MULTI-OMIC DATA PROVIDE A MORE COMPLETE UNDERSTANDING OF THE AUTISTIC BRAIN
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Date
2016-06-28
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Johns Hopkins University
Abstract
Autism is a complex neurodevelopmental disorder characterized by persistent social deficits and restricted or repetitive patterns of behavior. Despite an established genetic basis of the disorder, efforts to elucidate the genetic underpinnings of the disorder and our understanding of its etiology remains incomplete. As such, we set out to study the effects downstream of genetic variation by studying alterations in both gene expression and DNA methylation (DNAm) in post-mortem brain samples collected from individuals affected with autism and controls. This work highlights that even when there is no primary genetic lesion detected, the autistic brain shows a characteristic pattern of upregulation at M2-activation state microglia genes, a state potentially driven by Type I interferon responses. Additionally, by combining transcriptomic data across autism and two related neuropsychiatric disorders, schizophrenia and bipolar disorder, we have garnered a better understanding of the relationship between these disorders, where genes differentially expressed in autism are concordantly differentially expressed in schizophrenia, but not in bipolar disorder. Finally, as gene expression is regulated, at least in part, by DNAm, we have characterized DNAm at cytosines across the genome and have detected hypermethylation at cytosines outside the commonly-studied CpG context, suggesting that autistic brains have slight increases at many CpH sites (where H=A,T, or C) throughout their genome. These sites are enriched in repetitive regions of the genome and regions containing human-specific CpGs, offering an insight into how this hypermethylation may be functioning mechanistically. Taken together, by studying the downstream effects of genetic variation, at the levels of DNAm and gene expression, we have moved toward a more complete understanding of the autistic brain.
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Keywords
Autism, RNA-Sequencing, Transcriptomics, Gene Expression, Data Analysis, Genomics, Brain