Disease global behavior: A systematic study of the human interactome network reveals conserved topological features among categories of diseases

Due to the complexity of human diseases, an inclusive approach such as network biology may be an appropriate choice to study their mechanism and investigate similar or distinctive patterns among disease groups. In literary works, network-based properties within phenotypically homogenous diseases have not been considered. This issue could help us in the diagnosis of diseases at beginning stages, finding an overall solution to treat analogous diseases, and exploring disease behavior. Herein, to answer the proposed question, we analyzed the human interactome network to manifest the topological patterns of different classes of diseases. Statistical comparisons suggest that the network structure of similar diseases in a group is conserved and differs from other groups. This is compatible with the fact that similar diseases in a category comprise a range of common origins such as pathways and cellular signaling interactions and gene expression profile. From network-based discriminating features, we focused on maximal cliques and observed that there are common super cliques inside disease families, which might be a reason for their related behaviors. Results illustrate that proteins inside maximal cliques have similar activities, and take part in the same biological processes. Existence of these functional modules in diseases of a family exhibits their influential roles. Keywords: Disease behavior, Maximal cliques, Network-based features, Human interactome, Systems biology

Abstract licence: CC BY-NC

A person counts once a day per paper. We keep no cookie and no address: a reader is a hash that changes every day. Any month under five reads shows no number.