Autism detectable in brain long before symptoms appear

Brain scans can be used to help detect autism in high-risk babies long before any symptoms emerge, according to a new USA study that could mark a "giant step forward" in autism research, scientists say.

Eighty percent of the time, researchers were able to identify which babies would be diagnosed with autism by age two by looking at differences in brain volume among those high-risk children. So, researchers from the University of North Carolina, looked at the brain scans of some of these higher risk babies at six, 12 and 24 months. "But in our study, brain imaging biomarkers at 6 and 12 months were able to identify babies who would be later diagnosed with autism", said Annette Estes, Professor at University of Washington. "Now we have very promising leads that suggest this may in fact be possible". They claim if autism is detected in the early stages of life, intensive treatment may help to rewire the brain and reverse symptoms.

A new study has focused on the early diagnosis of autism.

For the second part of the experiment, the team created an algorithm that used the scans to correctly predict the onset of autism in 8 out of 10 high-risk infants.

Scientists believe that there may be a correlation between brain growth visible on brain scans and the eventual development of autism spectrum disorder.

"It's a time we're talking about during the first year of life where the brain is most malleable", Piven said.

Previous research had identified enlarged brain size as a risk factor for autism.

Experts say that may be too late in terms of treating or minimizing the effects of autism, since whatever brain changes responsible for them have already taken place.

Early intervention could include training for parents on techniques to raise a child with autism, as well as finding a style of behavioural therapy that works for their child.

Scientists are using a variety of methods to try and devise a way to detect autism earlier, Wired notes.

"These findings not only are significant for the field of autism, but they also could inform the broader field of psychiatry and prevention science as it relates to various psychiatric conditions", Elison said.

The new algorithm described in the journal Nature on Wednesday, Feb. 15 offers hope for earlier intervention and better treatment outcomes.

In particular, the academics studied the growth in brain volume of the children who were later diagnosed with autism and compared the findings to brain scans of children who were not.

In the US, there are more than 3 million people with ASD, and tens of millions across the globe. Other key collaborators are McGill University, the University of Alberta, the University of Minnesota, the College of Charleston and New York University. That change happened before the child's first birthday.

As an NIH-funded Autism Center of Excellence, the researchers' data and tools are open-source and will eventually be submitted to the NIH's National Database for Autism Research.

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