Department of Veterinary Integrative Biosciences, Texas A&M University, TX, USA.
Genome Biol Evol. 2010;2:815-25. doi: 10.1093/gbe/evq064. Epub 2010 Oct 11.
Genes that underlie human disease are important subjects of systems biology research. In the present study, we demonstrate that Mendelian and complex disease genes have distinct and consistent protein-protein interaction (PPI) properties. We show that five different network properties can be reduced to two independent metrics when applied to the human PPI network. These two metrics largely coincide with the degree (number of connections) and the clustering coefficient (the number of connections among the neighbors of a particular protein). We demonstrate that disease genes have simultaneously unusually high degree and unusually low clustering coefficient. Such genes can be described as brokers in that they connect many proteins that would not be connected otherwise. We show that these results are robust to the effect of gene age and inspection bias variation. Notably, genes identified in genome-wide association study (GWAS) have network patterns that are almost indistinguishable from the network patterns of nondisease genes and significantly different from the network patterns of complex disease genes identified through non-GWAS means. This suggests either that GWAS focused on a distinct set of diseases associated with an unusual set of genes or that mapping of GWAS-identified single nucleotide polymorphisms onto the causally affected neighboring genes is error prone.
人类疾病相关基因是系统生物学研究的重要课题。本研究表明，孟德尔遗传疾病和复杂疾病基因具有独特且一致的蛋白质-蛋白质相互作用（PPI）特性。我们发现，当应用于人类 PPI 网络时，五种不同的网络特性可以简化为两个独立的度量标准。这两个度量标准与节点的度（连接数）和聚类系数（特定蛋白质的邻居之间的连接数）高度吻合。我们证明疾病基因的度异常高，而聚类系数异常低。这些基因可以被描述为“经纪人”，因为它们连接了许多原本不会相互连接的蛋白质。我们还发现，这些结果对基因年龄和检测偏差变化的影响具有稳健性。值得注意的是，全基因组关联研究（GWAS）中鉴定出的基因与非疾病基因的网络模式几乎无法区分，而与通过非 GWAS 方法鉴定出的复杂疾病基因的网络模式显著不同。这表明，GWAS 可能集中在与一组不常见基因相关的一组特定疾病上，或者 GWAS 鉴定出的单核苷酸多态性映射到因果相关的邻近基因上存在错误。
