Measurements in baby's first year may point to autism risk

Melba UnderwoodFeb 16, 2017

The team focused their work on babies with older siblings diagnosed with autism; these brothers and sisters have a 20% higher risk of also developing autism, compared to newborns without affected siblings.

The surface area of the cortex grows significantly faster between the ages of 6 and 12 months in children with autism than in those without the condition, the researchers found.

Researchers also will be looking for biomarkers such as rapid eye movement that could be associated with excessive brain growth, and could be easier for doctors to check.

Diagnosing autism very early in a child's life might mean better interventions and outcomes. In addition, brain overgrowth correlated with the severity of social deficits that emerged by age two.

About one in 70 children in the United Kingdom develops autism, but among those with a diagnosed sibling, the risk of the condition can rise to about one in five.

Schultz, Ph.D., is the director of the Center for Autism Research at Children's Hospital of Philadelphia.

Measuring changes in infants' brain growth can allow doctors to predict the likelihood that they will be diagnosed with autism in their toddler years, according to research published Wednesday by two University of Minnesota researchers.

Researchers found that, among infants with an older ASD sibling, the brain differences at 6 and 12 months of age successfully identified 80 percent of those infants who would be clinically diagnosed with autism at 24 months of age. But studies haven't proven these early behaviors to be reliable predictors, said co-author Jed Elison, an assistant professor in the U's Institute of Child Development.

The technology is not ready to use in clinics, but researchers who took part in the study believe it lays the groundwork for a tool that can predict autism in high-risk babies before their first birthday.

It worked well. Using just three variables-brain surface area, brain volume, and gender (boys are more likely to have autism than girls)-the algorithm identified up eight out of 10 kids with autism.

Numerous measurements the algorithm relied on most are related to surface area, and came from 6-month-old children.

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.

The researchers input measures of surface area, thickness and volume at 6 and 12 months into a machine-learning algorithm to predict which infants would later be diagnosed with autism. And the team was pleased with the prediction accuracy.

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.

If these findings could form the basis for a "pre-symptomatic" diagnosis of ASD, health care professionals could intervene even earlier. Parents who already have a child with autism may find it particularly hard to show up for repeated brain scans, Piven says.

By this point, however, fundamental developments in the brain have already occurred.

The research team has gathered additional behavioral and brain imaging data on these infants and children - such as changes in blood flow in the brain and the movement of water along white matter networks - to understand how brain connectivity and neural activity may differ between high-risk children who do and don't develop autism. "Now we have very promising leads that suggest this may in fact be possible".

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