Canadian university’s take part in research using MRIs to predict autism in babies

By taking a magnetic resonance imaging scan (MRI) of infants that have older siblings with autism, researchers from around the United States were able to correctly predict 80 per cent of infants who would likely have the mental condition at age two. At least two Canadian universities were among the institutions that collaborated in the study.

The study, which was published in the international weekly science journal Nature, is said to be the first of its kind to use MRI images of an infant’s brain to detect possible signs of autism.

The 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. Other clinical sites included the University of Washington, Washington University in St. Louis, and The Children’s Hospital of Philadelphia.

Two Canadian universities, McGill University and the University of Alberta where among a list of collaborators which includes the University of Minnesota, the College of Charleston, and New York University.

“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,” a ScienceDaily report quoted senior research author Joseph Piven, MD, the Thomas E. Castelloe distinguished professor of psychiatry at the University of North Carolina-Chapel Hill, as saying. “Typically, the earliest an autism diagnosis can be made is between ages two and three. 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.”

Piven and scores of other researchers involved in the study took MRI scans of infants six, 12, and 24 months of age.

They found that infants who developed autism had hyper-expansion of the brain surface area from six to 12 months. Infants with older siblings that have autism did not show evidence of the condition at 24 months of age.

Increased growth rate of surface area during the first year of life was linked to increased growth rate of overall brain volume by the second year.

Brain overgrowth was tied to the emergence of autistic social deficits in the second year, the report said.

A computer program was used on the data collected to develop a way to classify babies most likely to meet the criteria for autism at 24 months of age. The algorithm that was developed was applied to a separate set of study participants.

The researchers found that brain difference at 6 and 12 months of age correctly predicted eight out of ten babies who had older siblings with autism would themselves meet the criteria for autism at 24 months of age.

There is a potential for such a test to be used in identifying infants who may be at risk of developing autism. If the risk could be identified this early it may be possible to intervene “pre-symptomatically” before the defining symptoms of autism come out and when the brain is at its most malleable stage.

“Putting this into the larger context of neuroscience research and treatment, there is currently a big push within the field of neurodegenerative diseases to be able to detect the biomarkers of these conditions before patients are diagnosed, at a time when preventive efforts are possible,” Piven said. “In Parkinson’s for instance, we know that once a person is diagnosed, they’ve already lost a substantial portion of the dopamine receptors in their brain, making treatment less effective.”

 

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