Recent studies into the genetics of Autism spectrum disorders (ASD) have implicated both common and rare variants, including de-novo mutations, as risk factors for ASD. However, how much of the genetic risk can be attributed to rare versus common alleles is unknown. Furthermore, the genes already known to be disrupted by rare variants still account for only a small proportion of the cases. This genetic heterogeneity constitutes a considerable obstacle to establishing a thorough understanding of the etiology of ASD.
Objectives:
We used a system biology approach to address several fundamental questions regarding the genetic architecture of autism. First, can we identify gene networks that are perturbed by rare variations that in turn lead to ASD? Second, can we identify gene networks that are perturbed by common variations? Third, do rare and common variations converge on the same molecular pathways or do they represent diverse biological etiologies? Lastly, are genes in these modules expressed during specific periods in life which represent significant time points in the development of ASD?
Methods:
To answer these questions we first constructed a gene network using a WGCNA approach based on a widespread survey of gene expression undertaken by the Allen Human Brain Atlas project (http://www.brain-map.org). This survey of gene expression includes 1340 microarray measurements, representing the entirety of the adult human brain. Then, the network was integrated with results of a published autism genome-wide association study (GWAS), as well as with a database of known rare mutations in ASD. In order to identify the expression pattern of the modules during brain development, we used data from the BrainSpan database (http://developinghumanbrain.org/), including 492 microarray measurements of individuals ranging from 8 weeks post-conception to 40 years of age.
Results:
The constructed network included modules associated with specific cell types and processes. These include two neuronal modules that were found to be enriched for both rare and common variations that are potentially associated with ASD risk. The enrichment for common variations in these modules was validated in two independent cohorts. The module showing the highest enrichment for rare and common variants in ASD included highly connected genes that are involved in neuronal plasticity, and are expressed mainly in areas associated with learning and memory. Additionally, we found that the level of expression of the most connected genes in this module increases in the brain during fetal development, with a peak during the first year of life.
Conclusions:
Taken together, these results suggest a common role for rare and common variations in
autism, and illustrate how rare and de-novo mutations, in conjunction with common variations,
can act together to perturb key pathways involved in neuronal processes, and specifically
neuronal plasticity. Furthermore, the modules found in this study may serve as starting points
for designing potential therapeutic interventions for ASD.