Rare de novo variants associated with autism implicate a large functional network of genes involved in formation and function of synapses
By S. R. Gilman, I. Iossifov, D. Levy, M. Ronemus, M. Wigler, Dennis Vitkup. Neuron, 2011
699 citations recorded by the source corpus.
Summary 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. Identification of complex molecular networks underlying common human phenotypes is a major challenge of modern genetics. Recent evidence suggests that rare variants, including copy number variations (CNVs), play a significant role in the etiology of autism spectrum disorders (ASD). Although many such variants have been identified, the specific molecular networks associated with this complex disorder remain largely unknown. 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 discovered through an unbiased genome-wide study 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 observed in a large collection of affected individuals.
Subfields: Cell Biology, Cognitive Neuroscience, Molecular Biology
View Paper: https://www.semanticscholar.org/paper/fb39910b70a3db7821fa784b7c3bfd33d002ff00
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Cell Biology
In Cognitive Neuroscience
- Simon Baron-Cohen
- Meng-Chuan Lai
- Michael V. Lombardo
- Bhismadev Chakrabarti
- Bonnie Auyeung
- Daniel H. Geschwind
- Thomas Bourgeron
- Catherine Lord
In Molecular Biology
- Michael C. Schatz
- Catherine Lord
- W. Richard McCombie
- Benjamin J. Blencowe
- Michael Jeffrey Gandal
- Neelroop Parikshak
- Marc Vidal
- Richard K. Wilson
Citations in the corpus
- Autism risk factors: genes, environment, and gene-environment interactions (2012, background): “This model is supported by the observation that all recurrent genetic defects reported in autism, including autism without mental retardation, have been causally implicated in intellectual disability,(56) and that analysis of the genes affected by rare CNVs reveal that they are strongly functionally”
- Sex/Gender Differences and Autism: Setting the Scene for Future Research (2015, methodology): “Corresponding to the predictions from the multi-factorial multi-threshold etiological model (level 3) that females with autism have a greater etiological/genetic load (reflecting a female-protective effect), data from the SSC show a trend toward more gene-rich de novo copy number variations (CNVs) i”
- Rare de novo and transmitted copy-number variation in autistic spectrum disorders. (2011, neutral): “For this reason, we have attempted to perform automated func- 894 Neuron 70, 886–897, June 9, 2011 ª2011 Elsevier Inc. tional network analysis in a companion paper (Gilman et al., 2011).”
- Convergence of Genes and Cellular Pathways Dysregulated in Autism Spectrum Disorders (2014, background): “Enrichment of synaptic functioning has also been reported among inherited events in the AGRE families(47) and among de novo events in the Simons Simplex Collection.(36) Enriched sets delineate candidate genes disrupted by deletions not found in control subjects; these genes notably include those in ”
- Selecting causal genes from genome-wide association studies via functionally-coherent subnetworks (2014, background): “Full details of all GWA studies (including all associated SNPs) are available in supplementary tables and 4 .”
- A highly conserved program of neuronal microexons is misregulated in autistic brains (2014, background): “A GO analysis of genes with ASD-associated misregulation of microexons reveals significant enrichment of terms related to axonogenesis and synapse biology (Figure 7E), processes that have been previously implicated in autism (Gilman et al., 2011; Parikshak et al., 2013; Voineagu et al., 2011).”
- De Novo Gene Disruptions in Children on the Autistic Spectrum (2012, methodology): “To measure the significance of the observed overlap between the 72 CNV candidates and the FMRP-associated genes, we performed a permutation test: random CNV regions were selected, preserving the number of genes as in the real CNVs, the 72 most interconnected genes were identified using the greedy op”
- Systems biology and gene networks in neurodevelopmental and neurodegenerative disorders (2015, methodology): “The Network-Based Analysis of Genes (NETBAG) 127 approach combines multiple forms of literature-curated data using an integrated network approach that has been demonstrated to be effective for predicting gene essentiality in yeast 128 .”