Identification and Analysis of Behavioral Phenotypes in Autism Spectrum Disorder via Unsupervised Machine Learning

Background and objective: Autism spectrum disorder (ASD) is a heterogeneous disorder. Research has explored potential ASD subgroups with preliminary evidence supporting the existence of behaviorally and genetically distinct subgroups; however, research has yet to leverage machine learning to identify phenotypes on a scale large enough to robustly examine treatment response across such subgroups. The purpose of the present study was to apply Gaussian Mixture Models and Hierarchical Clustering to identify behavioral phenotypes of ASD and examine treatment response across the learned phenotypes. Materials and methods: The present study included a sample of children with ASD (N = 2400), the largest of its kind to date. Unsupervised machine learning was applied to model ASD subgroups as well as their taxonomic relationships. Retrospective treatment data were available for a portion of the sample (n =1034). Treatment response was examined within each subgroup via regression. Results: The application of a Gaussian Mixture Model revealed 16 subgroups. Further examination of the subgroups through Hierarchical Agglomerative Clustering suggested 2 overlying behavioral phenotypes with unique deficit profiles each composed of subgroups that differed in severity of those deficits. Furthermore, differentiated response to treatment was found across subtypes, with a substantially higher amount of variance accounted for due to the homogenization effect of the clustering. Discussion: The high amount of variance explained by the regression models indicates that clustering provides a basis for homogenization, and thus an opportunity to tailor treatment based on cluster memberships. These findings have significant implications on prognosis and targeted treatment of ASD, and pave the way for personalized intervention based on unsupervised machine learning

A Program Evaluation of Home and Center-Based Treatment for Autism Spectrum Disorder

The present study aimed to retrospectively compare the relative rates of mastery of exemplars for individuals with ASD (N = 313) who received home-based and center-based services. A between-group analysis found that participants mastered significantly more exemplars per hour when receiving center-based services than home-based services. Likewise, a paired-sample analysis found that participants who received both home and center-based services had mastered 100 % more per hour while at the center than at home. These analyses indicated that participants demonstrated higher rates of learning during treatment that was provided in a center setting than in the participant’s home

A Cluster Analysis of Challenging Behaviors in Autism Spectrum Disorder

We apply cluster analysis to a sample of 2,116 children with Autism Spectrum Disorder in order to identify patterns of challenging behaviors observed in home and centerbased clinical settings. The largest study of this type to date, and the first to employ machine learning, our results indicate that while the presence of multiple challenging behaviors is common, in most cases a dominant behavior emerges. Furthermore, the trend is also observed when we train our cluster models on the male and female samples separately. This work provides a basis for future studies to understand the relationship of challenging behavior profiles to learning outcomes, with the ultimate goal of providing personalized therapeutic interventions with maximum efficacy and minimum time and cost

A Study of Nuclear Transcription Factor-Kappa B in Childhood Autism

BACKGROUND: Several children with autism show regression in language and social development while maintaining normal motor milestones. A clear period of normal development followed by regression and subsequent improvement with treatment, suggests a multifactorial etiology. The role of inflammation in autism is now a major area of study. Viral and bacterial infections, hypoxia, or medication could affect both foetus and infant. These stressors could upregulate transcription factors like nuclear factor kappa B (NF-κB), a master switch for many genes including some implicated in autism like tumor necrosis factor (TNF). On this hypothesis, it was proposed to determine NF-κB in children with autism. METHODS: Peripheral blood samples of 67 children with autism and 29 control children were evaluated for NF-κB using electrophoretic mobility shift assay (EMSA). A phosphor imaging technique was used to quantify values. The fold increase over the control sample was calculated and statistical analysis was carried out using SPSS 15. RESULTS: We have noted significant increase in NF-κB DNA binding activity in peripheral blood samples of children with autism. When the fold increase of NF-κB in cases (n = 67) was compared with that of controls (n = 29), there was a significant difference (3.14 vs. 1.40, respectively; p<0.02). CONCLUSION: This finding has immense value in understanding many of the known biochemical changes reported in autism. As NF-κB is a response to stressors of several kinds and a master switch for many genes, autism may then arise at least in part from an NF-κB pathway gone awry

Imitation promotes affiliation in infant macaques at risk for impaired social behaviors

Parental responsiveness and synchronization during early face-to-face interactions between mother and infant have been theorized to affect a broad spectrum of positive developmental outcomes in social and cognitive infant growth and to facilitate the development of a sense of self in the baby. Here we show that being imitated can significantly affect the behavior of nursery-reared infant monkeys, which are at an increased risk for developing aberrant social behaviors. Infants look longer and lipsmack more at an experimenter both during imitation and after being imitated. These results demonstrate that from early in life imitation might be used as a privileged form of communication by adults to enhance infants’ visual engagement and their social communication. Imitation may therefore be useful to counteract the negative effects of early social adversities