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   By scanning the brains of babies whose siblings have autism, researchers say they have been able to make reasonably accurate forecasts about which of these high-risk infants will later develop autism themselves. The findings raise the prospect of diagnosing autism spectrum disorder (ASD) months before children develop symptoms, a goal that has proved elusive. Nature looks at the new study and its implications. 
   
   Why has it been so tough to diagnose autism in infants? 
   
   Children typically show symptoms of ASD, such as difficulty making eye contact, after the age of 2. Researchers believe that the brain changes underlying ASD begin much earlier — possibly even in the womb. But behavioural assessments haven't been helpful in predicting who will get autism, says Joseph Piven, a psychiatrist at the University of North Carolina (UNC) in Chapel Hill, who co-led the study, published online in Nature1. 
   
   “Children who end up with autism at 2 or 3, they don’t look like they have autism in the first year," he says. 
   
   Are there genetic signatures or biomarkers that could help predict an autism diagnosis? 
   
   Certain rare mutations are linked to ASD, but the vast majority of cases cannot be pinned to a single or even a handful of genetic risk factors. Beginning in the 1990s, Piven and other researchers noticed that children with autism tended to have larger brains than developmentally normal children, suggesting that brain growth could be a biomarker for ASD. But Piven and colleague Heather Cody Hazlett, a psychologist at UNC-Chapel Hill, say it had not been clear when overgrowth occurred. 
   
   What did their latest study look at? 
   
   Autism occurs in roughly 1 in 100 children in the general population, but infants with an older sibling with a diagnosis have about a 1 in 5 chance of developing ASD. As part of the US National Institutes of Health (NIH)-funded Infant Brain Imaging Study (IBIS), Piven and Hazlett’s team scanned the brains of 106 of these ‘high-risk’ infants at age 6, 12 and 24 months using magnetic resonance imaging (MRI), to see if they could catch the brain overgrowth in the act. They also followed 42 low-risk infants. 
   
   What did they find? 
   
   Fifteen of the high-risk infants were diagnosed with autism at 24 months. MRI scans revealed that the volume of these infants’ brains grew faster between 12 and 24 months, compared with children who were not diagnosed with ASD, and that this accelerated growth occurred at the same time that behavioural signs of autism appeared. 
   
   The researchers also found brain changes between 6 and 12 months, before ASD symptoms appeared. The cortical surface area — a measure of the size of folds on the outside of the brain — grew faster in infants later diagnosed with autism, compared with those who did not receive a diagnosis. 
   
   Hazlett et al, Nature 2017; 10.1038/nature21369 
   
   Could these brain changes be used to predict autism diagnosis in infants? 
   
   Hazlett and Piven’s team then used a deep-learning neural network, a form of machine learning, to ask if MRI scans at 6 and 12 months in a larger set of high-risk infants could predict an autism diagnosis at age 2. The algorithm correctly predicted 30 out of the 37 autism diagnoses (81%), while producing false-positives in 4 out of the 142 infants who were not later diagnosed. 
   
   “We now have this finding in these high familial risk infants that we can predict 8 out of 10 that we think will get autism,” says Piven, adding that behaviour-based predictions do no better than 50–50 at that age. “This has tremendous clinical implications.” 
   
   What will it take for these results to be used in the clinic? 
   
   A lot more research, agree Pivens’ team and other experts. In the first instance, the results need to be confirmed with a larger follow-up study of high-risk infants: Piven's team has applied for NIH funding for such a study. They are also looking at whether other brain-imaging techniques can detect the early brain changes. 
   
   “It’s an excellent piece of science, but ultimately it’s based on a few hundred individuals,” says Armin Raznahan, a clinician-scientist at the National Institute of Mental Health in Bethesda, Maryland. “The key thing is going to be replicating this.” 
   
   Even if the findings are robust, clinical applications could prove limited. Cynthia Schumann, an expert on autism brain imaging at the University of California, Davis, notes that the findings apply only to high-risk infants, and not to the general population. A large follow-up study would be needed to test whether autism can be predicted in the general population, she says. 
   
   Differences between MRI scanners and methods for extracting data could also swamp the subtle anatomical changes detected in the study, adds Raznahan. Widespread application would also depend on having a ‘growth-chart for the brain’ that is broadly applicable across the general population — a huge challenge, he notes. 
   
   If autism could be predicted in infants, could doctors do anything about it? 
   
   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. Having a reliable tool for early diagnosis could help researchers to test interventions, because it would help them to determine whether a treatment is working or not, adds Piven. ||||| Experimental research may lead to a new method to diagnose infants with autism before symptoms show. 
   
   In what they say is a first-of-its-kind study, researchers used magnetic resonance imaging (MRI) to examine the brains of infants at high risk for autism – those whose older siblings had the disorder – at 6 months, 12 months, and 24 months of age. 
   
   From the scans, researchers were able to correctly predict 80 percent of those infants who would later meet criteria for autism at 2 years of age. 
   
   The results revealed that early brain development biomarkers could be helpful in determining which high-risk babies will go on to develop autism. 
   
   “We see an increased rate of growth in the outer surface of the brain, the folds, the sort of waviness of the surface that’s followed by an overgrowth of the brain in the second year,” senior study author Joseph Piven, M.D., of the University of North Carolina-Chapel Hill, told CBS News. 
   
   That overgrowth of the brain coincided with the behaviors typical of autism that start to emerge when the child reaches their second year, the researchers say. 
   
   By identifying the brain changes early, there’s the potential to develop therapies that could intervene sooner, while the brain is still developing. 
   
   “It’s a time we’re talking about during the first year of life where the brain is most malleable,” Piven said. 
   
   About one out of 68 children develop autism in the United States, according to the Centers for Disease Control and Prevention. For infants with older siblings with autism, the risk may be as high as 20 out of every 100 births. 
   
   Most children aren’t diagnosed until at least the age of 2 or older. 
   
   Early diagnosis is key, experts say, because the sooner the disorder is recognized, the sooner families and doctors can employ intervention strategies like behavioral and communications therapies, and more likely the child is to achieve a better outcome. In fact, one study published in 2014 found that if intervention begins as early as the first 6 months of life, it can significantly improve a child’s condition and possibly even eliminate symptoms. 
   
   Though the current research was only done in babies who have an older sibling with autism, the researchers say it may eventually be useful to the general population. 
   
   “We haven’t had a way to detect the biomarkers of autism before the condition sets in and symptoms develop,” Piven said in a statement. “Now we have very promising leads that suggest this may in fact be possible.” ||||| Images revealed which infants would go on to have an autism diagnosis, raising hopes for earlier care and interventions for those affected 
   
   Babies who are most at risk of developing autism as toddlers have been identified from brain scans in the first year of life. 
   
   The images helped doctors spot which of a group of children who were already at risk because of autism in the family would later be diagnosed with the condition. 
   
   
   
   The work raises hopes that affected children could be helped with earlier specialised care and interventions to help their social abilities before any behavioural symptoms start to appear. 
   
   
   
   Brain scans of premature babies reveal changes that may raise risk of autism Read more 
   
   Scientists studied 106 babies, all of whom had an older brother or sister with autism, and found that telltale features in brain images taken at six and 12 months revealed which infants would go on to have an autism diagnosis. 
   
   
   
   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. 
   
   
   
   “We don’t have such a tool yet, but if we did, parents of high-risk infants wouldn’t need to wait for a diagnosis of autism spectrum disorder at two, three or even four years,” said Annette Estes, a co-author on the study and director of the University of Washington in Seattle. “Researchers could start developing interventions to prevent these children from falling behind in social and communication skills,” she added. 
   
   
   
   About one in 70 children in the UK develops autism, but among those with a diagnosed sibling, the risk of the condition can rise to about one in five. The test has not been tried on children who are not at high risk. 
   
   
   
   Writing in the journal Nature, the scientists describe how they compared brain scans of high-risk babies with those from 42 low-risk children who had no siblings with autism. On each lab visit, scientists assessed the children’s behaviour and intellectual abilities. 
   
   
   
   Study offers potential breakthrough in care of children with autism Read more 
   
   The images, taken as the babies slept, revealed that high-risk infants who developed autism experienced a “hyperexpansion” of the brain’s surface in the first year of life. The unusual growth preceded a rise in brain volume over the following year that was linked to social difficulties the children developed. 
   
   
   
   The scientists next used a machine learning algorithm to predict from the scans and the infant’s sex which high-risk children would be diagnosed with autism at the age of two. The computer identified eight in 10 of those who developed autism. In about 3% of cases, it predicted autism that did not appear. 
   
   
   
   Estes said that by the time children are diagnosed at the age of two to four years old, they have often already fallen behind their peers in terms of social skills, language and communication. Once children have missed those developmental milestones, she added, catching up is a struggle for many and nearly impossible for some. 
   
   
   
   “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. 
   
   
   
   Carol Povey, director of the National Autistic Society’s Centre for Autism, said: “If confirmed by further research, it’s possible that MRI scanning of this type could be developed to help families who already have an autistic child to access earlier diagnosis for subsequent children. This would mean those children could receive the right support as early as possible. 
   
   “It is important to highlight, however, that autism is a complex condition which manifests in many different ways. No single test is likely to be able to identify potential autism in all children, but this technology could help simplify and speed up the route to autism assessment for some children.”
target: – Promising new research may make it possible to detect autism in babies before symptoms appear. Researchers scanned the brains of infants with autistic siblings considered at high risk of developing the disorder themselves. They report in the journal Nature that brain changes identified in MRIs of infants allowed them to predict with 80% accuracy in the first year which ones would go to show autistic symptoms. Children usually do not show signs of autistic spectrum disorder (ASD), such as not making eye contact, until age 2 or older. Early intervention has been shown to ease and even reverse symptoms. Lead author Joseph Piven tells CBS News "the first year of life (is) where the brain is most malleable" and responsive to treatment. Though small in scope, the first-ever study could lead to development of a tool to predict autism in high-risk infants—and perhaps in the general population—before their first birthday "to prevent these children from falling behind in social and communication skills," co-author Annette Estes tells the Guardian. One in 100 children develop autism, but that risk zooms to one in five for those with an autistic sibling, per Nature. Scientists analyzed the brain scans of 106 babies at high risk and 42 at low risk for the disorder. Those in the high-risk group who later went on to develop ASD saw unusual growth of the outer surface of the brains in the first year of life, followed by "an overgrowth of the brain" in the second year, Piven tells CBS. That brain growth was linked to ASD symptoms. ("Neural fingerprint" of mom's voice may help unlock secrets of autistic brains.)