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Chan, S. Y., & Loscalzo, J. (2012). The emerging paradigm of network medicine in the study of human disease. Circulation Research, 111(3), 359–374. Added by: Dr. Enrique Feoli (12/01/2021, 18:15) Last edited by: Dr. Enrique Feoli (04/02/2021, 02:21) |
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| Resource type: Journal Article DOI: 10.1161/CIRCRESAHA.111.258541 BibTeX citation key: Chan2012 View all bibliographic details  |
Categories: BioAcyl Corp Subcategories: Network Medicine Creators: Chan, Loscalzo Collection: Circulation Research |
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| Abstract |
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The molecular pathways that govern human disease consist of molecular circuits that coalesce into complex, overlapping networks. These network pathways are presumably regulated in a coordinated fashion, but such regulation has been difficult to decipher using only reductionistic principles. The emerging paradigm of “network medicine” proposes to utilize insights garnered from network topology (eg, the static position of molecules in relation to their neighbors) as well as network dynamics (eg, the unique flux of information through the network) to understand better the pathogenic behavior of complex molecular interconnections that traditional methods fail to recognize. As methodologies evolve, network medicine has the potential to capture the molecular complexity of human disease while offering computational methods to discern how such complexity controls disease manifestations, prognosis, and therapy. This review introduces the fundamental concepts of network medicine and explores the feasibility and potential impact of network-based methods for predicting individual manifestations of human disease and designing rational therapies. Wherever possible, we emphasize the application of these principles to cardiovascular disease.
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| Notes |
An introduction to network-based strategies in biomedical research.A, Hypothetical biological network. Essential genes (called “hubs”) demonstrate dense interconnectivity with other genes and hold a central topographical position in the network; nonessential genes (called “nodes”) tend to be placed at the network periphery and are less well connected to other genes. Genes that are responsible for normal biological variability tend to be nonessential, whereas deficiencies of “hub” genes typically cause embryonic lethality.1 Many human disease genes (arrow) are located at the periphery and display a preference to interact with other disease genes (the “local hypothesis”). Adapted from Chan et al,107 with permission. B, The universe of “network medicine” links genetic, “-OMIC,” biochemical, cellular, physiological, and clinical data to create an interconnected graph that can be used to model predictively a (patho)biological event(s). Adapted from Morel et al,108 with permission (illustration credit: Ben Smith). |
| Paraphrases |
Properties of biological networks.A, The connectivity of random networks is reflected by a Poisson distribution, whereas a scale-free (or clustered) network is defined by a power law distribution. As a result, there exist nodes that are sparsely linked as well as nodes that are more highly linked (hubs). B, As depicted by a hypothetical complex electric circuit, the detailed analysis of 1 or 2 resistors in isolation allows for little insight into the behavior of the circuit as a whole. Thus, similar to scale-free networks, this circuit displays emergent behavior. Moreover, detailed analysis of every resistor in the circuit is not necessary but rather can be inferred to understand the circuit as a whole. Thus, scale-free networks and this circuit are overdetermined. C, Depiction of the 3 modularity concepts of biological networks. Topological modules (left) are defined by locally dense neighborhoods of the interactome. Functional modules (gray nodes, center) are defined by network neighborhoods in which there is a statistically significant segregation of nodes of related function. Disease modules are groups of nodes whose perturbation (mutations, deletions, copy number variations, or expression changes) can be linked to a particular disease phenotype and can cross functional molecules, shown as red nodes. Adapted from Barabasi et al,1 with permission.
Added by: Dr. Enrique Feoli
(2021-01-12 18:23:45)
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