基于生物信息学预测儿童轻重症疟疾的潜在生物靶标

Prediction of Potential Biomarkers for Pediatric Severe Malaria based on Bioinformatics

目的:基于生物信息学方法对儿童轻重症疟疾的基因表达谱(GSE33811)进行潜在生物学靶标的预测。方法:利用R语言和在线分析等生物信息学方法进行差异表达、功能富集及网络互作的分析。结果:获得243个差异的基因,差异基因主要参与NOD样受体信号通路、对生物刺激反应的调节、参与免疫应答的中性粒细胞激活等。通过Cytoscape筛选出10个核心基因(IL1B、STAT1、OAS1、OAS2、IRF1、DDX58、CD4、GBP1、IFIT3和IFIH1)。结论:该分析将为儿童轻重症疟疾的治疗与预防提供新的靶点及研究思路。

Objective:The aim of this study is to predict potential biological targets in pediatric severe and mild malaria using bioinformatics methods with the gene expression profile(GSE33811).Methods:Differential expression,functional enrichment,and network interaction analyses are performed using bioinformatics methods such as R language and online analysis.Results:We identified 243 differentially expressed genes.The functions of these genes are mainly enriched in the NOD-like receptor signaling pathway,regulation of biological stimulus response,and activation of neutrophils involved in immune response.Core genes namely IL1B,STAT1,OAS1,OAS2,IRF1,DDX58,CD4,GBP1,IFIT3,and IFIH1 are screened out through the Cytoscape.Conclusion:This analysis will provide new targets and research ideas for the treatment and prevention of severe and mild malaria in children.