The latest autism research news stories with ASF Chief Science Officer Alycia Halladay
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Thank you to Dennis Wall from Stanford University for explaining what Machine Learning is, how it’s related to Artificial Intelligence (today’s four buzz words) and how these new technologies are helping families get a diagnosis. He talks about the overall goals of these techniques, highlighting Cognoa’s CanvasDx to provide remote diagnoses to potentially reduce the waiting lists for families.
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In the last version of the Diagnostic and Statistical Manual, the different subtypes of autism were folded into one label: autism spectrum disorder. A similar revision is being made around the International Classification of Diseases, the system the WHO uses across the world to describe autism and provide appropriate reimbursements for services and supports. In this version, the ICD-11, a combination of 300 different presentations of autism are described. A diagnosis can be made if 1 feature of social-communication and 1 feature of repetitive behaviors are documented, with an onset of any time in life. This is causing a lot of confusion in the community, because since the presentations are not specific to autism, it is difficult to provide an accurate diagnosis using the ICD-11. This week we talk to German psychiatrist Inge Kamp-Becker, MD, who outlines what the changes are, and how misdiagnosis can be made and what those consequences might be. Her summary is linked below.
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Everyone who has looked for support for autism spectrum disorder is familiar with waitlists. Waitlists for evaluation, diagnosis, intervention, consultations and referrals. These waitlists prevent important opportunities for services and many groups developing technologies, policies, and approaches to reduce the waitlists or work around them. On this week’s podcast, we talk to Dr. Sharief Taraman from Cognoa to hear about their recent study on the scope of the problem on waitlists, what causes them, and how digital therapeutics may help them.
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Can biomarkers that measure things like visual social attention be a good proxy for an in person behavioral diagnosis? Why would this be important? This week’s podcast explores two new studies the the Journal of the American Medical Association that show a simple device called EarliPoint can be used to shorten the wait times to receive a diagnostic evaluation. Currently autism can be diagnosed at 18 months but most families do not get into an appointment until 4-5 years of age. That can change. Families were able to easily complete it, it predicted things like not just a diagnosis but behavioral features and cognitive ability. It’s been deployed in 6 speciality centers, been approved by the FDA, and hopefully coming to a clinic near you soon.
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The disparity in diagnosis between Black kids and white kids is narrowing, but not by luck or coincidence. Based on previous research, clinicians are altering their professional training and their outreach to make sure more Black families are diagnosed and receive interventions. On today’s podcast, we highlight a recent study that focused on different ways to lower the age of diagnosis and improve access to early intervention in Black families. This intervention improved cognitive outcomes in Black kids.
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This week’s #ASFpodcast highlights a few articles from the Journal of Autism and Developmental Disorders this week which examined the tolerability and efficacy of online diagnostic procedures and interventions, from the perspective of both parents and clinicians. They seem to work about the same, although there were some caveats. For many reasons, online and telehealth options are here to stay, and more needs to be done to improve their accuracy, acceptability, feasibility and effectiveness. These early studies are promising though, and lead the way to even more improvements to help make them a viable option for families in the future.
https://link.springer.com/article/10.1007/s10803-022-05435-z
https://link.springer.com/article/10.1007/s10803-022-05576-1
https://link.springer.com/article/10.1007/s10803-022-05554-7
https://link.springer.com/article/10.1007/s10803-022-05580-5https://link.springer.com/article/10.1007/s10803-022-05607-x
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This week’s podcast highlights a paper from the IBIS (infant brain imaging study) that tracks infants from 6 months to 5 years of age to examine how ASD symptoms cluster together. These infants either have a diagnosis or they don’t, or they have something which doesn’t meet diagnostic threshold but is still impairing in some way. Ignoring the actual diagnosis, if the data is clustered together around how symptoms present, what happens? What does that mean for some of the longest standing research findings in ASD? For example, using this new approach which ignores and actual diagnosis, are more males are diagnosed than females? As it turns out, it equals out these ratios. What does this mean? Listen to this week’s podcast to hear directly from the first author, Catherine Burrows!
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The racial and ethnic disparities in the diagnosis of ASD has always been unacceptable, but it’s been hard to figure out. This week, researchers published their findings from a close look at 500 African American families with ASD to understand what the barriers were to a timely diagnosis. The results are not surprising, but they are also alarming. Some of these families may benefit from telehealth in the future. Telehealth is not perfect, but it turning out to be helpful. For example, it may be beneficial in treating insomnia in people with ASD. Delivering cognitive behavioral therapy online resulted in improvements in sleep in adolescents with ASD. It isn’t a panacea, but it seems to be more helpful than people gave it credit for before the pandemic.
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In this week’s podcast, I semi-plagiarize from a recent summary of sex differences in ASD, written by Drs. Meng-Chuan Lai and Peter Szatmari from the University of Toronto. They delve into why more males are diagnosed with females, and differences in the presentation of those features of ASD that differ between males and females. These include camouflaging, differences in language style, differences based on behaviors determined by sex, and associated features like anxiety and internalizing behaviors. Thank you to the authors for putting together the information in a way that makes sense.
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Two studies missed last year (sorry) but are of importance to the autism community include a modified version of Cognitive Behavioral Therapy to treat anxiety, which was adapted and updated for people with ASD. It also works better than traditional CBT, which is good news for the 80% of people with ASD that also suffer from anxiety. Also, in recognition of MLK day today, the CDC released information last year that shows that 1/4 of those that they counted in their prevalence numbers were missed by schools or other health care providers. Unfortunately, those who were black or hispanic were more likely to be those that were missed but still met criteria. This just shows that educators have to do better in helping those with ASD from all racial and ethnic backgrounds.