Network medicine: a network-based approach to human disease
By Albert-László Barabási, Natali Gulbahce & Joseph Loscalzo
Published: 17 December 2010
Given the functional interdependencies between the molecular components in a human cell, a disease is rarely a consequence of an abnormality in a single gene, but reflects the perturbations of the complex intracellular and intercellular network that links tissue and organ systems. The emerging tools of network medicine offer a platform to explore systematically not only the molecular complexity of a particular disease, leading to the identification of disease modules and pathways, but also the molecular relationships among apparently distinct (patho)phenotypes. Advances in this direction are essential for identifying new disease genes, for uncovering the biological significance of disease-associated mutations identified by genome-wide association studies and full-genome sequencing, and for identifying drug targets and biomarkers for complex diseases.
Key Points
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.