1. Christofolini DM, Meloni VA, de Paula Ramos MA, Oliveira MM, de Mello CB, Pellegrino R, Takeno SS, Melaragno MI. {{Autistic disorder phenotype associated to a complex 15q intrachromosomal rearrangement}}. {Am J Med Genet B Neuropsychiatr Genet}. 2012.
The proximal regions of acrocentric chromosomes, particularly 15q11.2, are frequently involved in structural rearrangement. However, interstitial duplications involving one of the chromosome 15 homologues are less frequent, with few patients described with molecular techniques. These patients present distinctive clinical findings including developmental delay and intellectual disability, minor dysmorphic facial features, epilepsy, and autistic behavior. Here we describe an interstitial rearrangement of chromosome 15 composed of a triplication approximately 6.9 Mb from 15q11.2 to 15q13.2 followed by a duplication of approximately 2.4 Mb from 15q13.2 to 15q13.3, defined using different approaches as MLPA, qPCR, array and FISH. FISH revealed that the middle part of the triplicated segment was in inverted position. The parental origin of the rearrangement was assessed using methylation assay and SNP array that revealed the maternal origin of the additional material. The patient presents most of the clinical features associated to 15q11.2 triplication: minor dysmorphic facial features, generalized epilepsy, absence seizures, intellectual disability, and autistic behavior. In conclusion, the use of more accurate molecular tools enabled a detailed investigation, providing the identification of intrachromosome duplication/triplication and bringing new light to the study of genetic causes of autistic disorders. (c) 2012 Wiley Periodicals, Inc.
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2. Corsello CM, Akshoomoff N, Stahmer AC. {{Diagnosis of autism spectrum disorders in 2-year-olds: a study of community practice}}. {J Child Psychol Psychiatry}. 2012.
Background: Longitudinal research studies have demonstrated that experienced clinicians using standardized assessment measures can make a reliable diagnosis of autism spectrum disorders (ASDs) in children under age 3. Limited data are available regarding the sensitivity and specificity of these measures in community settings. The aims of this study were to determine how well a standardized diagnostic observational measure (Autism Diagnostic Observation Schedule – ADOS) functions alone, and with a brief parent measure within a community setting when administered by community clinicians. Methods: Clinical records for 138 children between the ages of 24 and 36 months of age who were evaluated for possible ASD or social/language concerns at a hospital-based developmental evaluation clinic were examined. Evaluations were conducted by community-based clinical psychologists. Classification results obtained from standardized diagnostic measures were compared with case reviewer diagnosis, by reviewers blind to scores on diagnostic measures, using The Records-based Methodology for ASD Case Definition that was developed by the Metropolitan Atlanta Developmental Disabilities Surveillance Program. Results: When compared with case review diagnosis, the ADOS demonstrated strong sensitivity and specificity for both Autism versus Not Autism and ASD versus Nonspectrum (NS) diagnoses in this young sample. The Social Communication Questionnaire (SCQ), using the lower cutoff of >/=12, had adequate sensitivity when differentiating Autism from Not Autism, but weak sensitivity when differentiating ASD from NS, missing about 80% of the children with pervasive developmental disorder – not otherwise specified. Using either the Modified Checklist for Autism in Toddlers or the SCQ in combination with the ADOS did not result in improved specificity over the ADOS alone and led to a drop in sensitivity when differentiating ASD from NS disorders. Conclusions: These results demonstrate that following best practice guidelines, the ADOS can be successfully incorporated into clinical practice with relatively good sensitivity and specificity, and worked well with a referred sample of 2-year-olds. A parent questionnaire did not lead to any improvement in diagnostic classification above the ADOS used in isolation.
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3. Frith U. {{Why we need cognitive explanations of autism}}. {Q J Exp Psychol (Hove)}. 2012.
[Formula: see text] In the 70 years since autism was described and named there have been huge changes in the conceptualization of this enigmatic condition. This review takes a personal perspective on the history of autism research. The origins of the first cognitive theories of autism, theory of mind and weak central coherence, are discussed and updated to inform future developments. Selected experimental findings are interpreted in the historical context of changes that have been brought about by advances in methodology. A three-level framework graphically illustrates a causal chain between brain, mind, and behaviour to facilitate the identification of phenotypes in neurodevelopmental disorders. Cognition is placed at the centre of the diagram to reveal that it can link together brain and behaviour, when there are complex multiple mappings between the different levels.
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4. Han S, Tai C, Westenbroek RE, Yu FH, Cheah CS, Potter GB, Rubenstein JL, Scheuer T, de la Iglesia HO, Catterall WA. {{Autistic-like behaviour in Scn1a(+/-) mice and rescue by enhanced GABA-mediated neurotransmission}}. {Nature}. 2012.
Haploinsufficiency of the SCN1A gene encoding voltage-gated sodium channel Na(V)1.1 causes Dravet’s syndrome, a childhood neuropsychiatric disorder including recurrent intractable seizures, cognitive deficit and autism-spectrum behaviours. The neural mechanisms responsible for cognitive deficit and autism-spectrum behaviours in Dravet’s syndrome are poorly understood. Here we report that mice with Scn1a haploinsufficiency exhibit hyperactivity, stereotyped behaviours, social interaction deficits and impaired context-dependent spatial memory. Olfactory sensitivity is retained, but novel food odours and social odours are aversive to Scn1a(+/-) mice. GABAergic neurotransmission is specifically impaired by this mutation, and selective deletion of Na(V)1.1 channels in forebrain interneurons is sufficient to cause these behavioural and cognitive impairments. Remarkably, treatment with low-dose clonazepam, a positive allosteric modulator of GABA(A) receptors, completely rescued the abnormal social behaviours and deficits in fear memory in the mouse model of Dravet’s syndrome, demonstrating that they are caused by impaired GABAergic neurotransmission and not by neuronal damage from recurrent seizures. These results demonstrate a critical role for Na(V)1.1 channels in neuropsychiatric functions and provide a potential therapeutic strategy for cognitive deficit and autism-spectrum behaviours in Dravet’s syndrome.
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5. Simonoff E, Jones CR, Pickles A, Happe F, Baird G, Charman T. {{Severe mood problems in adolescents with autism spectrum disorder}}. {J Child Psychol Psychiatry}. 2012.
Introduction: Severe mood dysregulation and problems (SMP) in otherwise typically developing youth are recognized as an important mental health problem with a distinct set of clinical features, family history and neurocognitive characteristics. SMP in people with autism spectrum disorders (ASDs) have not previously been explored. Method: We studied a longitudinal, population-based cohort of adolescents with ASD in which we collected parent-reported symptoms of SMP that included rage, low and labile mood and depressive thoughts. Ninety-one adolescents with ASD provided data at age 16 years, of whom 79 had additional data from age 12. We studied whether SMP have similar correlates to those seen in typically developing youth. Results: Severe mood problems were associated with current (parent-rated) and earlier (parent- and teacher-rated) emotional problems. The number of prior psychiatric diagnoses increased the risk of subsequent SMP. Intellectual ability and adaptive functioning did not predict to SMP. Maternal mental health problems rated at 12 and 16 years were associated with SMP. Autism severity as rated by parents was associated with SMP, but the relationship did not hold for clinician ratings of autistic symptoms or diagnosis. SMP were associated with difficulty in identifying the facial expression of surprise, but not with performance recognizing other emotions. Relationships between SMP and tests of executive function (card sort and trail making) were not significant after controlling for IQ. Conclusions: This is the first study of the behavioural and cognitive correlates of severe mood problems in ASD. As in typically developing youth, SMP in adolescents with ASD are related to other affective symptoms and maternal mental health problems. Previously reported links to deficits in emotion recognition and cognitive flexibility were not found in the current sample. Further research is warranted using categorical and validated measures of SMP.
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6. Walker L, Gozzi M, Lenroot R, Thurm A, Behseta B, Swedo S, Pierpaoli C. {{Diffusion Tensor Imaging in Young Children with Autism: Biological Effects and Potential Confounds}}. {Biol Psychiatry}. 2012.
BACKGROUND: Diffusion tensor imaging (DTI) has been used over the past decade to study structural differences in the brains of children with autism compared with typically developing children. These studies generally find reduced fractional anisotropy (FA) and increased mean diffusivity (MD) in children with autism; however, the regional pattern of findings varies greatly. METHODS: We used DTI to investigate the brains of sedated children with autism (n = 39) and naturally asleep typically developing children (n = 39) between 2 and 8 years of age. Tract based spatial statistics and whole brain voxel-wise analysis were performed to investigate the regional distribution of differences between groups. RESULTS: In children with autism, we found significantly reduced FA in widespread regions and increased MD only in posterior brain regions. Significant age x group interaction was found, indicating a difference in developmental trends of FA and MD between children with autism and typically developing children. The magnitude of the measured differences between groups was small, on the order of approximately 1%-2%. Subjects and control subjects showed distinct regional differences in imaging artifacts that can affect DTI measures. CONCLUSIONS: We found statistically significant differences in DTI metrics between children with autism and typically developing children, including different developmental trends of these metrics. However, this study indicates that between-group differences in DTI studies of autism should be interpreted with caution, because their small magnitude make these measurements particularly vulnerable to the effects of artifacts and confounds, which might lead to false positive and/or false negative biological inferences.
