Abstract
Autism spectrum disorder (ASD) is a phenotypically and genetically heterogeneous neurodevelopmental disorder. Despite this heterogeneity, previous studies have shown patterns of molecular convergence in post-mortem brain tissue from autistic subjects. Here, we integrate genome-wide measures of mRNA expression, miRNA expression, DNA methylation, and histone acetylation from ASD and control brains to identify a convergent molecular subtype of ASD with shared dysregulation across both the epigenome and transcriptome. Focusing on this convergent subtype, we substantially expand the repertoire of differentially expressed genes in ASD and identify a component of upregulated immune processes that are associated with hypomethylation. We utilize eQTL and chromosome conformation datasets to link differentially acetylated regions with their cognate genes and identify an enrichment of ASD genetic risk variants in hyperacetylated noncoding regulatory regions linked to neuronal genes. These findings help elucidate how diverse genetic risk factors converge onto specific molecular processes in ASD.
Highlights
Autism spectrum disorder (ASD) is a phenotypically and genetically heterogeneous neurodevelopmental disorder
We utilize similarity network fusion (SNF), an integrative method that has identified molecular subtypes when integrating transcriptomic with epigenomic datasets in cancer[17], to integrate mRNA expression, miRNA expression, DNA methylation, and histone acetylation datasets from ASD brain (Fig. 1a)
We find an enrichment of ASD genetic risk in regulatory regions linked to neuronal genes that are hyperacetylated in ASD brains, suggesting a causal role for these elements
Summary
Autism spectrum disorder (ASD) is a phenotypically and genetically heterogeneous neurodevelopmental disorder. Assessment of ASD risk is challenging due to its genetic architecture which encompasses alleles of varying frequencies (common, rare, very rare) and inheritance patterns (Mendelian autosomal and X-linked, additive, de novo)[3,4,5] that likely interact together within individuals and families[6,7] Despite this genetic complexity, molecular studies have identified consistent patterns of changes in post-mortem brain tissue from ASD subjects[8,9,10,11,12]. We utilize similarity network fusion (SNF), an integrative method that has identified molecular subtypes when integrating transcriptomic with epigenomic datasets in cancer[17], to integrate mRNA expression, miRNA expression, DNA methylation, and histone acetylation datasets from ASD brain (Fig. 1a) This unbiased data-driven analysis identifies two distinct molecular subtypes of ASD, one, which represents the majority of cases, showing a cohesive molecular pattern, and the other without consistent changes in molecular measures. We find an enrichment of ASD genetic risk in regulatory regions linked to neuronal genes that are hyperacetylated in ASD brains, suggesting a causal role for these elements
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