1. Chen FS, Yoon JM. {{Brief Report: Broader Autism Phenotype Predicts Spontaneous Reciprocity of Direct Gaze}}. {J Autism Dev Disord};2010 (Nov 16)

We report evidence for a relationship in the general population between self-reported autism-associated traits and the spontaneous reciprocation of direct gaze, a behavior that we propose may reflect a tendency to synchronize with social partners. Adults viewed videos of actors whose gaze was either directed towards or averted from them. Individuals with lower scores on four subscales of the Autism-Spectrum Quotient (AQ) scale showed a greater tendency to look at directed relative to averted eyes; individuals with higher scores on the AQ did not. This relationship was specific to autism-associated traits and to gaze towards the eyes; it did not generalize to a social anxiety measure or to gaze towards the mouth. We discuss implications for our understanding of the broader autism phenotype.

2. Devlin B, Melhem N, Roeder K. {{Do common variants play a role in risk for autism? Evidence and theoretical musings}}. {Brain Res};2010 (Nov 12)

Both rare and common genetic variants underlie risk for almost any complex disease. Over the past few years a common tool for identifying common risk variants is genome-wide association or GWA. Our analyses focus on results from GWA targeting common variants affecting risk for autism spectrum disorders (ASD). Thus far three large GWA studies have been published, each of which highlights a single, non-overlapping risk locus. Evaluation of these studies suggests that combination of their data would diminish evidence for all of these loci, making none of them significant. Despite this paucity of findings, statistical theory can be used to infer a plausible distribution of effect sizes for SNPs affecting risk for ASD. We lay out this theory, calculate plausible distributions, and discuss the results in the context of results from GWA studies for schizophrenia.

3. Fuentes CT, Mostofsky SH, Bastian AJ. {{Perceptual reasoning predicts handwriting impairments in adolescents with autism}}. {Neurology};2010 (Nov 16);75(20):1825-1829.

BACKGROUND: We have previously shown that children with autism spectrum disorder (ASD) have specific handwriting deficits consisting of poor form, and that these deficits are predicted by their motor abilities. It is not known whether the same handwriting impairments persist into adolescence and whether they remain linked to motor deficits. METHODS: A case-control study of handwriting samples from adolescents with and without ASD was performed using the Minnesota Handwriting Assessment. Samples were scored on an individual letter basis in 5 categories: legibility, form, alignment, size, and spacing. Subjects were also administered an intelligence test and the Physical and Neurological Examination for Subtle (Motor) Signs (PANESS). RESULTS: We found that adolescents with ASD, like children, show overall worse performance on a handwriting task than do age- and intelligence-matched controls. Also comparable to children, adolescents with ASD showed motor impairments relative to controls. However, adolescents with ASD differ from children in that Perceptual Reasoning Indices were significantly predictive of handwriting performance whereas measures of motor skills were not. CONCLUSIONS: Like children with ASD, adolescents with ASD have poor handwriting quality relative to controls. Despite still demonstrating motor impairments, in adolescents perceptual reasoning is the main predictor of handwriting performance, perhaps reflecting subjects’ varied abilities to learn strategies to compensate for their motor impairments.

4. Funahashi Y, Imaeda M, Ishikawa M. {{[Examination at the sit-down of chair in autism spectrum disorder with children–with a pressure weighing device]}}. {No To Hattatsu};2010 (Nov);42(6):463-465.

5. Kaiser MD, Hudac CM, Shultz S, Lee SM, Cheung C, Berken AM, Deen B, Pitskel NB, Sugrue DR, Voos AC, Saulnier CA, Ventola P, Wolf JM, Klin A, Vander Wyk BC, Pelphrey KA. {{Neural signatures of autism}}. {Proc Natl Acad Sci U S A};2010 (Nov 15)

Functional magnetic resonance imaging of brain responses to biological motion in children with autism spectrum disorder (ASD), unaffected siblings (US) of children with ASD, and typically developing (TD) children has revealed three types of neural signatures: (i) state activity, related to the state of having ASD that characterizes the nature of disruption in brain circuitry; (ii) trait activity, reflecting shared areas of dysfunction in US and children with ASD, thereby providing a promising neuroendophenotype to facilitate efforts to bridge genomic complexity and disorder heterogeneity; and (iii) compensatory activity, unique to US, suggesting a neural system-level mechanism by which US might compensate for an increased genetic risk for developing ASD. The distinct brain responses to biological motion exhibited by TD children and US are striking given the identical behavioral profile of these two groups. These findings offer far-reaching implications for our understanding of the neural systems underlying autism.

6. King BH, Lord C. {{Is Schizophrenia on the Autism Spectrum?}}. {Brain Res};2010 (Nov 12)

With the ongoing consideration of the diagnostic criteria for mental disorders that is active in the Diagnostic and Statistical Manual of Mental Disorders (DSM-V) and International Classification of Diseases (ICD-10) revision processes, it is timely to review the phenomenological overlap between autism and schizophrenia. These disorders have at various times been regarded alternatively as closely related and as non-overlapping and incompatible. Nevertheless, there are several reports in the literature that have described individuals with both autism and schizophrenia, and the broader phenotypes of these disorders clearly intersect. Recent studies reveal Theory of Mind deficits in both disorders, and mirror neuron impairments also appear to be shared. There also may be similar connectivity deficits emerging in functional imaging studies, and both disorders share several genetic signals that are being identified through detection of copy number variants. Taken together, these data suggest that it may be time to revisit the possibility that these disorders are related.

7. Lampi KM, Banerjee PN, Gissler M, Hinkka-Yli-Salomaki S, Huttunen J, Kulmala U, Lindroos J, Niemela S, Rihko M, Ristkari T, Saanakorpi K, Sarlin T, Sillanmaki L, McKeague IW, Surcel HM, Helenius H, Brown AS, Sourander A. {{Finnish Prenatal Study of Autism and Autism Spectrum Disorders (FIPS-A): Overview and Design}}. {J Autism Dev Disord};2010 (Nov 17)

This article presents an overview of the Finnish Prenatal Study of Autism and Autism Spectrum Disorders (FIPS-A), a new study designed to examine the relationship between prenatal serologic factors, mediating and moderating developmental antecedents, and risk of autism spectrum disorders (ASD). The FIPS-A is based on register linkages between births from 1987 to 2005 ascertained from the Finnish Medical Birth Register (FMBR) and other national registers on treatment for this group of disorders. All subjects were members of the Finnish Maternity Cohort (FMC), which consists of virtually all births in Finland from 1983 to the present, and which includes archived maternal serum samples. This study also capitalizes on other registry information, such as systematically collected data on pregnancy, prenatal and neonatal complications and manual data collection from well-child clinics providing developmental data from birth to the age of 7 years. In this paper, we describe the methods used in the FIPS-A study, including a description of the national registers, available data and case ascertainment procedures. Finally, we discuss implications of the data for future work on uncovering putative aetiologies of ASD and key strengths and limitations of the design.

8. Oliver C, Berg K, Moss J, Arron K, Burbidge C. {{Delineation of Behavioral Phenotypes in Genetic Syndromes: Characteristics of Autism Spectrum Disorder, Affect and Hyperactivity}}. {J Autism Dev Disord};2010 (Nov 16)

We investigated autism spectrum disorder (ASD) symptomatology, hyperactivity and affect in seven genetic syndromes; Angelman (AS; n = 104), Cri du Chat (CdCS; 58), Cornelia de Lange (CdLS; 101), Fragile X (FXS; 191), Prader-Willi (PWS; 189), Smith-Magenis (SMS; 42) and Lowe (LS; 56) syndromes (age range 4-51). ASD symptomatology was heightened in CdLS and FXS. High levels of impulsivity were seen in SMS, AS, CdCS, FXS and adults with CdLS. Negative affect was prominent in adults with CdLS, while positive affect was prominent in adults with AS and FXS. Heightened levels of overactivity and impulsivity were identified in FXS, AS and SMS while low levels were identified in PWS. These findings confirm and extend previously reported behavioral phenotypes.

9. Radua J, Via E, Catani M, Mataix-Cols D. {{Voxel-based meta-analysis of regional white-matter volume differences in autism spectrum disorder versus healthy controls}}. {Psychol Med};2010 (Nov 16):1-12.

BACKGROUND: We conducted a meta-analysis of voxel-based morphometry (VBM) studies in autism spectrum disorder (ASD) to clarify the changes in regional white-matter volume underpinning this condition, and generated an online database to facilitate replication and further analyses by other researchers.MethodPubMed, ScienceDirect, Web of Knowledge and Scopus databases were searched between 2002 (the date of the first white-matter VBM study in ASD) and 2010. Manual searches were also conducted. Authors were contacted to obtain additional data. Coordinates were extracted from clusters of significant white-matter difference between patients and controls. A new template for white matter was created for the signed differential mapping (SDM) meta-analytic method. A diffusion tensor imaging (DTI)-derived atlas was used to optimally localize the changes in white-matter volume. RESULTS: Thirteen datasets comprising 246 patients with ASD and 237 healthy controls met inclusion criteria. No between-group differences were found in global white-matter volumes. ASD patients showed increases of white-matter volume in the right arcuate fasciculus and also in the left inferior fronto-occipital and uncinate fasciculi. These findings remained unchanged in quartile and jackknife sensitivity analyses and also in subgroup analyses (pediatric versus adult samples). CONCLUSIONS: Patients with ASD display increases of white-matter volume in tracts known to be important for language and social cognition. Whether the results apply to individuals with lower IQ or younger age and whether there are meaningful neurobiological differences between the subtypes of ASD remain to be investigated.