'U' researcher may have way to predict autism

Autism detectable in brain long before symptoms appear

The study, which was published in the periodical Natureon Wednesday, looked at 106 babies with older siblings who have autism (the likelihood of having autism spectrum disorder rises to around one in five with an older sibling with ASD, while generally the odds look more like one in 100).

The researchers fed the brain scan images into an artificial intelligence. "Often we don't keep in mind the degree of work it takes to do this kind of study", Dawson says.

Using magnetic resonance imaging (MRI), researchers took brain scans at 6 months, 12 months and 24 months of children who were at high risk for autism because their older siblings had the disorder. "The earlier an intervention is implemented, the better the outcome for kids with autism". The subsequent overgrowth was then linked to the emergence of autistic social deficits in the child's toddler years.

A team from several leading institutions in the US and Canada published a paper Wednesday in the journal Nature, demonstrating an algorithm they created that improved early diagnosis of the condition among several children known to be at high risk.

They say they were able to predict which ones were going to develop autism with 80 percent accuracy.

Giving children brain scans, particularly those in high-risk families, could lead to children being diagnosed earlier.

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.

In most cases, autism can't be diagnosed until children are two years old, but sometimes signs of the condition appear earlier. This is important, says co-author Heather Cody Hazlett, a psychologist at the Carolina Institute of Developmental Disabilities, because behavioral cues don't work very well for infants: Before the age of two, children who go on to develop autism behave nearly identically to those who do not. These so-called 'baby sibs' are about 20 times more likely to have autism than are children in the general population.

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For the first time, a new study suggests it's possible to predict within the first year of life if a child will develop autism.

This research was led by researchers at the Carolina Institute for Developmental Disabilities (CIDD) at the University of North Carolina, which is directed by the study's senior author, Joseph Piven, MD, the Thomas E. Castelloe Distinguished Professor of Psychiatry at the University of North Carolina-Chapel Hill. In other words, in autism, the developing brain first appears to expand in surface area by 12 months, then in overall volume by 24 months.

The researchers made measurements of cortical surface areas and cortical thickness at 6 and 12 months of age and studied the rate of growth between 6 and 12 months of age. To generate these predictive results, the team drew on machine learning, a statistical approach that uses pattern recognition to make very detailed predictions.

Hear from one of the researchers who conducted the study, tonight on NBC Nightly News.

There is no evidence that the risk of developing autism can be reduced in infants, says Raznahan, and the immediate application of early diagnosis would be to inform families. The findings raise the prospect of diagnosing autism spectrum disorder (ASD) months before children develop symptoms, a goal that has proved elusive.

If these findings could form the basis for a "pre-symptomatic" diagnosis of ASD, health care professionals could intervene even earlier.

By this point, however, fundamental developments in the brain have already occurred. The test has not been tried on children who are not at high risk. "The fact that they're not consistent suggests that some of the expansion in surface area may actually not be relevant to the detection of autism", he says.

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