Carolina Institute for Developmental Disabilities

Carrboro, NC, United States

Carolina Institute for Developmental Disabilities

Carrboro, NC, United States
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Elison J.T.,University of North Carolina at Chapel Hill | Elison J.T.,Carolina Institute for Developmental Disabilities | Sasson N.J.,University of Texas at Dallas | Turner-Brown L.M.,Carolina Institute for Developmental Disabilities | And 2 more authors.
Research in Autism Spectrum Disorders | Year: 2012

Because previous studies of attention in autism spectrum disorders (ASD) have been restricted in age range examined, little is known about how these processes develop over the course of childhood. In this study we examined cross-sectional age effects on patterns of visual attention to social and nonsocial information in 43 typically developing children and 51 children with ASD ranging in age from 2 to 18. Results indicated a sharp increase in visual exploration with age and a decrease in perseverative and detail-focused attention for both groups of children. However, increased age was associated with greater increases in visual exploration for typically developing children than for those children with ASD. The developmental differences were most pronounced for attention to certain nonsocial stimuli as children with ASD demonstrated a disproportionate attentional bias for these stimuli from very early in life. Disproportionate visual attention to certain nonsocial objects relative to social stimuli in ASD spanned from early to late childhood, and thus may represent both an early and a persistent characteristic of the disorder. © 2011 Elsevier Ltd. All rights reserved.


News Article | April 7, 2016
Site: www.biosciencetechnology.com

A tiny juvenile fish. That’s what’s at the center of a big effort to image the brain of a vertebrate organism like never before. Spencer Smith, Ph.D., assistant professor in the Department of Cell Biology and Physiology and the UNC Neuroscience Center at the UNC School of Medicine, is part of an international team that hopes to create a new imaging system to study individual neurons in high resolution throughout the entire brain of a freely moving vertebrate. This sort of technological feat has never been accomplished. “We will image neural activity in high resolution, enough to see individual neurons, as if we’re reading the zebrafish’s mind while it’s completely unrestrained and performing natural movements and behaviors,” Smith said. “There will be no surgery, nothing tethered to the animals.” Smith, who is also a member of the Carolina Institute for Developmental Disabilities, added, “This is basic science, for sure, but if we’re successful, we hope our work will allow us and other scientists to gain insights that will have broader applicability to human health down the road.” To bring this unique project to life, the team received a $900,000 grant from the Human Frontier Science Program (HSFP), an organization that funds basic scientific research through the financial support of 15 countries, including the United States. We all know about MRIs, PET scans, and CT scans. These important diagnostic tools can provide images that tell us a lot about human biology, disease, and to an extent what’s happening in the human brain. But they can’t be used to study what specific kinds of neurons are doing, what roles these neurons play in various neurological conditions, or even which neurons are important for typical behaviors and where the cells are located. For that, scientists need technology that can focus in on individual neurons, and it would be best if scientists could focus on individual neurons throughout the brain while the animals are freely moving about. That kind of microscope doesn’t exist. Smith and his colleagues – German scientist Benjamin Judkewitz, Ph.D., of Charité Berlin & Humboldt University, and Spain’s Ruben Portugues, Ph.D., at the Max Planck Institute of Neurobiology  – are taking on this challenge. They’re building a new kind of microscope with a wide enough field of view to image nearly the entire brain of a juvenile zebrafish while the fish is living its life. That is, the researchers hope to create real-time high-resolution visualizations of individual neurons firing throughout the brain of the transparent fish while it’s hunting for prey, swimming back and forth, darting here and there. “That’s the high bar,” Smith said. “The low bar would be to track neuronal activity throughout most of the brain while the fish is stationary or moving slowly. Both are difficult challenges, but tracking the fish during fast motion will be quite a trick and will require the expertise of the entire team. That’s why this grant is a good fit for the HFSP, which funds high-risk, high-reward international and interdisciplinary projects that are, frankly, difficult to get funded otherwise.” Smith’s lab at UNC is building the optics – the microscope they hope is capable of capturing images of individual neurons firing throughout the juvenile zebrafish’s brain while it navigates its world. One fish is four millimeters long. Therefore, it can live in a small dish, swim freely, and hunt for even tinier critters. Still, optics large enough for this sort of experiment have never been made before, which is why Smith’s lab is custom-designing the optics and having the parts custom-made. He is also creating a new kind of scanning engine to rapidly image the moving fish. The other scientists are working on the fast-tracking system so that the microscope can capture high resolution images of individual neurons across the brain even while the fish moves quickly through three dimensions. Smith’s European colleagues will also conduct the actual experiments on the zebrafish. The grant is for three years. By the end, the scientists hope to have a new piece of technology that they and other scientists can use to gain insights into how vertebrates process visual information while moving to achieve a goal, such as hunting prey. Down the line, it’s conceivable that Smith and his colleagues could extend this kind of technology to other organisms and answer various questions about brain functions of other model animals, including other complex vertebrate organisms. This work builds upon Smith’s other projects – the creation of imaging systems that can image multiple brain areas of a mouse. The limitation of this innovation is that the mouse must be stationary. Therefore, there are a limited number of experiments related to visual processing that Smith and others can perform. “Scientists have developed computer models of neural activity related to visual processing and motor activity,” Smith said. “But if we can’t measure neural activity during an animal’s natural behavior, then we can’t completely validate those models.” He added, “This won’t happen soon, but we’re already thinking about optically monitoring individual neural activity throughout the brains of freely moving rodents without any instrumentation on their heads or tethers,” Smith said. “From a physics standpoint, there’s no reason why we couldn’t do that. If we can, then we could learn a lot about brain function related to behaviors and even neurological conditions. This zebrafish research is a big, complicated first step in that direction.”


News Article | February 15, 2017
Site: www.chromatographytechniques.com

Autism can be predicted in most infants through measurements of the brain, according to a groundbreaking new study in the journal Nature. Bigger brains between the ages of 6 and 12 months allowed a team from the Children’s Hospital of Philadelphia and the University of North Carolina-Chapel Hill to predict autism by age 2 with 90 percent accuracy. “The results of this study are a real breakthrough for early diagnosis of autism,” said Robert Schultz, who leads the Center for Autism Research at CHOP. “While we have known for some time that autism emerges in subtle, gradual ways over the first few years of life, this study offers the first firm evidence before a child’s first birthday predicting whether certain high-risk children are likely to be diagnosed with autism.” The scientists used MRI imaging on 106 high-risk infants (who had autistic older siblings) and 42 low-risk infants. The scans were conducted at 6, 12 and 24 months. They assessed the growth of the brain using a computer-generated algorithm. When combined with brain volume and sex of the infants, it predicted most of the ASD cases among the group. The analysis was most accurate in predicting the high-risk babies that did not develop autism, they added. The ultimate value in early treatment and detection may be early interventions, which have proven to mitigate negative effects of being on the spectrum, they added. “We haven’t had a way to detect the biomarkers of autism before the condition sets in and symptoms develop,” said Joseph Piven, the senior author of the study, from the Carolina Institute for Developmental Disabilities at UNC. “Now we have very promising leads that suggest this may in fact be possible.” The latest CDC estimates find that one in 68 children of schooling age are diagnosed with autism in the United States – though some debate exists as to whether the spectrum is more prevalent, or if detection is better. Currently about 3 million people of all ages live with autism in the U.S.


News Article | February 15, 2017
Site: www.eurekalert.org

This first-of-its-kind study used MRIs to image the brains of infants, and then researchers used brain measurements and a computer algorithm to accurately predict autism before symptoms set in CHAPEL HILL, NC - Using magnetic resonance imaging (MRI) in infants with older siblings with autism, researchers from around the country were able to correctly predict 80 percent of those infants who would later meet criteria for autism at two years of age. The study, published today in Nature, is the first to show it is possible to identify which infants - among those with older siblings with autism - will be diagnosed with autism at 24 months of age. "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," said senior author Joseph Piven, MD, the Thomas E. Castelloe Distinguished Professor of Psychiatry at the University of North Carolina-Chapel Hill. "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." This 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, where Piven is director. The project's other clinical sites included the University of Washington, Washington University in St. Louis, and The Children's Hospital of Philadelphia. Other key collaborators are McGill University, the University of Alberta, the University of Minnesota, the College of Charleston, and New York University. "This study could not have been completed without a major commitment from these families, many of whom flew in to be part of this," said first author Heather Hazlett, PhD, assistant professor of psychiatry at the UNC School of Medicine and a CIDD researcher. "We are still enrolling families for this study, and we hope to begin work on a similar project to replicate our findings." People with Autism Spectrum Disorder (or ASD) have characteristic social deficits and demonstrate a range of ritualistic, repetitive and stereotyped behaviors. It is estimated that one out of 68 children develop autism in the United States. For infants with older siblings with autism, the risk may be as high as 20 out of every 100 births. There are about 3 million people with autism in the United States and tens of millions around the world. Despite much research, it has been impossible to identify those at ultra-high risk for autism prior to 24 months of age, which is the earliest time when the hallmark behavioral characteristics of ASD can be observed and a diagnosis made in most children. For this Nature study, Piven, Hazlett, and researchers from around the country conducted MRI scans of infants at six, 12, and 24 months of age. They found that the babies who developed autism experienced a hyper-expansion of brain surface area from six to 12 months, as compared to babies who had an older sibling with autism but did not themselves show evidence of the condition at 24 months of age. Increased growth rate of surface area in the first year of life was linked to increased growth rate of overall brain volume in the second year of life. Brain overgrowth was tied to the emergence of autistic social deficits in the second year. Previous behavioral studies of infants who later developed autism - who had older siblings with autism -revealed that social behaviors typical of autism emerge during the second year of life. The researchers then took these data - MRIs of brain volume, surface area, cortical thickness at 6 and 12 months of age, and sex of the infants - and used a computer program to identify a way to classify babies most likely to meet criteria for autism at 24 months of age. The computer program developed the best algorithm to accomplish this, and the researchers applied the algorithm to a separate set of study participants. The researchers found that 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. "This means we potentially can identify infants who will later develop autism, before the symptoms of autism begin to consolidate into a diagnosis," Piven said. If parents have a child with autism and then have a second child, such a test might be clinically useful in identifying infants at highest risk for developing this condition. The idea would be to then intervene 'pre-symptomatically' before the emergence of the defining symptoms of autism. Research could then begin to examine the effect of interventions on children during a period before the syndrome is present and when the brain is most malleable. Such interventions may have a greater chance of improving outcomes than treatments started after diagnosis. "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." Piven said the idea with autism is similar; once autism is diagnosed at age 2-3 years, the brain has already begun to change substantially. "We haven't had a way to detect the biomarkers of autism before the condition sets in and symptoms develop," he said. "Now we have very promising leads that suggest this may in fact be possible." For this research, NIH funding was provided by the Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD), the National Institute of Mental Health (NIMH), and the National Institute of Biomedical Imaging and Bioengineering. Autism Speaks and the Simons Foundation contributed additional support.


News Article | February 15, 2017
Site: www.eurekalert.org

A study published today in the journal Nature is the first to show that it is possible to predict within the first year of life, whether some infants will go on to develop autism. The ability to identify autism risk during infancy could set the stage for developing very early preventive treatments when the brain is most malleable. Earlier detection also provides opportunities for early treatment--and earlier intervention is known to be associated with better long term outcomes. Researchers used magnetic resonance imaging (MRI) technology to capture brain images of infants who are considered at high risk for developing autism spectrum disorder (ASD) by virtue of having an older sibling with ASD. The research team took different measurements of the child's brain at 6 and 12 months of age, including overall volume, surface area and thickness of the cerebral cortex in particular regions. A computer-generated algorithm was used to combine these measurements and was able to predict which babies would develop autism by age two with more than 90 percent accuracy. The Center for Autism Research (CAR) at Children's Hospital of Philadelphia (CHOP) was a major study site in the multicenter research project. The study's lead site was based at University of North Carolina-Chapel Hill. "The results of this study are a real breakthrough for early diagnosis of autism," said Robert T. Schultz, PhD, who directs the Center for Autism Research and led the CHOP study site. "While we have known for some time that autism emerges in subtle, gradual ways over the first few years of life, this study offers the first firm evidence before a child's first birthday predicting whether certain high-risk children are likely to be diagnosed with autism." Despite extensive research, it has been impossible until now to identify these children before the second year of life, when behaviors typical of autism emerge. "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," said the study's senior author, Joseph Piven, MD, of the Carolina Institute for Developmental Disabilities (CIDD) at the University of North Carolina. Autism Spectrum Disorder (or ASD) is a complex developmental disability characterized by difficulties in social interaction, verbal and nonverbal communication, and repetitive behaviors or interests. Behavioral symptoms usually become evident between ages two and four, and research has shown that children who receive the earliest treatment tend to reap the most benefits. It is estimated that one in 68 school-aged children are diagnosed with autism. In infants who have older siblings with autism, the risk of developing ASD may be as high as 20 out of every 100 births. There are about 3 million people with autism in the United States and tens of millions around the world. For this Nature study, Piven, Schultz, and researchers from across North America conducted MRI scans of 106 high-risk infants and 42 low-risk infants at six, 12, and 24 months of age. They found that the babies who developed autism experienced much more rapid growth of the brain's surface area from six to 12 months than babies who did not show evidence of autism at 24 months of age. The study team also found a link between increased growth rate of surface area in the first year of life and an increased growth rate of overall brain volume in the second year of life. Extensive prior research has identified enlarged brain size as a risk factor for autism. This most recent study shows this pattern of rapid growth originates in specific brain regions long before brain size itself shows significant enlargement. In addition, brain overgrowth correlated with the severity of social deficits that emerged by age two. 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. These measurements, combined with brain volume and sex of the infants predicted with a high degree of accuracy who would develop autism by age 24 months. To generate these predictive results, the team drew on machine learning, a statistical approach that uses pattern recognition to make very detailed predictions. 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. This analytic approach was also almost perfect in predicting which high-risk babies would not develop autism by age 2 years. The authors emphasize that the effectiveness of the algorithm needs to be reproduced in future studies in order to be ready for clinical use. "If we are able to replicate these results in further studies, these findings promise to change how we approach infant and toddler screening for autism, making it possible to identify infants who will later develop autism before the behavioral symptoms of autism become apparent," Schultz said. For example, if parents have a child with autism and then have a second child, such a test might be clinically useful in identifying infants at highest risk for developing this condition. The idea would be to then intervene 'pre-symptomatically' before the defining symptoms of autism emerge. The study also has implications for developing new autism treatments, said Schultz, a pediatric neuropsychologist. "Using brain imaging, we were able to pinpoint areas of the brain where atypical development contributes to autism. Understanding these neural mechanisms may guide us in developing opportunities for early treatment--possibly, before the symptoms of autism become outwardly visible." The same collaborators published a related study last month using functional MRI scans to identify brain networks involved in a key social behavior called initiation of joint attention. In this behavior--often impaired in ASD--a baby focuses on an object and draws another person's attention to that object. This study is the earliest known description of how functional brain systems underlie an important social behavior. In addition to adding to the neurobiology of how social behavior develops, those findings may inform efforts to design new treatments. "Putting this into the larger context of neuroscience research and treatment, there is currently a big push within the field to be able to detect the biomarkers of these conditions before patients are diagnosed, at a time when preventive efforts are possible," Piven added. "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." Piven said the idea with autism is similar; once autism is diagnosed at age two to three years, the brain has already begun to change substantially. "We haven't had a way to detect the biomarkers of autism before the condition sets in and symptoms develop," he said. "Now we have very promising leads that suggest this may in fact be possible." The National Institutes of Health (grants HD055741, EB005149, HD003110 and MH093510) funded this study. This research was led by researchers at the Carolina Institute for Developmental Disabilities (CIDD) at the University of North Carolina, which is directed by the study's senior author, Joseph Piven, MD, the Thomas E. Castelloe Distinguished Professor of Psychiatry at the University of North Carolina-Chapel Hill. Other clinical sites included Children's Hospital of Philadelphia, the University of Washington, and Washington University in St. Louis. Other key collaborators are McGill University, the University of Alberta, the College of Charleston, and New York University. Heather Cody Hazlett, et al "Early Brain Development in Infants at High Risk for Autism Spectrum Disorder" Nature, in print Feb. 16, 2017. http://doi. About Children's Hospital of Philadelphia: Children's Hospital of Philadelphia was founded in 1855 as the nation's first pediatric hospital. Through its long-standing commitment to providing exceptional patient care, training new generations of pediatric healthcare professionals, and pioneering major research initiatives, Children's Hospital has fostered many discoveries that have benefited children worldwide. Its pediatric research program is among the largest in the country. In addition, its unique family-centered care and public service programs have brought the 535-bed hospital recognition as a leading advocate for children and adolescents. For more information, visit http://www.


News Article | February 16, 2017
Site: www.biosciencetechnology.com

Using magnetic resonance imaging (MRI) in infants with older siblings with autism, researchers from around the country were able to correctly predict 80 percent of those infants who would later meet criteria for  autism at two years of age. The study, published today in Nature, is the first to show it is possible to identify which infants – among those with older siblings with autism – will be diagnosed with autism at 24 months of age. “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,” said senior author Joseph Piven, MD, the Thomas E. Castelloe Distinguished Professor of Psychiatry at the University of North Carolina-Chapel Hill. “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.” This 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, where Piven is director. The project’s other clinical sites included the University of Washington, Washington University in St. Louis, and The Children’s Hospital of Philadelphia. Other key collaborators are McGill University, the University of Alberta, the University of Minnesota, the College of Charleston, and New York University. “This study could not have been completed without a major commitment from these families, many of whom flew in to be part of this,” said first author Heather Hazlett, PhD, assistant professor of psychiatry at the UNC School of Medicine and a CIDD researcher. “We are still enrolling families for this study, and we hope to begin work on a similar project to replicate our findings.” People with Autism Spectrum Disorder (or ASD) have characteristic social deficits and demonstrate a range of ritualistic, repetitive and stereotyped behaviors. It is estimated that one out of 68 children develop autism in the United States. For infants with older siblings with autism, the risk may be as high as 20 out of every 100 births. There are about 3 million people with autism in the United States and tens of millions around the world. Despite much research, it has been impossible to identify those at ultra-high risk for autism prior to 24 months of age, which is the earliest time when the hallmark behavioral characteristics of ASD can be observed and a diagnosis made in most children. For this Nature study, Piven, Hazlett, and researchers from around the country conducted MRI scans of infants at six, 12, and 24 months of age. They found that the babies who developed autism experienced a hyper-expansion of brain surface area from six to 12 months, as compared to babies who had an older sibling with autism but did not themselves show evidence of the condition at 24 months of age. Increased growth rate of surface area in the first year of life was linked to increased growth rate of overall brain volume in the second year of life. Brain overgrowth was tied to the emergence of autistic social deficits in the second year. Previous behavioral studies of infants who later developed autism – who had older siblings with autism –revealed that social behaviors typical of autism emerge during the second year of life. The researchers then took these data – MRIs of brain volume, surface area, cortical thickness at 6 and 12 months of age, and sex of the infants – and used a computer program to identify a way to classify babies most likely to meet criteria for autism at 24 months of age. The computer program developed the best algorithm to accomplish this, and the researchers applied the algorithm to a separate set of study participants. The researchers found that 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. “This means we potentially can identify infants who will later develop autism, before the symptoms of autism begin to consolidate into a diagnosis,” Piven said. If parents have a child with autism and then have a second child, such a test might be clinically useful in identifying infants at highest risk for developing this condition. The idea would be to then intervene ‘pre-symptomatically’ before the emergence of the defining symptoms of autism. Research could then begin to examine the effect of interventions on children during a period before the syndrome is present and when the brain is most malleable.  Such interventions may have a greater chance of improving outcomes than treatments started after diagnosis. “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.” Piven said the idea with autism is similar; once autism is diagnosed at age 2-3 years, the brain has already begun to change substantially. “We haven’t had a way to detect the biomarkers of autism before the condition sets in and symptoms develop,” he said. “Now we have very promising leads that suggest this may in fact be possible.”


News Article | February 16, 2017
Site: www.rdmag.com

A new diagnostic method has correctly predicted autism in 80 percent of high-risk infants, according to a new study. Researchers at the University of North Carolina have developed a method using magnetic resonance imaging (MRI) in infants with older siblings with autism to correctly predict whether infants would later meet the criteria for autism at two years old. “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,” Dr. Joseph Piven, the Thomas E. Castelloe Distinguished Professor of Psychiatry at UNC and senior author of the paper, said in a statement. “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.” It is estimated that one out of every 68 children develop Autism Spectrum Disorder (ASD) in the U.S. The patients have characteristic social deficits and demonstrate a range of ritualistic, repetitive and stereotyped behaviors. Despite extensive research, it has been impossible to identify those at ultra-high risk for autism prior to two-years old, which is the earliest time when the hallmark behavioral characteristics of ASD can be observed and a diagnosis made in most children. In the study, the researchers conducted MRI scans of infants at six, 12 and 24 months old. The researchers found that the babies who developed autism experienced a hyper-expansion of brain surface area from six to 12 months, as compared to babies who had an older sibling with autism but did not themselves show evidence of the condition at 24 months of age. They also found that increased growth rate of surface area in the first year of life was linked to increased growth rate of overall brain volume in the second year, which is tied to the emergence of autistic social deficits in the second year. The next step was to take the data—MRI’s of brain volume, surface area, cortical thickness at six and 12 months of age and the sex of the infants—and used a computer program to identify a way to classify babies most likely to meet criteria for autism at two-years old. The computer program developed an algorithm that the researchers applied to a separate set of study participants. The researchers concluded that brain differences at six and 12 months in infants with older siblings with autism correctly predicted eight of 10 infants who would later meet criteria for autism at two-years old in comparison to those with older ASD siblings who did not meet the criteria at two years old. “This means we potentially can identify infants who will later develop autism, before the symptoms of autism begin to consolidate into a diagnosis,” Piven said. This test could be helpful to parents who have a child with autism and have a second child, where they could intervene ‘pre-symptomatically’ before the emergence of the defining symptoms of autism. Researchers could then begin to examine the effect of interventions on children during a period before the syndrome is present and when the brain is most malleable. “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.” The research, which was led by researchers at the Carolina Institute for Developmental Disabilities (CIDD) at the University of North Carolina, where Piven is director, included hundreds of children from across the country. The project’s other clinical sites included the University of Washington, Washington University in St. Louis and The Children’s Hospital of Philadelphia. Other key collaborators are McGill University, the University of Alberta, the University of Minnesota, the College of Charleston and New York University. “This study could not have been completed without a major commitment from these families, many of whom flew in to be part of this,” first author Heather Hazlett, Ph.D., assistant professor of psychiatry at the UNC School of Medicine and a CIDD researcher, said in a statement.


Taylor A.M.,University of North Carolina at Chapel Hill | Taylor A.M.,Neuroscience Center | Taylor A.M.,Carolina Institute for Developmental Disabilities | Menon S.,University of North Carolina at Chapel Hill | And 3 more authors.
Lab on a Chip - Miniaturisation for Chemistry and Biology | Year: 2015

Understanding how axons are guided to target locations within the brain is of fundamental importance for neuroscience, and is a widely studied area of research. Biologists have an unmet need for reliable and easily accessible methods that generate stable, soluble molecular gradients for the investigation of axon guidance. Here we developed a microfluidic device with contiguous media-filled compartments that uses gravity-driven flow to generate a stable and highly reproducible gradient within a viewing compartment only accessible to axons. This device uses high-resistance microgrooves to both direct the growth of axons into an isolated region and to generate a stable gradient within the fluidically isolated axon viewing compartment for over 22 h. Establishing a stable gradient relies on a simple and quick pipetting procedure with no external pump or tubing. Since the axons extend into the axonal compartment through aligned microgrooves, the analysis of turning is simplified. Further, the multiple microgrooves in parallel alignment serve to increase sample sizes, improving statistical analyses. We used this method to examine growth cone turning in response to the secreted axon guidance cue netrin-1. We report the novel finding that growth cones of embryonic mouse cortical axons exhibited attractive turning in the lower concentrations of netrin-1, but were repulsed when exposed to higher concentrations. We also performed immunocytochemistry in growth cones exposed to a netrin-1 gradient within the axon viewing compartment and show that netrin receptors associated with both attraction and repulsion, DCC and UNC5H, localized to these growth cones. Together, we developed an accessible gradient chamber for higher throughput axon guidance studies and demonstrated its capabilities. This journal is © The Royal Society of Chemistry.


News Article | February 15, 2017
Site: www.scientificamerican.com

Parents often notice the first signs of autism in their children at around 12 to 18 months. Maybe a child isn’t making eye contact, or won’t smile when mom or dad walks in the door. But a new study suggests there is evidence of autism in the brain even earlier—well before a child’s first birthday—and that the signs can be seen on a magnetic resonance imaging (MRI) scan. “We’re learning that there are biological changes that occur at [the time] or before the symptoms start to emerge,” says Geraldine Dawson, a clinical psychologist and autism researcher at Duke University who was not involved in the new work. “It’s the ability to detect autism at its very earliest stages that’s going to allow us to intervene before the full syndrome is manifest.” For the study, published this week in Nature, researchers conducted MRI scans on 150 children three times: at six months old, one year and two years. Just over 100 of the children were at high risk because they had an older sibling diagnosed with autism. The faster growth rate of the surface areas of their brains correctly predicted eight times out of 10 which of the high-risk children would go on to be diagnosed with the condition. Enlargement of the brain seemed to correlate with the arrival of symptoms, says Heather Hazlett, a psychologist at the University of North Carolina’s Carolina Institute for Developmental Disabilities (CIDD), and the paper’s lead author. Still, with only 100 at-risk children, the study is too small to be considered definitive—nor should doctors rush to use MRIs to diagnose autism, Hazlett says. But if the study results are confirmed in future research, it could offer a new option for screening high-risk children before their symptoms become obvious—and possibly at a time when treatment will be most effective. The faster pattern of brain growth “is a potential biomarker that could be used to identify those infants who perhaps could benefit from early stimulation,” Dawson says. "This could help those children have the best outcomes.” Autism spectrum disorders—so called because they present a wide range, or spectrum, of different social and communication challenges—are often characterized by behaviors that include rocking motions or obsessions. Parents often do not notice things that would point to an autism diagnosis until about 18 months, when typical children are expected to be talking and interacting socially. By showing the child’s neurobiology changes before behavior does, the study may help parents better understand their child’s experience, says biopsychologist Alycia Halladay, chief science officer at the Autism Science Foundation, a nonprofit that supports research but was not involved in the new work. By showing scientists more about how brains develop prior to an autism diagnosis, the study may also offer insights into the genetic triggers of autism, says James McPartland, a psychologist at Yale University’s Child Study Center who also did not take part in the research. “When we know more about neural pathways, we can think more about the genetic pathways,” he says. One thing the study could not show is whether there is anything different about the autism in families that have more than one child with the condition, compared with autism that seems to have no familial connection. One in every 68 children is diagnosed with autism; but among the younger siblings of a child on the spectrum, the rate is as high as one in five. A number of studies are underway among these younger siblings of children on the spectrum, often called “baby sibs,” who are more likely to develop autism. This group is easier to study than the general population because fewer test subjects are needed to find children who will go on to develop autism. But it is not clear if these “baby sibs” are somehow categorically different from others on the spectrum. To find enough children to make their study useful, the research team followed more than 500 infants, scanning many of them in the middle of the night so they would be in a deep sleep. It took years to get enough valid data on 150 of them, and the families volunteered their time. “Often we don’t keep in mind the degree of work it takes to do this kind of study,” Dawson says. Hazlett and senior author Joseph Piven, a colleague at the CIDD, say they began the research about a decade ago, after an earlier study suggested the brains of autistic children were already unusually large by the time they reached their second birthdays—and before autism’s behavioral symptoms usually emerge. Piven, a psychiatrist, says the mechanism is not precisely clear. But he speculates babies who go on to become autistic experience the world differently in the first year of life than kids who will not have autism do—and that this altered experience of the world may contribute to subsequent brain development in autism. Dawson says because the brain is changing so much in the first year of life, it may be a critical window of development when behavioral interventions—such as teaching a child to pay attention to a parent’s facial expressions—might have the biggest effect. Because it has not been clear until recently that autistic differences begin as early as pregnancy and infancy, there are no therapies to treat such young children. But such treatments are currently being tested. By giving researchers a potential tool to diagnose babies, Dawson says the new study could open up possibilities for testing the potential new therapies. McPartland described possible treatments as “hyper-parenting.” Whereas it might be okay to leave a neurotypical child to play with a toy, a child headed for autism might benefit from more interaction, he says, with a parent cooing, laughing and singing. “Supersaturate a child’s environment with social information much as you can,” he says. “And hope that it takes.”


Menon S.,University of North Carolina at Chapel Hill | Boyer N.P.,University of North Carolina at Chapel Hill | Winkle C.C.,University of North Carolina at Chapel Hill | McClain L.M.,Massachusetts Institute of Technology | And 6 more authors.
Developmental Cell | Year: 2015

Neuronal growth cone filopodia contain guidance receptors and contribute to axon guidance; however, the mechanism by which the guidance cue netrin increases filopodia density is unknown. Here, we demonstrate that TRIM9, an E3 ubiquitin ligase that localizes to filopodia tips and binds the netrin receptor DCC, interacts with and ubiquitinates the barbed-end polymerase VASP to modulate filopodial stability during netrin-dependent axon guidance. Studies with murine Trim9+/+ and Trim9-/- cortical neurons, along with a non-ubiquitinatable VASP mutant, demonstrate that TRIM9-mediated ubiquitination of VASP reduces VASP filopodial tip localization, VASP dynamics at tips, and filopodial stability. Upon netrin treatment, VASP is deubiquitinated, which promotes VASP tip localization and filopodial stability. Trim9 deletion induces axon guidance defects in vitro and in vivo, whereas a gradient of deubiquitinase inhibition promotes axon turning in vitro. We conclude that a gradient of TRIM9-mediated ubiquitination of VASP creates a filopodial stability gradient during axon turning. © 2015 Elsevier Inc.

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