Earlier Diagnoses of Autism in Children Could Mean More Effective Treatment

Being able to predict whether an infant will develop autism may be closer than we think, says a study published last week in the journal Nature. This study is the first to show it is possible to identify which infants, among those with older siblings with autism, will be diagnosed with autism at 24 months of age.

Using magnetic-resonance imaging, researchers at the University of North Carolina used the scans taken at 6 months, 12 months and 2 years to examine the brains of infants at high risk of autism. As a result, they were able to predict with an 80 percent accuracy rate which babies who had an older sibling with autism would be later diagnosed with the disorder.

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“Our study shows that early brain development biomarkers could be very useful in identifying babies at the highest risk for autism before behavioral symptoms emerge,” said senior author Dr. Joseph Piven the Thomas E. Castelloe Distinguished Professor of Psychiatry at the University of North Carolina at Chapel Hill.

“Typically, the earliest an autism diagnosis can be made is between ages 2 and 3. But for babies with older autistic siblings, our imaging approach may help predict during the first year of life which babies are most likely to receive an autism diagnosis at 24 months,” he adds.

People with Autism Spectrum Disorder have characteristic social deficits and demonstrate a range of ritualistic, repetitive and stereotyped behaviors. It is estimated that 1 out of 68 children develop autism in the United States. For infants with older siblings with autism, the risk may be as high as 20 out of every 100 births. There are about 3 million people with autism in the United States and tens of millions around the world.

“We haven’t had a way to detect the biomarkers of autism before the condition sets in and symptoms develop,” Dr. Piven said in a statement. “Now we have very promising leads that suggest this may in fact be possible.” 

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What you need to know about this study:

How it works

This new diagnostic method requires MRI brain scans to look for the features of autism.

Overgrowth in brain volume during the first year of life forecasts whether a child at high risk of developing autism spectrum disorder is likely to receive a diagnosis at age 2, according to the study.

Who was involved

The study included 106 babies considered to be at high risk of developing autism because they had an older sibling with the disorder and 42 babies who were considered to be at low risk of developing autism.

Speed of brain growth matters

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. They also experienced a highly accelerated brain volume growth between the ages of 1 and 2, which was linked to the emergence of social symptoms (not engaging in pretend play and delayed speech/language) related to autism in a child’s second year of life.

Predictions for siblings

The researchers found that brain differences at 6 and 12 months of age in infants with older siblings with autism correctly predicted 8 out of 10 infants who would later meet criteria for autism at 24 months of age in comparison to those infants with older ASD siblings who did not meet criteria for autism at 24 months.

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For parents who have a child with autism and then go on to have another child, this test may be helpful in identifying infants at highest risk for developing autism earlier on. This is significant because according to Piven, once autism is diagnosed at ages 2 to 3 years, the brain has already begun to change substantially.

If doctors find that the second child has autism, there could be some pre-symptomatic interventions before the emergence of the defining symptoms of autism. Researchers can then look at whether or not these pre-symptomatic interventions work, especially during a time when the syndrome is present and the brain is most malleable.


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