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The degree of white matter (WM) myelination is rather inhomogeneous across the brain. White matter appears differently across the cortical lobes in MR images acquired during early postnatal development. Specifically at 1-year of age, the gray/white matter contrast of MR T1 and T2 weighted images in prefrontal and temporal lobes is reduced as compared to the rest of the brain, and thus, tissue segmentation results commonly show lower accuracy in these lobes. In this novel work, we propose the use of spatial intensity growth maps (IGM) for T1 and T2 weighted images to compensate for local appearance inhomogeneity. The IGM captures expected intensity changes from 1 to 2 years of age, as appearance homogeneity is greatly improved by the age of 24 months. The IGM was computed as the coefficient of a voxel-wise linear regression model between corresponding intensities at 1 and 2 years. The proposed IGM method revealed low regression values of 1–10% in GM and CSF regions, as well as in WM regions at maturation stage of myelination at 1 year. However, in the prefrontal and temporal lobes we observed regression values of 20–25%, indicating that the IGM appropriately captures the expected large intensity change in these lobes mainly due to myelination. The IGM is applied to cross-sectional MRI datasets of 1-year-old subjects via registration, correction and tissue segmentation of the IGM-corrected dataset. We validated our approach in a small leave-one-out study of images with known, manual ‘ground truth’ segmentations.

Background Increasing evidence suggests that autism is a disorder of distributed neural networks that may exhibit abnormal developmental trajecto- ries. Characterisation of white matter early in the developmental course of the disorder is critical to understanding these aberrant trajectories. Methods A cross-sectional study of 2 -t o6-year-old children with autism was conducted using diffusion tensor imaging combined with a novel statistical approach employing fractional anisotropy distribu- tions. Fifty-eight children aged 18-79 months were imaged: 33 were diagnosed with autism, 8 with general developmental delay, and 17 were typically developing. Fractional anisotropy values within global white matter, cortical lobes and the cerebel- lum were measured and transformed to random F distributions for each subject. Each distribution of values for a region was summarised by estimating d

The Broad Autism Phenotype Questionnaire (BAPQ) was administered to a large community-based sample of biological parents of children with autism (PCAs) and comparison parents (CPs) (n = 1,692). Exploratory factor analysis and internal consistency parameters confirmed a robust three-factor structure of the BAPQ, corresponding to the proposed aloof, pragmatic language and rigidity subscales. Based upon the distribution of Broad Autism Phenotype (BAP) features in the general population, new normative cutoff values for BAPQ subscales were established that provide increased specificity relative to those previously reported, and thus enhance the utility of the BAPQ for diagnostically classifying the BAP. These cutoffs were also used to estimate prevalence of the BAP and its three components, with rates ranging between 14-23% for PCAs and between 5-9% for CPs. Analysis of patterns of BAP characteristics within family members revealed that BAP features were more likely to co-occur in PCAs relative to CPs. Collectively, these findings extend the utility of the BAPQ and provide additional evidence that it is an efficient and reliable tool for disaggregating the heterogeneity of autism through the identification of meaningful subgroups of parents. Autism Res 2013, 6: 134-143. © 2013 International Society for Autism Research, Wiley Periodicals, Inc.

Diffusion MR imaging has received increasing attention in the neuroimaging community, as it yields new insights into the microstructural organization of white matter that are not available with conventional MRI techniques. While the technology has enormous potential, diffusion MRI suffers from a unique and complex set of image quality problems, limiting the sensitivity of studies and reducing the accuracy of findings. Furthermore, the acquisition time for diffusion MRI is longer than conventional MRI due to the need for multiple acquisitions to obtain directionally encoded Diffusion Weighted Images (DWI). This leads to increased motion artifacts, reduced signal-to-noise ratio (SNR), and increased proneness to a wide variety of artifacts, including eddy-current and motion artifacts, “venetian blind” artifacts, as well as slice-wise and gradient-wise inconsistencies. Such artifacts mandate stringent Quality Control (QC) schemes in the processing of diffusion MRI data. Most existing QC procedures are conducted in the DWI domain and/or on a voxel level, but our own experiments show that these methods often do not fully detect and eliminate certain types of artifacts, often only visible when investigating groups of DWI's or a derived diffusion model, such as the most-employed diffusion tensor imaging (DTI). Here, we propose a novel regional QC measure in the DTI domain that employs the entropy of the regional distribution of the principal directions (PD). The PD entropy quantifies the scattering and spread of the principal diffusion directions and is invariant to the patient's position in the scanner. High entropy value indicates that the PDs are distributed relatively uniformly, while low entropy value indicates the presence of clusters in the PD distribution. The novel QC measure is intended to complement the existing set of QC procedures by detecting and correcting residual artifacts. Such residual artifacts cause directional bias in the measured PD and here called dominant direction artifacts. Experiments show that our automatic method can reliably detect and potentially correct such artifacts, especially the ones caused by the vibrations of the scanner table during the scan. The results further indicate the usefulness of this method for general quality assessment in DTI studies.

Nonverbal motion cues (a clenched fist) convey essential information about the intentions of the actor. Individuals with anorexia nervosa (AN) have demonstrated impairment in deciphering intention from facial affective cues, but it is unknown whether such deficits extend to deciphering affect from body motion cues.We examined the capacities of adults with AN (n = 21) or those weight restored for ≥12 months (WR; n = 20) to perceive affect in biological motion cues relative to healthy controls (HC; n = 23).Overall, individuals with AN evidenced greater deficit in discriminating affect from biological motion cues than WR or HC. Follow-up analyses showed that individuals with AN differed especially across two of the five conditions--deviating most from normative data when discriminating sadness and more consistently discriminating anger relative to WR or HC.Implications of these findings are discussed in relation to some puzzling interpersonal features of AN.

Individuals with autism demonstrate marked impairments in the perception, processing, and interpretation of social information. Recent findings suggest that abnormal social orienting may serve as a persistent and developmentally critical mechanism underlying deficits in this domain, and may help differentiate autism from other neurodevelopmental disorders sharing similar social cognitive impairments. This chapter uses social orienting as an example of the significant benefit that can be gained by integrating the fields of cognitive neuroscience and developmental psychopathology through the identification of neuropsychological mechanisms contributing to the development of abnormal brain–behavior relationships. Social orienting may represent a potentially fruitful mechanism for disentangling the pathogenesis of social deficits in autism.

Substantial phenotypic overlap exists between fragile X syndrome (FXS) and autism, suggesting that FMR1 (the gene causing FXS) poses a significant risk for autism. Crosspopulation comparisons of FXS and autism therefore offer a potentially valuable method for refining the range of phenotypes associated with variation in FMR1. This study adopted a broader phenotype approach, focusing on parents who are at increased genetic liability for autism or FXS. Women who were carriers of FMR1 in its premutation state were compared with mothers of individuals with autism, and controls in an attempt to determine whether subtle features of the broad autism phenotype may express at elevated rates among FMR1 premutation carriers. The principal personality and language features comprising the broad autism phenotype (i.e., rigid and aloof personality, and particular patterns of pragmatic language use) were assessed among 49 premutation carriers who were mothers of individuals with FXS, 89 mothers of individuals with autism, and 23 mothers of typically developing individuals. Relative to controls, the autism and premutation parent groups showed elevated rates of certain personality and language characteristics of the broad autism phenotype. Findings suggest partially overlapping personality and language profiles among autism and premutation parent groups, with rigid personality style and patterns of pragmatic language use emerging as features most clearly shared between groups. These results provide further evidence for the overlap of autism and FXS, and may implicate FMR1 in some of the subtle features comprising the broad autism phenotype. � 2012 Wiley Periodicals, Inc.

Evidence from prospective studies of high-risk infants suggests that early symptoms of autism usually emerge late in the first or early in the second year of life after a period of relatively typical development. The authors prospectively examined white matter fiber tract organization from 6 to 24 months in high-risk infants who developed autism spectrum disorders (ASDs) by 24 months.The participants were 92 high-risk infant siblings from an ongoing imaging study of autism. All participants had diffusion tensor imaging at 6 months and behavioral assessments at 24 months; a majority contributed additional imaging data at 12 and/or 24 months. At 24 months, 28 infants met criteria for ASDs and 64 infants did not. Microstructural properties of white matter fiber tracts reported to be associated with ASDs or related behaviors were characterized by fractional anisotropy and radial and axial diffusivity.The fractional anisotropy trajectories for 12 of 15 fiber tracts differed significantly between the infants who developed ASDs and those who did not. Development for most fiber tracts in the infants with ASDs was characterized by higher fractional anisotropy values at 6 months followed by slower change over time relative to infants without ASDs. Thus, by 24 months of age, those with ASDs had lower values.These results suggest that aberrant development of white matter pathways may precede the manifestation of autistic symptoms in the first year of life. Longitudinal data are critical to characterizing the dynamic age-related brain and behavior changes underlying this neurodevelopmental disorder.

With the publication of the first articles of this 2012 volume, the Journal of Neurodevelopmental Disorders enters the exciting world of open access publishing. The Journal will now be published by BioMed Central, (part of Springer Science+Business Media) as a fully open access journal. This change will mean that all articles will be made freely and permanently accessible online immediately upon publication, will be available to readers throughout the world without subscription charges or registration barriers, and be indexed in both PubMed and PubMed Central.

International audience; Statistical analysis of longitudinal imaging data is crucial for understanding normal anatomical development as well as disease progression. This fundamental task is challenging due to the difficulty in modeling longitudinal changes, such as growth, and comparing changes across different populations. We propose a new approach for analyzing shape variability over time, and for quantifying spatiotemporal population differences. Our approach estimates 4D anatomical growth models for a reference population (an average model) and for individuals in different groups. We define a reference 4D space for our analysis as the average population model and measure shape variability through diffeomorphisms that map the reference to the individuals. Conducting our analysis on this 4D space enables straightforward statistical analysis of deformations as they are parameterized by momenta vectors that are located at homologous locations in space and time. We evaluate our method on a synthetic shape database and clinical data from a study that seeks to quantify brain growth differences in infants at risk for autism.

Objective:Individuals with autism as young as 2 years have been observed to have larger brains than healthy comparison subjects. Studies using head circumference suggest that brain enlargement is a postnatal event that occurs around the latter part of the first year. To the authors' knowledge, no previous brain imaging studies have systematically examined the period prior to age 2. In this study they used magnetic resonance imaging (MRI) to measure brain volume in 6-month-olds at high familial risk for autism. Method:The Infant Brain Imaging Study (IBIS) is a longitudinal imaging study of infants at high risk for autism. This cross-sectional analysis compared brain volumes at 6 months of age in high-risk infants (N=98) and infants without family members with autism (N=36). MRI scans were also examined for radiologic abnormalities Results:No group differences were observed for intracranial, cerebrum, cerebellum, or lateral ventricle volume or for head circumference. Conclusions:The authors did not observe ...

In this paper, we propose a new method for longitudinal shape analysis that fits a linear mixed-effects model, while simultaneously optimizing correspondences on a set of anatomical shapes. Shape changes are modeled in a hierarchical fashion, with the global population trend as a fixed effect and individual trends as random effects. The statistical significance of the estimated trends are evaluated using specifically designed permutation tests. We also develop a permutation test based on the Hotelling T2 statistic to compare the average shapes trends between two populations. We demonstrate the benefits of our method on a synthetic example of longitudinal tori and data from a developmental neuroimaging study.

Context Brain enlargement has been observed in 2-year-old children with autism, but the underlying mechanisms are unknown. Objective To investigate early growth trajectories in brain volume and cortical thickness. Design Longitudinal magnetic resonance imaging study. Setting Academic medical centers. Participants Fifty-nine children with autism spectrum disorder (ASD) and 38 control children. Intervention Children were examined at approximately 2 years of age. Magnetic resonance imaging was repeated approximately 24 months later (when aged 4-5 years; 38 children with ASD; 21 controls). Main Outcome Measures Cerebral gray and white matter volumes and cortical thickness. Results We observed generalized cerebral cortical enlargement in individuals with ASD at both 2 and 4 to 5 years of age. Rate of cerebral cortical growth across multiple brain regions and tissue compartments in children with ASD was parallel to that seen in the controls, indicating that there was no increase in rate of cerebral cortical growth during this interval. No cerebellar differences were observed in children with ASD. After controlling for total brain volume, a disproportionate enlargement in temporal lobe white matter was observed in the ASD group. We found no significant differences in cortical thickness but observed an increase in an estimate of surface area in the ASD group compared with controls for all cortical regions measured (temporal, frontal, and parieto-occipital lobes). Conclusions Our longitudinal magnetic resonance imaging study found generalized cerebral cortical enlargement in children with ASD, with a disproportionate enlargement in temporal lobe white matter. There was no significant difference from controls in the rate of brain growth for this age interval, indicating that brain enlargement in ASD results from an increased rate of brain growth before age 2 years. The presence of increased cortical volume, but not cortical thickness, suggests that early brain enlargement may be associated with increased cortical surface area. Cortical surface area overgrowth in ASD may underlie brain enlargement and implicates a distinct set of pathogenic mechanisms.

Objective To examine pre-, peri-, and neonatal factors in autism using composite optimality scores. Method Pre-, peri-, and neonatal composite optimality scores were examined in 39 autistic subjects and 39 randomly matched sibling controls using a modification of the Gillberg Optimality Scale (Modified-GOS). Scores were based on best-estimate ratings of maternal interviews and medical records. Rules for best-estimate ratings were derived from a study of agreement between these two sources. Results Significant differences in optimality between autistic probands and their siblings were not present after adjustment for "maternal parity.‘' Examination of specific variables revealed that only maternal parity differed significantly between autistic subjects and randomly matched sibling controls, reflecting an excess of first and fourth born among the autistic subjects. Conclusion The findings of this study suggest that previous reports of an association between optimality and autism are aresult of failure to adjust for birth order. J. Am. Acad. Child Adolesc. Psychiatry , 1993, 32,6:1256–1263.

Autism is arguably the quintessential neurodevelopmental disorder. However, despite an explosion of research over the past decade, we know relatively little about the development of autism itself. Recent longitudinal research has provided important new insights—and has raised new questions—concerning the complexities of the disorder.

Nishiyama et al. (2013) recently examined the reliability and construct validity of the Broad Autism Phenotype Questionnaire (BAPQ) and three other instruments with the goal of measuring quantitative autistic traits in 64 individuals with autism spectrum disorder (ASD) and two population samples. As the authors of the BAPQ (Hurley et al. 2007; Sasson et al. 2013),we write to point out that although the study appeared to be carefully and thoughtfully conducted in almost every way, the BAPQ was not designed to be administered to individuals with ASD, nor measure the defining characteristics of autism. Thus, we question the appropriateness of the validation process employed by the authors as well as their interpretation of the study’s results. In contrast to the other questionnaires examined in Nishiyama et al. (2013), the BAPQ does not measure autistic traits but rather is, to our knowledge, the only instrument currently available in the field that was specifically designed to measure the broad autism phenotype. As described in our two papers that detail the development of the instrument, examine its psychometric properties and discuss its extensive validation (Hurley et al. 2007; Sasson et al. 2013), the BAPQ was designed on the basis of the senior author’s experience conducting direct assessments of the parents of autistic individuals, who themselves specifically did not have an ASD (Piven et al. 1997). This distinction is important, and results in three primary ways in which the constructs underlying the BAP and ASD differ. First, while the BAP is often referred to as representing characteristics that are milder but qualitatively similar to ASD, there are also areas in which the two differ qualitatively. For instance, the BAPQ purports to measure the personality construct ‘rigidity’, defined primarily as a preference for routine. An example might include a father who prefers to go to the same restaurant every Saturday night or gets uncomfortable when asked to vary his route to work by two blocks in order to mail a letter for his wife. This differs vastly from characteristics like immediate and delayed echolalia, which is an example of a repetitive and stereotyped characteristic specific to ASD that is not addressed in the BAPQ. Second, there is a difference between the level of severity in the construct of the BAP as assessed by the BAPQ and the level of severity inherent in a diagnosis of ASD. Specifically the BAP is not associated with clinical impairment in our studies (Piven 2002), whereas impairment is an implicit aspect of the diagnosis of ASD. Finally, while the BAPQ is both a selfand informant-report questionnaire, the validity of its use as a self-report questionnaire in individuals with ASD, who by definition have impairments in language and appreciation of social nuances, is suspect. In summary, we believe that Nishiyama et al. (2013) inappropriately evaluated the BAPQ by assessing its ability to differentiate adults with ASD from a population sample, a task it was not designed to address. Although the BAPQ performed well in this context and we applaud the conceptualization of the characteristics inherent in the genetic liability for autism as quantitative traits, it is critical to keep in mind that the measurement of constructs at different ends of such a dimension are not equivalent. To us, this invalidates the results of this paper with respect to analyses involving the BAPQ. J. Piven (&) University of North Carolina, Chapel Hill, NC, USA e-mail: joe_piven@med.unc.edu

Although autism spectrum disorders (ASDs) have a substantial genetic basis, most of the known genetic risk has been traced to rare variants, principally copy number variants (CNVs). To identify common risk variation, the Autism Genome Project (AGP) Consortium genotyped 1558 rigorously defined ASD families for 1 million single-nucleotide polymorphisms (SNPs) and analyzed these SNP genotypes for association with ASD. In one of four primary association analyses, the association signal for marker rs4141463, located within MACROD2, crossed the genome-wide association significance threshold of P < 5 × 10−8. When a smaller replication sample was analyzed, the risk allele at rs4141463 was again over-transmitted; yet, consistent with the winner's curse, its effect size in the replication sample was much smaller; and, for the combined samples, the association signal barely fell below the P < 5 × 10−8 threshold. Exploratory analyses of phenotypic subtypes yielded no significant associations after correction for multiple testing. They did, however, yield strong signals within several genes, KIAA0564, PLD5, POU6F2, ST8SIA2 and TAF1C. Author has checked copyright TS 14.06.13 The subscript characters from the abstract have not copied across properly. TS

BackgroundIndividuals with schizophrenia and individuals with high-functioning autism (HFA) seem to share some social, behavioral and biological features. Although marked impairments in social cognition have been documented in both groups, little empirical work has compared the social cognitive functioning of these two clinical groups.MethodForty-four individuals with schizophrenia, 36 with HFA and 41 non-clinical controls completed a battery of social cognitive measures that have been linked previously to specific brain regions.ResultsThe results indicate that the individuals with schizophrenia and HFA were both impaired on a variety of social cognitive tasks relative to the non-clinical controls, but did not differ from one another. When individuals with schizophrenia were divided into negative symptom and paranoid subgroups, exploratory analyses revealed that individuals with HFA may be more similar, in terms of the pattern of social cognition impairments, to the negative symptom group than to the paranoia group.ConclusionsOur findings provide further support for similarities in social cognition deficits between HFA and schizophrenia, which have a variety of implications for future work on gene–brain–behavior relationships.

SYNOPSISSocial language use (pragmatics) in parents of autistic individuals and controls was compared. Autism parents displayed atypical pragmatic behaviours more often than controls. Preliminary factor analysis suggested three parsimonious groupings of pragmatic abnormalities: Disinhibited Social Communication, Awkward/Inadequate Expression, and Odd Verbal Interaction. The pragmatic features observed in some autism parents are milder but conceptually similar to the social language deficits of autism. Possible reasons for familial aggregation of pragmatic language deficits are discussed.

Member of the Autism Genome Project Consortium: Astrid M. Vicente Although autism is a highly heritable neurodevelopmental disorder, attempts to identify specific susceptibility genes have thus far met with limited success. Genome-wide association studies using half a million or more markers, particularly those with very large sample sizes achieved through meta-analysis, have shown great success in mapping genes for other complex genetic traits. Consequently, we initiated a linkage and association mapping study using half a million genome-wide single nucleotide polymorphisms (SNPs) in a common set of 1,031 multiplex autism families (1,553 affected offspring). We identified regions of suggestive and significant linkage on chromosomes 6q27 and 20p13, respectively. Initial analysis did not yield genome-wide significant associations; however, genotyping of top hits in additional families revealed an SNP on chromosome 5p15 (between SEMA5A and TAS2R1) that was significantly associated with autism (P = 2 x 10(-7)). We also demonstrated that expression of SEMA5A is reduced in brains from autistic patients, further implicating SEMA5A as an autism susceptibility gene. The linkage regions reported here provide targets for rare variation screening whereas the discovery of a single novel association demonstrates the action of common variants.

Context Cerebral cortical volume enlargement has been reported in 2- to 4-year-olds with autism. Little is known about the volume of subregions during this period of development. The amygdala is hypothesized to be abnormal in volume and related to core clinical features in autism. Objectives To examine amygdala volume at 2 years with follow-up at 4 years of age in children with autism and to explore the relationship between amygdala volume and selected behavioral features of autism. Design Longitudinal magnetic resonance imaging study. Setting University medical setting. Participants Fifty autistic and 33 control (11 developmentally delayed, 22 typically developing) children between 18 and 35 months (2 years) of age followed up at 42 to 59 months (4 years) of age. Main Outcome Measures Amygdala volumes in relation to joint attention ability measured with a new observational coding system, the Social Orienting Continuum and Response Scale; group comparisons including total tissue volume, sex, IQ, and age as covariates. Results Amygdala enlargement was observed in subjects with autism at both 2 and 4 years of age. Significant change over time in volume was observed, although the rate of change did not differ between groups. Amygdala volume was associated with joint attention ability at age 4 years in subjects with autism. Conclusions The amygdala is enlarged in autism relative to controls by age 2 years but shows no relative increase in magnitude between 2 and 4 years of age. A significant association between amygdala volume and joint attention suggests that alterations to this structure may be linked to a core deficit of autism.

Aim Fragile X syndrome is associated with cognitive deficits in inhibitory control and with abnormal neuronal morphology and development. Method In this study, we used a diffusion tensor imaging (DTI) tractography approach to reconstruct white-matter fibers in the ventral frontostriatal pathway in young males with fragile X syndrome (n=17; mean age 2y 9mo, SD 7mo, range 1y 7mo–3y 10mo), and two age-matched comparison groups: (1) typically developing (n=13; mean age 2y 3mo, SD 7mo, range 1y 7mo–3y 6mo) and (2) developmentally delayed (n=8; mean age 3y, SD 4mo, range 2y 9mo–3y 8mo). Results We observed that young males with fragile X syndrome exhibited increased density of DTI reconstructed fibers than those in the typically developing (p=0.001) and developmentally delayed (p=0.001) groups. Aberrant white-matter structure was localized in the left ventral frontostriatal pathway. Greater relative fiber density was found to be associated with lower IQ (Mullen composite scores) in the typically developing group (p=0.008). Interpretation These data suggest that diminished or absent fragile X mental retardation 1 protein expression can selectively alter white-matter anatomy during early brain development and, in particular, neural pathways. The results also point to an early neurobiological marker for an important component of cognitive dysfunction associated with fragile X syndrome.

The study examined 75 autistic individuals who met DSM-III-R criteria for autistic disorder at 5 years of age. Diagnosis was based on information elicited using a standardized interview for autism. Two of 75 (2.7%) autistic subjects expressed the fragile X marker (Xq27.3) in 40% of cells counted and had other affected family members. Two additional subjects expressed the fragile X anomaly at low rates (1%). These rates are compared with those reported in other studies. Methodological differences, which may underlie the varying rates reported across studies, are discussed.

Eighty-one parents of 42 autistic probands and 34 parents of 18 Down syndrome probands were examined using a semistructured, investigator-based version of the Schedule for Affective Disorders and Schizophrenia Lifetime Version to estimate the lifetime risk of psychiatric disorder. The lifetime prevalence rate of anxiety disorder was significantly greater in parents of autistic probands than in parents of Down syndrome probands. The lifetime prevalence rate of major depressive disorder, while not significantly different in cases and controls, may be high in the parents of autistic probands (27%) in comparison with populations rates.

Infantile autism was first described by Kanner in 1943.1 Based on the observation that symptoms often began shortly after birth and always by two or three years of age, Kanner believed that autism was caused by an unknown, inborn defect. Because this syndrome was so severe and peculiar, it seemed unlikely to be an understandable outcome of a child's life experiences. In the years since Kanner first described this disorder, research findings have supported his initial interpretations. It is now generally accepted that autism has a biologic cause, and considerable research has been carried out with the aim of uncovering its nature. Both hereditary factors and the prenatal and perinatal environment have been considered. This paper will review the role of genetic factors in the cause of autism; the role of the prenatal and perinatal environment is considered in the paper by Nelson.51 Three types of genetic associations have been described: (1) the familial aggregation of autism, per se—autism is more common in the sibs of affected children; (2) the familial aggregation of other disorders in the family members of autistic children—a variety of disorders that are mild, but probably conceptually related, have recently been described in relatives; and (3) autism appears in association with a few particular disorders of known genetic etiology. FAMILIAL AGGREGATION OF AUTISM Population and Family Studies In most case series and a few population-based studies, the prevalence of autism in the siblings of autistic children has been estimated to be about 2% to 3%.2,3 While this number is small, it is 50 to 100 times greater than the expected rate of autism of 4 to 5 per 10 000 in the population.4,5

Autism spectrum disorders (ASDs) represent a group of childhood neurodevelopmental and neuropsychiatric disorders characterized by deficits in verbal communication, impairment of social interaction, and restricted and repetitive patterns of interests and behaviour. To identify common genetic risk factors underlying ASDs, here we present the results of genome-wide association studies on a cohort of 780 families (3,101 subjects) with affected children, and a second cohort of 1,204 affected subjects and 6,491 control subjects, all of whom were of European ancestry. Six single nucleotide polymorphisms between cadherin 10 (CDH10) and cadherin 9 (CDH9)-two genes encoding neuronal cell-adhesion molecules-revealed strong association signals, with the most significant SNP being rs4307059 (P = 3.4 x 10(-8), odds ratio = 1.19). These signals were replicated in two independent cohorts, with combined P values ranging from 7.4 x 10(-8) to 2.1 x 10(-10). Our results implicate neuronal cell-adhesion molecules in the pathogenesis of ASDs, and represent, to our knowledge, the first demonstration of genome-wide significant association of common variants with susceptibility to ASDs.

SummaryIn his original description of autism, Kanner [1] noted that the parents of autistic children often exhibited unusual social behavior themselves, consistent with what we now know about the high heritability of autism [2]. We investigated this so-called Broad Autism Phenotype in the parents of children with autism, who themselves did not receive a diagnosis of any psychiatric illness. Building on recent quantifications of social cognition in autism [3], we investigated face processing by using the “bubbles” method [4] to measure how viewers make use of information from specific facial features in order to judge emotions. Parents of autistic children who were assessed as socially aloof (N = 15), a key component of the phenotype [5], showed a remarkable reduction in processing the eye region in faces, together with enhanced processing of the mouth, compared to a control group of parents of neurotypical children (N = 20), as well as to nonaloof parents of autistic children (N = 27, whose pattern of face processing was intermediate). The pattern of face processing seen in the Broad Autism Phenotype showed striking similarities to that previously reported to occur in autism [3] and for the first time provides a window into the endophenotype that may result from a subset of the genes that contribute to social cognition.

With great potential in studying neuro-development, neuro-degeneration, and the aging process, longitudinal image data is gaining increasing interest and attention in the neuroimaging community. In this paper, we present a parametric nonlinear model to statistically study multivariate longitudinal data with asymptotic properties. We demonstrate our preliminary results in a combined study of two longitudinal neuroimaging data sets of early brain development to cover a wider time span and to gain a larger sample size. Such combined analysis of multiple longitudinal image data sets has not been conducted before and presents a challenge for traditional analysis methods. To our knowledge, this is the first multivariate nonlinear longitudinal analysis to study early brain development. Our methodology is generic in nature and can be applied to any longitudinal data with nonlinear growth patterns that can not easily be modeled by linear methods.

Despite compelling evidence from twin and family studies indicating a strong genetic involvement in the etiology of autism, the unequivocal detection of autism susceptibility genes remains an elusive goal. The purpose of this review is to evaluate the current state of autism genetics research, with attention focused on new techniques and analytic approaches. We first present a brief overview of evidence for the genetic basis of autism, followed by an appraisal of linkage and candidate gene study findings and consideration of new analytic approaches to the study of complex psychiatric conditions, namely, genome-wide association studies, assessment of structural variation within the genome, and the incorporation of endophenotypes in genetic analysis.

This paper describes a framework for quantitative analysis of neuroimaging data of traveling human phantoms used for cross-site validation. We focus on the analysis of magnetic resonance image data including intra- and inter-site comparison. Locations and magnitude of geometric deformation is studied via unbiased atlas building and metrics on deformation fields. Variability of tissue segmentation is analyzed by comparison of volumes, overlap of tissue maps, and a new Kullback-Leibler divergence on tissue probabilities, with emphasis on comparing probabilistic rather than binary segmentations. We show that results from this information theoretic measure are highly correlated with overlap. Reproducibility of automatic, atlas-based segmentation of subcortical structures is examined by comparison of volumes, shape overlap and surface distances. Variability among scanners of the same type but also differences to a different scanner type are discussed. The results demonstrate excellent reliability across multiple sites that can be achieved by the use of the today’s scanner generation and powerful automatic analysis software. Knowledge about such variability is crucial for study design and power analysis in new multi-site clinical studies.

This study examined the frequency of personality, language, and social-behavioral characteristics believed to comprise the broad autism phenotype (BAP), across families differing in genetic liability to autism. We hypothesized that within this unique sample comprised of multiple-incidence autism families (MIAF), single-incidence autism families (SIAF), and control Down syndrome families (DWNS), a graded expression would be observed for the principal characteristics conferring genetic susceptibility to autism, in which such features would express most profoundly among parents from MIAFs, less strongly among SIAFs, and least of all among comparison parents from DWNS families, who should display population base rates. Analyses detected linear expression of traits in line with hypotheses, and further suggested differential intrafamilial expression across family types. In the vast majority of MIAFs both parents displayed BAP characteristics, whereas within SIAFs, it was equally likely that one, both, or neither parent show BAP features. The significance of these findings is discussed in relation to etiologic mechanisms in autism and relevance to molecular genetic studies.

Context Brain maturation starts well before birth and occurs as a unified process with developmental interaction among different brain regions. Gene and environment play large roles in such a process. Studies of individuals with genetic disorders such as fragile X syndrome (FXS), which is a disorder caused by a single gene mutation resulting in abnormal dendritic and synaptic pruning, together with healthy individuals may provide valuable information. Objective To examine morphometric spatial patterns that differentiate between FXS and controls in early childhood. Design A cross-sectional in vivo neuroimaging study. Setting Academic medical centers. Participants A total of 101 children aged 1 to 3 years, comprising 51 boys with FXS, 32 typically developing boys, and 18 boys with idiopathic developmental delay. Main Outcome Measures Regional gray matter volume as measured by voxel-based morphometry and manual tracing, supplemented by permutation analyses; regression analyses between gray and white matter volumes, IQ, and fragile X mental retardation protein level; and linear support vector machine analyses to classify group membership. Results In addition to aberrant brain structures reported previously in older individuals with FXS, we found reduced gray matter volumes in regions such as the hypothalamus, insula, and medial and lateral prefrontal cortices. These findings are consistent with the cognitive and behavioral phenotypes of FXS. Further, multivariate pattern classification analyses discriminated FXS from typical development and developmental delay with more than 90% prediction accuracy. The spatial patterns that classified FXS from typical development and developmental delay included those that may have been difficult to identify previously using other methods. These included a medial to lateral gradient of increased and decreased regional brain volumes in the posterior vermis, amygdala, and hippocampus. Conclusions These findings are critical in understanding interplay among genes, environment, brain, and behavior. They signify the importance of examining detailed spatial patterns of healthy and perturbed brain development.

Data sharing in autism neuroimaging presents scientific, technical, and social obstacles. We outline the desiderata for a data-sharing scheme that combines imaging with other measures of phenotype and with genetics, defines requirements for comparability of derived data and recommendations for raw data, outlines a core protocol including multispectral structural and diffusion-tensor imaging and optional extensions, provides for the collection of prospective, confound-free normative data, and extends sharing and collaborative development not only to data but to the analytical tools and methods applied to these data. A theme in these requirements is the need to preserve creative approaches and risk-taking within individual laboratories at the same time as common standards are provided for these laboratories to build on.

To apply phenotypic and statistical methods designed to account for heterogeneity to linkage analyses of the autism Collaborative Linkage Study of Autism (CLSA) affected sibling pair families.The CLSA contains two sets of 57 families each; Set 1 has been analyzed previously, whereas this study presents the first analyses of Set 2. The two sets were analyzed independently, and were further split based on the degree of phrase speech delay in the siblings. Linkage analysis was carried out using the posterior probability of linkage (PPL), a Bayesian statistic that provides a mathematically rigorous mechanism for combining linkage evidence across multiple samples.Two-point PPLs from Set 1 led to the follow-up genotyping of 18 markers around linkage peaks on 1q, 13p, 13q, 16q, and 17q in both sets of families. Multipoint PPLs were then calculated for the entire CLSA sample. These analyses identified four regions with at least modest evidence in support of linkage: 1q at 173 cM, PPL=0.12; 13p at 21 cM, PPL=0.16; 16q at 63 cM, PPL=0.36; Xq at 40 cM, PPL=0.11.We find strengthened evidence for linkage of autism to chromosomes 1q, 13p, 16q, and Xq, and diminished evidence for linkage to 7q and 13q. The verity of these findings will be tested by continuing to update our PPL analyses with data from additional autism datasets.

Magnetic resonance imaging (MRI) scans were performed on 13 high-functioning male autistic subjects and 13 male nonautistic control subjects comparable in age and nonverbal IQ. Scans were rated for the presence of cerebral cortical malformations. Five autistic subjects had polymicrogyria, one had schizencephaly and macrogyria, and one had macrogyria. None of the control subjects had abnormalities of this type. These abnormalities result from a defect in the migration of neurons to the cerebral cortex during the first 6 months of gestation. The detection of these malformations by MRI, their pathogenesis, and the implications regarding the pathogenesis of autism are discussed.

The family history method was used to obtain developmental, social, and psychiatric histories on the 67 adult siblings of 37 autistic probands. Two of 67 siblings (3.0%) were autistic, three siblings (4.4%) had severe social dysfunction and isolation, 10 (15%) had cognitive disorders, and 10 (15%) had received treatment for affective disorder. This study is the first to investigate the frequency of disorders in the adult siblings of autistic probands. These results suggest aggregation of a variety of neuropsychiatric disorders in the siblings of autistic individuals.

The search for the molecular basis of autism is challenging. The high heritability of the disorder led to great optimism that traditional linkage methods would rapidly identify disease genes for this phenotypically complex disorder and provide a means for understanding its underlying pathophysiology in the same way that the identification of the MeCP3 gene provided the impetus for major advances in the understanding of Rett Syndrome. Similarly, structural neuroimaging studies and neurochemical investigations of serotonin initially met with considerable optimism. In each of these cases, unexpected deficiencies of the methods coupled with heterogeneity in autism limited progress. Researchers have responded by developing more sensitive methods and by more precisely defining subject and control groups with particular attention to narrowly defined phenotypes, age, cognitive ability, and gender. There has been particular emphasis on taking a developmental perspective, especially regarding imaging and studies of brain chemistry and function.

Schizophrenia and autism both feature significant impairments in social cognition and social functioning, but the specificity and mechanisms of these deficits remain unknown. Recent research suggests that social cognitive deficits in both disorders may arise from dysfunctions in the neural systems that underlie social cognition. We explored the neural activation of discrete brain regions implicated in social cognitive and face processing in schizophrenia subgroups and autism spectrum disorders during complex social judgments of faces. Twelve individuals with autism spectrum disorders (ASD), 12 paranoid individuals with schizophrenia (P-SCZ), 12 non-paranoid individuals with schizophrenia (NP-SCZ), and 12 non-clinical healthy controls participated in this cross sectional study. Neural activation, as indexed by blood oxygenation level dependent (BOLD) contrast, was measured in a priori regions of interest while individuals rated faces for trustworthiness. All groups showed significant activation of a social cognitive network including the amygdala, fusiform face area (FFA), superior temporal sulcus (STS), and ventrolateral prefrontal cortex (VLPFC) while completing a task of complex social cognition (i.e. trustworthiness judgments). ASD and P-SCZ individuals showed significantly reduced neural activation in the right amygdala, FFA, and left VLPFC as compared to controls and in the left VLPFC as compared to NP-SCZ individuals during this task. These findings lend support to models hypothesizing well-defined neural substrates of social cognition and suggest a specific neural mechanism that may underlie social cognitive impairments in both autism and paranoid schizophrenia.

An important goal of statistical shape analysis is the discrimination between populations of objects, exploring group differences in morphology not explained by standard volumetric analysis. Certain applications additionally require analysis of objects in their embedding context by joint statistical analysis of sets of interrelated objects. In this paper, we present a framework for discriminant analysis of populations of 3-D multi-object sets. In view of the driving medical applications, a skeletal object parametrization of shape is chosen since it naturally encodes thickening, bending and twisting. In a multi-object setting, we not only consider a joint analysis of sets of shapes but also must take into account differences in pose. Statistics on features of medial descriptions and pose parameters, which include rotational frames and distances, uses a Riemannian symmetric space instead of the standard Euclidean metric. Our choice of discriminant method is the distance weighted discriminant (DWD) because of its generalization ability in high dimensional, low sample size settings. Joint analysis of 10 subcortical brain structures in a pediatric autism study demonstrates that multi-object analysis of shape results in a better group discrimination than pose, and that the combination of pose and shape performs better than shape alone. Finally, given a discriminating axis of shape and pose, we can visualize the differences between the populations.

A main focus of statistical shape analysis is the description of variability of a population of geometric objects. In this paper, we present work towards modeling the shape and pose variability of sets of multiple objects. Principal geodesic analysis (PGA) is the extension of the standard technique of principal component analysis (PCA) into the nonlinear Riemannian symmetric space of pose and our medial m-rep shape description, a space in which use of PCA would be incorrect. In this paper, we discuss the decoupling of pose and shape in multi-object sets using different normalization settings. Further, we introduce methods of describing the statistics of object pose and object shape, both separately and simultaneously using a novel extension of PGA. We demonstrate our methods in an application to a longitudinal pediatric autism study with object sets of 10 subcortical structures in a population of 47 subjects. The results show that global scale accounts for most of the major mode of variation across time. Furthermore, the PGA components and the corresponding distribution of different subject groups vary significantly depending on the choice of normalization, which illustrates the importance of global and local pose alignment in multi-object shape analysis. Finally, we present results of using distance weighted discrimination analysis (DWD) in an attempt to use pose and shape features to separate subjects according to diagnosis, as well as visualize discriminating differences.

International audience; Autism spectrum disorders (ASDs) are common, heritable neurodevelopmental conditions. The genetic architecture of ASDs is complex, requiring large samples to overcome heterogeneity. Here we broaden coverage and sample size relative to other studies of ASDs by using Affymetrix 10K SNP arrays and 1,181 [corrected] families with at least two affected individuals, performing the largest linkage scan to date while also analyzing copy number variation in these families. Linkage and copy number variation analyses implicate chromosome 11p12-p13 and neurexins, respectively, among other candidate loci. Neurexins team with previously implicated neuroligins for glutamatergic synaptogenesis, highlighting glutamate-related genes as promising candidates for contributing to ASDs.

To provide an overview of diffusion tensor imaging (DTI) and its application to the study of white matter in the developing brain in both healthy and clinical samples.The development of DTI and its application to brain imaging of white matter tracts is discussed. Forty-eight studies using DTI to examine diffusion properties of the developing brain are reviewed in the context of the structural magnetic resonance imaging literature. Reports of how brain diffusion properties are affected in pediatric clinical samples and how they relate to cognitive and behavioral phenotypes are reviewed.DTI has been used successfully to describe white matter development in pediatric samples. Changes in white matter diffusion properties are consistent across studies, with anisotropy increasing and overall diffusion decreasing with age. Diffusion measures in relevant white matter regions correlate with behavioral measures in healthy children and in clinical pediatric samples.DTI is an important tool for providing a more detailed picture of developing white matter than can be obtained with conventional magnetic resonance imaging alone.

Both autism and schizophrenia feature deficits in aspects of social cognition that may be related to amygdala dysfunction, but it is unclear whether these are similar or different patterns of impairment. We compared the visual scanning patterns and emotion judgments of individuals with autism, individuals with schizophrenia and controls on a task well characterized with respect to amygdala functioning. On this task, eye movements of participants are recorded as they assess emotional content within a series of complex social scenes where faces are either included or digitally erased. Results indicated marked abnormalities in visual scanning for both disorders. Controls increased their gaze on face regions when faces were present to a significantly greater degree than both the autism or schizophrenia groups. While the control and the schizophrenia groups oriented to face regions faster when faces were present compared to when they were absent, the autism group oriented at the same rate in both conditions. The schizophrenia group, meanwhile, exhibited a delay in orienting to face regions across both conditions, although whether anti-psychotic medication contributed to this effect is unclear. These findings suggest that while processing emotional information in social scenes, both individuals with autism and individuals with schizophrenia fixate faces less than controls, although only those with autism fail to orient to faces more rapidly based on the presence of facial information. Autism and schizophrenia may therefore share an abnormality in utilizing facial information for assessing emotional content in social scenes, but differ in the ability to seek out socially relevant cues from complex stimuli. Impairments in social orienting are discussed within the context of evidence suggesting the role of the amygdala in orienting to emotionally meaningful information.

The association between developmental trajectories of language-related white matter fiber pathways from 6 to 24 months of age and individual differences in language production at 24 months of age was investigated. The splenium of the corpus callosum, a fiber pathway projecting through the posterior hub of the default mode network to occipital visual areas, was examined as well as pathways implicated in language function in the mature brain, including the arcuate fasciculi, uncinate fasciculi, and inferior longitudinal fasciculi. The hypothesis that the development of neural circuitry supporting domain-general orienting skills would relate to later language performance was tested in a large sample of typically developing infants. The present study included 77 infants with diffusion weighted MRI scans at 6, 12 and 24 months and language assessment at 24 months. The rate of change in splenium development varied significantly as a function of language production, such that children with greater change in fractional anisotropy (FA) from 6 to 24 months produced more words at 24 months. Contrary to findings from older children and adults, significant associations between language production and FA in the arcuate, uncinate, or left inferior longitudinal fasciculi were not observed. The current study highlights the importance of tracing brain development trajectories from infancy to fully elucidate emerging brain-behavior associations while also emphasizing the role of the splenium as a key node in the structural network that supports the acquisition of spoken language.

People with autism are impaired in their social behavior, including their eye contact with others, but the processes that underlie this impairment remain elusive. We combined high-resolution eye tracking with computational modeling in a group of 10 high-functioning individuals with autism to address this issue. The group fixated the location of the mouth in facial expressions more than did matched controls, even when the mouth was not shown, even in faces that were inverted and most noticeably at latencies of 200–400 ms. Comparisons with a computational model of visual saliency argue that the abnormal bias for fixating the mouth in autism is not driven by an exaggerated sensitivity to the bottom-up saliency of the features, but rather by an abnormal top-down strategy for allocating visual attention.

Altered visual exploration of faces likely contributes to social cognition deficits seen in autism. To investigate the relationship between face gaze and social cognition in autism, we measured both face gaze and how facial regions were actually used during emotion judgments from faces. Compared to IQ-matched healthy controls, nine high-functioning adults with autism failed to make use of information from the eye region of faces, instead relying primarily on information from the mouth. Face gaze accounted for the increased reliance on the mouth, and partially accounted for the deficit in using information from the eyes. These findings provide a novel quantitative assessment of how people with autism utilize information in faces when making social judgments.

This paper addresses the challenging problem of statistics on images by describing average and variability. We describe computational anatomy tools for building 3-D and spatio-temporal 4-D atlases of volumetric image data. The method is based on the previously published concept of unbiased atlas building, calculating the nonlinear average image of a population of images by simultaneous nonlinear deformable registration. Unlike linear averaging, the resulting center average image is sharp and encodes the average structure and geometry of the whole population. Variability is encoded in the set of deformation maps. As a new extension, longitudinal change is assessed by quantifying local deformation between atlases taken at consecutive time points. Morphological differences between groups are analyzed by the same concept but comparing group-specific atlases. Preliminary tests demonstrate that the atlas building shows excellent robustness and a very good convergence, i.e. atlases start to stabilize after 5 images only and do not show significant changes when including more than 10 volumetric images taken from the same population.

The broad autism phenotype (BAP) is a set of personality and language characteristics that reflect the phenotypic expression of the genetic liability to autism, in non-autistic relatives of autistic individuals. These characteristics are milder but qualitatively similar to the defining features of autism. A new instrument designed to measure the BAP in adults, the Broad Autism Phenotype Questionnaire (BAPQ), was administered to 86 parents of autistic individuals and 64 community control parents. Sensitivity and specificity of the BAPQ for detecting the BAP were high (>70%). Parents of children with autism had significantly higher scores on all three subscales: aloof personality, rigid personality, and pragmatic language. This instrument provides a valid and efficient measure for characterizing the BAP.