Open AccessEdgetic perturbation models of human inherited disorders
Author(s) -
Zhong Quan,
Simonis Nicolas,
Li QianRu,
Charloteaux Benoit,
Heuze Fabien,
Klitgord Niels,
Tam Stanley,
Yu Haiyuan,
Venkatesan Kavitha,
Mou Danny,
Swearingen Venus,
Yildirim Muhammed A,
Yan Han,
Dricot Amélie,
Szeto David,
Lin Chenwei,
Hao Tong,
Fan Changyu,
Milstein Stuart,
Dupuy Denis,
Brasseur Robert,
Hill David E,
Cusick Michael E,
Vidal Marc
Publication year - 2009
Publication title -
molecular systems biology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 8.523
H-Index - 148
ISSN - 1744-4292
DOI - 10.1038/msb.2009.80
Subject(s) - interactome , biology , computational biology , phenotype , systems biology , genetics , gene , gene regulatory network , allele , disease , biological network , mutant , human genetics , bioinformatics , gene expression , medicine , pathology
Cellular functions are mediated through complex systems of macromolecules and metabolites linked through biochemical and physical interactions, represented in interactome models as ‘nodes’ and ‘edges’, respectively. Better understanding of genotype‐to‐phenotype relationships in human disease will require modeling of how disease‐causing mutations affect systems or interactome properties. Here we investigate how perturbations of interactome networks may differ between complete loss of gene products (‘node removal’) and interaction‐specific or edge‐specific (‘edgetic’) alterations. Global computational analyses of ∼50 000 known causative mutations in human Mendelian disorders revealed clear separations of mutations probably corresponding to those of node removal versus edgetic perturbations. Experimental characterization of mutant alleles in various disorders identified diverse edgetic interaction profiles of mutant proteins, which correlated with distinct structural properties of disease proteins and disease mechanisms. Edgetic perturbations seem to confer distinct functional consequences from node removal because a large fraction of cases in which a single gene is linked to multiple disorders can be modeled by distinguishing edgetic network perturbations. Edgetic network perturbation models might improve both the understanding of dissemination of disease alleles in human populations and the development of molecular therapeutic strategies.