|本期目录/Table of Contents|

[1]王凡,赵倩.基于生物信息学分析法洛四联症miRNA的免疫调控机制[J].天津医科大学学报,2025,31(04):322-328.[doi:10.20135/j.issn.1006-8147.2025.04.0322]
　WANG Fan,ZHAO Qian.Bioinformatics analysis of the immunoregulatory mechanisms of microRNA in tetralogy of Fallot[J].Journal of Tianjin Medical University,2025,31(04):322-328.[doi:10.20135/j.issn.1006-8147.2025.04.0322]
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基于生物信息学分析法洛四联症miRNA的免疫调控机制(PDF)

《天津医科大学学报》[ISSN:1006-8147/CN:12-1259/R]

卷:
31卷
期数:
2025年04期
页码:
322-328
栏目:
基础医学
出版日期:
2025-07-10

文章信息/Info

Title:
Bioinformatics analysis of the immunoregulatory mechanisms of microRNA in tetralogy of Fallot
文章编号:
1006-8147(2025)04-0322-07
作者:
王凡; 赵倩
（天津医科大学基础医学院细胞生物学系，天津 300070）
Author(s):
WANG Fan; ZHAO Qian
（Department of Cell Biology， School of Basic Medical Sciences， Tianjin Medical University， Tianjin 300070， China）
关键词:
法洛四联症;  PPI互作网络;  免疫调控
Keywords:
tetralogy of Fallot;  PPI interaction network;  immunoregulatory
分类号:
R541.1
DOI:
10.20135/j.issn.1006-8147.2025.04.0322
文献标志码:
A
摘要:
目的：通过生物信息学方法，构建法洛四联症（TOF）免疫相关的miRNA-mRNA调控网络，探究miRNA对免疫基因的调控作用。方法：利用Gene Expression Omnibus （GEO）数据库中与TOF相关的mRNA和miRNA数据进行分析，结合差异分析、免疫浸润分析及靶基因预测，整合免疫相关基因（IRGs），筛选miRNA-mRNA调控对。通过外部验证集筛选高AUC得分基因，并构建转录因子（TF）-miRNA-mRNA调控网络。结果：差异分析得到1 875个差异表达基因（DEGs）和27个差异表达miRNAs（DEmiRNAs）。其中浆细胞、杀伤性T细胞、单核细胞以及静止肥大细胞等免疫细胞组分在患病样本中显著高于正常样本，T细胞滤泡辅助细胞、休眠自然杀伤细胞、γδT细胞、嗜酸性粒细胞、活化肥大细胞等免疫细胞组分在患病样本中显著低于正常样本。整合DEGs与DEmiRNAs，通过外部验证集筛选得到16个关键mRNA和16个miRNA，预测得到4个调控关键miRNA的TF，并构建36节点（node）与32条边（edge）的免疫相关的TF-miRNA-mRNA网络。基于调控网络的MCC得分筛选出4个与免疫相关的核心基因与5个核心miRNA。结论：成功构建了TOF的免疫相关TF-miRNA-mRNA调控网络，鉴定出5个核心调控miRNA及其靶向的4个免疫相关核心基因，揭示了miRNA介导的免疫调控在TOF中的潜在作用。
Abstract:
Objective： To construct an immune-related miRNA-mRNA regulatory network in tetralogy of Fallot（TOF） using bioinformatics approaches and investigate the regulatory roles of miRNAs in immune genes. Methods： mRNA and miRNA expression data related to TOF from the Gene Expression Omnibus（GEO） database were analyzed. Differential expression analysis， immune infiltration analysis， and target gene prediction were performed to identify immune-related genes（IRGs） and screen for miRNA-mRNA regulatory pairs. High-AUC genes were selected using an external validation set， and a transcription factor（TF）-miRNA-mRNA regulatory network was constructed. Results： A total of 1 875 differentially expressed genes（DEGs） and 27 differentially expressed miRNAs （DEmiRNAs） were identified by differential analysis. Among them， immune cell components such as plasma cells， killer T cells， monocytes， and resting mast cells were significantly enriched in disease samples， while T follicular helper cells， resting NK cells， γδ T cells， eosinophils and activated mast cells showed significant depletion compared to normal controls. Integration of DEGs and DEmiRNAs yielded 16 key mRNAs and 16 miRNAs through an external validation set. Four TFs regulating key miRNAs were predicted， forming an immune-related TF-miRNA-mRNA network with 36 nodes and 32 edges. Based on MCC scores of the regulatory network， four core immune-related genes and five core miRNAs were screened. Conclusion： An immune-related TF-miRNA-mRNA regulatory network for TOF has been successfully constructed， identifying five core regulatory miRNAs and four immune-related target core genes. These findings highlight the potential role of miRNA-mediated immune regulation in TOF.

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备注/Memo

备注/Memo:
作者简介:王凡（2000-），女，硕士在读，研究方向：表观遗传学；生物信息学；通信作者：赵倩，E-mail：zhaoq@tmu.edu.cn。
更新日期/Last Update: 2025-07-10