Genetic factors contribute significantly to Autism Spectrum Disorders, yet no single genetic factor accounts for more than 1% of ASD cases, indicating significant heterogeneity. This leads to the question: Is autism a heterogeneous collection of hundreds of distinct, individually rare conditions, or are there common pathways into which these rare conditions can be grouped?
To provide an overview of gene expression studies in ASD, which provide a genome-wide, relatively unbiased assessment of pathway convergence in ASD.
We performed gene expression in blood and brain using microarrays, and in some cases RNAseq and used multiple types of analyses to assess convergence. One method uses an “outlier analysis” approach to identify gene expression changes associated with certain individual pathogenic mutations in the Simons Simplex Collection (e.g. Luo et al. 2012 AJHG) and in AGRE. This method is based on the assumption that ASD is a collection of rare disorders. Another approach involves direct comparison between blood or lymphoblast gene expression in probands versus siblings as a group. This method is implicitly searching for some common shared risk among probands. Finally, we have performed gene expression profiling in brain, using multiple analytic methods to define the molecular pathology and gene expression networks associated with ASD.
Outlier analysis shows that genes dysregulated in probands, but not in unaffected siblings, are enriched in development/ neurogenesis/ synaptogenesis (neural related pathways; p = 9.54E-03), and synaptic cell adhesion (p = 2.0E-02). Some of these same pathways are altered in brain gene expression studies and in our study of gene expression in lymphoblasts focusing on monogenic chromosomal disorders that increase risk for ASD. These data suggest a very strong peripheral signal in rare, monogenic forms of ASD, including del(16p) and dup(22q). When we take the approach that searches for common derangements of expression across ASD, we find that the signal separating cases from controls is much less strong than when using the rare variant approach. This is consistent with GWAS studies that show no strong individual SNP effects, but an overall skewing of association, which favors the contribution of multiple small variants of small effect. Finally, overlapping the brain data with the blood data identifies a few genes that are differentially expressed in ASD in both cases.
Rare pathogenic structural variants cause significant transcriptomic changes that converge on neural pathways, even in peripheral blood. Similarly, gene expression in brain suggests convergent molecular processes might link cases of ASD with distinct molecular etiologies. This may have significant implications for therapeutic development.