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Review
. 2016 Dec;73(23):4517-4530.
doi: 10.1007/s00018-016-2304-0. Epub 2016 Jul 12.

Searching for convergent pathways in autism spectrum disorders: insights from human brain transcriptome studies

Akira Gokoolparsadh  1 , Gavin J Sutton  1 , Alexiy Charamko  1 , Nicole F Oldham Green  1 , Christopher J Pardy  1 , Irina Voineagu  2
Affiliations
Review

Searching for convergent pathways in autism spectrum disorders: insights from human brain transcriptome studies

Akira Gokoolparsadh et al. Cell Mol Life Sci. 2016 Dec.

Abstract

Autism spectrum disorder (ASD) is one of the most heritable neuropsychiatric conditions. The complex genetic landscape of the disorder includes both common and rare variants at hundreds of genetic loci. This marked heterogeneity has thus far hampered efforts to develop genetic diagnostic panels and targeted pharmacological therapies. Here, we give an overview of the current literature on the genetic basis of ASD, and review recent human brain transcriptome studies and their role in identifying convergent pathways downstream of the heterogeneous genetic variants. We also discuss emerging evidence on the involvement of non-coding genomic regions and non-coding RNAs in ASD.

Keywords: Autism; Brain; Transcriptome.

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Figures

Fig. 1
Fig. 1
Outline of study designs for integrating human brain transcriptome data and genetic association data in ASD. Left transcriptome data are generated from ASD and control brain tissue. Right transcriptome data are generated from brain tissue samples from healthy individuals. These data can include multiple brain regions, multiple cortical layers or distinct developmental or aging stages. The integration of normal brain transcriptome data with genetic variant data can be done using either a seeded approach (by identifying genes coexpressed with ASD-associated genes) or a data-driven approach (by constructing coexpression networks and then assessing their overrepresentation for ASD associated variants). CAGE: cap analysis of gene expression
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