摘要
目的基于孟德尔随机化(Mendelian randomization,MR)方法探究癫痫(epilepsy,EP)与1型糖尿病(type 1 diabetes mellitus,T1DM)的因果关系,并应用生物信息学方法筛选EP与T1DM的关键基因。方法从IEU Open GWAS Project数据库中获取EP和T1DM相关的数据,选择与暴露因素显著相关的单核苷酸多态性(single nucleotide polymorphisms,SNPs)作为工具变量,以逆方差加权法(inverse variance weighted,IVW)作为MR分析的主要方法,并采用比值比(odds ratio,OR)分析EP与T1DM的因果关系。通过基因表达综合数据库(Gene Expression Omnibus,GEO)下载EP与T1DM的基因芯片数据集,提取共同差异基因并进行富集分析,利用Cytoscape软件的Cytohubba工具包获取Degree值排名前10的基因并筛选关键基因,最终探究EP与T1DM的共同作用机制。结果MR分析结果显示,全面性癫痫(generalized epilepsy,GE)是T1DM的危险因素(OR=1.173,95%CI:1.007~1.367,P=0.040);生物信息学分析结果显示,EP与T1DM存在12个共同差异基因,分别为CD69、CXCL1、DACH1、ELANE、FOLR3、HBB、HIST2H2BE、HP、PMP22、PTGDS、SKAP1和TAGAP。基因本体论(Gene Ontology,GO)分析结果显示,共同差异基因生物学过程(biological process,BP)主要富集在抗菌肽介导的抗菌体液免疫应答、急性炎症反应和髓系白细胞介导的免疫等;细胞组分(cellular component,CC)主要富集在特定颗粒腔、三级颗粒腔、特定颗粒、分泌颗粒腔、细胞质囊泡腔、囊泡腔、三级颗粒等;分子功能(molecular function,MF)主要富集在有机酸结合、丝氨酸型内肽酶活性、丝氨酸型肽酶活性、丝氨酸水解酶活性等。京都基因与基因组百科全书(Kyoto Encyclopedia of Genes and Genomes,KEGG)通路分析结果显示,共同差异基因富集在抗叶酸耐药性、叶酸的运输和代谢、非洲锥虫病、疟疾、军团菌病、花生四烯酸代谢、幽门螺旋杆菌感染中的上皮细胞信号传导通路。关键基因HBB、PMP22、HP、FOLR3、CD69、DACH1、ELANE和PTGDS可能是EP与T1DM的生物标志物或治疗靶点。结论GE是引发T1DM的危险因素之一,HBB、PMP22、HP、FOLR3、CD69、DACH1、ELANE与PTGDS可能是治疗EP与T1DM的关键靶点。
Objective To explore the causal relationship between epilepsy(EP)and type 1 diabetes mellitus(T1DM)based on Mendelian randomization(MR)method,and to apply bioinformatics analysis to screen the key genes of EP and T1DM.Methods Relevant data of EP and T1DM was obtained from the IEU Open GWAS Project database.Single nucleotide polymorphisms(SNPs)significantly associated with exposure factors were selected as instrumental variables.The inverse variance weighted(IVW)method was the main method of MR analysis,and odds ratio(OR)was adopted to analyze the causal relationship between EP and T1DM.The gene chip dataset of EP and T1DM were downloaded through the Gene Expression Omnibus(GEO)database,and common differentially genes were taken for enrichment analysis.The Cytohubba toolkit of Cytoscape software was used to obtain the genes with the top 10 Degree values and screen the key genes to explore the common mechanism of EP and T1DM.Results The results of MR analysis showed that generalized epilepsy(GE)was a risk factor for T1DM(OR=1.173,95%CI:1.007-1.367,P=0.040).The results of bioinformatic analysis showed that there were 12 common differential genes between EP and T1DM,namely CD69,CXCL1,DACH1,ELANE,FOLR3,HBB,HIST2H2BE,HP,PMP22,PTGDS,SKAP1 and TAGAP.The results of Gene Ontology(GO)analysis showed that the biological process(BP)of common differential gene was mainly enriched in antimicrobial humoral immune response mediated by antimicrobial peptide,acute inflammatory response,myeloid leukocyte mediated immunity,etc.;cellular component(CC)was mainly enriched in specific granule lumen,tertiary granule lumen,specific granule,secretory granule lumen,cytoplasmic vesicle lumen,vesicle lumen,tertiary granule,etc.;molecular function(MF)was mainly enriched in organic acid binding,serine-type endopeptidase activity,serine-type peptidase activity,serine hydrolase activity,etc.The results of Kyoto Encyclopedia of Gene and Genomes(KEGG)pathway analysis showed that the common differential genes were enriched in antifolate resistance,folate transport and metabolism,African trypanosomiasis,malaria,legionellosis,arachidonic acid metabolism,epithelial cell signaling in Helicobacter pylori infection.The key genes HBB,PMP22,HP,FOLR3,CD69,DACH1,ELANE,and PTGDS may be biomarkers or therapeutic targets for EP and T1DM.Conclusion GE was one of the risk factors for T1DM and HBB,PMP22,HP,FOLR3,CD69,DACH1,ELANE,and PTGDS may be the key argets for the treatment of EP and T1DM.
作者
曾佳威
连璐
谭雅匀
范晶晶
刁丽梅
ZENG Jiawei;LIAN Lu;TAN Yayun;FAN Jingjing;DIAO Limei(The First Clinical Faculty of Guangxi University of Chinese Medicine,Nanning 530001,China;Department of Neurology,The Guangxi Zhuang Autonomous Region Brain Hospital,Liuzhou 545005,Guangxi Zhuang Autonomous Region,China)
出处
《数理医药学杂志》
2025年第12期883-893,共11页
Journal of Mathematical Medicine
基金
国家自然科学基金地区科学基金项目(82360875)。
关键词
癫痫
1型糖尿病
孟德尔随机化
生物信息学
Epilepsy
Type 1 diabetes mellitus
Mendelian randomization
Bioinformatics
