Goh Kwang-Il, Cusick Michael E, Valle David, Childs Barton, Vidal Marc, Barabási Albert-László
Center for Complex Network Research and Department of Physics, University of Notre Dame, Notre Dame, IN 46556, USA.
Proc Natl Acad Sci U S A. 2007 May 22;104(21):8685-90. doi: 10.1073/pnas.0701361104. Epub 2007 May 14.
A network of disorders and disease genes linked by known disorder-gene associations offers a platform to explore in a single graph-theoretic framework all known phenotype and disease gene associations, indicating the common genetic origin of many diseases. Genes associated with similar disorders show both higher likelihood of physical interactions between their products and higher expression profiling similarity for their transcripts, supporting the existence of distinct disease-specific functional modules. We find that essential human genes are likely to encode hub proteins and are expressed widely in most tissues. This suggests that disease genes also would play a central role in the human interactome. In contrast, we find that the vast majority of disease genes are nonessential and show no tendency to encode hub proteins, and their expression pattern indicates that they are localized in the functional periphery of the network. A selection-based model explains the observed difference between essential and disease genes and also suggests that diseases caused by somatic mutations should not be peripheral, a prediction we confirm for cancer genes.
由已知的疾病-基因关联所连接的疾病和疾病基因网络,提供了一个平台,可在单一的图论框架中探索所有已知的表型和疾病基因关联,这表明许多疾病有着共同的遗传起源。与相似疾病相关的基因,其产物之间发生物理相互作用的可能性更高,其转录本的表达谱相似性也更高,这支持了存在不同的疾病特异性功能模块。我们发现,人类必需基因可能编码枢纽蛋白,且在大多数组织中广泛表达。这表明疾病基因在人类相互作用组中也可能发挥核心作用。相比之下,我们发现绝大多数疾病基因是非必需的,且没有编码枢纽蛋白的倾向,它们的表达模式表明它们位于网络的功能边缘。基于选择的模型解释了观察到的必需基因和疾病基因之间的差异,还表明由体细胞突变引起的疾病不应处于边缘位置,我们对癌症基因的研究证实了这一预测。