遗传 ›› 2015, Vol. 37 ›› Issue (7): 655-663.doi: 10.16288/j.yczz.15-061

• 综述 • 上一篇    下一篇

整合分析多组学数据筛选疾病靶点的精准医学策略

谢兵兵1, 2, 杨亚东1, 丁楠1, 2, 方向东1   

  1. 1. 中国科学院北京基因组研究所, 中国科学院基因组科学与信息重点实验室, 北京 100101;
    2. 中国科学院大学, 北京 100049
  • 收稿日期:2015-02-02 修回日期:2015-03-31 出版日期:2015-07-20 发布日期:2015-07-20
  • 通讯作者: 方向东,博士,研究员,研究方向:干细胞与重要疾病的组学与转化医学。E-mail: fangxd@big.ac.cn
  • 作者简介:谢兵兵,在读硕士研究生,专业方向:基因组学数据挖掘。Tel: 010-84097538;E-mail: xiebb@big.ac.cn
  • 基金资助:
    中国科学院干细胞与再生医学研究战略性科技先导专项子课题(编号:XDA01040405),国家自然科学基金面上项目(编号:31471115)和青年项目(编号:31401160)资助

Identification of disease targets for precision medicine by integrative analysis of multi-omics data

Bingbing Xie1, 2, Yadong Yang1, Nan Ding1, 2, Xiangdong Fang1   

  1. 1. CAS Key Laboratory of Genome Sciences and Information, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 100101, China;
    2. University of Chinese Academy of Sciences, Beijing 100049, China
  • Received:2015-02-02 Revised:2015-03-31 Online:2015-07-20 Published:2015-07-20

摘要: 随着高通量测序技术的不断发展与完善,对于不同层次和类型的生物组学数据的获取及分析方法也日趋成熟与完善。基于单组学数据的疾病研究已经发现了诸多新的疾病相关因子,而整合多组学数据研究疾病靶点的工作方兴未艾。生命体是一个复杂的调控系统,疾病的发生与发展涉及基因变异、表观遗传改变、基因表达异常以及信号通路紊乱等诸多层次的复杂调控机制,利用单一组学数据分析致病因子的局限性愈发显著。通过对多种层次和来源的高通量组学数据的整合分析,系统地研究临床发病机理、确定最佳疾病靶点已经成为精准医学研究的重要发展方向,将为疾病研究提供新的思路,并对疾病的早期诊断、个体化治疗和指导用药等提供新的理论依据。本文详细介绍了基因组、转录组和表观组等系统组学研究在疾病靶点筛选方面出现的新技术手段和研究进展,并对它们之间的整合分析新策略和优势进行了讨论。

关键词: 基因组, 转录组, 表观遗传组, 整合分析, 疾病靶点

Abstract: With the development and improvement of high-throughput sequencing technologies, the acquisition and processing approaches of various biological omics data on different levels are becoming more mature. Despite several new disease-associated factors have been discovered based on single omics data analysis, identification of disease targets by integrative analysis of multi-omics data is still growing. Since life is a complex regulatory system in which the regulation of gene mutations, epigenetic alterations, abnormal gene expression as well as anomalous variations in signal pathway are related with the occurrence and development of diseases, it is obvious that finding therapeutic factors using single omics data analysis has its limitation. Systematical studies of clinical and pathological mechanisms and identification of optimal therapeutic targets through integrative analysis of multi-omics data from different levels and resources have become an important research direction of precision medicine, which would provide innovative perspectives on disease study and new theoretical basis for early diagnosis, personalized treatment and medicine guide. In this review, we introduce new technologies and research progresses in screening therapeutic targets using systematic omics such as genomics, transcriptomics and epigenomics, and also discusse new strategies and advantages of integrative analysis among them.

Key words: genomic, transcriptomic, epigenetic, integrative analysis, disease targets