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A potential biomarker to AID, not MAKE, a diagnosis

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The media has just called another biological marker a “diagnostic test”, when in this case, it was always intended to be an aid, not a test itself. It involves using baby hair strands to look a variation in metabolism of certain chemical elements across time. Remarkably, it showed similar results in autistic children in Japan, the US and Sweden. It’s not ready to be used as a diagnostic test, so what is it supposed to do? Listen to an interview with the inventor and researcher, Dr. Manish Arora from The Icahn School of Medicine at Mt. Sinai School here.

The full article (open access) can be found here: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9740182/

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The true title should be: “A new open source screening tool to help detect autism”

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Many of the existing tools to identify autism cost money or are not specific for ASD, and they are hidden behind paywalls and are hard to obtain. A group of scientists led by Tom Frazer at John Caroll University put together a 39 questionnaire called the Autism Symptoms Dimensions Questionnaire to be filled out by parents of children. It’s free and open source! But that’s just the first step. The media got the intent wrong, yet again.

It should not replace a full diagnosis. Autism is complex, and even those with genetic forms of autism show heterogeneity in symptoms. They each need comprehensive evaluations. But this is a good start. Check it out here!!! It’s open source:

References below:

https://pubmed.ncbi.nlm.nih.gov/36670671/

https://onlinelibrary.wiley.com/doi/epdf/10.1111/dmcn.15497

https://pubmed.ncbi.nlm.nih.gov/36639821/

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ADHD and ASD diagnosis both on the rise. Coincidence or commonalities?

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Like ASD, the prevalence of ADHD has increased significantly in the past 2 decades. A critical analysis examines the factors, and many of them can be applicable to the increase in the rise of autism diagnoses: increased diagnosis in adults, looser diagnostic criteria, and untrained professionals making the diagnoses. While they are not of course the same, listen to some of their arguments and read their comments (link below) to see if you agree with my assessment.

https://onlinelibrary.wiley.com/doi/epdf/10.1002/jclp.23348

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Can we solve the pandemic problems around diagnosis and intervention?

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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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Is autism a yes/no diagnosis?

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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!

https://www.sciencedirect.com/science/article/abs/pii/S0006322322013130?casa_token=ZFZpvnUOIBkAAAAA:G667QIkX_Vd6JPeWvIPABo1FPrdNL_3IiW-ajy7xR2Nme_I4ztOEf2xJ4FyhGHTMgrb8Lqq6Og

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How is ASD diagnosis happening right now?

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Early on in the pandemic, clinicians struggled with how to turn in-person evaluations into Telehealth evaluations. One year later: what have they done? How have they modified? How do parents feel about these changes? Should they stay or should they go? This topic will be featured on our ASF Day of Learning on April 22nd as well. Also COVID related, new data on the effects of maternal immune infection on autism outcomes in children – with a bright light at the end of the story. At least a bright light at some maternal infections. Listen to the opening song and keep on “staying away”.

https://pubmed.ncbi.nlm.nih.gov/33730320/

https://pubmed.ncbi.nlm.nih.gov/33720503/

https://www.nature.com/articles/s41593-020-00762-9

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Parents describe the “best things” about their kids with ASD

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Parents may see challenges in their kids with ASD, but they also know what is great about them and the unique gifts they bring to the world. Now, researchers from Canada have inventoried and categorized these list of great qualities in a large study of children from 3-10 years of age. These “best things” identified and counted across ages should also be used when planning how to transition kids with ASD from EI or preschool into kindergarten. Another study included this week from Curtin University in Australia describes how parents see this process becoming a lot easier.

https://pubmed.ncbi.nlm.nih.gov/33532881/

https://pubmed.ncbi.nlm.nih.gov/33520781/

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Better ways of subgrouping ASD?

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On this week’s podcast, two new studies which explore the concept of subgroups of ASD are described. First, a “genetics-first” approach. Dr. Samuel Chawner at Cardiff University compares autism symptoms in those with copy number variants to those with no known genetic cause and asks: how similar to each other are they and can genetics be a way to subgroup? Second, the UC Davis MIND Institute explores the specificity of a subgroup of ASD based on presence of autoantibodies in mothers. Should there be a mix of the two and how do families interpret these findings? Listen here:

https://pubmed.ncbi.nlm.nih.gov/33384013/

https://pubmed.ncbi.nlm.nih.gov/33483694/

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The autism brain at 3 months old

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Biological features of ASD can be seen long before behavioral impairments in children are seen. Researchers are now studying the activity of the brain at 3 months in infants that go on to develop autism and those that do not. There are distinct features in the brain seen in a 3 month old that goes on to develop ASD. In addition, excessive brain activity resulting in seizures can increase the probability of a later ASD diagnosis in infants with a rare genetic disorder called Tuberous Sclerosis. This podcast will explain how connectivity and activity in a 3 month old can influence a later diagnosis. What we don’t know more about is those intervening months, and what can be done to mitigate symptoms.

https://www.sciencedirect.com/science/article/abs/pii/S2451902220301403?via%3Dihub

https://onlinelibrary.wiley.com/doi/epdf/10.1002/acn3.51128

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Sex differences: It’s not about the diagnostic measurements.

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A fresh take on an existing topic: why there are more boys diagnosed with ASD than girls. Even from a few months old, girls are different than boys, and they show subtle differences in toddlerhood. But at the time of diagnosis, they score the same on standardized instruments of ASD used to categorize someone as having ASD or not. This means it isn’t about the measures. It could be cultural factors, it could be a protective effect, but there needs to be a better understanding of these differences across the lifespan to help everyone with ASD, especially females.

https://www.cell.com/current-biology/retrieve/pii/S096098222030419X?_returnURL=https%3A%2F%2Flinkinghub.elsevier.com%2Fretrieve%2Fpii%2FS096098222030419X%3Fshowall%3Dtrue

https://doi.org/10.1007/s10803-020-04526-z

https://doi.org/10.1111/jcpp.13242