A systems biology approach to genetic studies of complex diseases
A systems biology approach to genetic studies of complex diseases
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DOI：
10.1016/j.febslet.2005.08.058
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发表时间：
2005-10-10
期刊：
影响因子：
3.5
通讯作者：
Zhou, XD
中科院分区：
文献类型：
--
作者：
Xiong, MA;Feghali-Bostwick, CA;Zhou, XD
揭示复杂疾病的潜在机制给生物学家带来了巨大的挑战。然而，传统的连锁和连锁不平衡分析在识别孟德尔性状相关基因方面取得了成功，但在发现影响复杂疾病发展的基因方面却没有类似的成功。新兴的功能基因组和蛋白质组(‘组学’)资源和技术为开发系统识别复杂疾病相关基因的新方法提供了很好的机会。在这份报告中，我们提出了一种系统生物学方法，它整合了基因组数据，以寻找与复杂疾病有关的基因。该方法包括五个步骤：(1)利用基因-基因相互作用数据集生成候选基因集；(2)从基因表达数据中重建候选基因集；(3)识别网络中正常和异常样本之间的差异调控基因；(4)通过使用RNAi干扰网络并使用RT-PCR监测反应来验证网络中基因之间的调控关系；(5)对差异调控基因进行基因分型，并通过直接关联研究检验它们与疾病的关联。为了在原则上证明这一概念，所提出的方法被应用于自身免疫性疾病硬皮病或系统性硬化症的遗传学研究。(C)2005年，由Elsevier B.V.代表欧洲生化学会联合会出版。
Revealing mechanisms underlying complex diseases poses great challenges to biologists. The traditional linkage and linkage disequilibrium analysis that have been successful in the identification of genes responsible for Mendelian traits, however, have not led to similar success in discovering genes influencing the development of complex diseases. Emerging functional genomic and proteomic ('omic') resources and technologies provide great opportunities to develop new methods for systematic identification of genes underlying complex diseases. In this report, we propose a systems biology approach, which integrates omic data, to find genes responsible for complex diseases. This approach consists of five steps: (1) generate a set of candidate genes using gene-gene interaction data sets; (2) reconstruct a genetic network with the set of candidate genes from gene expression data; (3) identify differentially regulated genes between normal and abnormal samples in the network; (4) validate regulatory relationship between the genes in the network by perturbing the network using RNAi and monitoring the response using RT-PCR; and (5) genotype the differentially regulated genes and test their association with the diseases by direct association studies. To prove the concept in principle, the proposed approach is applied to genetic studies of the autoimmune disease scleroderma or systemic sclerosis. (c) 2005 Published by Elsevier B.V. on behalf of the Federation of European Biochemical Societies.