Relations between Executive Function and Sleep in ASD Children with Comorbid ADHD Symptoms

Poster Presentation
Thursday, May 10, 2018: 5:30 PM-7:00 PM
Hall Grote Zaal (de Doelen ICC Rotterdam)
A. M. Cremone-Caira1, J. Buirkle2, K. Trier2, R. Gilbert2 and S. Faja2, (1)Boston Children's Hospital Labs of Cognitive Neuroscience, Boston, MA, (2)Boston Children's Hospital, Boston, MA
Background: Approximately 50% of children with ASD have concurrent symptoms of ADHD (Rommelse et al., 2010). Alongside the hallmark symptoms of these disorders, children with ASD and ADHD commonly have executive function (EF) deficits and sleep disturbances (Corbett et al., 2009; Thomas et al., 2015). Whether sleep or EF predict comorbidity of ADHD symptoms in ASD is unknown. Understanding factors that contribute to, or exacerbate, comorbidity may improve interventions and clinical outcomes in these populations.

Objectives: To determine whether EF and sleep disturbances predict comorbid ADHD symptoms in children with ASD.

Methods: Caregivers of 108 children with ASD (17 females; Mage=9.13±1.38 years) completed the BRIEF (n=103) and Children’s Sleep Habits Questionnaire (CSHQ; n=99) to gauge EF and sleep. The Total CSHQ Score was used to index global sleep disturbance and differentiate children with (n=64) and without (n=35) clinically significant levels of sleep problems (Total CSHQ Score >41; Owens, Spirito, & McGuinn, 2000). The ADHD subscale of the CBCL was used to assess comorbid ADHD symptoms (n=103). Higher scores on these measures reflect greater impairment in functioning.

Results: BRIEF Index Scores and ADHD symptoms did not differ between children with and without clinically significant sleep problems (p’s³0.210). BRIEF outcomes were positively correlated with ADHD symptoms in both groups (r’s³0.270, p’s£0.046). In a linear regression model, greater deficits on the BRIEF Metacognitive Index (β=0.419, p=0.001) and greater Total CSHQ Scores (β=0.214, p=0.060) were independently associated with increased ADHD symptoms among children with clinical sleep problems. Total CSHQ Scores did not predict ADHD symptoms in the group of children without clinical sleep problems (β=-0.024, p=0.881). Among children with clinical sleep problems, follow-up analysis of subscales included in the Metacognitive Index indicated that more problems with Working Memory (WM) were associated with increased ADHD symptoms (β=0.550, p£0.001). Total CSHQ Score was also significantly related to increased ADHD symptoms (β=0.228, p=0.028) in this model. However, WM and Total CSHQ did not interact to predict additional variance in ADHD symptoms (β=0.096, p=0.437).

Conclusions: Preliminary analyses indicate that children with ASD who have EF deficits and clinically significant sleep problems are more likely to have ADHD symptoms than children without sleep problems. These findings are consistent with work suggesting that both EF deficits and poor sleep contribute to comorbid neurodevelopmental disorders. Previous literature indicates that poor sleep is related to WM deficits in typically developing children (Steenari et al., 2003). As WM is impaired in ASD and ADHD (Andersen et al., 2015), the results of the current study suggest that targeting sleep may improve WM and, consequently, improve clinical outcomes in children with comorbid diagnoses. Importantly, however, WM and Total CSHQ Score did not interact to predict comorbid ADHD symptoms in this sample, suggesting that EF and sleep act through independent mechanisms to increase vulnerability for comorbidity. Future analyses will evaluate the role of specific sleep deficits (CSHQ subscales) and objective measures of EF in predicting comorbid outcomes.