Groundbreaking new research could lead to early diagnosis of autism


Groundbreaking new research could lead to early diagnosis of autism

- Researchers at the University of Minnesota were part of a national study that found measuring infants' brain growth during their first year of life can predict the likelihood that they will be diagnosed with autism when they are two years old or older. 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.

The researchers used magnetic resonance imaging (MRI) to scan the brains of 148 infants, 106 of whom have an older sibling with autism. Hazlett took MRI scans of the babies at six months, 12 months and 24 months to track any changes.

'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'.

"It's showing us that the early postnatal years are critical to study in order to understand autism", says Mark Johnson, director of the Centre for Brain and Cognitive Development at Birkbeck, University of London, who was not involved in the new work.

"Our hope is that early intervention, before age two, can change the clinical course of those children whose brain development has gone awry and help them acquire skills that they would otherwise struggle to achieve", said Stephen Dager, a co-author at the University of Washington's Center on Human Development and Disability. U of M researchers assisted on the project.

MRIs are very expensive, and it's hard to convince a 12 month old child to lay still long enough to get a good brain image. The faster growth is associated with poor performance on tests of social communication. This sequence is consistent with results in mice. This most recent study shows this pattern of rapid growth originates in specific brain regions long before brain size itself shows significant enlargement. When combined with brain volume and sex of the infants, it predicted most of the ASD cases among the group.

Scientists have successfully detected autism in babies using an MRI scan.

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The algorithm analyzed data from all but 10 of the participants to predict the diagnostic status of the remaining individuals, and repeated the process 10 times.

However, Amaral points out, "When you are able to look at large numbers of kids, what you find is that the big brains are typical of 15 percent of boys with autism".

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.

However, by considering other factors as well including additional brain measurements and the child's sex, the researchers used a statistical approach known as machine learning to assess with near ideal accuracy who would develop autism.

Piven said the research can be likened to similar efforts to detect other brain disorders earlier in life, such as Parkinson's or Alzheimer's, before they begin to impair patients. They found that the babies who developed autism experienced a hyper-expansion of brain surface area from 6 to 12 months, as compared to babies who had an older sibling with autism but did not themselves show evidence of autism at 24 months of age. "Now we have very promising leads that suggest this may in fact be possible". "It's unlikely that's going to be adopted as a screening protocol".

Researchers across the U.S. tested the method on hundreds of infants with autistic siblings, making them "at-risk". The families also return for follow-up visits so we can measure how their child's brain grows over time. That brain volume "overgrowth" was linked to the emergence of social symptoms related to autism in the children's second year, which can include things like not engaging in pretend play and delayed speech and language.



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