摘要
目的:该研究旨在通过生物信息学、机器学习及动物实验的整合研究策略探究不明原因复发性流产(URSA)着床窗口期(WOI)子宫内膜细胞衰老的分子机制及补肾活血法的干预作用。方法:通过基因表达综合(GEO)数据库平台获取包含健康育龄妇女及URSA患者着床窗口期子宫内膜的微阵列基因集。利用R语言的“limma”包筛选URSA差异表达基因(DEGs)。利用加权基因共表达网络分析(WGCNA)获取与URSA最相关模块基因,并进行基因本体论(GO)富集分析和京都基因与基因组百科全书(KEGG)富集分析。通过人类基因数据库(GeneCards)与在线人类孟德尔遗传(OMIM)数据库获取细胞衰老相关基因集。利用韦恩图在线制图软件筛选“URSA DEGs、最相关模块基因与细胞衰老相关基因”的交集基因。而后利用检索相互作用基因/蛋白质的搜索工具(STRING)对交集基因进行蛋白质-蛋白质相互作用(PPI)网络分析,并通过Cytohubba筛选关键基因。此外,通过最小绝对值选择与收缩算子(LASSO)回归与随机森林算法筛选URSA细胞衰老诊断基因。最后,构建URSA小鼠模型,并随机分为模型组,补肾活血组及阿司匹林组,每组6只;另取6只正常妊娠小鼠作为空白组。补肾活血组给予寿胎丸合当归散配方颗粒药液(12.35 g·kg^(-1))灌胃,阿司匹林组以阿司匹林肠溶片(0.011 mL·g^(-1))灌胃。空白组、模型组给予等量蒸馏水灌胃。于发现阴道栓的第1天记为妊娠第1天(GD1)开始,连续每日给药,于GD5给药12 h后处死,收集子宫内膜组织样本。利用实时荧光定量聚合酶链式反应(Real-time PCR)和免疫荧光检测细胞衰老相关诊断基因在URSA小鼠着床窗口期子宫内膜组织的表达及补肾活血法的干预作用。结果:纳入GSE165004微阵列基因集进行生物信息学分析。根据R语言的“limma”包筛选出URSA DEGs 585个(P<0.05)。WGCNA结果提示品红色模块基因与URSA密切相关(r=0.32,P<0.05)。对品红色模块基因的KEGG分析结果提示,基因主要在细胞衰老、Hippo、NF-κB等信号通路中富集(P<0.05)。此外,通过GeneCards与OMIM网站获取细胞衰老相关基因2138个;通过韦恩图在线制图工具获得URSA差异表达基因、品红色模块基因与细胞衰老相关基因的交集基因27个,此即URSA着床窗口期子宫内膜组织细胞衰老相关DEGs。PPI分析结果显示核突触蛋白α(SNCA)、血红素加氧酶1(HOMX1)、基质金属蛋白酶1(MMP1)为关键基因。LASSO回归与随机森林共筛选出4个诊断基因,包括凝溶胶蛋白(GSN)、细胞周期蛋白2(CCND2)、RB结合蛋白8(RBBP8)和溶血磷脂酸受体1(LPAR1)。动物实验证实,与空白组比较,模型组GSN的mRNA水平和荧光强度明显升高(P<0.05),CCND2、RBBP8和LPAR1的mRNA和荧光强度明显减低(P<0.05)。与模型组比较,补肾活血组GSN表达水平明显下降(P<0.05),CCND2、LPAR1和RBBP8的表达水平明显上升(P<0.05)。结论:URSA着床窗口期子宫内膜细胞衰老与多个基因的调节相关,补肾活血法可作用于多个细胞衰老相关靶点,这可能是其改善URSA子宫内膜容受性的关键机制。
Objective:This study aims to explore the molecular mechanism of endometrial cell senescence during the window of implantation(WOI)in unexplained recurrent spontaneous abortion(URSA)and the intervention effect of Bushen Huoxue method through the integrated research strategy of bioinformatics,machine learning,and animal experiments.Method:The microarray gene sets of the endometrium of healthy women of childbearing age and patients with URSA during WOI were retrieved through the gene expression omnibus(GEO)database.The differentially expressed genes(DEGs)of URSA were screened by using the limma package of R language.Weighted gene co-expression network analysis(WGCNA)was used to obtain the most relevant module genes of URSA,and the gene ontology(GO)enrichment analysis and Kyoto encyclopedia of genes and genomes(KEGG)enrichment analysis were performed.Gene sets related to cell senescence were obtained by the Human Gene Database(GeneCards)and Online Mendelian Inheritance in Man(OMIM).The Venn online mapping software was used to screen the intersection genes of DEGs of URSA,the most relevant module genes,and the genes related to cell senescence.Then,the search tool for the retrieval of interacting genes/proteins(STRING)was used to analyze the protein-protein interaction(PPI)network of the interacting genes,and the hub genes were screened through Cytohubba.In addition,the least absolute selection and shrinkage operator(LASSO)and random forest algorithm were used to screen diagnostic genes related to cell senescence of URSA.Finally,mouse models with URSA were established and randomly divided into the model group,Bushen Huoxue group,and aspirin group,with six mice in each group,and six normal pregnant mice were selected as a blank group.The Bushen Huoxue group was given Shoutai pill combined with Danggui powder formula granular liquid(12.35 g·kg^(-1))by gavage,and the aspirin group was gavaged with aspirin at a dose of 0.011 mL·g^(-1).The blank group and model group were given the same volume of distilled water by gavage.Drug administration began on the first day after the discovery of vaginal thrombus(recorded as the first day of gestation,i.e.GD1),and the mice were sacrificed 12 hours after administration at GD5.The endometrium samples were collected.Quantitative real-time polymerase chain reaction(Real-time PCR)and immunofluorescence were used to detect the expression of cell senescence-related diagnostic genes in the endometrium tissue of URSA mice during WOI and the intervention effect of the Bushen Huoxue method.Result:The gene set of the GSE165004 microarray was included for bioinformatics analysis.According to the“limma”package of R language,585 DEGs of URSA were selected(P<0.05).WGCNA results suggested that the gene in the magenta module was the most closely related to URSA(r=0.32,P<0.05).The results of the KEGG analysis of the magenta module suggested that the genes were mainly enriched in cell senescence,Hippo,and NF-κB signaling pathways(P<0.05).In addition,2138 genes related to cell senescence were obtained from Genecards and OMIM websites.The Venn online mapping tool was used to obtain 27 intersecting genes of DEGs of URSA,the magenta module genes,and cell senescence-related genes,namely,cell senescence-related DEGs in endometrium tissue during WOI of URSA.PPI analysis showed that synuclein alpha(SNCA),heme oxygenase 1(HOMX1),and matrix metallopeptidase 1(MMP1)were hub genes.Besides,four diagnostic genes were identified by LASSO regression and random forest,including gelsolin(GSN),cyclin2(CCND2),RB binding protein 8(RBBP8),and lysophosphatidic acid receptor 1(LPAR1).Animal experiments confirmed that the mRNA level and fluorescence intensity of GSN were significantly increased(P<0.05),while the mRNA and fluorescence intensity of CCND2,LPAR1,and RBBP8 were significantly decreased(P<0.05)in the model group when compared with the blank group.The expression level of GSN was decreased(P<0.05),while the expression levels of CCND2,LPAR1,and RBBP8 were remarkably increased(P<0.05)in the Bushen Huoxue group when compared with the model group.Conclusion:The senescence of endometrial cells during WOI of URSA is related to multiple genes.Bushen Huoxue method can act on multiple targets that are related to cell senescence,which may be the key mechanism of improving endometrial receptivity in URSA.
作者
赵小萱
马景
丁心逸
赵宏利
ZHAO Xiaoxuan;MA Jing;DING Xinyi;ZHAO Hongli(Hangzhou Traditional Chinese Medicine Hospital Affiliated to Zhejiang Chinese Medical University,Hangzhou 310007,China;The Third Clinical School of Zhejiang Chinese Medical University,Hangzhou 310053,China)
出处
《中国实验方剂学杂志》
CAS
CSCD
北大核心
2024年第19期106-115,共10页
Chinese Journal of Experimental Traditional Medical Formulae
基金
浙江省中医药科技项目(2023ZR038)
国家自然科学基金青年科学基金项目(82305294,82305299)
浙江省自然科学基金项目(LQ24H270019)
杭州市医药卫生项目(A20230675)
浙江中医药大学附属医院科研项目(2022FSYYZQ16,2022FSYYZZ13,2024ZJKZKTS37)
杭州市农业与社会发展科研重点项目(202004A13)。
关键词
不明原因复发性流产
着床窗口期
细胞衰老
补肾活血法
机器学习
unexplained recurrent spontaneous abortion
window of implantation
cell senescence
Bushen Huoxue method
machine learning