Researchers have come up with a diagnostic approach that they say could improve how autism is both identified and classified. The new technique, developed by a team at the Yeshiva University's Albert Einstein College of Medicine, joins a number of efforts with a goal of finding better ways to spot and treat the condition.
Details are outlined in the online edition of the Journal of Autism and Developmental Disorders.
The Albert Einstein College of Medicine researchers believe the better way to diagnose autism might be measuring how quickly the brain responds to sights and sounds. This approach, they said, could make it easier to diagnose the condition earlier and also objectively classify people on the autism spectrum.
Their study involved 43 children with autism spectrum disorders ages 6 to 17. Each was subjected to a basic auditory tone, a visual image (red circle), or a tone combined with the image. Researchers told patients to press a red button as son as they heard the tone, saw the image or saw and heard both the image/sound at the same time. As this happened, the scientists made continual EEG recordings by way of 700 scalp electrodes on each patient.
The more time it took patients with autism spectrum disorders to process auditory signals, the worse their autistic symptoms. There was a similar, but weaker correlation between how quickly patients processed both audio-visual signals and their autism severity. But there wasn't an identifiable link between what patients saw and their degree of autism symptoms.
Their work builds on an earlier study by some of the same researchers that suggested EEG recordings could determine how badly an individual was affected by an autism spectrum disorder. That earlier study concluded patients with autism spectrum disorders processed sound, touch and vision slower than normally developing children, according to the research announcement.
While more research about this diagnostic approach is needed, the scientists said their work reflects progress, considering that with autism, clinicians don't know how to classify patients into subgroups.
"This has greatly limited our understanding of the disorder and how to treat it," associate professor and study leader Sophie Molholm said in a statement. "We clearly need a more objective way to diagnose and classify this disorder." That would be key, because many believe an earlier intervention works better for autism treatment.
Others in the life sciences field, and academia, have felt the same way. This past summer, Asuragen gained approval to offer a test in New York state that would determine the likelihood a woman will have a child with fragile X syndrome, a genetic cause of autism spectrum disorders and other intellectual disabilities. SynapDx is working with the Broad Institute of Harvard and MIT to advance next-generation DNA sequencing for more accurate and clinically useful autism diagnostic tools. And researchers at a variety of institutions are pursuing a quest for new and viable autism biomarkers.
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