The changes in brain development that underlie autism spectrum disorder (ASD) may be detectable in children as young as 6 months, according to research reported online today in the American Journal of Psychiatry. While core behaviors associated with ASD (impaired social communication and repetitive behaviors) tend to be identified after a baby’s first birthday, researchers found clear differences in brain communication pathways as early as 6 months in infants who later received a definitive diagnosis of ASD.
As part of the Infant Brain Imaging Study (IBIS), senior author Joe Piven, M.D., director of the University of North Carolina’s Carolina Institute for Developmental Disabilities in Chapel Hill, and his colleagues studied early brain and behavior development in 92 infants. These infants had older siblings on the autism spectrum and, so, were at elevated risk of developing ASD themselves.
“These results offer promise that we may one day be able to identify infants at risk for autism before the behavioral symptoms are present,” says study co-author Geri Dawson, Ph.D., Autism Speaks chief science officer. “The goal,” she adds, “is to intervene as early as possible to prevent or reduce the onset of disabling symptoms.” One promising area of follow-up research is to identify the specific genetic and biological mechanisms behind the observed differences in brain development.
In their report, the researchers describe using a magnetic resonance imaging technology called diffusion tensor imaging to evaluate the brains of infants at 6 months, 1 year and 2 years of age. This allowed them to create three-dimensional pictures showing changes over time in each infant’s “white matter.” White matter represents the part of the brain that is particularly rich in the nerve fibers that form major information pathways between different brain regions.
The 28 infants who went on to develop ASD showed different white matter development for 12 of the 15 major brain pathways studied compared with 64 infants who did not go on to develop ASD. At 6 months, there was evidence that the white matter fiber tracts were different in infants who later developed ASD from those of infant siblings who did not develop ASD, and over time it appears that there is a slowing in white matter development. It is a brain marker that differs in children who go on to be classified with autism. These developmental differences may suggest slower white matter development during early childhood, when the brain is making and strengthening vital connections.
“It’s too early to tell whether the brain imaging techniques used in the study will be useful in identifying children at risk for ASD in early infancy,” Piven says. “But the results could guide the development of better tools for predicting the risk that a child will develop ASD and perhaps measuring whether early intervention therapies improve underlying brain biology.”
This work was supported by grants from the National Institutes of Child Health and Development, Autism Speaks and the Simons Foundation. Further support was provided by the National Alliance for Medical Image Computing, funded by a National Institute of Biomedical Imaging and Bioengineering grant. With funding from Autism Speaks, the IBIS team is also looking at the genetic and environmental influences on brain and behavior development in these high-risk infants.About Autism
Jane E. Rubinstein | EurekAlert!
UC San Diego cancer scientists identify new drug target for multiple tumor types
12.07.2019 | University of California - San Diego
Bacteria engineered as Trojan horse for cancer immunotherapy
04.07.2019 | Columbia University School of Engineering and Applied Science
Scientists at the University Würzburg and University Hospital of Würzburg found that megakaryocytes act as “bouncers” and thus modulate bone marrow niche properties and cell migration dynamics. The study was published in July in the Journal “Haematologica”.
Hematopoiesis is the process of forming blood cells, which occurs predominantly in the bone marrow. The bone marrow produces all types of blood cells: red...
For some phenomena in quantum many-body physics several competing theories exist. But which of them describes a quantum phenomenon best? A team of researchers from the Technical University of Munich (TUM) and Harvard University in the United States has now successfully deployed artificial neural networks for image analysis of quantum systems.
Is that a dog or a cat? Such a classification is a prime example of machine learning: artificial neural networks can be trained to analyze images by looking...
An international research group led by scientists from the University of Bayreuth has produced a previously unknown material: Rhenium nitride pernitride. Thanks to combining properties that were previously considered incompatible, it looks set to become highly attractive for technological applications. Indeed, it is a super-hard metallic conductor that can withstand extremely high pressures like a diamond. A process now developed in Bayreuth opens up the possibility of producing rhenium nitride pernitride and other technologically interesting materials in sufficiently large quantity for their properties characterisation. The new findings are presented in "Nature Communications".
The possibility of finding a compound that was metallically conductive, super-hard, and ultra-incompressible was long considered unlikely in science. It was...
An interdisciplinary research team at the Technical University of Munich (TUM) has built platinum nanoparticles for catalysis in fuel cells: The new size-optimized catalysts are twice as good as the best process commercially available today.
Fuel cells may well replace batteries as the power source for electric cars. They consume hydrogen, a gas which could be produced for example using surplus...
The fly agaric with its red hat is perhaps the most evocative of the diverse and variously colored mushroom species. Hitherto, the purpose of these colors was...
24.06.2019 | Event News
29.04.2019 | Event News
17.04.2019 | Event News
17.07.2019 | Earth Sciences
17.07.2019 | Information Technology
17.07.2019 | Materials Sciences