Daniels A.M.,Autism Speaks |
Hoffberg A.,Behavioral Health Leadership Institute |
Agus D.,Behavioral Health Leadership Institute |
Fingerhood M.I.,Johns Hopkins University
Journal of Addiction Medicine | Year: 2014
The aims of this retrospective, descriptive study were to describe clients served by a buprenorphine program in a community-based recovery center and to present initial treatment outcomes. A record review was conducted for clients treated from July 2010 to August 2011. Client demographic, health, substance use, and treatment history data were abstracted from the records of the first 78 clients served. Buprenorphine and opiate use data were collected via urine toxicology reports, collected weekly among clients who remained enrolled in treatment. The average percentages of weeks spent opiate free and buprenorphine compliant were 83% (SD = 26%) and 95% (SD = 13%), respectively. When positive heroin toxicology and negative buprenorphine toxicology were replaced for the missing/unknown data, the average percentages of opiate-abstinent weeks and buprenorphine compliance were 60% (SD = 34%) and 74% (SD = 28%), respectively. Roughly half of all clients (49%) were successfully transitioned to continue treatment with buprenorphine in a primary care setting. Findings from this study demonstrate that buprenorphine treatment for opiate dependence can be incorporated into a community-based recovery center with high rates of opiate abstinence and treatment adherence. © 2014 American Society of Addiction Medicine.
Corrigan N.M.,University of Washington |
Shaw D.W.W.,University of Washington |
Estes A.M.,University of Washington |
Richards T.L.,University of Washington |
And 6 more authors.
JAMA Psychiatry | Year: 2013
IMPORTANCE: Autism spectrum disorder (ASD) is a neurodevelopmental disorder with symptoms emerging during early childhood. The pathophysiology underlying the disorder remains incompletely understood. OBJECTIVE: To examine cross-sectional and longitudinal patterns of brain chemical concentrations in children with ASD or idiopathic developmental delay (DD) from 3 different age points, beginning early in the clinical course. DESIGN: Proton magnetic resonance spectroscopic imaging data were acquired longitudinally for children with ASD or DD, and primarily cross-sectionally for children with typical development (TD), at 3 to 4, 6 to 7, and 9 to 10 years of age. SETTING: Recruitment, diagnostic assessments, and magnetic resonance imaging were performed at the University of Washington in Seattle. PARTICIPANTS: Seventy-three children (45 with ASD, 14 with DD, and 14 with TD) at 3 to 4 years of age; 69 children (35 with ASD, 14 with DD, and 20 with TD) at 6 to 7 years of age; and 77 children (29 with ASD, 15 with DD, and 33 with TD) at 9 to 10 years of age. MAIN OUTCOMES AND MEASURES: Concentrations of N-acetylaspartate (NAA), choline (Cho), creatine (Cr), myo-inositol (mI), and glutamine plus glutamate (Glx) in cerebral gray matter (GM) and white matter (WM) at 3 to 4, 6 to 7, and 9 to 10 years of age, and calculation of rates of change of these chemicals between 3 and 10 years of age. RESULTS: At 3 to 4 years of age, the ASD group exhibited lower NAA, Cho, and Cr concentrations than did the TD group in both GM and WM, alterations that largely were not observed at 9 to 10 years of age. The DD group exhibited reduced GM and WM NAA concentrations at 3 to 4 years of age; GM NAA concentrations remained reduced at 9 to 10 years of age compared with the TD group. There were distinct differences between the ASD and DD groups in the rates of GM NAA, Cho, and Cr changes between 3 and 10 years of age. CONCLUSIONS AND RELEVANCE: The GM chemical changes between 3 and 10 years of age differentiated the children with ASD from those with DD. Most notably, a dynamic reversal of GM NAA reductions was observed in the children with ASD. By contrast, persistent GM NAA reductions in the children with DD suggest a different, more static, underlying developmental process.
Daniels A.M.,Autism Speaks |
Mandell D.S.,University of Pennsylvania
Autism | Year: 2014
The diagnosis of autism is often delayed, which translates into a missed opportunity to provide treatment during a critical developmental period. This study reviews studies that assessed factors associated with age at autism spectrum disorder diagnosis and provides recommendations on future research, programs, and policies to improve early detection. A search for all peer-reviewed articles containing the words autism, age, and diagnosis in either the title or abstract was performed. A total of 42 studies published from January 1990 through March 2012 were identified. Mean age at diagnosis for all autism spectrum disorders ranged from 38 to 120 months and has decreased over time. Factors associated with earlier diagnosis included greater symptom severity, high socioeconomic status, and greater parental concern about initial symptoms. Family interactions with the health and education systems prior to diagnosis also influenced age at diagnosis. Geographic variation in age at autism spectrum disorder diagnosis was identified in a number of studies, suggesting that community resources and state policies play a role in early identification. Early detection efforts should include enhanced parental and provider education on the early recognition of developmental problems, interventions aimed at streamlining the process from first concern to eventual diagnosis, and strategies that target underserved populations. © The Author(s) 2013.
Yuen R.K.C.,Applied Genomics |
Thiruvahindrapuram B.,Applied Genomics |
Merico D.,Applied Genomics |
Walker S.,Applied Genomics |
And 31 more authors.
Nature Medicine | Year: 2015
Autism spectrum disorder (ASD) is genetically heterogeneous, with evidence for hundreds of susceptibility loci. Previous microarray and exome-sequencing studies have examined portions of the genome in simplex families (parents and one ASD-affected child) having presumed sporadic forms of the disorder. We used whole-genome sequencing (WGS) of 85 quartet families (parents and two ASD-affected siblings), consisting of 170 individuals with ASD, to generate a comprehensive data resource encompassing all classes of genetic variation (including noncoding variants) and accompanying phenotypes, in apparently familial forms of ASD. By examining de novo and rare inherited single-nucleotide and structural variations in genes previously reported to be associated with ASD or other neurodevelopmental disorders, we found that some (69.4%) of the affected siblings carried different ASD-relevant mutations. These siblings with discordant mutations tended to demonstrate more clinical variability than those who shared a risk variant. Our study emphasizes that substantial genetic heterogeneity exists in ASD, necessitating the use of WGS to delineate all genic and non-genic susceptibility variants in research and in clinical diagnostics. © 2015 Nature America, Inc. All rights reserved.
The "Autism & Beyond" iPhone app could one day screen for autism signs in children. More An app that can study people's facial expressions and emotional responses could one day be helpful in detecting autism signs in children, new research found. The iPhone app, called "Autism & Beyond," was developed by scientists and software developers at Duke University in North Carolina and uses mathematical algorithms to automatically detect people's expressions and emotional cues, based on muscle movements in the face. The app is currently available as a free download from Apple's App Store, for families who are interested in participating in a six-month medical research study, the researchers said. Children in the study will be presented with a short video clip designed to elicit emotional responses and social interactions. Using the iPhone's front-facing camera, the app will then measure the children's responses to the videos through video analysis and machine learning, the researchers said. [11 Facts Every Parent Should Know About Their Baby's Brain] "A core component of the app is emotion," said Dr. Guillermo Sapiro, a professor of electrical and computer engineering at Duke University, who developed the algorithm. The app works by "following facial landmarks that are automatically detected and from classifying emotions as well as head position," Sapiro told Live Science. The app can be downloaded for children up to 6 years old, with components of the app differing based on the child's age, Sapiro said. Autism spectrum disorders often appear in infancy and early childhood, characterized by signs such as failing to make eye contact, not responding to his or her name being called, or playing with toys in unusual and repetitive ways, according to Autism Speaks, an advocacy organization in the United States. Sapiro said that the app is not designed to be a self-diagnosis resource but could be used as a potential screening tool for autism. In the future, the app, which was developed with funding from the U.S. Office of Naval Research, could also be used to screen for other developmental health issues, including post-traumatic stress disorder (PTSD), traumatic brain injury and depression. But it may be too soon to know if this app will be effective in the real world, said Dan Smith, head of innovative technologies at Autism Speaks, who is not involved with the current research. For autism in particular, there is no specific medical "test" to diagnose the health issue, which is estimated to affect about 1 percent of the population worldwide and more than 3.5 million Americans, according to the Autism Society. "It's way too early to know whether [the app] picks up differences in people with autism or PTSD, and it's too early to say if those differences could predict or identify people with a condition better than [can] current methods," Smith told Live Science. "We just don't know yet if this type of information they're gathering is useful for improving diagnostics or assessing the risk." However, Smith said he thinks that, at some point, "there will be some reliable markers to track certain stimuli with certain facial expressions or response to emotional stimuli." Copyright 2016 LiveScience, a Purch company. All rights reserved. This material may not be published, broadcast, rewritten or redistributed.