Network medicine: a network-based approach to human disease

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Abstract
A disease phenotype is rarely a consequence of an abnormality in a single effector gene product, but reflects various pathobiological processes that interact in a complex network. Here we present an overview of the organizing principles that govern cellular networks and the implications of these principles for understanding disease. Network-based approaches have potential biological and clinical applications, from the identification of disease genes to better drug targets. Whereas essential genes tend to be associated with hubs, or highly connected proteins, disease genes tend to segregate at the network's functional periphery, avoiding hubs. Disease genes have a high propensity to interact with each other, forming disease modules. The identification of these disease modules can help us to identify disease pathways and predict other disease genes. The highly interconnected nature of the interactome means that, at the molecular level, it is difficult to consider diseases as being independent of one another. The mapping of network-based dependencies between pathophenotypes has culminated in the concept of the diseasome, which represents disease maps whose nodes are diseases and whose links represent various molecular relationships between the disease-associated cellular components. Diseases linked at the molecular level tend to show detectable comorbidity. Network medicine has important applications to drug design, leading to the emergence of network pharmacology, and also in disease classification.