Attention-deficit/hyperactivity disorder and autism spectrum disorder (ASD) often coexist in children and adults, but the range of cognitive abilities can vary widely in these patients. Researchers from around the world are leveraging symptom, cognitive assessment, and neurobiological measures to gain insights on how individuals with ADHD/ASD approach and solve problems.
Several experts discussed the progress of their research during the session, “Overlap and differences of ADHD and autism – new findings of functional imaging and cognition studies” at the World Congress on ADHD – Virtual Event.
“The overlap of these two disorders is a critical issue for our field,” said Sarah Karalunas, PhD, assistant professor of clinical psychology at Purdue University, West Lafayette, Ind., who moderated the session. Clinicians are often asked to make differential diagnoses between these two disorders. Only recently has the DSM-5 allowed their codiagnosis. “There’s increasing recognition that there may be shared cognitive and physiological features that reflect their shared risk and account for the high levels of symptom overlap,” said Dr. Karalunas.
Shared cognitive markers
Under the DSM’s change, “it’s now recognized that an estimated 20%-60% of children with ASD have comorbidities with ADHD, and around 20%-40% of children with ADHD have ASD symptoms,” said Beth Johnson, PhD, a research fellow with the Turner Institute for Brain and Mental Health at Monash University, Melbourne.
The shared overlap on genetic traits and comorbidities such as intellectual disability, anxiety, depression, and oppositional defiant disorder, make it difficult for clinicians to predict clinical outcomes, noted Dr. Johnson.
“We’re now understanding that they’re likely to be multiple autisms and ADHDs, that these symptoms exist on a spectrum of severity or ability,” she said. Dr. Johnson discussed a data-driven subtyping approach based on neurocognitive and symptom profiles in children with ADHD. The aim was to better understand how symptoms are managed across ADHD, ASD and comorbid ASD-ADHD.
As part of this research, her team recruited 295 controls and 117 children with ADHD who underwent clinical phenotyping and also completed working memory tasks, stop signal, and sustained attention tasks.
The researchers divided the children into four stable clusters based on the ADHD rating scale and autism questionnaire data: high ASD/ADHD traits, high ADHD/low ASD, low ADHD/moderate ASD, and low ADHD/ASD. Approximately half of the children with ADHD showed moderate to high ASD symptoms. Looking at neurocognition across the tasks, unsurprisingly, performance was lowest among the high-ASD/ADHD children, with performance on the stop signal being the most pronounced. “Notably, performance on the working memory task worsened with increasing ADHD symptoms,” she reported.
Drift model identifies information processing
Dr. Karalunas has also compared subgroups of ADHD and ASD children. “Our analysis examined whether cognitive impairments in ASD reflect a shared risk mechanism or co-occurring ADHD symptoms and why we see an overlap in these types of impairments,” she said.
Her study included 509 children with ADHD, 97 with ASD, and 301 controls (typical development). All three groups underwent a full cognitive assessment battery that measured attention arousal, basic processing speed, and working memory. Those tasks were collapsed into a series of variables as well as a set of tasks measuring response inhibition, switching, interference control, reward discounting, and measure of reaction time variability.
Four cognitive profiles emerged: a typically developing group, an ADHD group, an ASD group with low levels of ADHD symptoms and an ASD group with high levels of ADHD symptoms.
The ADHD group did worse on many of the tasks than the control group, and the ASD group with low ADHD levels also did poorly relative to the typically developing sample. This shows that autism – even in absence of co-occurring ADHD – demonstrates more cognitive impairment than typically developing kids. The ADHD group with high levels of autism did the most poorly across all of the tasks.
The findings also revealed a symptom severity pattern: the group with fewer symptoms did the best and the group with the most symptoms did the worst. “Overall, this reflects severity of impairment,” said Dr. Karalunas.
To identify measures more specific to either ADHD or autism, Dr. Karalunas and colleagues did a follow-up analysis to characterize cognitive performance. To accomplish this, they applied a drift-diffusion model to the same four cognitive profiles. The model assessed three parameters: drift rate, which relates to the speed or efficiency of information processing, boundary separation or speed accuracy trade-offs (impulsivity), and nondecision time such as motor preparation.
Using the same four cognitive profiles, they found that the ADHD group had slower drift rate relative to the control, although the two groups did not differ on boundary separation, which meant there were no differences on waiting to need to respond. The ADHD group had faster nondecision times. “This is a classic pattern, shown in the literature,” said Dr. Karalunas.