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Classification and adaptive behavior prediction of children with autism spectrum disorder based upon multivariate data analysis of markers of oxidative stress and DNA methylation.

ABSTRACT: The number of diagnosed cases of Autism Spectrum Disorders (ASD) has increased dramatically over the last four decades; however, there is still considerable debate regarding the underlying pathophysiology of ASD. This lack of biological knowledge restricts diagnoses to be made based on behavioral observations and psychometric tools. However, physiological measurements should support these behavioral diagnoses in the future in order to enable earlier and more accurate diagnoses. Stepping towards this goal of incorporating biochemical data into ASD diagnosis, this paper analyzes measurements of metabolite concentrations of the folate-dependent one-carbon metabolism and transulfuration pathways taken from blood samples of 83 participants with ASD and 76 age-matched neurotypical peers. Fisher Discriminant Analysis enables multivariate classification of the participants as on the spectrum or neurotypical which results in 96.1% of all neurotypical participants being correctly identified as such while still correctly identifying 97.6% of the ASD cohort. Furthermore, kernel partial least squares is used to predict adaptive behavior, as measured by the Vineland Adaptive Behavior Composite score, where measurement of five metabolites of the pathways was sufficient to predict the Vineland score with an R2 of 0.45 after cross-validation. This level of accuracy for classification as well as severity prediction far exceeds any other approach in this field and is a strong indicator that the metabolites under consideration are strongly correlated with an ASD diagnosis but also that the statistical analysis used here offers tremendous potential for extracting important information from complex biochemical data sets.

SUBMITTER: Howsmon DP

PROVIDER: S-EPMC5354243 | biostudies-literature | 2017 Mar

REPOSITORIES: biostudies-literature

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Classification and adaptive behavior prediction of children with autism spectrum disorder based upon multivariate data analysis of markers of oxidative stress and DNA methylation.

Howsmon Daniel P DP Kruger Uwe U Melnyk Stepan S James S Jill SJ Hahn Juergen J

PLoS computational biology 20170316 3

The number of diagnosed cases of Autism Spectrum Disorders (ASD) has increased dramatically over the last four decades; however, there is still considerable debate regarding the underlying pathophysiology of ASD. This lack of biological knowledge restricts diagnoses to be made based on behavioral observations and psychometric tools. However, physiological measurements should support these behavioral diagnoses in the future in order to enable earlier and more accurate diagnoses. Stepping towards ...[more]

PMID: 28301476

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Project description:Several studies associate autism spectrum disorder (ASD) pathophysiology with metabolic abnormalities related to DNA methylation and intracellular redox homeostasis. In this regard, three completed clinical trials are reexamined in this work: treatment with (i) methylcobalamin (MeCbl) in combination with low-dose folinic acid (LDFA), (ii) tetrahydrobiopterin, and (iii) high-dose folinic acid (HDFA) for counteracting abnormalities in the folate-dependent one-carbon metabolism (FOCM) and transsulfuration (TS) pathways and also for improving ASD-related symptoms and behaviors. Although effects of treatment on individual metabolites and behavioral measures have previously been investigated, this study is the first to consider the effect of interventions on a set of metabolites of the FOCM/TS pathways and to correlate FOCM/TS metabolic changes with behavioral improvements across several studies. To do so, this work uses data from one case-control study and the three clinical trials to develop multivariate models for considering these aspects of treatment. Fisher discriminant analysis (FDA) is first used to establish a model for distinguishing individuals with ASD from typically developing (TD) controls, which is subsequently evaluated on the three treatment data sets, along with one data set for a placebo, to characterize the shift of FOCM/TS metabolism toward that of the TD population. Treatment with MeCbl plus LDFA and, separately, treatment with tetrahydrobiopterin significantly shifted the metabolites toward the values of the control group. Contrary to this, treatment with HDFA had a lesser, though still noticeable, effect whilst the placebo group showed marginal, but not insignificant, variations in metabolites. A second analysis is then performed with non-linear kernel partial least squares (KPLS) regression to predict changes in adaptive behavior, quantified by the Vineland Adaptive Behavior Composite, from changes in FOCM/TS biochemical measurements provided by treatment. Incorporating the 74 samples receiving any treatment, including placebo, into the regression analysis yields an R 2 of 0.471 after cross-validation when using changes in six metabolic measurements as predictors. These results are suggestive of an ability to effectively improve pathway-wide FOCM/TS metabolic and behavioral abnormalities in ASD with clinical treatment.

Project description:An emerging paradigm suggests children with autism display a unique pattern of environmental, genetic, and epigenetic triggers that make them susceptible to developing dysfunctional heavy metal and chemical detoxification systems. These abnormalities could be caused by alterations in the methylation, sulfation, and metalloprotein pathways. This study sought to evaluate the physiological and behavioral effects of children with autism sleeping in an International Organization for Standardization Class 5 cleanroom.Ten children with autism, ages 3-12, slept in a cleanroom for two weeks to evaluate changes in toxin levels, oxidative stress, immune dysregulation, and behavior. Before and after the children slept in the cleanroom, samples of blood and hair and rating scale scores were obtained to assess these changes.Five children significantly lowered their concentration of oxidized glutathione, a biomarker of oxidative stress. The younger cohort, age 5 and under, showed significantly greater mean decreases in two markers of immune dysregulation, CD3% and CD4%, than the older cohort. Changes in serum magnesium, influencing neuronal regulation, correlated negatively while changes in serum iron, affecting oxygenation of tissues, correlated positively with age. Changes in serum benzene and PCB 28 concentrations showed significant negative correlations with age. The younger children demonstrated significant improvements on behavioral rating scales compared to the older children. In a younger pair of identical twins, one twin showed significantly greater improvements in 4 out of 5 markers of oxidative stress, which corresponded with better overall behavioral rating scale scores than the other twin.Younger children who slept in the cleanroom altered elemental levels, decreased immune dysregulation, and improved behavioral rating scales, suggesting that their detoxification metabolism was briefly enhanced. The older children displayed a worsening in behavioral rating scale performance, which may have been caused by the mobilization of toxins from their tissues. The interpretation of this exploratory study is limited by lack of a control group and small sample size. The changes in physiology and behavior noted suggest that performance of larger, prospective controlled studies of exposure to nighttime or 24 hour cleanroom conditions for longer time periods may be useful for understanding detoxification in children with autism.Clinical Trial Registration Number NCT02195401 (Obtained July 18, 2014).

Project description:Background: Autism spectrum disorder (ASD) is a developmental disorder characterized by deficits in social interaction, restricted interest and repetitive behavior. Oxidative stress in response to environmental exposure plays a role in virtually every human disease and represents a significant avenue of research into the etiology of ASD. The aim of this study was to explore the diagnostic utility of four urinary biomarkers of oxidative stress. Methods: One hundred and thirty-nine (139) children and adolescents with ASD (89% male, average age = 10.0 years, age range = 2.1 to 18.1 years) and 47 healthy children and adolescents (49% male, average age 9.2, age range = 2.5 to 20.8 years) were recruited for this study. Their urinary 8-OH-dG, 8-isoprostane, dityrosine and hexanoil-lisine were determined by using the ELISA method. Urinary creatinine was determined with the kinetic Jaffee reaction and was used to normalize all biochemical measurements. Non-parametric tests and support vector machines (SVM) with three different kernel functions (linear, radial, polynomial) were used to explore and optimize the multivariate prediction of an ASD diagnosis based on the collected biochemical measurements. The SVM models were first trained using data from a random subset of children and adolescents from the ASD group (n = 70, 90% male, average age = 9.7 years, age range = 2.1 to 17.8 years) and the control group (n = 24, 45.8% male, average age = 9.4 years, age range = 2.5 to 20.8 years) using bootstrapping, with additional synthetic minority over-sampling (SMOTE), which was utilized because of unbalanced data. The computed SVM models were then validated using the remaining data from children and adolescents from the ASD (n = 69, 88% male, average age = 10.2 years, age range = 4.3 to 18.1 years) and the control group (n = 23, 52.2% male, average age = 8.9 years, age range = 2.6 to 16.7 years). Results: Using a non-parametric test, we found a trend showing that the urinary 8-OH-dG concentration was lower in children with ASD compared to the control group (unadjusted p = 0.085). When all four biochemical measurements were combined using SVMs with a radial kernel function, we could predict an ASD diagnosis with a balanced accuracy of 73.4%, thereby accounting for an estimated 20.8% of variance (p < 0.001). The predictive accuracy expressed as the area under the curve (AUC) was solid (95% CI = 0.691-0.908). Using the validation data, we achieved significantly lower rates of classification accuracy as expressed by the balanced accuracy (60.1%), the AUC (95% CI = 0.502-0.781) and the percentage of explained variance (R2 = 3.8%). Although the radial SVMs showed less predictive power using the validation data, they do, together with ratings of standardized SVM variable importance, provide some indication that urinary levels of 8-OH-dG and 8-isoprostane are predictive of an ASD diagnosis. Conclusions: Our results indicate that the examined urinary biomarkers in combination may differentiate children with ASD from healthy peers to a significant extent. However, the etiological importance of these findings is difficult to assesses, due to the high-dimensional nature of SVMs and a radial kernel function. Nonetheless, our results show that machine learning methods may provide significant insight into ASD and other disorders that could be related to oxidative stress.

Project description:Objective: Children with autism spectrum disorder (ASD) experience significant challenges with their motor coordination. It is not, however, well understood how motor coordination may impact the behavioral functioning of children with ASD. Therefore the purpose of this study was to explore the relationships between motor coordination and adaptive behavior in 7-12-year-old children with ASD. Methods: Motor coordination was assessed using the Movement Assessment Battery for Children, 2nd Edition (MABC-2) and adaptive behavior was assessed by parental report using the Vineland Adaptive Behavior Scales, 2nd Edition (VABS-2) as part of a larger cross-sectional study. Descriptive characteristics were calculated for MABC-2 and VABS-2 scores and Spearman's rank order correlation analyses were used to examine the relationship between motor coordination and adaptive behavior. Results: On average, the participants (n = 26) exhibited significant challenges in regard to their motor coordination with all but two participants classified as having significant motor impairments by scoring at or below the 16th percentile on the MABC-2. Results from the correlation analyses indicated that manual dexterity was positively related to daily living skills (? = 0.58, p < 0.003), and overall motor coordination was positively related to daily living skills (? = 0.60, p < 0.003) and overall adaptive behavior (? = 0.57, p < 0.003). In all instances, better motor coordination was related to more adaptive behaviors. Conclusion: These results highlight the profound motor coordination challenges that children with ASD experience and also suggest that these challenges, particularly with manual dexterity, are related to the daily behavior of children with ASD. The interrelatedness of motor and adaptive behavior suggests the need to further explore the impact of motor-based interventions for this population, as well as conduct longitudinal studies to disentangle these relationships.

Project description:BackgroundHeterogeneity in adaptive behavior abilities among people with autism spectrum disorder (ASD) is expressed not only as uneven levels of impairment across domains, but also in the developmental trajectories of adaptive skills. We studied the question of whether, after accounting for global adaptive behavior development, we find evidence of heterogeneity in the trajectories of specific domains of adaptive behavior.MethodsA sample of 504 children with ASD was obtained by combining data from two independent natural history studies conducted in North America. We used a factor of curves model to explain growth between 36 and 138 months in Vineland Adaptive Behavior Scales, Second Edition (VABS) age equivalents as a function of domain-specific and global growth processes.ResultsThe domain-specific trajectories in all three domains (Communication, Daily Living Skills, and Socialization) reflected impairment relative to age expectations as well as slower-than-expected growth with age, and the parameters of these trajectories were moderately-to-strongly correlated across domains. The global adaptive behavior trajectory had an initial (36-41 months of age) developmental level of about 22 age-equivalent months, and eventually slowed after initially increasing by about 6 months each year. The global trajectory accounted for the majority of variance in the domain-level processes; however, additional variance remained (14%-38%) in the domain-level intercepts, slopes, and quadratic processes.ConclusionsThese results extend existing theoretical and empirical support for the hierarchical structure of adaptive behavior to include its development over time in clinical samples of children with ASD. A latent global trajectory may be sufficient to describe the growth of adaptive behavior in children with ASD; however, the remaining domain-specific variability after accounting for global adaptive behavior development allows for the possibility that differential effects of intervention on specific domains may be possible and detectable.

Project description:BACKGROUND:Although temperament has been recognized as an important contributor to childhood psychopathology, its role in emergent autism spectrum phenotypes is not well understood. This study examined whether toddlers with autism spectrum disorder (ASD) display temperamental vulnerabilities compared to toddlers with other developmental challenges, whether these characteristics are distinct from core autism symptoms, if they are stable over time, and if they contribute to social outcomes in preschool. METHODS:Parents of 165 toddlers with ASD, 58 nonverbal ability- and chronological age- (CA) matched developmentally delayed (DD) toddlers, and 92 CA-matched typically developing (TD) toddlers completed the Toddler Behavior Assessment Questionnaire-Supplemental (TBAQ-S) at 26 months (SD = 6; Time 1). TBAQ-S data were also available for a subset of toddlers with ASD (n = 126) at 43 months (SD = 9; Time 2). RESULTS:Compared to the DD and TD groups, toddlers with ASD exhibited vulnerabilities within the Effortful Control domain as well as the Surgency domain. They also displayed greater Negative Emotionality compared to TD peers. In the ASD group, temperamental characteristics were not concurrently related to autism severity or developmental level and individual differences were highly stable over time. Changes in Perceptual Sensitivity, Inhibitory Control, and Low-Intensity Pleasure from age 2 to 3.5 uniquely predicted autism symptom severity and adaptive social skill level at Time 2. CONCLUSIONS:Temperamental vulnerabilities in toddlers with ASD are stable over time and involve attentional and behavioral control as well as affective reactivity. They contribute uniquely to social outcomes in preschool and are likely to signal risk for developing later maladaptive attentional, affective, and behavioral symptoms. Considering biologically based dimensions may shed light on noncore facets of the early ASD phenotype that are potentially relevant to the emergence of comorbid conditions later in childhood.

Dataset Information

Classification and adaptive behavior prediction of children with autism spectrum disorder based upon multivariate data analysis of markers of oxidative stress and DNA methylation.

Publications

Classification and adaptive behavior prediction of children with autism spectrum disorder based upon multivariate data analysis of markers of oxidative stress and DNA methylation.

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