A Dartmouth-led research team has identified a non-verbal, neural marker of autism.
This marker shows that individuals with autism are slower to dampen neural activity in response to visual signals in the brain.
This first-of-its kind marker was found to be independent of intelligence and offers an objective way to potentially diagnose autism in the future.
The results are published in Current Biology.
“Autism is hard to screen for in children, when the first signs are present.
A trained clinician may be able to detect autism at 18-months or even younger; yet, the average age of a diagnosis of autism in the U.S. is about four years old,” explains lead author Caroline Robertson, an assistant professor of psychological and brain sciences at Dartmouth, and director of the Dartmouth Autism Research Initiative.
“We need objective, non-invasive screening tools that don’t depend on assessing a child’s behavior.
ne of the big goals of the field is to develop objective neural markers of autism that can work with non-verbal individuals.
This neural marker is just that,” she added.
People with autism have long been thought to have differences in inhibiting the neural signals in the brain.
This is thought to underpin symptoms in autism, such as hypersensitivity to sensory input, which includes differences in processing visual information.
When the human brain is presented with two different images at the same time, the images rock back and forth in awareness, toggling between the left and right eye.
Prior research led by Robertson has demonstrated that the autistic brain is slower in switching from one image to the next (also known as slower binocular rivalry) due to differences in inhibitory neural transmission in the brain.
In the autistic brain, the neurotransmitter, GABA, has difficulty filtering and regulating sensory signals, including in this case, suppressing one of the images.
The new study used brain imaging to measure the slower rate of binocular rivalry in individuals with autism.
With these results, the research team was able to accurately determine if participants had autism and predict the severity of autism symptoms, which were measured using traditional clinical assessments.
To obtain the neural data, the study measured brain signals from a single electroencephalography (EEG) electrode that was placed on a participant’s head, over the visual region of the brain.
Participants were presented with one of two visual images: red checkerboards in the left eye and green checkerboards in the right eye that flickered back and forth at different rates.
The research revealed that neural data could be used to predict whether or not an individual had autism with 87 percent accuracy.
The findings were striking and tracked with clinical measures of autism: participants with a higher level of autism had a slower rate of binocular rivalry, where the brain was slower in switching from one image to the next.
The research offers new promise for the way autism is diagnosed.
“This visual test may be a non-verbal marker of autism in adults.
Our next steps are to learn whether this test could potentially be used to detect autism in pre-verbal children and non-verbal adults and develop it into a screening tool for the condition.
In the meantime, this result gives us new insight into the brain in autism, showing that visual regions of the brain are affected” says Robertson.
The researchers also note that the visual sensitivities individuals with autism experience differ significantly among people on the autism spectrum, so while measuring these differences in visual processing may not detect autism in all individuals, it might help to better understand the autism spectrum.
Autism Spectrum Disorder (ASD) is a heterogeneous neurodevelopmental disorder with an estimated prevalence of 1 in 59 children, according to CDC’s Autism and Developmental Disabilities Monitoring Network [Baio et al., 2018], or one in 132 persons worldwide [Baxter et al., 2015].
The core symptoms of ASD include impairments in social communication and interaction, restricted or repetitive behavior, and unusual sensory sensitivity or interests [American Psychiatric Association, 2013].
Common associated symptoms vary from aggression, self‐injurious behavior, impulsivity and irritability to hyperactivity, anxiety and mood symptoms [Baird, Cass, & Slonims, 2003].
Current primary treatment emphasizes forms of behavioral interventions (e.g., applied behavior analysis) to advance development and adaptive skills, but also various pharmacological treatments to target maladaptive co‐occurring conditions (psychostimulants, alpha agonists, antidepressants, and antipsychotics) [Zwaigenbaum et al., 2015]. To date, no efficacious pharmacotherapy for the core symptoms of ASD exists [Ji & Findling, 2015].
Drug development for core impairments in the social and communicative domains has been limited, in part due to a lack of well validated, sensitive measures suitable for clinical trials across the life span [Anagnostou et al., 2015; Baxter et al., 2015; Brugha, Doos, Tempier, Einfeld, & Howlin, 2015; Zwaigenbaum et al., 2015; Zwaigenbaum, Bryson, & Garon, 2013], in contrast to restricted interests, repetitive behaviors, and anxiety, where such measures are available [Lecavalier et al., 2014; Scahill et al., 2015].
There are even larger gaps in the development of valid core symptom outcome measures and biomarkers (defined as “a characteristic that is objectively measured and evaluated as an indicator of normal biological processes, pathogenic processes or pharmacologic responses to a therapeutic intervention” [Strimbu & Tavel, 2010]), for adults with ASD [Brugha et al., 2015]. Most of the evidence in the research of clinical endpoints in ASD originates from studies in young children.
This is suboptimal for the purpose of drug development, where the ICH guidelines [European Medicines Agency, 2000] recommend the start of pediatric interventional studies after substantial experience in adults for drugs in development for non‐serious and non‐life‐threatening indications.
Treatment development in ASD is also challenged by the phenotypic and etiologic heterogeneity of the disorder [Geschwind & Levitt, 2007], including the evidence that the core symptom dimensions may have separate genetic architectures [Ronald et al., 2006], which hinders the identification of drug targets, compared with other single gene disorders (e.g., mammalian Target Of Rapamycin (mTOR) pathway in tuberous sclerosis).
However, all individuals with ASD share social impairments in relatedness and reciprocity and communication deficits, argued to represent a convergence of etiologies in terms of shared neurobiology [Happe & Ronald, 2008].
Research aiming to delineate disruptions in biological processes has spurred considerable study of the cognitive phenotypes of ASD. Not surprisingly, efforts to identify the major cognitive contributors to social impairments in ASD have revealed a multifaceted underpinning of these core processes and deficits [Adolphs, 2001].
Diagnostic scales used in ASD target relatively heterogeneous groups of behaviors and were not originally developed to sensitively assess social communication or more narrow components of social responsiveness in the context of a clinical trial.
By understanding the component processes underlying social cognition and communication, therapeutic effects should be more easily identified and quantified more accurately. Results from contemporary investigations attempting to fractionate social and communication impairments in ASD and link them mechanistically to biologically proximal information processing functions have been mixed; no single biomarker or cognitive domain has emerged as “primary” thus far.
Studies find considerable overlap in performance between ASD individuals and controls, and more variability and likely subgroups within ASD subjects, such as for facial emotional recognition [Jones & Klin, 2013], supporting phenotypic and genetic heterogeneity.
Therefore, there is a great need for the identification of biomarkers, or objective indicators, of deficits at different system levels of social cognition and social communication in ASD which can mechanistically be related to symptoms—moving from proximal to distal levels of information processing and integration to behavior—and are sensitive to change, and may therefore be used as reliable outcome measures and stratification of patient populations in treatment trials [Beversdorf & Missouri Autism Summit, 2016; Jeste, Frolich, & Loo, 2015; Strimbu & Tavel, 2010].
Charting behavioral changes arising from pharmacological effects on pathophysiology and disease processes with valid and precise assessments will facilitate the development of more efficacious, targeted treatments in ASD [Jeste et al., 2015; Zwaigenbaum et al., 2013]. As the initial evaluation of novel compounds usually takes place in adult patients who may differ in many aspects from the treatment population of children, it is necessary to establish biomarkers not only in children or adolescents, but also for adults.
The primary objective of this study was to assess the concurrent validity of exploratory assessments of social information processing and cognition in adult patients with ASD through characterization of their relationship with standardized measures of symptoms, behavior, and functioning.
These measures included eye‐tracking paradigms as a measure of attunement to, and extraction of, socially relevant information, and Affective Speech Recognition test (ASR), and Reading‐the‐Mind‐in‐the‐Eyes Test (RMET), as measures of the ability to detect and process socially relevant information in human communication. We also explored effects on olfaction as a sensory modality assumed to play a role in social interaction, and a novel clinical assessment, the Social Communication Interaction Test (SCIT), to directly evaluate separate domains of social communication.
The second objective was to examine the feasibility to implement these exploratory assessments in a clinical study context across multiple sites in order to gauge potential application in clinical trials. A companion manuscript describing the assessment of the discriminant validity of these exploratory assessments between ASD and healthy controls is currently in preparation.
More information:Current Biology (2019). www.cell.com/current-biology/f … 0960-9822(19)30871-1
Journal information: Current Biology
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