Using magnetic resonance imaging (MRIs), a team of researchers from across the country just found it may be possible to predict which babies will go on to develop autism ― all before they turn 1.
Right now the earliest a child can receive a reliable diagnosis of autism is generally thought to be age 2, at which point certain hallmark behaviors and communication problems have emerged, like an inability to string several words together or avoiding eye contact.
But the new findings ― although preliminary ― could represent a major breakthrough in terms of doctors’ ability to predict a child’s autism risk at much younger ages, even before symptoms appear.
“The field has struggled to predict autism earlier and earlier,” study researcher Dr. Joseph Piven of the Carolina Institute for Developmental Disabilities (CIDD) at the University of North Carolina told The Huffington Post. “We’ve kind of reached a wall around 2 years of age. Prior to that, behavioral markers just don’t seem to help in detecting kids that end up with autism.”
In the study, published in the journal Nature on Wednesday, researchers at autism centers across the country ran MRI scans of babies’ brains when they were 6 months old, 1 year old and then again when they turned 2.
The study included 106 babies considered to be at high-risk of developing autism, because they had an older sibling with the disorder. (Children who have older siblings with autism have roughly a 1 in 5 risk of developing the disorder; for children in the general population it’s closer to 1 in 100.) For comparison, researchers also included just over 40 babies who were considered to be at low-risk of developing autism.
The MRIs revealed that babies who eventually developed autism experienced much more rapid growth of their brain’s surface area ― essentially, the folds on the surface of the brain ― in their first year than children who did not develop the disorder.
And between ages 1 and 2, the rate of brain volume growth they experienced was also highly accelerated. That brain volume “overgrowth” was linked to the emergence of social symptoms related to autism in the children’s second year, which can include things like not engaging in pretend play and delayed speech and language.
The researchers took all of that information about changes in brain volume and surface area and put it into a computer program in order to create an algorithm that they hoped would be able to predict which babies would go on to develop autism. Ultimately, they were able to correctly identify 80 percent of high-risk babies who were later given a diagnosis of autism at 24 months.
“We view this is, particularly in this high-familial risk sample, as a very real possibility of pre-symptomatic detection,” Piven said. “So, detecting autism before it really appears. Before the consolidation of symptoms and brain deficits and at a time when the brain is most malleable, giving us the greatest chance of having an impact with early intervention.”
Current estimates suggest 1 in 68 children in the United States have been identified with autism, and while early intervention ― which at this point typically means behavioral therapy ― can be highly beneficial in managing and even erasing symptoms, the Centers for Disease Control and Prevention says most children do not get diagnosed until closer to age 4. The new findings hold particular promise for families of children who are at high-risk for the disorder, and may have practical implications for them “in the not too distant future,” Piven argued.
The MRI images also provide some key insights into what he called the cascade of brain and behavior changes in a child’s first two years of life that result in the emergence of autism.
“There’s a developmental sequence,” he said, “and it raises the possibility that we could sort of disrupt that sequence early on.”
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