Journal Article

Edgetic perturbation models of human inherited disorders

Cusick, Michael E, Dupuy, Denis, Simonis, Nicolas, Li, Qian‐Ru, Heuze, Fabien, Szeto, David, Yu, Haiyuan, Vidal, Marc, Swearingen, Venus, Yan, Han, Mou, Danny, Dricot, Amélie, Hill, David E, Yildirim, Muhammed A, Zhong, Quan, Charloteaux, Benoit, Lin, Chenwei, Hao, Tong, Venkatesan, Kavitha, Fan, Changyu, Klitgord, Niels, Brasseur, Robert, Milstein, Stuart, Tam, Stanley

2009

Overview

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. Synopsis Genotype‐to‐phenotype relationships in human genetic disease are often modeled as: ‘mutation in gene X leads to loss of gene product X, which leads to disease A’. However, single ‘gene‐loss’ models cannot explain the increasingly appreciated prevalence of complex genotype‐to‐phenotype relationships, particularly with instances of allelic or locus hetrogeneity (Goh et al , 2007 ). Genes and gene products function not in isolation but as components of complex networks of macromolecules (DNA, RNA, or proteins) and metabolites linked through biochemical or physical interactions, often represented in ‘interactome’ network models as ‘nodes’ and ‘edges’, respectively. Here we use network perturbation models to explain molecular dysfunctions underlying human disease in addition to the gene‐loss model. We hypothesize that different mutations leading to different molecular defects to proteins may cause distinct perturbations of cellular networks, giving rise to distinct phenotypic outcomes (Figure 1 ). For example, truncations close to the start of an open‐reading frame, or mutations that grossly destabilize a protein structure, can be modeled as removing a protein node from the network (‘node removal’). Alternatively, single amino‐acid substitutions that affect specific binding sites, or truncations that preserve certain domains of a protein, may give rise to partially functional gene products with specific changes in distinct molecular interaction(s) (edge‐specific or ‘edgetic’ perturbations) (Figure 1B ). Taking advantage of the large number of known disease‐causing allelic variations in human Mendelian disorders, we investigated how disease‐associated mutations may cause complete loss of gene products or, alternatively, may cause specific loss or gain of individual molecular interaction(s). We examined ∼50 000 Mendelian disease‐causing alleles, affecting over 1900 protein‐coding genes, altogether associated with more than 2000 human disorders available in the Human Gene Mutation Database (HGMD) (Stenson et al , 2003 ), that can be subdivided into two subsets: truncating’ alleles (truncations or frameshifts caused by stop codons, out‐of‐frame insertions or deletions, or defective splicing) versus ‘in‐frame’ alleles (missense mutations and in‐frame insertions or deletions). Over 50% (27 919/52 491) of Mendelian alleles in HGMD correspond to ‘in‐frame’ mutations. Our hypothesis is that, ‘in‐frame’ alleles may affect specific interactions of a given gene product while leaving most other interactions unperturbed. Although exceptions may apply, our hypothesis has several predictions. First, ‘truncating’ versus ‘in‐frame’ alleles may distribute differently among autosomal dominant and autosomal recessive disease, given that dominant mutations are more likely to be edgetic than recessive ones. Indeed, autosomal dominant and autosomal recessive traits annotated in the Online Mendelian Inheritance in Man (OMIM) database (Hamosh et al , 2005 ) show a clear separation with respect to the associated ‘in‐frame’ versus ‘truncating’ mutations. Among genes affected solely by ‘in‐frame’ mutations, the proportion of dominant diseases is ∼10‐fold higher than that of recessive ones, supporting ‘in‐frame’ mutations causing distinct molecular defects as opposed to ‘truncating’ mutations. A proof‐of‐principle characterization of binary protein interaction defects of mutant alleles associated with five genetic disorders supports our hypothesis that ‘in‐frame’ alleles indeed produce mostly functional proteins, preserving many specific protein interactions. As grossly disruptive mutations versus mutations leading to loss or gain of specific interaction(s) probably distribute differently on protein structures, we examined available three‐dimensional structures of all disease proteins. Mutated residues in autosomal dominant disease are significantly more exposed to the surface of the structure than those in autosomal recessive disease, consistent with the idea that disease with distinct modes of inheritance probably involves distinct network perturbations. A second testable prediction of our edgetic perturbation model is that edgetic perturbation versus gene loss for a given gene product might in some cases cause different diseases. We examined 142 genes associated with two or more distinct diseases in which at least five distinct alleles have been reported for each disease. We found ∼30% of the cases for which distribution of ‘in‐frame’ versus ‘truncating’ mutations is significantly different between the two diseases linked to the same gene ( P <0.05). Hence, when affecting the same gene, node removal versus edgetic perturbation can confer strikingly different phenotypes. A third testable prediction is that different edgetic perturbations for a given gene product might cause phenotypically distinguishable diseases (Figure 6 ). We used predicted Pfam domains (Finn et al , 2006 ) as surrogates for functional interaction domains, assuming that ‘in‐frame’ mutations located in distinct Pfam domain‐encoding sequences probably alter distinct interactions. Among 169 genes associated with two or more diseases and encoding proteins containing at least two Pfam domains, nine proteins have at least two Pfam domains significantly enriched with ‘in‐frame’ mutations ( P <0.05). For each of the nine proteins, we found a striking pattern of near mutual exclusivity, whereby different Pfam domains seem to be specifically affected in distinct disorders (Figure 6B ). We conclude that edgetic alleles probably underlie many complex genotype‐to‐phenotype relationships in human disease, such as incomplete penetrance or variable expressivity, as well as allele‐specific phenotypic variations among patients. Edgetic perturbation of human inherited disorders might help explain how seemingly devastating alleles have appeared and persevered in human populations. We present alternative models to explain molecular dysfunctions underlying human inherited disorders based on interaction‐specific or “edgetic” perturbations rather than complete loss of gene products. We find that a substantial fraction of known genetic variants in human Mendelian disorders likely cause edgetic perturbations. We find frequent situations where edgetic perturbation models can explain how different mutations in a single gene can cause distinct disorders. Edgetic perturbation models should provide alternative explanations to complex genotype‐to‐phenotype relationships

• Publisher: Nature Publishing Group UK,John Wiley & Sons, Ltd,EMBO Press,Nature Publishing Group,Springer Nature
• Subject: Alleles / binary protein interaction / Binding sites / Biochemistry, biophysics & molecular biology / Biochimie, biophysique & biologie moléculaire / Complex systems / Computer applications / Defects / Disease / Disease - genetics / Disorders / EMBO24 / Genes / Genetic Diseases, Inborn - genetics / Genetic disorders / Genotype & phenotype / Genotypes / genotype‐to‐phenotype relationships / Hereditary diseases / human Mendelian disorders / Human populations / Humans / Hypotheses / Life sciences / Macromolecules / Metabolites / Models, Genetic / Mutation / Mutation - genetics / network perturbation / Nodes / Ontology / Perturbation methods / Phenotypes / Population genetics / Proteins / Sciences du vivant / Transcription factors