基于基因组学数据的缺血性脑卒中免疫分子标志物的鉴定  

Identification of immune molecular markers for ischemic stroke based on genomic data

作　　者：张文婧 徐雅琪 黄一铭 王凤琳 王爱民 王清华 石福艳[1] ZHANG Wenjing;XU Yaqi;HUANG Yiming;WANG Fenglin;WANG Aimin;WANG Qinghua;SHI Fuyan(Department of Public Health,Weifang Medical University,Weifang 261053,China)

机构地区：[1]潍坊医学院公共卫生学院卫生统计学教研室,潍坊261053

出　　处：《中华疾病控制杂志》2024年第6期664-671,共8页Chinese Journal of Disease Control & Prevention

基　　金：国家自然科学基金(81803337,81872719,82003560);国家统计局课题(2018LY79);山东省自然科学基金(ZR2019MH034,ZR2020MH340,ZR2023MH313);潍坊医学院2022年度研究生科研创新基金。

摘　　要：目的基于基因组学数据,探索缺血性脑卒中免疫相关分子标志物,为缺血性脑卒中的预防和临床治疗提供理论依据。方法选取基因表达综合数据库(gene expression omnibus,GEO)中GSE16561和GSE58294两个数据,对缺血性脑卒中相关免疫分子标志物进行分析和探索。基于免疫学数据库和分析网站(the immunology database and analysis portal,ImmPort)数据库,获取免疫相关的基因,分析其在缺血性脑卒中组和正常对照组中的差异表达,鉴定差异表达免疫基因(differentially expressed immune genes,DEIGs),并利用蛋白质互作网络(protein-protein interaction,PPI)鉴定免疫相关的关键基因。基于DEIGs进行通路富集分析,发现缺血性脑卒中可能富集的分子信号通路。最后,基于CIBERSORT算法评估22种免疫细胞的浸润丰度,并计算其在缺血性脑卒中组和正常对照组中的差异,以此推断缺血性脑卒中相关的免疫细胞。结果差异分析结果表明37个DEIGs在两组间差异均有统计学意义(均P<0.05),包含缺血性脑卒中样本上调基因31个,下调基因6个。通路分析结果表明鉴定的DEIGs主要富集于免疫相关分子通路上。PPI的分析结果显示,TLR4、TLR2、MMP-9、CCR7、STAT3、TNFSF13B、S100A12、CD19、CAMP和SLC11A1是缺血性脑卒中密切相关的关键免疫基因。CIBERSORT结果表明,与正常对照样本相比较,缺血性脑卒中样本免疫回应细胞的富集水平较低(均P<0.05),而免疫抑制细胞的水平较高(均P<0.05)。结论研究基于转录组表达数据鉴定了缺血性脑卒中相关的免疫基因、免疫信号通路和免疫细胞,从3个分子水平上揭示了与缺血性脑卒中相关的免疫分子标志物,对缺血性脑卒中的有效防控和治疗策略的制定具有重要意义。Objective To explore the immune-related molecular markers for ischemic stroke based on genomic data,and to provide theoretical basis for the prevention and clinical treatment of ischemic stroke.Methods GSE16561 and GSE58294 from the gene expression omnibus(GEO)database were used for the analysis and exploration of molecular markers immune-related to ischemic stroke.Based on the immunology database and analysis portal(ImmPort)database,immune-related genes were obtained and their differential expression in ischemic stroke group and normal controls group were also analyzed to identify differentially expressed immune genes(DEIGs).Immune-related hub genes were identified by protein-protein interaction(PPI).Pathway analysis of DEIGs was performed to find the possible molecular signaling pathways of ischemic stroke.Finally,the infiltration abundance of 22 immune cells was evaluated based on the CIBERSORT algorithm,and the difference between ischemic stroke group and normal control group was subsequently calculated to determine ischemic stroke-related immune cells.Results Differential analysis results showed that 37 DEIGs had statistically significant differences between two groups(all P<0.05),including 31 up-regulated genes and 6 down-regulated genes in ischemic stroke samples.Pathway analysis results showed that the identified DEIGs were mainly enriched in immune-related molecular pathways.PPI analysis results showed that TLR4,TLR2,MMP-9,CCR7,STAT3,TNFSF13B,S100A12,CD19,CAMP and SLC11A1 were key hub immune genes closely related to ischemic stroke.Based on CIBERSORT results,we found that immune response cells were less enriched in ischemic stroke samples(all P<0.05).However,the levels of immunosuppressive cells were higher(all P<0.05).Conclusions Based on transcriptome expression data,this study identifies immune genes,immune signaling pathways and immune cells associated with ischemic stroke.This study reveals the immune molecular markers associated with ischemic stroke at three molecular levels,which is of great signi

关 键 词：缺血性脑卒中 免疫基因 信号通路 免疫细胞 分子标志物 组学数据 

分 类 号：R743.3[医药卫生—神经病学与精神病学]