A study published in the journal Nature is the first to show that it is possible to predict within the first year of life, whether some infants will go on to develop autism. The ability to identify autism risk during infancy could set the stage for developing very early preventive treatments when the brain is most malleable. Earlier detection also provides opportunities for early treatment – and earlier intervention is known to be associated with better long–term outcomes.

Researchers used magnetic resonance imaging (MRI) technology to capture brain images of infants who are considered at high risk for developing autism spectrum disorder (ASD) by virtue of having an older sibling with ASD. The research team took different measurements of the child’s brain at 6 and 12 months of age, including overall volume, surface area and thickness of the cerebral cortex in particular regions. A computer–generated algorithm was used to combine these measurements and was able to predict which babies would develop autism by age two with more than 90 percent accuracy.

Despite extensive research, it has been impossible until now to identify these children before the second year of life, when behaviors typical of autism emerge. “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 the study’s senior author, Joseph Piven, MD, of the Carolina Institute for Developmental Disabilities (CIDD) at the University of North Carolina.

For this study, Piven, Schultz and researchers from across North America conducted MRI scans of 106 high–risk infants and 42 low–risk infants at six, 12 and 24 months of age. They found that the babies who developed autism experienced much more rapid growth of the brain’s surface area from six to 12 months than babies who did not show evidence of autism at 24 months of age. The study team also found a link between increased growth rate of surface area in the first year of life and an increased growth rate of overall brain volume in the second year of life.

Extensive prior research has identified enlarged brain size as a risk factor for autism. This most recent study shows this pattern of rapid growth originates in specific brain regions long before brain size itself shows significant enlargement. In addition, brain overgrowth correlated with the severity of social deficits that emerged by age two.

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. These measurements, combined with brain volume and sex of the infants predicted with a high degree of accuracy who would develop autism by age 24 months. To generate these predictive results, the team drew on machine learning, a statistical approach that uses pattern recognition to make very detailed predictions. The 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 analytic approach was also almost perfect in predicting which high–risk babies would not develop autism by age 2 years.

The authors emphasize that the effectiveness of the algorithm needs to be reproduced in future studies in order to be ready for clinical use. “If we are able to replicate these results in further studies, these findings promise to change how we approach infant and toddler screening for autism, making it possible to identify infants who will later develop autism before the behavioral symptoms of autism become apparent,” Schultz said.