Abstract
Complex biological systems usually pose a trade-off between robustness and fragility where a small number of perturbations can substantially disrupt the system. Although biological systems are robust against changes in many external and internal conditions, even a single mutation can perturb the system substantially, giving rise to a pathophenotype. Recent advances in identifying and analyzing the sequential variations beneath human disorders help to comprehend a systemic view of the mechanisms underlying various disease phenotypes. Network-based disease-gene prioritization methods rank the relevance of genes in a disease under the hypothesis that genes whose proteins interact with each other tend to exhibit similar phenotypes. In this study, we have tested the robustness of several network-based disease-gene prioritization methods with respect to the perturbations of the system using various disease phenotypes from the Online Mendelian Inheritance in Man database. These perturbations have been introduced either in the protein-protein interaction network or in the set of known disease-gene associations. As the network-based disease-gene prioritization methods are based on the connectivity between known disease-gene associations, we have further used these methods to categorize the pathophenotypes with respect to the recoverability of hidden disease-genes. Our results have suggested that, in general, disease-genes are connected through multiple paths in the human interactome. Moreover, even when these paths are disturbed, network-based prioritization can reveal hidden disease-gene associations in some pathophenotypes such as breast cancer, cardiomyopathy, diabetes, leukemia, parkinson disease and obesity to a greater extend compared to the rest of the pathophenotypes tested in this study. Gene Ontology (GO) analysis highlighted the role of functional diversity for such diseases.
Highlights
A fundamental characteristic of biological systems is tolerance to noise
Complex biological systems have to balance between robustness and fragility which implies that a small number of rare perturbations can substantially disrupt the system [5]
Network-based disease gene prioritization methods rank the relevance of genes to a disease using known disease-gene associations and the network topology
Summary
A fundamental characteristic of biological systems is tolerance to noise. The ability to counteract both internal mechanistic failures and changes in environmental conditions plays a central role in the survival of the organism. Much effort needs to be taken to fully understand the complex implications on the whole system For this purpose, several methods have been developed recently to amplify available disease-gene associations using the principle of ‘‘guilt-by-association’’ through underlying biomolecular networks. Several methods have been developed recently to amplify available disease-gene associations using the principle of ‘‘guilt-by-association’’ through underlying biomolecular networks These methods typically exploit relationships of the disease causing genes with other candidate genes, using the neighborhood of known associations in the physical [7,8] or functional [9] interaction network. We have found that this was independent of the number of initial genes associated with the disease and rather mediated by the diversity of functions deduced by them These findings provide evidence on the role of functional diversity in defining robustness of biological systems
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