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Rare deletions or duplications of about 600 genetic “letters” in a region on chromosome 16 confer a high risk of autism spectrum disorders (ASDs) and other neurodevelopmental conditions.
Now, in a trifecta of genetics, brain imaging, and cognitive testing, a nationwide team led by researchers at UC San Francisco has used a computer technique known as machine learning to show that genetic cutouts and repeats in the chromosomal region called 16p11.2 often lead to opposite abnormalities in brain structure – deletions are associated with increases in the brain’s white matter, duplications with reduced white matter – but similar cognitive profiles.
The new report, published Aug. 8, 2017, in Radiology, shows that carriers of either duplications or deletions who also had the associated brain changes were most at risk of behavioral and cognitive traits characteristic of ASDs. The findings suggest that clinicians could one day use a combination of genetic tests and brain scans in very young children to predict the severity of ASDs they could develop in the future.
“This study draws a line from a brain imaging finding to a diagnosis of autism,” said Elliott Sherr, MD, PhD, a professor of neurology at UCSF and senior author of the study. “As genetic tools are used more and more often in younger kids, we would have the opportunity to identify kids who carry these mutations and study them at a much younger age.”
Every Case of Autism is Unique
Autism spectrum disorders affect 1 in every 68 children born in the U.S., and are characterized by impaired development, social and learning disabilities. In the clinic, an autism diagnosis generally relies on capturing those behavioral deviations. Since early interventions have been shown to be beneficial, early diagnosis is a long-sought goal.
Elliott Sherr, MD, PhD“If a child is profoundly delayed even in early milestones like learning to roll over or sit up, clinicians should be concerned …