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A year after the researchers published their work on the physiological test for signs of autism, a subsequent study confirms its exceptional success in assessing whether a child has an autistic spectrum disorder.

A physiological test that supports the diagnostic process of a clinician may reduce the age of autism diagnosis, leading to earlier treatment. The results of a study that uses an algorithm to predict whether a child has an autism spectrum disorder (ASD) based on metabolites in a blood sample are published in the June issue of Bioengineering & amp; Translational Medicine.

"We looked at groups of children with ASD regardless of our previous research and got a similar result. We can predict with children's autism with 88 percent accuracy, "said Jurgen Khan, lead author, system biologist, professor, head of Rensselaer, Polytechnic Institute of the Department of Biomedical Engineering and member of the Center for Biotechnology and Interdisciplinary Research. Rensselaer (CBIS). "This is very promising."

An estimated 1.7% of all children diagnosed with ASD are diagnosed as "developmental disabilities caused by differences in the brain," according to the Centers for Disease Control and Prevention. An earlier diagnosis is usually considered the best result, because children receive early care in the treatment of autism. The diagnosis of ASD is possible at the age of 18-24 months, however, since the diagnosis depends solely on clinical observations, most children do not diagnose ASD for up to 4 years. Instead of searching for a single ASD indicator, the developed approach uses large data methods to find the patterns of metabolites related to two related cellular pathways (a series of interactions between molecules that control cell function) with suspicious connections to ASD.

"Jürgen's work on the development of a physiological test for signs of autism is an example of how the interdisciplinary life science and technology interface brings new perspectives and solutions to improve human health," said Deepak Vashisht, CBIS Director. "This is an excellent result because of the greater emphasis on Alzheimer's and neurodegenerative diseases in CBIS, where our work combines several approaches to developing better diagnostic tools and biomanipulating new therapeutic drugs."

Initial success in 2017 analyzed data from a group of 149 people, about half, of which, previously were diagnosed with ASD. For each member of the group, Khan received data on 24 metabolites associated with two cellular pathways-the methionine cycle and the trans-sulfation route. By deliberately omitting data from one person in the group, Khan transferred the remaining set of data to advanced analysis methods and used the results to generate the prediction algorithm. Then the algorithm made a prediction about the data from the missed individual. Khan cross-validated the results, replacing another person from the group and repeating the process for all 149 participants. His method was correctly identified by 96.1 percent of all typically developing participants and 97.6 percent of ASD cohorts.

The new study applies Khan's approach to an independent set of data. To avoid a lengthy process of collecting new data through clinical trials, Khan and his team searched for existing data sets that included the metabolites that he analyzed in the initial study. Researchers have identified relevant data from three different studies, in which there were a total of 154 autistic children, conducted by researchers at the Arkansas Children's Research Institute. The data included only 22 of the 24 metabolites that he used to create the original prediction algorithm, but Khan determined that the available information would be sufficient for the test.

The team used its approach to recreate the prediction algorithm, this time using data from 22 metabolites from the original group of 149 children. Then the algorithm was applied to a new group of 154 children for testing purposes. When the prediction algorithm was applied to each person, he correctly predicted autism with 88 percent accuracy.

Khan said that the difference between the initial accuracy rate and the speed of the new study may be related to several factors, the most important being that two of the metabolites were not available in the second set of data. Each of the two metabolites was a strong indicator in the previous study.

In general, the second study confirms the initial results and gives an idea of ​​several approaches.

"The most significant result is the high degree of accuracy that we can obtain using this approach on data collected over the years, in addition to the initial set," Khan said. "This is an approach that we would like to see in clinical trials and, ultimately, in commercially available tests."

Khan joined the research of doctoral students: Troy Vargason, Daniel P. Hausmon, Robert A. Rubin from Whittier College; Leanna Delhi, Marie Tippett, Shannon Rose and Sirish K. Bennuri of the Children's Research Institute in Arkansas and the Arkansas University of Medical Sciences; John Slater, Stepan Melnik and S. Jill James of the University of Arkansas for Medical Sciences; and Richard E. Fry of Phoenix Children's Hospital. The study was partially funded by the National Institutes of Health.

Source:

Materials provided by the Rensselaer Polytechnic Institute.

Directory:

Daniel P. Hausmon, Troy Vargason, Robert A. Rubin, Leanna Delhi, Marie Tippet, Shannon Rose, Sirish K. Bennuri, John Slater, Stepan Melnik, S. Jill James, Richard E. Fry, Jurgen Khan. Multivariate methods allow for a biochemical classification of children with autism spectrum disorder compared to typically developing peers: comparison and validation. Bioengineering and translational medicine, 2018; DOI: 10.1002 / btm2.10095

Source: www.sciencedaily.com

Nicolett Zeliat

A new study shows that girls with signs of autism at an early stage have fewer problems with social communication than boys, but in their teens, their skills become worse. Researchers considered the social features of autism in the entire population, and not only in children with autism. Girls have fewer such social problems than boys at the age of 7, but their social skills correspond to boys under the age of 16.

Conclusions can help explain why girls often get an autism diagnosis later than boys.

"There is a group of girls who can not attend clinics aimed at working with social difficulties before adolescence," said lead researcher William Mandy, senior lecturer in clinical psychology at London College.

It is unclear why these difficulties occur during adolescence. Mandy and others say that terms can refer to the increasing complexity of the social environment of girls at this age.

"This can be an example of social needs in adolescence that exceed the potential, especially for women," says Stelios Georgiades, assistant professor at the Department of Psychiatry and Behavioral Neurobiology at McMaster University in Ontario, Canada, who did not participate. >

However, some experts doubt the relevance of the issue of social problems in adolescent girls.

"I was very surprised by these findings," says Tony Charman, a student of clinical child psychology at King's College London, who did not participate in the study. "It would be much easier to take seriously the probable truthfulness of the assertion about these traits of adolescent girls if you could see that this is repeated on other examples."

Tracking:

Mandy and his colleagues analyzed data from 9,744 children in the Avon Longitudinal Study of Parents and Children study. The study tracks the development of children born in south-west England between April 1991 and December 1992.

When the children were 7, 10, 13 and 16, their parents filled out a checklist of social communication disorders, which is a diagnostic tool. High scores on this questionnaire indicate possible autism, and help in its early treatment.

The researchers built estimates of each child by age, and then compared the average trajectory of boys with girls. They reported the results on April 19 in the Journal of Child Psychology and Psychiatry.

In general, the average score for boys and girls shows a slight decrease from 7 to 10 years and an increase in age from 10 to 16 years. But girls are rated lower than boys at the age of 7, and their average score increases in adolescence.

The same picture persists when researchers limit their analysis to children with the highest level of autism signs, based on their assessments in the control list. Sexual differences do not depend on the level of intelligence.

If children with an autism spectrum disorder follow the same pathways, clinicians may have to evaluate the girls several times to determine the symptoms of autism, says Hyun "Sophie" Kim, associate professor of psychology in clinical psychiatry in medicine Vella Cornell in New York , which did not participate in the study. "Repeated evaluations in adolescence can be important for girls who have subclinical symptoms at an early stage," she says.

Jump points:

The findings lend themselves to Georgiades' unpublished testimony, which indicates that the severity of autism signs increases in some children when they begin to go to school. The results are taken from a Canadian study called Pathways in Autism Spectrum Disorders, in which researchers monitored children under the age of 11.

"Trajectories of social traits are not linear," says Georgiades. "There are potentially important transition points - for example, in the school system at about the age of 6 and in adolescence between the ages of 11 and 12."

However, skeptics say that the apparent increase in signs of autism in adolescent girls may reflect common problems such as anxiety and depression that are more common in girls of this age than boys.

"Social behavior is a complex organism in itself, and it reflects a lot," says Elise Robinson, associate professor of epidemiology at Harvard University, who did not participate in the study. "It's hard to guess what changes occur in the spheres of influence when we grow old."

A study conducted by Mandy's team in 2017 contradicts the idea that high levels of anxiety explain new results. This study found that signs of autism predict social anxiety, but not vice versa.

Mandy and his colleagues analyzed data from 9,744 children in the Avon Longitudinal Study of Parents and Children study. The study tracks the development of children born in south-west England between April 1991 and December 1992.

When the children were 7, 10, 13 and 16, their parents filled out a checklist of social communication disorders, which is a diagnostic tool. High scores on this questionnaire indicate possible autism, and help in its early treatment.

The researchers built estimates of each child by age, and then compared the average trajectory of boys with girls. They reported the results on April 19 in the Journal of Child Psychology and Psychiatry.

In general, the average score for boys and girls shows a slight decrease from 7 to 10 years and an increase in age from 10 to 16 years. But girls are rated lower than boys at the age of 7, and their average score increases in adolescence.

The same picture persists when researchers limit their analysis to children with the highest level of autism signs, based on their assessments in the control list. Sexual differences do not depend on the level of intelligence.

If children with an autism spectrum disorder follow the same pathways, clinicians may have to evaluate the girls several times to determine the symptoms of autism, says Hyun "Sophie" Kim, associate professor of psychology in clinical psychiatry in medicine Vella Cornell in New York , which did not participate in the study. "Repeated evaluations in adolescence can be important for girls who have subclinical symptoms at an early stage," she says.

Jump points:

The findings lend themselves to Georgiades' unpublished testimony, which indicates that the severity of autism signs increases in some children when they begin to go to school. The results are taken from a Canadian study called Pathways in Autism Spectrum Disorders, in which researchers monitored children under the age of 11.

"Trajectories of social traits are not linear," says Georgiades. "There are potentially important transition points - for example, in the school system at about the age of 6 and in adolescence between the ages of 11 and 12."

However, skeptics say that the apparent increase in signs of autism in adolescent girls may reflect common problems such as anxiety and depression that are more common in girls of this age than boys.

"Social behavior is a complex organism in itself, and it reflects a lot," says Elise Robinson, associate professor of epidemiology at Harvard University, who did not participate in the study. "It's hard to guess what changes occur in the spheres of influence when we grow old."

A study conducted by Mandy's team in 2017 contradicts the idea that high levels of anxiety explain new results. This study found that signs of autism predict social anxiety, but not vice versa.

Mandy and his colleagues plan to study the characteristics of girls without autism, which demonstrate a dramatic increase in social problems of communication in adolescence in order to identify signs of social problems.

RECOMMENDATIONS:

Mandy W. et al., J. Child Psychol. Psychiatry Epub before printing (2018) PubMed

Source: www.spectrumnews.org

Missense mutations occur when a pair of DNA bases of one gene changes, and this change leads to the replacement of one amino acid with another in the protein of the gene. Mutations that disrupt the function of proteins are widely recognized as a source of risk for developing developmental disorders such as intellectual disability, congenital heart disease and ASD.

In a new study published in Nature Genetics, a comprehensive computational approach was developed to investigate the functional impact of missense mutations. The team, which includes Cuthhern Roder of the Carnegie Mellon University, tested this approach by analyzing the genetic structures of people with ASD who had mutations, as well as their siblings who did not have mutations. They found that the program successfully identified and identified priority missense mutations that contribute to the risk of a disease or disorder.

"Identification of genetic mutations that increase the likelihood of the disease is a serious problem for progress in personalized medicine. Using a machine learning model that predicts which mutations can disrupt the human interactive network, we have shown that these mutations are much more likely to occur in autistic sufferers than their brothers and sisters, "says Roder, professor of statistics and life sciences, in College of Humanities and Social Sciences Dietrich. "This result extends to several other mental disorders, suggesting that our conclusion may have an even wider application."

Materials provided by Carnegie Mellon University.

Journal Reference:

Siwei Chen, Robert Fragoza, Lambertus Klei, Yuan Liu, Jiebiao Wang, Kathryn Roeder, Bernie Devlin, Haiyuan Yu. The interacting perturbation structure prioritizes damaging mutant mutations for developmental disorders. Nature Genetics, 2018; DOI: 10.1038 / s41588-018-0130-z

Source: www.sciencedaily.com

Investigating the iPhone application for young children, which reveals signs of autism, has shown that it is easy to use, is welcomed by caretakers and works well with reliable scientific data.

The study, described on June 1 in the journal of open access to Digital Medicine, points the way to a wider, easier access to the diagnosis of autism and other neurodevelopmental disorders.

The application first manages the consent forms for care and polling, and then uses the phone's "selfie" camera to collect video reactions of young children's reactions while they watch films designed to identify the risk of autism, for example, emotions and attention on the device screen .

The child's video reactions are sent to the research servers, where the automatic behavioral coding software tracks the movement of video landmarks on the child's face and quantifies the emotions and attention of the child. For example, in response to a short video of bubbles floating around the screen, the video encoding algorithm looks for the movements of the person that will point to joy.

In this study, children whose parents rated their child as having a large number of autism symptoms showed less joyful emotions in response to the blisters.

Prevention of autism in young children is currently carried out in a clinical setting, rather than in the child's natural environment, and people with a high degree of preparation are required to learn and analyze the results. "It's not scalable," says Helen Egger of New York University, one of the co-leaders of the study.

This study, based on informed consent on data collection and preliminary analysis, was conducted using an application available free of charge from the Apple Store and based on Apple ResearchKit's open source development platform.

During the year, more than 10,000 downloads of the application were downloaded, and the study involved 1,756 families with children aged one to six years. Parents completed 5,618 polls and downloaded 4,441 videos. Useful data was collected on 88 percent of downloaded videos, demonstrating for the first time the possibility of using this type of tool for observation and coding in natural environments.

"This demonstrates the feasibility of this approach," says Geraldine Dawson, Ph.D., director of the Center for Autism and Brain Development and co-chair of the study. "Many educators were ready to participate, the data was of high quality, and the video analysis algorithms produced results consistent with the results we produce in our autism program."

The application-based approach can significantly improve in areas with insufficient protection and greatly facilitate tracking of changes in each child over time, said Guillermo Sapiro, Edmund T. Pratt, Jr. Professor of the Department of Electrical and Computer Engineering Duke and one of the co-chairs of the study .

"This technology has the potential to transform how we screen and control the development of children," said Sapiro.

The project reported consisted of a 12-month study. The whole test took about 20 minutes, and only a few minutes with the child's participation.

The application also included a widespread questionnaire that screens the autism spectrum disorder. On the basis of the questionnaire, participating families received some feedback from the appendix on what could be an obvious risk of autism in a child. If parents reported a high level of signs of autism in the questionnaire, they were asked to seek further medical advice.

Source:

Materials provided by Duke University.

Journal Reference:

Helen L. Egger, Geraldine Dawson, Jordan Hashemi, Kimberly L. Kh. Carpenter, Stephen Espinosa, Kathleen Campbell, Samuel Brotkin, Jana Shaich-Borg, Qian Qiu, Mariano Tepper, Jeffrey P. Baker, Richard A. Bloomfield , Guillermo Sapiro. Automatic analysis of emotions and attention in young children at home: a feasibility study of Autism ResearchKit. npj Digital Medicine, 2018; 1 (1) DOI: 10.1038 / s41746-018-0024-6

Source: www.sciencedaily.com

About our Centre

The Scientific and Practical Center for the Rehabilitation and Treatment of Autism Spectrum Disorders is working together with the Center for the Rehabilitation of Disabled Children "Our Sunny World".

Programs and Seminars

We offer a wide range of professional training programs and seminars for all groups of professionals interacting with autism spectrum disorders.

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