1. Fox NS, Roman AS. {{Beta 2 adrenergic agents and autism}}. {Am J Obstet Gynecol} (Aug 16)
2. Lai MC, Lombardo MV, Chakrabarti B, Sadek SA, Pasco G, Wheelwright SJ, Bullmore ET, Baron-Cohen S, Suckling J. {{A Shift to Randomness of Brain Oscillations in People with Autism}}. {Biol Psychiatry} (Aug 20)
BACKGROUND:: Resting-state functional magnetic resonance imaging (fMRI) enables investigation of the intrinsic functional organization of the brain. Fractal parameters such as the Hurst exponent, H, describe the complexity of endogenous low-frequency fMRI time series on a continuum from random (H = .5) to ordered (H = 1). Shifts in fractal scaling of physiological time series have been associated with neurological and cardiac conditions. METHODS:: Resting-state fMRI time series were recorded in 30 male adults with an autism spectrum condition (ASC) and 33 age- and IQ-matched male volunteers. The Hurst exponent was estimated in the wavelet domain and between-group differences were investigated at global and voxel level and in regions known to be involved in autism. RESULTS:: Complex fractal scaling of fMRI time series was found in both groups but globally there was a significant shift to randomness in the ASC (mean H = .758, SD = .045) compared with neurotypical volunteers (mean H = .788, SD = .047). Between-group differences in H, which was always reduced in the ASC group, were seen in most regions previously reported to be involved in autism, including cortical midline structures, medial temporal structures, lateral temporal and parietal structures, insula, amygdala, basal ganglia, thalamus, and inferior frontal gyrus. Severity of autistic symptoms was negatively correlated with H in retrosplenial and right anterior insular cortex. CONCLUSIONS:: Autism is associated with a small but significant shift to randomness of endogenous brain oscillations. Complexity measures may provide physiological indicators for autism as they have done for other medical conditions.
3. Losh M, Esserman D, Piven J. {{Rapid Automatized Naming as an Index of Genetic Liability to Autism}}. {J Neurodev Disord} (Jun 1);2(2):109-116.
This study investigated rapid automatized naming (RAN) ability in high functioning individuals with autism and parents of individuals with autism. Findings revealed parallel patterns of performance in parents and individuals with autism, where both groups had longer naming times than controls. Significant parent-child correlations were also detected, along with associations with language and personality features of the broad autism phenotype (retrospective reports of early language delay, socially reticent personality). Together, findings point towards RAN as a potential marker of genetic liability to autism.
4. Pintaudi M, Calevo MG, Vignoli A, Parodi E, Aiello F, Baglietto MG, Hayek Y, Buoni S, Renieri A, Russo S, Cogliati F, Giordano L, Canevini M, Veneselli E. {{Epilepsy in Rett syndrome: Clinical and genetic features}}. {Epilepsy Behav} (Aug 20)
Epilepsy often occurs in Rett syndrome and is considered a major problem. The aim of this study was to define the clinical features of epilepsy and the correlation between seizures and both genotype and clinical phenotype in the Rett population. One hundred sixty-five patients with Rett syndrome referred to four Italian centers were recruited. All patients underwent video/EEG monitoring and molecular analysis of the MECP2 gene or, in negative cases, of the CDKL5 and FOXG1 genes. The frequency of epilepsy was 79%. Drug-resistant epilepsy occurred in 30% of all our patients with Rett syndrome and in 38% of those with epilepsy. Our findings demonstrate that epilepsy differs among the various phenotypes and genotypes with respect to age at onset, drug responsiveness, and seizure semiology. The Hanefeld and preserved speech variants represent the extremes of the range of severity of epilepsy: the preserved speech variant is characterized by the mildest epileptic phenotype as epilepsy is much less frequent, starts later, and is less drug resistant than what is observed in the other phenotypes. Another important finding is that seizure onset before 1year of age and daily frequency are risk factors for drug resistance. Thus, this study should help clinicians provide better clinical counseling to the families of patients with Rett syndrome.
5. Schaefer GB, Starr L, Pickering D, Skar G, Dehaai K, Sanger WG. {{Array Comparative Genomic Hybridization Findings in a Cohort Referred for an Autism Evaluation}}. {J Child Neurol} (Aug 20)
The development and refinement of array comparative genomic hybridization has led to expanded applications as a diagnostic tool. Recent reports suggest a high diagnostic yield for array comparative genomic hybridization in autism spectrum disorders. The objective of this study was to determine the diagnostic yield in array comparative genomic hybridization for autism at the University of Nebraska Medical Center. The authors report the diagnostic yield of array comparative genomic hybridization in 89 samples with a primary indication of autism. Clinical information was reviewed for 89 identified cases. Twenty-one cases were excluded because of ambiguous information regarding the diagnosis, a diagnosis other than autism, or abnormal karyotype. Of 68 cases referred for array comparative genomic hybridization testing with a primary indication of autism, 14 (21%) had abnormal findings. This study supports array comparative genomic hybridization in the etiologic evaluation of autism and elevation of array to a first tier diagnostic test.
6. Semrud-Clikeman M, Walkowiak J, Wilkinson A, Christopher G. {{Neuropsychological differences among children with asperger syndrome, nonverbal learning disabilities, attention deficit disorder, and controls}}. {Dev Neuropsychol} (Sep);35(5):582-600.
Confusion is present as to possible diagnostic differences between Asperger syndrome (AS) and Nonverbal learning disabilities (NLD) and the relation of these disorders to attentional difficulties. Three-hundred and forty-five children participated in this study in 5 groups; NLD, AS, attention deficit hyperactivity disorder (ADHD): Combined type, ADHD: Inattentive type, and controls. The NLD group showed particular difficulty on visual-spatial, visual-motor, and fluid reasoning measures compared to the other groups. There was also a significant verbal-performance IQ split in this group related to difficulty in social functioning. This study extends the findings from previous studies and extends these findings to differences between AS and NLD groups.
7. Vlamings PH, Jonkman LM, van Daalen E, van der Gaag RJ, Kemner C. {{Basic Abnormalities in Visual Processing Affect Face Processing at an Early Age in Autism Spectrum Disorder}}. {Biol Psychiatry} (Aug 20)
BACKGROUND:: A detailed visual processing style has been noted in autism spectrum disorder (ASD); this contributes to problems in face processing and has been directly related to abnormal processing of spatial frequencies (SFs). Little is known about the early development of face processing in ASD and the relation with abnormal SF processing. We investigated whether young ASD children show abnormalities in low spatial frequency (LSF, global) and high spatial frequency (HSF, detailed) processing and explored whether these are crucially involved in the early development of face processing. METHODS:: Three- to 4-year-old children with ASD (n = 22) were compared with developmentally delayed children without ASD (n = 17). Spatial frequency processing was studied by recording visual evoked potentials from visual brain areas while children passively viewed gratings (HSF/LSF). In addition, children watched face stimuli with different expressions, filtered to include only HSF or LSF. RESULTS:: Enhanced activity in visual brain areas was found in response to HSF versus LSF information in children with ASD, in contrast to control subjects. Furthermore, facial-expression processing was also primarily driven by detail in ASD. CONCLUSIONS:: Enhanced visual processing of detailed (HSF) information is present early in ASD and occurs for neutral (gratings), as well as for socially relevant stimuli (facial expressions). These data indicate that there is a general abnormality in visual SF processing in early ASD and are in agreement with suggestions that a fast LSF subcortical face processing route might be affected in ASD. This could suggest that abnormal visual processing is causative in the development of social problems in ASD.
