Jayne Bellando

Metabolic imbalance associated with methylation dysregulation and oxidative damage in children with autism.

Oxidative stress and abnormal DNA methylation have been implicated in the pathophysiology of autism. We investigated the dynamics of an integrated metabolic pathway essential for cellular antioxidant and methylation capacity in 68 children with autism, 54 age-matched control children and 40 unaffected siblings. The metabolic profile of unaffected siblings differed significantly from case siblings but not from controls. Oxidative protein/DNA damage and DNA hypomethylation (epigenetic alteration) were found in autistic children but not paired siblings or controls. These data indicate that the deficit in antioxidant and methylation capacity is specific for autism and may promote cellular damage and altered epigenetic gene expression. Further, these results suggest a plausible mechanism by which pro-oxidant environmental stressors may modulate genetic predisposition to autism.

PREFERENCE-BASED HEALTH-RELATED QUALITY OF LIFE OUTCOMES IN CHILDREN WITH AUTISM SPECTRUM DISORDERS: A COMPARISON OF GENERIC INSTRUMENTS

BackgroundCost-effectiveness analysis of pharmaceutical and other treatments for children with autism spectrum disorders (ASDs) has the potential to improve access to services by demonstrating the value of treatment to public and private payers, but methods for measuring QALYs in children are under-studied. No cost-effectiveness analyses have been undertaken in this population using the cost-per-QALY metric.ObjectiveThis study describes health-related quality-of-life (HR-QOL) outcomes in children with ASDs and compares the sensitivity of two generic preference-based instruments relative to ASD-related conditions and symptoms.MethodsThe study design was cross-sectional with prospectively collected outcome data that were correlated with retrospectively assessed clinical information. Subjects were recruited from two sites of the Autism Treatment Network (ATN) in the US: a developmental centre in Little Rock, Arkansas, and an outpatient psychiatric clinic at Columbia University Medical Center in New York. Children that met Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition (DSM-IV) criteria for an ASD by a multidisciplinary team evaluation were asked to participate in a clinical registry. Families of children with an ASD that agreed to be contacted about participation in future research studies as part of the ATN formed the sampling frame for the study. Families were included if the child with the ASD was between 4 and 17 years of age and the family caregiver spoke English. Eligible families were contacted by mail to see if they would be interested in participating in the study with 150 completing surveys. HR-QOL outcomes were described using the Health Utilities Index (HUI) 3 and the Quality of Well-Being Self-Administered (QWB-SA) scale obtained by proxy via the family caregiver.ResultsChildren were diagnosed as having autistic disorder (76%), pervasive developmental disorder-not otherwise specified [PDD-NOS] (15%), and Asperger’s disorder (9%). Average HUI3 and QWB-SA scores were 0.68 (SD 0.21, range 0.07–1) and 0.59 (SD 0.16, range 0.18–1), respectively. The HUI3 score was significantly correlated with clinical variables including adaptive behaviour (ρ=0.52;p<0.001) and cognitive functioning (ρ=0.36;p<0.001). The QWB-SA score had weak correlation with adaptive behaviour (ρ=0.25;p<0.001) and cognitive functioning (ρ=0.17;p<0.005). Change scores for the HUI3 were larger than the QWB-SA for all clinical measures. Scores for the HUI3 increased 0.21 points (95% CI 0.14, 0.29) across the first to the third quartile of the cognitive functioning measure compared with 0.05 (95% CI −0.01, 0.11) for the QWB-SA. Adjusted R2 values also were higher for the HUI3 compared with the QWB-SA across all clinical measures.ConclusionsThe HUI3 was more sensitive to clinical measures used to characterize children with autism compared with the QWB-SA score. The findings provide a benchmark to compare scores obtained by alternative methods and instruments. Researchers should consider incorporating the HUI3 in clinical trials and other longitudinal research studies to build the evidence base for describing the cost effectiveness of services provided to this important population.

Predicting Health Utilities for Children with Autism Spectrum Disorders

Comparative effectiveness of interventions for children with autism spectrum disorders (ASDs) that incorporates costs is lacking due to the scarcity of information on health utility scores or preference‐weighted outcomes typically used for calculating quality‐adjusted life years (QALYs). This study created algorithms for mapping clinical and behavioral measures for children with ASDs to health utility scores. The algorithms could be useful for estimating the value of different interventions and treatments used in the care of children with ASDs. Participants were recruited from two Autism Treatment Network sites. Health utility data based on the Health Utilities Index Mark 3 (HUI3) for the child were obtained from the primary caregiver (proxy‐reported) through a survey (N = 224). During the initial clinic visit, proxy‐reported measures of the Child Behavior Checklist, Vineland II Adaptive Behavior Scales, and the Pediatric Quality of Life Inventory 4.0 (start measures) were obtained and then merged with the survey data. Nine mapping algorithms were developed using the HUI3 scores as dependent variables in ordinary least squares regressions along with the start measures, the Autism Diagnostic Observation Schedule, to measure severity, child age, and cognitive ability as independent predictors. In‐sample cross‐validation was conducted to evaluate predictive accuracy. Multiple imputation techniques were used for missing data. The average age for children with ASDs in this study was 8.4 (standard deviation = 3.5) years. Almost half of the children (47%) had cognitive impairment (IQ ≤ 70). Total scores for all of the outcome measures were significantly associated with the HUI3 score. The algorithms can be applied to clinical studies containing start measures of children with ASDs to predict QALYs gained from interventions. Autism Res 2014, 7: 649–663.

Parent Training Interventions

Parent training involves teaching parents and primary caregivers how to address and intervene with their children’s problem behaviors. These types of interventions have gained increasing popularity over the past several decades. Additionally, they have a strong evidence base supporting positive outcomes for both parents’ and children’s behavior, from different theoretical orientations, and across a number of populations and problems. Several behavioral parent training programs have been developed that teach a number of different skills including attending, rewarding, giving effective instructions, ignoring, and time-out. This chapter discusses and reviews many of these parent training programs and their supporting evidence. Current and anticipated trends such as the increasing use of technology in parent training and the dissemination of parent training programs to different countries and cultures are also discussed. Overall, while the field of parent training and its future looks bright, more work is needed to better understand what specific variables contribute to the effectiveness of parent training programs and what works best for whom.

Helping the student with Asperger's Disorder with social and behavioral issues in the school: nursing, psychology, and educators working in unison.

School Health provides a forum to discuss policy, practice, research, issues and trends, and pearls of wisdom to enhance the day-to-day care of children in the school setting, from day care to high school.

Developmental functioning and medical Co-morbidity profile of children with complex and essential autism

Children with Autism Spectrum Disorders (ASD) may be characterized as “complex” (those with microcephaly and/or dysmorphology) or “essential” (those with neither of these two). Previous studies found subjects in the complex group exhibited lower IQ scores, poorer response to behavioral intervention, more seizures and more abnormal EEGs and brain MRIs compared to the essential group. The objective of this study was to determine if there are differences in complex versus essential subjects based on several developmental/psychological measures as well as certain medical comorbidities. This study utilized data from 1,347 individuals (2–17 years old) well‐characterized subjects enrolled in Autism Treatment Network (ATN) Registry. Head circumference measurement and the Autism Dysmorphology Measure (ADM) were used by trained physicians to classify subjects as complex or essential. Significantly lower scores were seen for complex subjects in cognitive level, adaptive behavior and quality of life. Complex subjects showed significantly increased physician‐documented GI symptoms and were on a higher number of medications. No significant differences in autism severity scores, behavioral ratings and parent‐reported sleep problems were found. After adjusting for multiple comparisons made, adaptive scores remained significantly lower for the complex group, and the complex group used a significantly higher number of medications and had increased GI symptoms. Complex and essential autism subtypes may have distinct developmental and medical correlates and thus underlines the importance of looking for microcephaly and dysmorphology, when evaluating a child with autism. Determining this distinction in autism may have implications in prognosis, identifying medical co‐morbidities, directing diagnostic evaluations and treatment interventions. Autism Res 2017, 10: 1344–1352.

Autism Speaks Toolkits Resources for Busy Physicians

Given the increased prevalence of autism spectrum disorders (ASD), it is likely that busy primary care providers (PCP) are providing care to individuals with ASD in their practice. Autism Speaks provides a wealth of educational, medical, and treatment/intervention information resources for PCPs and families, including at least 32 toolkits. This article serves to familiarize PCPs and families on the different toolkits that are available on the Autism Speaks website. This article is intended to increase physicians’ knowledge on the issues that families with children with ASD frequently encounter, to increase their ability to share evidence-based information to guide treatment and care for affected families in their practice.