帕金森病关键基因及通路的筛选及其生物信息学分析

Screening of key genes and pathways in Parkinson's disease and its bioinformatics analysis

目的通过分析帕金森病患者与健康人基因芯片数据,寻找差异基因及其关键通路。方法利用GEO数据库中高通量基因芯片数据库筛选出帕金森病患者与健康对照的芯片。采用GO基因功能注释和KEGG通路富集分析,筛选出帕金森病的特征基因簇和通路,并进行蛋白质相互作用网络可视化分析。结果筛选出15个差异基因及7个关键节点蛋白。经差异基因分析后,发现神经丝、网格蛋白包被组装及多巴胺受体信号通路富集程度最高。结论本研究利用生物信息学方法,从不同的角度研究帕金森病的遗传学背景,在基因层面为帕金森病的诊断学标志与精准治疗提供新的思路。

Objective To find out the differential genes and their key pathways by analyzing the gene microarray data of Parkinson's patients and healthy people.Methods The high-throughput gene chip database in the GEO database was used to screen the chips of Parkinson's patients and healthy controls.Go gene function annotation and KEGG pathway enrichment analysis were used,the characteristic gene clusters and pathways of Parkinson's disease were screened,and the network visualization analysis of protein interaction was performed.Results 15 differential genes and 7 key node proteins were screened.After differential gene analysis,it was found that neurofilament,clathrin-coated assembly,and the degree of dopamine receptor signaling pathway enrichment were the highest.Conclusion This study uses bioinformatic methods to study the genetic background of Parkinson's disease from different perspectives,and provides new ideas for the diagnostic markers and precise treatment of Parkinson's disease at the genetic level.