This first–of–its–kind study used MRIs to image the brains of infants, and then researchers used brain measurements and a computer algorithm to accurately predict autism before symptoms set in.
Using MRI in infants with older siblings with autism, researchers from around the country were able to correctly predict 80 percent of those infants who would later meet criteria for autism at two years of age.

The study, published in the journal Nature, 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.

“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 Joseph Piven, MD, the Thomas E. Castelloe Distinguished Professor of Psychiatry at the University of North Carolina–Chapel Hill.

This research project included hundreds of children from across the country and was led by researchers at the Carolina Institute for Developmental Disabilities (CIDD) at the University of North Carolina, where Piven is director. The project’s other clinical sites included the University of Washington, Washington University in St. Louis, and The Children’s Hospital of Philadelphia. Other key collaborators are McGill University, the University of Alberta, the University of Minnesota, the College of Charleston, and New York University.

“This study could not have been completed without a major commitment from these families, many of whom flew in to be part of this,” said first author Heather Hazlett, PhD, assistant professor of psychiatry at the UNC School of Medicine and a CIDD researcher. “We are still enrolling families for this study, and we hope to begin work on a similar project to replicate our findings.”

For this study, Piven, Hazlett, and researchers from around the country conducted MRI scans of infants at six, 12, and 24 months of age. They found that the babies who developed autism experienced a hyper–expansion of brain surface area from six to 12 months, as compared to babies who had an older sibling with autism but did not themselves show evidence of the condition at 24 months of age. Increased growth rate of surface area in the first year of life was linked to increased growth rate of overall brain volume in the second year of life. Brain overgrowth was tied to the emergence of autistic social deficits in the second year.

Previous behavioral studies of infants who later developed autism – who had older siblings with autism –revealed that social behaviors typical of autism emerge during the second year of life.

The researchers then took these data – MRIs of brain volume, surface area, cortical thickness at 6 and 12 months of age, and sex of the infants – and used a computer program to identify a way to classify babies most likely to meet criteria for autism at 24 months of age. The computer program developed the best algorithm to accomplish this, and the researchers applied the algorithm to a separate set of study participants.

The researchers found that brain differences at 6 and 12 months of age in infants with older siblings with autism correctly predicted eight out of ten 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.

“This means we potentially can identify infants who will later develop autism, before the symptoms of autism begin to consolidate into a diagnosis,” Piven said.

If parents have a child with autism and then have a second child, such a test might be clinically useful in identifying infants at highest risk for developing this condition.