Multiplex gene and phenotype network to characterize shared genetic pathways of epilepsy and autism

Abstract It is well established that epilepsy and autism spectrum disorder (ASD) commonly co-occur; however, the underlying biological mechanisms of the co-occurence from their genetic susceptibility are not well understood. Our aim in this study is to characterize genetic modules of subgroups of ep...

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Autores principales: Jacqueline Peng, Yunyun Zhou, Kai Wang
Formato: article
Lenguaje:EN
Publicado: Nature Portfolio 2021
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Acceso en línea:https://doaj.org/article/538145d3e7294c148050618d6296d848
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Sumario:Abstract It is well established that epilepsy and autism spectrum disorder (ASD) commonly co-occur; however, the underlying biological mechanisms of the co-occurence from their genetic susceptibility are not well understood. Our aim in this study is to characterize genetic modules of subgroups of epilepsy and autism genes that have similar phenotypic manifestations and biological functions. We first integrate a large number of expert-compiled and well-established epilepsy- and ASD-associated genes in a multiplex network, where one layer is connected through protein–protein interaction (PPI) and the other layer through gene-phenotype associations. We identify two modules in the multiplex network, which are significantly enriched in genes associated with both epilepsy and autism as well as genes highly expressed in brain tissues. We find that the first module, which represents the Gene Ontology category of ion transmembrane transport, is more epilepsy-focused, while the second module, representing synaptic signaling, is more ASD-focused. However, because of their enrichment in common genes and association with both epilepsy and ASD phenotypes, these modules point to genetic etiologies and biological processes shared between specific subtypes of epilepsy and ASD. Finally, we use our analysis to prioritize new candidate genes for epilepsy (i.e. ANK2, CACNA1E, CACNA2D3, GRIA2, DLG4) for further validation. The analytical approaches in our study can be applied to similar studies in the future to investigate the genetic connections between different human diseases.