基于知识融合策略构建双相障碍致病基因网络  

Construction of Responsible Gene Network for Bipolar Disorder by Using a Knowledge-integration-based Strategy

作　　者：刘轲[1] 赵虎[1] 刘燕[1] 饶绍奇[2,3] 

机构地区：[1]中山大学中山医学院,广东广州510080 [2]广东医学院公共卫生学院,广东东莞523808 [3]中山大学公共卫生学院,广东广州510080

出　　处：《中山大学学报（医学科学版）》2013年第3期471-477,共7页Journal of Sun Yat-Sen University:Medical Sciences

基　　金：国家自然科学基金(30830104;31071166);广东省自然科学基金(8251008901000007);广东省科技计划攻关项目(2009A030301004);东莞市科技重点项目(201108101015);广东医学院基金项目(XG1001;XZ1105;STIF201122;JB1214)

摘　　要：【目的】提出基于知识融合策略构建基因网络方法 ,并应用于双相障碍相关的致病基因网络分析。【方法】将Wellcome Trust Case Control Consortium(WTCCC)提供的双相障碍全基因组单核苷酸多态(SNP)数据与人类蛋白质-蛋白质互作数据库对应的基因做交集。通过单体型全模型logistic回归模型检验获得经多重检验校正统计学显著的基因互作对子,并由此构建致病基因网络以及挖掘连通度显著高于理论分布的核心致病基因。【结果】采用知识融合的方法,将数据维度从482 248个SNP位点降至98 157。经统计模型检验获得3 841个互作基因用于构建双相障碍致病基因网络,并挖掘出115个核心致病基因。其中,在连通度高于30的29个核心基因中,有12个重复了以前的报道(PRKCA,EGFR,ESR1,ATXN1,FYN,CREBBP,TP53,AKT1,CSNK2A1,DLG1,PTN和LYN),另外17个未被报道过的基因从其生物功能以及致病分子机制上看,可能是新的双相障碍易感基因(SMAD3,SRC,GRB2,PIK3R1,ZBTB16,ABL1,APP,EP300,TGFBR1,SYK,YWHAZ,INSR,MAPK1,PRKCB,PRKCD,SMAD2和SVIL)。【结论】本文提出的基于蛋白质-蛋白质互作知识引导的基因网络构建方法是一种可靠的系统性分析方法,有助于全面地了解复杂疾病的分子网络机制和确立核心风险基因。[Objective] To propose a knowledge-fusion strategy for constructing gene networks,and to apply the proposed approach to analyze the gene networks for bipolar disorder （BPD）.[Methods] The intersecting gene set between all genes in a proteinprotein interaction （PPI） database and the genes in the whole genome single nucleotide polymorphism （SNP） dataset for BPD,provided by the Wellcome Trust Case Control Consortium （WTCCC）,were defined.Statistically significant epistatic gene pairs in the gene set were then obtained by using a haplotype-based full-model logistic regression and multiple testing corrections.Finally,a disease-causing gene network was constructed by using these epistatic gene pairs,and the hub genes whose connection degrees were significantly higher than theoretical ones were identified.[Results] By using the proposed knowledge-fusion strategy,the data dimension for the whole genome SNP data for BPD was reduced,from 482,248 SNPs to 98,157 SNPs.A total of 3,841 genes with significant epistasis identified by using the abovementioned statistical model were used to construct the underlying gene network for BPD,from which 115 hub-genes were found.Among 29 hub-genes with degrees more than 30,12 were found repeating the previous findings PRKCA,EGFR,ESR1,ATXN1,FYN,CREBBP,TP53,AKT1,CSNK2A1,DLG1,PTN,and LYN）,while the remaining 17 genes might be novel susceptibility genes,judged by their functional involvements （SMAD3,SRC,GRB2,PIK3R1,ZBTB16,ABL1,APP,EP300,TGFBR1,SYK,YWHAZ,INSR,MAPK1,PRKCB,PRKCD,SMAD2,and SVIL）.[Conclusion] This real data analysis demonstrates that the proposed gene network approach,which was guided by PPI knowledge,was a reliable systematic method,and would help us have a global view on the underlying molecular networking mechanisms for complex diseases,and would help us find the hub risk genes.

关 键 词：双相障碍 知识学习 蛋白质-蛋白质互作 全基因组关联 基因网络 核心风险基因 

分 类 号：R739[医药卫生—肿瘤]