Calculating genetic risk for dysfunction in pleiotropic biological processes using whole exome sequencing data

Abstract

Background: Numerous genes are implicated in autism spectrum disorder (ASD). ASD encompasses a wide-range and severity of symptoms and co-occurring conditions; however, the details of how genetic variation contributes to phenotypic differences are unclear. This creates a challenge for translating genetic evidence into clinically useful knowledge. Sleep disturbances are particularly prevalent co-occurring conditions in ASD, and genetics may inform treatment. Identifying convergent mechanisms with evidence for dysfunction that connect ASD and sleep biology could help identify better treatments for sleep disturbances in these individuals.

Methods: To identify mechanisms that influence risk for ASD and co-occurring sleep disturbances, we analyzed whole exome sequence data from individuals in the Simons Simplex Collection (n = 2380). We predicted protein damaging variants (PDVs) in genes currently implicated in either ASD or sleep duration in typically developing children. We predicted a network of ASD-related proteins with direct evidence for interaction with sleep duration-related proteins encoded by genes with PDVs. Overrepresentation analyses of Gene Ontology-defined biological processes were conducted on the resulting gene set. We calculated the likelihood of dysfunction in the top overrepresented biological process. We then tested if scores reflecting genetic dysfunction in the process were associated with parent-reported sleep duration.

Results: There were 29 genes with PDVs in the ASD dataset where variation was reported in the literature to be associated with both ASD and sleep duration. A network of 108 proteins encoded by ASD and sleep duration candidate genes with PDVs was identified. The mechanism overrepresented in PDV-containing genes that encode proteins in the interaction network with the most evidence for dysfunction was cerebral cortex development (GO:0,021,987). Scores reflecting dysfunction in this process were associated with sleep durations; the largest effects were observed in adolescents (p = 4.65 × 10^-3).

Conclusions: Our bioinformatic-driven approach detected a biological process enriched for genes encoding a protein-protein interaction network linking ASD gene products with sleep duration gene products where accumulation of potentially damaging variants in individuals with ASD was associated with sleep duration as reported by the parents. Specifically, genetic dysfunction impacting development of the cerebral cortex may affect sleep by disrupting sleep homeostasis which is evidenced to be regulated by this brain region. Future functional assessments and objective measurements of sleep in adolescents with ASD could provide the basis for more informed treatment of sleep problems in these individuals.

Keywords: Autism spectrum disorders; Exome sequencing; Genetic risk scores; Pleiotropy; Sleep duration; Systems biology.

Fig. 1

Evidence of any dysfunction in pleiotropy network biological processes in individuals with ASD. Plotted are the proportion of individuals with autism spectrum disorder (ASD) with evidence of dysfunction (DBP > 0) versus no evidence of dysfunction (DBP = 0) in biological processes with overrepresentation of ASD and/or sleep duration (SD) genes in the ASD-SD protein–protein interaction network

Fig. 2

Genetic risk scores reflecting the level of dysfunction in pleiotropy network biological processes in individuals with ASD. Shown are the distributions of raw scores, across individuals with autism spectrum disorder (ASD), for each process with significantly more PDV-containing genes encoding proteins in the ASD-sleep duration protein–protein interaction network. No scores were normally distributed (p ≤ 8.46 × 10^–48)

Fig. 3

Network of proteins encoded by autism spectrum disorder (ASD) and sleep duration (SD) genes implicated in cerebral cortex development. Shown is the protein–protein interaction network predicted for the products of genes with predicted damaging variants identified in individuals with ASD that are assigned to the Gene Ontology biological process of “GO:0,021,987: cerebral cortex development”. Proteins are colored according to the associated condition as follows: blue = ASD-related protein, yellow = SD-related protein, green = both ASD, and SD-related protein

Fig. 4

Association between dysfunctional cerebral cortex development scores and sleep duration. Plotted is the linear prediction for the relationship between dysfunctional biological process (DBP) scores for cerebral cortex development (GO:0,021,987) and reported sleep duration in minutes. 95% confidence intervals around fitted lines are indicated in gray; Beta coefficients (β) and the corresponding p value are provided