关性肾病;PTPRC.蛋白酪氨酸磷酸酶受体C型;CCL. C-C基序趋化因子配体;TYROBP. TYRO蛋白酪氨酸激酶结合蛋白;CXCL. C-X-C基序趋化因子配体;ITGB2.整合素亚基β2; a. BKVAN和功能稳定的移植物中免疫细胞亚群的分布;b. BKVAN与功能稳定的移植物差异浸润的免疫细胞与核心基因的Pearson相关性分析,|相关系数(r)|>0.6以黑体标记;*P<0.05, **P<0.01, ***P<0.001, ****P<0.0001
图5 BKVAN和BKV血症共同核心基因筛选 注:BKVAN. BK病毒相关性肾病;BKV. BK病毒;a和b. CD2分别诊断BKVAN和BKV血症受试者工作特征曲线;c和d. CD2在BKVAN和BKV血症中的表达量
图6 BKVAN和BKV血症中CD2基因集富集分析 注:BKVAN. BK病毒相关性肾病;GOBP.基因本体生物过程;BKV. BK病毒;a. CD2在BKVAN中的标准化富集分数前5位的GOBP; b. CD2在BKV血症中标准化富集分数前5位的GOBP
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