Depression and Anxiety in the Aging ASD Cohort: Relationships with Cognition and Social Networks

Background:  The population of adults with autism spectrum disorder (ASD) is rapidly growing, yet there are few studies investigating the effects of aging. ASD individuals have high comorbidity with other psychiatric disorders, especially depression and anxiety. In typically developing (TD) individuals, psychiatric symptoms increase with age which is hypothesized to be related to decreased social support. Many ASD individuals struggle with decreased social support at even younger ages. It is critical to understand mood symptom changes with age, since these factors negatively affect cognition, which can further impair functioning of ASD individuals.

Objectives:  To evaluate the relationship between age and mood measures in ASD, we utilized self-report measures of depression, anxiety, and social networks and related findings to cognitive scores. We hypothesized that psychiatric symptoms are exacerbated in older cohorts of ASD, and that symptoms are related to level of social support and predict cognition. 

Methods:  Data were obtained for 16 high-functioning middle-age (40-65 years) ASD, 11 young-adult ASD (18-25 years), and age-matched TD (16 middle-age; 9 young-adult) male participants. Self-report measures were Beck Depression Inventory-II (BDI-II), State-Trait Anxiety Inventory (STAI), and Social Network Index. Mood measures were correlated with cognitive measures of executive functioning, memory, and visual detail processing.

Results: Participants did not significantly differ in IQ (p=0.18). For all mood and social network measures, there were main effects for diagnosis, such that ASD participants reported higher levels of depression and anxiety and lower levels of social networks, as compared to TD (all p<0.01). Based on clinical cutoffs, 88% of the middle-age ASD group reported significant levels of anxiety and 44% reported significant depression, as compared to 45% in the young-adult ASD group for both anxiety and depression. Social network measures did not significantly correlate with mood measures in either middle-age or young-adult ASD participants. In young-adult ASD participants, mood measures significantly predicted performance on several cognitive measures, most pronounced for memory. However, mood measures did not correlate with cognitive performance in the middle-age ASD group. IQ levels did not account for a significant amount of the variance in any dependent measure and effects did not change when values were added as covariates. 

Conclusions:  Findings suggest older adults with ASD experience greater levels of depression and anxiety and less social support than their TD counterparts. Further, rates of clinically significant anxiety in this sample of older adults with ASD are higher than ever reported in younger samples, including the young-adults in the present study. Interestingly, mood symptoms did not correlate with measures of social support or cognition in middle-age ASD participants. This dissociation between mood and cognition suggests cognitive deficits in older adults with ASD may be mediated by other effects of aging. Further, increased rates of psychiatric symptoms may not be a result of lack of social support in older adults with ASD. Understanding age-related changes and accurately detecting symptoms through measures uniquely designed for the ASD population is essential to providing appropriate care plans and effective treatment interventions for mental health in ASD.