摘要
目的运用生物信息学方法揭示阿尔茨海默症(AD)的生物学过程和通路,预测疾病潜在风险基因。方法首先对收集的AD易感基因进行基因本体论分析和通路富集分析发掘易感基因涉及的生物学过程和通路,并且提取关键的通路串话聚类模块;应用施泰纳最小树算法构建AD特异性蛋白质子网络,预测潜在风险基因。结果研究得到587个AD易感基因。进行GO和通路富集分析得到参与AD的显著性生物学过程和48条关键通路。通过分析特异性子网络,预测出5个潜在风险基因:HSP90AB1、PRKACA、GRB2、PPP1CA和PRKN。结论AD的发生可能是不同系统的通路共同异常所导致,免疫系统在其中发挥较为重要的作用;预测得到5个AD潜在易感基因。
Objective Bioinformatics methods were used to reveal the biological processes and pathways of Alzheimer’s disease.Potential risk genes were predicted to provide guidance for high-risk population.Methods AD susceptible genes were collected and analyzed by WebGestalt for gene ontology(GO)and pathway enrichment.Cross-talk clustering was extracted and AD specific sub-network was constructed by Steiner’s minimum tree algorithm to predict potential risk genes.Results Five hundred and eighty-seven AD susceptible genes and forty-eight pathways were obtained.Five potential risk genes were predicted by analyzing specific subnetworks:HSP90AB1,PRKACA,GRB2,PPP1CA and PRKN.Conclusion The occurrence of AD may be caused by the common abnormality of the pathways in different systems,in which the immune system plays an important role,and the prediction of five AD risk genes may become a new drug target for AD therapy.
作者
樊婷
王举
Fan Ting;Wang Ju(School of Biomedical Engineering,Tianjin Medical University,Tianjin 300070,China;不详)
出处
《航天医学与医学工程》
CAS
CSCD
北大核心
2019年第6期497-502,共6页
Space Medicine & Medical Engineering
基金
国家自然科学基金(2016YFC0906300)
关键词
阿尔茨海默症
通路富集分析
通路串话网络
GO分析
特异性子网络
Alzheimer’s disease
pathway enrichment analysis
pathway crosstalk network
GO analysis
specific sub-network
