Integrative genomics identifies a convergent molecular subtype that links epigenomic with transcriptomic differences in autism

• Published in: Nature communications Vol. 11; no. 1; pp. 4873 - 14
• Main Authors: Ramaswami, Gokul, Won, Hyejung, Gandal, Michael J., Haney, Jillian, Wang, Jerry C., Wong, Chloe C. Y., Sun, Wenjie, Prabhakar, Shyam, Mill, Jonathan, Geschwind, Daniel H.
• Format: Journal Article
• Language: English
• Published: London Nature Publishing Group UK 25.09.2020; Nature Portfolio
• Subjects: 38; 38/61; 38/91; 45; 45/15; 631/114/2114; 631/208/177; 631/208/199; 631/337/176; 692/617/375/366/1373; Humanities and Social Sciences; multidisciplinary; Science; Science (multidisciplinary)
• ISSN: 2041-1723; 2041-1723
• DOI: 10.1038/s41467-020-18526-1

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. Autism spectrum disorder (ASD) is a neurodevelopmental disorder characterized by impaired social interactions with repetitive and restrictive behaviours. Here the authors integrate mRNA expression, miRNA expression, DNA methylation, and histone acetylation datasets from a collection of post mortem brain tissues and identify a convergent molecular subtype of ASD.