Autism spectrum disorders: from genes to neurobiology

Abstract

Advances in genome-wide technology, coupled with the availability of large cohorts, are finally yielding a steady stream of autism spectrum disorder (ASD) genes carrying mutations of large effect. These findings represent important molecular clues, but at the same time present notable challenges to traditional strategies for moving from genes to neurobiology. A remarkable degree of genetic heterogeneity, the biological pleiotropy of ASD genes, and the tremendous complexity of the human brain are prompting the development of new strategies for translating genetic discoveries into therapeutic targets. Recent developments in systems biology approaches that 'contextualize' these genetic findings along spatial, temporal, and cellular axes of human brain development are beginning to bridge the gap between high-throughput gene discovery and testable pathophysiological hypotheses.

Figure 1. Systems biology approaches in ASD

Two main types of systems biology analysis, which we refer to as ‘static’ versus ‘contextualized’, have been recently applied to ASD genes. Panel A: A set of 131 ASD risk genes [40] evaluated for enrichment of gene ontology terms using DAVID [71,72] identifies ‘chromatin regulator’, ‘alternative splicing’, and ‘phosphoprotein’ as enriched terms. The grids illustrate temporal (X-axis; developmental periods as defined in [66]) and spatial (Y-axis; anatomical brain regions) variables, and the intensity of red indicates the strength of evidence in each panel. The ‘?’ in panel A reflects the absence of data on these dimensions from static enrichment analyses. Panels B-E: illustrate several recent approaches to contextualized analyses: Panel B: BrainSpan exon array expression dataset was used to create co-expression networks based on a small number of high confidence ASD genes [40]. Each of the spatially and temporally defined networks was then evaluated for the presence of additional ASD associated genes. Two spatiotemporal windows were found to be significantly enriched for ASD genes: midfetal prefrontal cortex and thalamus/cerebellar cortex during neonatal to early childhood. The enriched networks were then assessed for additional properties with regard to cortical layer and cell type [66]. Panel C: Weighted gene co-expression network analysis was conducted with BrainSpan RNA-seq expression data from the neocortex, and resultant modules were assessed for enrichment of ASD-associated genes [68]. Based on the temporal expression pattern and biological properties of the genes within enriched modules, biological processes likely key during early fetal development and late fetal to early infancy were identified. Laminar and cellular specificity were also assessed. Panel D: A specificity index was calculated by brain region and developmental epoch for expression of ASD risk genes identified from whole-exome sequencing [31-35]. The authors determined that expression of the set of ASD genes is particularly specific to early midfetal neocortex as well as the early midfetal striatum [69]. Panel E: A third recent analysis utilized exon transcriptome-mutation contingency indices [70]. After summarizing exon level mutation rates based on population controls, the authors identified critical exons (defined as having high expression but low mutational burden) and observed that enrichment of critical exons in genes mutated in ASD cases versus unaffected sibling controls [33,35] is strongest in prenatal neocortex and striatum.