1. Jiao Y, Chen R, Ke X, Chu K, Lu Z, Herskovits EH. {{Predictive models of autism spectrum disorder based on brain regional cortical thickness}}. {Neuroimage}. 2009 Dec 21.
Autism spectrum disorder (ASD) is a neurodevelopmental disorder with a wide phenotypic range, often affecting personality and communication. Previous voxel-based morphometry (VBM) studies of ASD have identified both gray- and white-matter volume changes. However, the cerebral cortex is a 2-D sheet with a highly folded and curved geometry, which VBM cannot directly measure. Surface-based morphometry (SBM) has the advantage of being able to measure cortical surface features, such as thickness. The goals of this study were twofold: to construct diagnostic models for ASD, based on regional thickness measurements extracted from SBM, and to compare these models to diagnostic models based on volumetric morphometry. Our study included 22 subjects with ASD (mean age 9.2+/-2.1 years) and 16 volunteer controls (mean age 10.0+/-1.9 years). Using SBM, we obtained regional cortical thicknesses for 66 brain structures for each subject. In addition, we obtained volumes for the same 66 structures for these subjects. To generate diagnostic models, we employed four machine-learning techniques: support vector machines (SVMs), multilayer perceptrons (MLPs), functional trees (FTs), and logistic model trees (LMTs). We found that thickness-based diagnostic models were superior to those based on regional volumes. For thickness-based classification, LMT achieved the best classification performance, with accuracy=87%, area under the receiver operating characteristic (ROC) curve (AUC)=0.93, sensitivity=95%, and specificity=75%. For volume-based classification, LMT achieved the highest accuracy, with accuracy=74%, AUC=0.77, sensitivity=77%, and specificity=69%. The thickness-based diagnostic model generated by LMT included 7 structures. Relative to controls, children with ASD had decreased cortical thickness in the left and right pars triangularis, left medial orbitofrontal gyrus, left parahippocampal gyrus, and left frontal pole, and increased cortical thickness in the left caudal anterior cingulate and left precuneus. Overall, thickness-based classification outperformed volume-based classification across a variety of classification methods.
2. Knaus TA, Silver AM, Kennedy M, Lindgren KA, Dominick KC, Siegel J, Tager-Flusberg H. {{Language laterality in autism spectrum disorder and typical controls: A functional, volumetric, and diffusion tensor MRI study}}. {Brain Lang}. 2009 Dec 21.
Language and communication deficits are among the core features of autism spectrum disorder (ASD). Reduced or reversed asymmetry of language has been found in a number of disorders, including ASD. Studies of healthy adults have found an association between language laterality and anatomical measures but this has not been systematically investigated in ASD. The goal of this study was to examine differences in gray matter volume of perisylvian language regions, connections between language regions, and language abilities in individuals with typical left lateralized language compared to those with atypical (bilateral or right) asymmetry of language functions. Fourteen adolescent boys with ASD and 20 typically developing adolescent boys participated, including equal numbers of left- and right-handed individuals in each group. Participants with typical left lateralized language activation had smaller frontal language region volume and higher fractional anisotropy of the arcuate fasciculus compared to the group with atypical language laterality, across both ASD and control participants. The group with typical language asymmetry included the most right-handed controls and fewest left-handers with ASD. Atypical language laterality was more prevalent in the ASD than control group. These findings support an association between laterality of language function and language region anatomy. They also suggest anatomical differences may be more associated with variation in language laterality than specifically with ASD. Language laterality therefore may provide a novel way of subdividing samples, resulting in more homogenous groups for research into genetic and neurocognitive foundations of developmental disorders.
3. Loth E, Gomez JC, Happe F. {{When seeing depends on knowing: Adults with Autism Spectrum Conditions show diminished top-down processes in the visual perception of degraded faces but not degraded objects}}. {Neuropsychologia}. 2009 Dec 21.
Behavioural, neuroimaging and neurophysiological approaches emphasise the active and constructive nature of visual perception, determined not solely by the environmental input, but modulated top-down by prior knowledge. For example, degraded images, which at first appear as meaningless ‘blobs’, can easily be recognized as, say, a face, after having seen the same image un-degraded. This conscious perception of the fragmented stimuli relies on top-down priming influences from systems involved in attention and mental imagery on the processing of stimulus attributes, and feature-binding [Dolan, R. J., Fink, G. R., Rolls, E., Booth, M., Holmes, A., Frackowiak, R. S. J., et al. (1997). How the brain learns to see objects and faces in an impoverished context. Nature, 389, 596-599]. In Autism Spectrum Conditions (ASC), face processing abnormalities are well-established, but top-down anomalies in various domains have also been shown. Thus, we tested two alternative hypotheses: (i) that people with ASC show overall reduced top-down modulation in visual perception, or (ii) that top-down anomalies affect specifically the perception of faces. Participants were presented with sets of three consecutive images: degraded images (of faces or objects), corresponding or non-corresponding grey-scale photographs, and the same degraded images again. In a passive viewing sequence we compared gaze times (an index of focal attention) on faces/objects vs. background before and after viewers had seen the undegraded photographs. In an active viewing sequence, we compared how many faces/objects were identified pre- and post-exposure. Behavioural and gaze tracking data showed significantly reduced effects of prior knowledge on the conscious perception of degraded faces, but not objects in the ASC group. Implications for future work on the underlying mechanisms, at the cognitive and neurofunctional levels, are discussed.
4. Monnerat LS, Moreira AD, Alves MC, Bonvicino CR, Vargas FR. {{Identification and characterization of novel sequence variations in MECP2 gene in Rett syndrome patients}}. {Brain Dev}. 2009 Dec 21.
Rett syndrome (RS) is a neurodevelopmental disorder caused by mutations in MECP2 gene. Exons 2, 3, and 4, in addition to intronic and 3’UTR adjacent regions, were sequenced in 80 patients with RS. Twenty-nine sequence variations were detected in 49 patients, 34 (69.4%) patients with the classic form of RS, and 15 (30.6%) patients with atypical forms of RS. Thirteen of the 29 detected mutations represent novel sequence variations. Missense mutation T158M was the most commonly observed mutation, detected in nine patients (11.2%). Six hotspot pathogenic mutations (R133C, T158M, R168X, R255X, R270X, and R294X) were responsible for the phenotype in 26/80 patients (32.5%).
5. Percy AK, Lee HS, Neul JL, Lane JB, Skinner SA, Geerts SP, Annese F, Graham J, McNair L, Motil KJ, Barrish JO, Glaze DG. {{Profiling Scoliosis in Rett Syndrome}}. {Pediatr Res}. 2009 Dec 21.
To understand scoliosis, related co-morbidities, and phenotype-genotype correlations in individuals with Rett syndrome (RTT), the Rare Disease Clinical Research Network database for RTT was probed. Clinical evaluations included a detailed history and physical examination, comprehensive anthropometric measurements, and two quantitative measures of clinical status, Clinical Severity Scale (CSS) and Motor-Behavioral Analysis (MBA). All data were exported to the Data Technology Coordinating Center (DTCC) at the University of South Florida. Scoliosis assessment was based on direct examination and curvature measurements by radiography (Cobb angle). Statistical analyses included univariate and multiple logistic regression models, adjusting for age at enrollment or mutation type. Scoliosis data were available from 554 classic RTT participants, mean age = 10 years (0-57 yr). Scoliosis was noted in 292 (53%); mean age = 15 yr with scoliosis and 6 yr without. Using multiple regression analysis, MBA severity score, later acquisition, loss, or absent walking, and constipation were associated with scoliosis. Two common methyl-CpG-binding protein 2 (MECP2) mutations, R294X and R306C, had reduced risk for scoliosis. These findings corroborated previous reports on scoliosis and extended understanding of co-morbidities, clinical severity, and relative risk reduction for specific mutations. Clinical trial design should account for scoliosis and related factors judiciously.
