Attention Deficit / Hyperactivity Disorder i autistic spectrum disorder (ASD) often coexist in children and adults, but the range of cognitive abilities can vary greatly in these patients. Researchers around the world are leveraging symptoms, cognitive assessment, and neurobiological measures to learn about how individuals with ADHD/ ASD approach and problem solving.
Several experts discussed the progress of their research during the session, “Overlap and Differences in ADHD and Autism: New Findings in 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,” he said Sarah Karalunas, doctor, 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 its co-diagnosis. “There is a growing recognition that there may be shared cognitive and physiological traits that reflect their shared risk and explain the high levels of symptom overlap,” Karalunas said.
Shared cognitive markers
According to the DSM change, “it is now recognized that between 20% and 60% of children with ASD have comorbidities with ADHD and that between 20% and 40% of children with ADHD have symptoms of ASD,” Beth said. Johnson, researcher. fellow at the Turner Institute for Brain and Mental Health at Monash University, Melbourne.
The shared overlap of genetic traits and comorbidities such as intellectual disability, anxiety, depression, i challenging opposing disorder, make it difficult to predict clinical outcomes for physicians, Johnson noted.
“We now understand that it is likely to be multiple autisms and ADHD, that these symptoms exist in a spectrum of severity or capacity,” he said. Johnson discussed a data-based subtype approach based on neurocognitive profiles and symptoms in children with ADHD. The goal was to better understand how symptoms are managed through ADHD, ASD, and comorbid ADHD-ADHD.
As part of this research, his team recruited 295 controls and 117 children with ADHD who underwent clinical phenotypes 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 score scale and the autism questionnaire data: high traits of ADHD / ADHD, high ADHD / low ADHD, low ADHD / moderate ADHD, and low ADHD / ADD . Approximately half of children with ADHD had moderate to high symptoms of ASD. Regarding neurocognition in all tasks, it is not surprising that the performance is the lowest among children with high ADHD / ADHD, with the performance in stopping signal being the most pronounced. “Notably, the performance of working memory task worsened with increasing ADHD symptoms,” she reported.
The drift model identifies information processing
Karalunas has done the same compared subgroups of children with ADHD and ASD. “Our analysis examined whether cognitive impairments in ASD reflect a mechanism of shared risk or symptoms of ADHD that occur simultaneously and why we see an overlap in such deficiencies,” he said.
Their study included 509 children with ADHD, 97 with ASD, and 301 controls (typical development). All three groups underwent a comprehensive cognitive assessment battery that measured attention arousal, baseline processing speed, and working memory. These tasks collapsed into a number of variables, as well as a set of tasks that measure response inhibition, change, interference control, reward discounting, and measurement of reaction time variability. .
Four cognitive profiles emerged: one typically developing group, one ADHD group, one ASD group with low levels of ADHD symptoms, and one group of ASD with high levels of ADHD symptoms.
The ADHD group did worse in many of the tasks than the control group, and the ASD group with low levels of ADHD also did poorly in relation to the sample that normally develops. This shows that autism, even in the absence of simultaneous ADHD, demonstrates more cognitive impairment than developing children. The ADHD group with high levels of autism made things poorer in all tasks.
The results also revealed a pattern of severity of symptoms: the group with fewer symptoms did the best and the group with more symptoms did the worst. “Overall, this reflects the severity of the deterioration,” Karalunas said.
To identify more specific measures of ADHD or autism, Karalunas and colleagues conducted a follow-up analysis to characterize cognitive performance. To achieve this, they applied a drift diffusion model to the same four cognitive profiles. The model evaluated three parameters: drift rate, which is related to the speed or efficiency of information processing, the compensation of the separation of borders or the accuracy of the speed (impulsivity) and the time of non-decision, such as the engine preparation.
Using the same four cognitive profiles, they found that the ADHD group had a slower drift rate relative to control, although the two groups did not differ in the separation of boundaries, which meant that there were no differences. waiting for the need to respond. The ADHD group had faster non-decision times. “This is a classic pattern, which is shown in the literature,” Karalunas said.
In other results, an interesting pattern began to evolve
Both groups of ASD, for example, had much wider border separations, which meant they expected to be safe before responding than ADHD or the groups they normally developed. In contrast, the two groups of ADHD had much faster decision times, while the two groups that did not have ADHD had similar non-decision times.
Unlike the previous analysis, which saw how a pattern of symptom severity developed, “we obtained two parameters that appear to make a much more specific follow-up of specific symptom domains,” Karalunas observed.
The results suggest that there is a substantial overlap in cognitive impairments of ADHD / ASD. “But right now we have pretty solid evidence that these similarities aren’t explained by the overlap of symptoms, especially for things like response and inhibition, working memory, and processing speed. They seem to be independently related to ADHD. and autism, regardless of the level of comorbid ADHD symptoms in the autism group, ”Karalunas said.
The hope is to expand these types of analyzes to address the interaction of cognition-emotion and social cognition and to empirically define groups based on cognitive performance, he said.
Neurocognitive studies
Researchers have also been studying neural networks to assess ASD and ADHD. Roselyne Chauvin, PhD, postdoctoral fellow at the University of Washington, St. Louis, discussed the concept of “generic task connectivity,” in which researchers look for a common network between specific task paradigms to approach a common alteration between deficiencies.
In his research, Chauvin and colleagues examined connectivity modulations in three tasks: working memory, reward processing tasks, and stop signal tasks, comparing ADHD patients with siblings and controls. The ADHD group showed reduced sensitivity or a lower number of modulated connections in the tasks compared to the other groups. Investigators wondered where those lost connections were.
Dividing the cohorts into generic task groups and task-specific groups, Chauvin and colleagues found that the ADHD group had no common processing skills. They were also able to identify reproducible missing circuits in ADHD participants. Among the cohorts, there was a higher modulation of task-specific edges in the ADHD group.
Patients with ADHD seemed to use alternative strategies more suited to tasks that were more difficult and suboptimal.
He also previewed his ongoing work with the EU-AIMS Longitudinal European Autism Project (LEAP) database to study TEA-ADHD comorbidity. In this project, she and her colleagues examined several tasks: emotion processing probing, inhibitory control, mind theory, and reward anticipation. By comparing groups of ASD with or without ADHD comorbidity or a shared connection, she and her team were able to develop a functional profile predictive of the severity of ADHD. As an example, “for the connection that only uses ASD with ADHD comorbidity, the more they used those connections of greater amplitude in modulation, within this connection subset, the greater would be a severity of ADHD,” he said Chauvin.
Charlotte Tye, Ph.D.
Second, neural correlates of different behavioral and cognitive profiles have not been extensively studied Charlotte Tye, Ph.D., based at the Institute of Psychiatry, Psychology and Neuroscience, King’s College, London. Electroencephalography is a useful technique for understanding the neural correlates of cognitive impairments and mocking different patterns of coincidence in ASD and ADHD.
Tye and colleagues tried this approach in a cohort of 8-13 year old boys diagnosed with ASD and / or ADHD, who measured EEG while children did various continuous performance tasks to assess changes in brain activity. Examining the amplitude of P3 (potential components related to the event), it was found that children with ADHD or ADHD + ASD had an attenuated amplitude of P3, compared with children with typical development and those with ASD.
“This suggests that children diagnosed with ADHD have reduced inhibitory control,” Tye said. In contrast, children with ASD showed reduced conflict control, as it was indicated by altered N2 amplitude in all task conditions.
These, and other studies conducted by Tye and colleagues indicate that children with ADHD show reduced neural responses during attentional processing, while autistic children show typical neural responses, supporting specific profiles.
“Autistic children diagnosed with ADHD appear to show unique patterns of neural responses to autism and ADHD, supporting additive co-occurrence rather than a different condition. This contributes to the identification of transdiagnostic subgroups within conditions. of neurodevelopment to guide personalized intervention and suggests that children with autism and ADHD occurring simultaneously need support for both conditions, ”Tye said.
Karalunas said in an interview that “an important feature of all these findings is“ we can’t just look at how someone does a general test. ”“ There’s a lot of variability between people who have the same diagnosis and the our research really has to account for that. “
This article originally appeared on MDedge.com, which is part of the Medscape professional network.
