Teasing apart the heterogeneity of autism: Same behavior, different brains in toddlers with Fragile X Syndrome and autism

Department of Psychiatry, The University of North Carolina at Chapel Hill, CB#3367, Chapel Hill, NC 27599-3367, USA.
Journal of Neurodevelopmental Disorders (Impact Factor: 3.27). 03/2009; 1(1):81-90. DOI: 10.1007/s11689-009-9009-8
Source: PubMed


To examine brain volumes in substructures associated with the behavioral features of children with FXS compared to children with idiopathic autism and controls. A cross-sectional study of brain substructures was conducted at the first time-point as part of an ongoing longitudinal MRI study of brain development in FXS. The study included 52 boys between 18-42 months of age with FXS and 118 comparison children (boys with autism-non FXS, developmental-delay, and typical development). Children with FXS and autistic disorder had substantially enlarged caudate volume and smaller amygdala volume; whereas those children with autistic disorder without FXS (i.e., idiopathic autism) had only modest enlargement in their caudate nucleus volumes but more robust enlargement of their amygdala volumes. Although we observed this double dissociation among selected brain volumes, no significant differences in severity of autistic behavior between these groups were observed. This study offers a unique examination of early brain development in two disorders, FXS and idiopathic autism, with overlapping behavioral features, but two distinct patterns of brain morphology. We observed that despite almost a third of our FXS sample meeting criteria for autism, the profile of brain volume differences for children with FXS and autism differed from those with idiopathic autism. These findings underscore the importance of addressing heterogeneity in studies of autistic behavior.

Download full-text


Available from: Guido Gerig, Jun 09, 2014
  • Source
    • "As in FXS and other monogenic disorders, social anxiety and social avoidance, rather than pure social deficits, may be better descriptors of the CdLS behavioral phenotype [Budimirovic et al., 2006; Hall et al., 2010]. In parallel to FXS, where imaging studies now show a clear divergence of brain structure from idiopathic autism [Hazlett et al., 2009; Hoeft et al., 2011], imaging studies of CdLS are needed to delineate the biological substrate of social behavior. Admittedly, the biological relationship between social deficits and social anxiety is complex. "
    [Show abstract] [Hide abstract]
    ABSTRACT: Cornelia de Lange syndrome (CdLS) is a cohesinopathy causing delayed growth and limb deficits. Individuals with CdLS have mild to profound intellectual disability and autistic features. This study characterizes the behavioral phenotype of children with CdLS, focusing on autistic features, maladaptive behaviors, and impact of age. Children with CdLS (5–18 years) were administered normed instruments to characterize autism features (Childhood Autism Rating Scale, CARS), maladaptive behaviors (Aberrant Behavior Checklist), and adaptive skills (Vineland Adaptive Behaviors Scales). CdLS features and severity were rated with Diagnostic Criteria for CdLS. Forty-one children with CdLS (23 females, 18 males) were classified as having “no autism” (n = 7; 17.1%), “mild autism” (n = 17; 41.4%), and “severe autism” (n = 17; 41.4%), using CARS scores. Characteristic items were abnormal emotional response, stereotypies, odd object use, rigidity, lack of verbal communication, and low intellectual functioning. Verbal communication deficits and repetitive behaviors were higher compared to sensory, social cognition, and behavior abnormalities (P ≤ 0.0001). Maladaptive behaviors associated with autism traits were stereotypies (P = 0.003), hyperactivity (P = 0.01), and lethargy (P = 0.03). Activities of daily living were significantly affected; socialization adaptive skills were a relative strength. However, with advancing age, both socialization (P < 0.0001) and communication (P = 0.001) domains declined significantly. CdLS is characterized by autistic features, notably excessive repetitive behaviors and expressive language deficits. While other adaptive skills are impacted, socialization adaptive skills are less affected. Advancing age can worsen communication and socialization deficits relative to neurotypical peers. © 2014 Wiley Periodicals, Inc.
    Full-text · Article · Jun 2014 · American Journal of Medical Genetics Part A
  • Source
    • "FXS is a monogenic disorder with a characteristic behavioral phenotype that often includes features of autism. Children with FXS experience, for example, social anxiety and avoidance, repetitive behaviors such as hand-flapping, and impaired speech and communication [17,18]. Up to one-third of children with FXS meet diagnostic criteria for autism, and FXS is the most common known cause of autism, accounting for 2% to 3% of cases. "
    [Show abstract] [Hide abstract]
    ABSTRACT: Autism and the fragile X syndrome (FXS) are related to each other genetically and symptomatically. A cardinal biological feature of both disorders is abnormalities of cerebral cortical brain volumes. We have previously shown that the monoamine oxidase A (MAOA) promoter polymorphism is associated with cerebral cortical volumes in children with autism, and we now sought to determine whether the association was also present in children with FXS. Participants included 47 2-year-old Caucasian boys with FXS, some of whom also had autism, as well as 34 2-year-old boys with idiopathic autism analyzed in a previous study. The MAOA promoter polymorphism was genotyped and tested for relationships with gray and white matter volumes of the cerebral cortical lobes and cerebro-spinal fluid volume of the lateral ventricles. MAOA genotype effects in FXS children were the same as those previously observed in idiopathic autism: the low activity MAOA promoter polymorphism allele was associated with increased gray and white matter volumes in all cerebral lobes. The effect was most pronounced in frontal lobe gray matter and all three white matter regions: frontal gray, F = 4.39, P = 0.04; frontal white, F = 5.71, P = 0.02; temporal white, F = 4.73, P = 0.04; parieto-occipital white, F = 5.00, P = 0.03. Analysis of combined FXS and idiopathic autism samples produced P values for these regions <0.01 and effect sizes of approximately 0.10. The MAOA promoter polymorphism is similarly associated with brain structure volumes in both idiopathic autism and FXS. These data illuminate a number of important aspects of autism and FXS heritability: a genetic effect on a core biological trait of illness, the specificity/generalizability of the genetic effect, and the utility of examining individual genetic effects on the background of a single gene disorder such as FXS.
    Full-text · Article · Mar 2014 · Journal of Neurodevelopmental Disorders
  • Source
    • "This software pipeline employs BatchMake pipeline scripts that call tools within the AutoSeg toolset based on the Insight Tool Kit (ITK). AutoSeg has been used and is in use in a number of studies, including Parkinson's disease (Lewis et al., 2009; Du et al., 2011, 2012; Sterling et al., 2013), autism (Hazlett et al., 2009, 2011, 2012), schizophrenia (McClure et al., 2013), craniosynostosis (Paniagua et al., 2013), and drug abuse (Gerig et al., 2011). AutoSeg entails intensity inhomogeneity correction , brain tissue classification based skull-stripping, rigid and non-rigid image registration, and multi-atlas-based segmentation with atlas selection. "
    [Show abstract] [Hide abstract]
    ABSTRACT: Automated segmenting and labeling of individual brain anatomical regions, in MRI are challenging, due to the issue of individual structural variability. Although atlas-based segmentation has shown its potential for both tissue and structure segmentation, due to the inherent natural variability as well as disease-related changes in MR appearance, a single atlas image is often inappropriate to represent the full population of datasets processed in a given neuroimaging study. As an alternative for the case of single atlas segmentation, the use of multiple atlases alongside label fusion techniques has been introduced using a set of individual "atlases" that encompasses the expected variability in the studied population. In our study, we proposed a multi-atlas segmentation scheme with a novel graph-based atlas selection technique. We first paired and co-registered all atlases and the subject MR scans. A directed graph with edge weights based on intensity and shape similarity between all MR scans is then computed. The set of neighboring templates is selected via clustering of the graph. Finally, weighted majority voting is employed to create the final segmentation over the selected atlases. This multi-atlas segmentation scheme is used to extend a single-atlas-based segmentation toolkit entitled AutoSeg, which is an open-source, extensible C++ based software pipeline employing BatchMake for its pipeline scripting, developed at the Neuro Image Research and Analysis Laboratories of the University of North Carolina at Chapel Hill. AutoSeg performs N4 intensity inhomogeneity correction, rigid registration to a common template space, automated brain tissue classification based skull-stripping, and the multi-atlas segmentation. The multi-atlas-based AutoSeg has been evaluated on subcortical structure segmentation with a testing dataset of 20 adult brain MRI scans and 15 atlas MRI scans. The AutoSeg achieved mean Dice coefficients of 81.73% for the subcortical structures.
    Full-text · Article · Feb 2014 · Frontiers in Neuroinformatics
Show more