Integrative analysis of human protein, function and disease networks

摘要: Protein-protein interaction (PPI) networks serve as a powerful tool for unraveling protein functions, disease-gene and disease-disease associations. However, a direct strategy for integrating protein interaction, protein function and diseases is still absent. Moreover, the interrelated relationships among these three levels are poorly understood. Here we present a novel systematic method to integrate protein interaction, function, and disease networks. We first identified topological modules in human protein interaction data using the network topological algorithm (NeTA) we previously developed. The resulting modules were then associated with functional terms using Gene Ontology to obtain functional modules. Finally, disease modules were constructed by associating the modules with OMIM and GWAS. We found that most topological modules have cohesive structure, significant pathway annotations and good modularity. Most functional modules (70.6%) fully cover corresponding topological modules, and most disease modules (88.5%) are fully covered by the corresponding functional modules. Furthermore, we identified several protein modules of interest that we describe in detail, which demonstrate the power of our integrative approach. This approach allows us to link genes, and pathways with their corresponding disorders, which may ultimately help us to improve the prevention, diagnosis and treatment of disease.