Rare De Novo Variants Associated with Autism Implicate a Large Functional Network of Genes Involved in Formation and Function of Synapses

Center for Computational Biology and Bioinformatics and Department of Biomedical Informatics, Columbia University, 1130 St. Nicolas Ave, New York, NY 10032, USA.
Neuron (Impact Factor: 15.05). 06/2011; 70(5):898-907. DOI: 10.1016/j.neuron.2011.05.021
Source: PubMed


Identification of complex molecular networks underlying common human phenotypes is a major challenge of modern genetics. In this study, we develop a method for network-based analysis of genetic associations (NETBAG). We use NETBAG to identify a large biological network of genes affected by rare de novo CNVs in autism. The genes forming the network are primarily related to synapse development, axon targeting, and neuron motility. The identified network is strongly related to genes previously implicated in autism and intellectual disability phenotypes. Our results are also consistent with the hypothesis that significantly stronger functional perturbations are required to trigger the autistic phenotype in females compared to males. Overall, the presented analysis of de novo variants supports the hypothesis that perturbed synaptogenesis is at the heart of autism. More generally, our study provides proof of the principle that networks underlying complex human phenotypes can be identified by a network-based functional analysis of rare genetic variants.

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    ABSTRACT: Modelling of gene networks is widely used in systems biology to study the functioning of complex biological systems. Most of the existing mathematical modelling techniques are useful for analysis of well-studied biological processes, for which information on rates of reactions is available. However, complex biological processes such as those determining the phenotypic traits of organisms or pathological disease processes, including pathogen-host interactions, involve complicated cross-talk between interacting networks. Furthermore, the intrinsic details of the interactions between these networks are often missing. In this study, we developed an approach, which we call mosaic network modelling, that allows the combination of independent mathematical models of gene regulatory networks and, thereby, description of complex biological systems. The advantage of this approach is that it allows us to generate the integrated model despite the fact that information on molecular interactions between parts of the model (so-called mosaic fragments) might be missing. To generate a mosaic mathematical model, we used control theory and mathematical models, written in the form of a system of ordinary differential equations (ODEs). In the present study, we investigated the efficiency of this method in modelling the dynamics of more than 10,000 simulated mosaic regulatory networks consisting of two pieces. Analysis revealed that this approach was highly efficient, as the mean deviation of the dynamics of mosaic network elements from the behaviour of the initial parts of the model was less than 10%. It turned out that for construction of the control functional, data on perturbation of one or two vertices of the mosaic piece are sufficient. Further, we used the developed method to construct a mosaic gene regulatory network including hepatitis C virus (HCV) as the first piece and the tumour necrosis factor (TNF)-induced apoptosis and NF-κB induction pathways as the second piece. Thus, the mosaic model integrates the model of HCV subgenomic replicon replication with the model of TNF-induced apoptosis and NF-κB induction. Analysis of the mosaic model revealed that the regulation of TNF-induced signaling by the HCV network is crucially dependent on the RIP1, TRADD, TRAF2, FADD, IKK, IκBα, c-FLIP, and BAR genes. Overall, the developed mosaic gene network modelling approach demonstrated good predictive power and allowed the prediction of new regulatory nodes in HCV action on apoptosis and the NF-κB pathway. Those theoretical predictions could be a basis for further experimental verification.
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    • "This notion has been put forward, where possible roles of stem cell proliferation and neuronal migration in ASD has been discussed (review Casanova 2014). However, when we consider the field as a whole, a strong emphasis has been laid on defective synaptogenesis, synapse maintenance, and neuronal activity (Glessner et al. 2009; Gilman et al. 2011; Baudouin et al. 2012; Berkel et al. 2012; Clement et al. 2012, 2013; Gai et al. 2012) (reviews Geschwind 2008; Walsh et al. 2008; Toro et al. 2010; van Bokhoven 2011; Grant 2012; Spooren et al. 2012; Zoghbi and Bear 2012). "
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    ABSTRACT: Autism Spectrum Disorders (ASD) encompass a group of neurodevelopmental diseases that demonstrate strong heritability, however the inheritance is not simple and many genes have been associated with these disorders. ASD is regarded as a neurodevelopmental disorder, and abnormalities at different developmental stages are part of the disease etiology. This review provides a general background on neuronal migration during brain development and discusses recent advancements in the field connecting ASD and aberrant neuronal migration. This article is protected by copyright. All rights reserved.
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    • "More recently, exome sequencing of parent– offspring trios has shown that de novo point mutations contribute to ASD in 10–30 % of sporadic patients (Murdoch and State 2013; Krumm et al. 2014; O'Roak et al. 2011, 2012; Sanders et al. 2012; Neale et al. 2012; Iossifov et al. 2012, 2014). These studies predicted that ASD could result from genetic abnormalities in several hundreds of different genes, many of which are, nonetheless, interconnected or part of common functional pathways (Neale et al. 2012; O'Roak et al. 2012; Sanders et al. 2012; Iossifov et al. 2012; Gilman et al. 2011). Examples of pathways repeatedly involved in ASD include: synaptic function, illustrated by mutations in SHANK1-3 scaffolding proteins, neuroligins , neurexins, contactins and contactin-associated proteins encoding genes; the mTOR pathway, illustrated by mutations in TSC1/TSC2 or PTEN that cause syndromic forms of ASD; chromatin remodeling; and Wnt signaling (Krumm et al. 2014; Jeste and Geschwind 2014; Huguet et al. 2013). "
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