Social motivation in infancy is associated with familial recurrence of ASD.

Pre-diagnostic deficits in social motivation are hypothesized to contribute to autism spectrum disorder (ASD), a heritable neurodevelopmental condition. We evaluated psychometric properties of a social motivation index (SMI) using parent-report item-level data from 597 participants in a prospective cohort of infant siblings at high and low familial risk for ASD. We tested whether lower SMI scores at 6, 12, and 24 months were associated with a 24-month ASD diagnosis and whether social motivation's course differed relative to familial ASD liability. The SMI displayed good internal consistency and temporal stability. Children diagnosed with ASD displayed lower mean SMI T-scores at all ages and a decrease in mean T-scores across age. Lower group-level 6-month scores corresponded with higher familial ASD liability. Among high-risk infants, strong decline in SMI T-scores was associated with 10-fold odds of diagnosis. Infant social motivation is quantifiable by parental report, differentiates children with versus without later ASD by age 6 months, and tracks with familial ASD liability, consistent with a diagnostic and susceptibility marker of ASD. Early decrements and decline in social motivation indicate increased likelihood of ASD, highlighting social motivation's importance to risk assessment and clarification of the ontogeny of ASD.

Emergence of Developmental Delay in Infants and Toddlers With an FMR1 Mutation.

BACKGROUND: Children with FMR1 gene expansions are known to experience a range of developmental challenges, including fragile X syndrome. However, little is known about early development and symptom onset, information that is critical to guide earlier identification, more accurate prognoses, and improved treatment options. METHODS: Data from 8 unique studies that used the Mullen Scales of Early Learning to assess children with an FMR1 gene expansion were combined to create a data set of 1178 observations of >500 young children. Linear mixed modeling was used to explore developmental trajectories, symptom onset, and unique developmental profiles of children <5 years of age. RESULTS: Boys with an FMR1 gene full mutation showed delays in early learning, motor skills, and language development as young as 6 months of age, and both sexes with a full mutation were delayed on all developmental domains by their second birthday. Boys with a full mutation continued to gain skills over early childhood at around half the rate of their typically developing peers; girls with a full mutation showed growth at around three-quarters of the rate of their typically developing peers. Although children with a premutation were mostly typical in their developmental profiles and trajectories, mild but significant delays in fine motor skills by 18 months were detected. CONCLUSIONS: Children with the FMR1 gene full mutation demonstrate significant developmental challenges within the first 2 years of life, suggesting that earlier identification is needed to facilitate earlier implementation of interventions and therapeutics to maximize effectiveness.

Longitudinal identification of clinically distinct neurophenotypes in young children with fragile X syndrome.

Fragile X syndrome (FXS), due to mutations of the FMR1 gene, is the most common known inherited cause of developmental disability. The cognitive, behavioral, and neurological phenotypes observed in affected individuals can vary considerably, making it difficult to predict outcomes and determine the need for interventions. We sought to examine early structural brain growth as a potential marker for identification of clinically meaningful subgroups. Participants included 42 very young boys with FXS who completed a T1-weighted anatomical MRI and cognitive/behavioral assessment at two longitudinal time points, with mean ages of 2.89 y and 4.91 y. Topological data analysis (TDA), an unsupervised approach to multivariate pattern analysis, was applied to the longitudinal anatomical data to identify coherent but heretofore unknown subgroups. TDA revealed two large subgroups within the study population based solely on longitudinal MRI data. Post hoc comparisons of cognition, adaptive functioning, and autism severity scores between these groups demonstrated that one group was consistently higher functioning on all measures at both time points, with pronounced and significant unidirectional differences (P < 0.05 for time point 1 and/or time point 2 for each measure). These results support the existence of two longitudinally defined, neuroanatomically distinct, and clinically relevant phenotypes among boys with FXS. If confirmed by additional analyses, such information may be used to predict outcomes and guide design of targeted therapies. Furthermore, TDA of longitudinal anatomical MRI data may represent a useful method for reliably and objectively defining subtypes within other neuropsychiatric disorders.

Fragile X syndrome.

Fragile X syndrome (FXS) is the leading inherited form of intellectual disability and autism spectrum disorder, and patients can present with severe behavioural alterations, including hyperactivity, impulsivity and anxiety, in addition to poor language development and seizures. FXS is a trinucleotide repeat disorder, in which >200 repeats of the CGG motif in FMR1 leads to silencing of the gene and the consequent loss of its product, fragile X mental retardation 1 protein (FMRP). FMRP has a central role in gene expression and regulates the translation of potentially hundreds of mRNAs, many of which are involved in the development and maintenance of neuronal synaptic connections. Indeed, disturbances in neuroplasticity is a key finding in FXS animal models, and an imbalance in inhibitory and excitatory neuronal circuits is believed to underlie many of the clinical manifestations of this disorder. Our knowledge of the proteins that are regulated by FMRP is rapidly growing, and this has led to the identification of multiple targets for therapeutic intervention, some of which have already moved into clinical trials or clinical practice.

Functional neuroimaging of high-risk 6-month-old infants predicts a diagnosis of autism at 24 months of age.

Autism spectrum disorder (ASD) is a neurodevelopmental disorder characterized by social deficits and repetitive behaviors that typically emerge by 24 months of age. To develop effective early interventions that can potentially ameliorate the defining deficits of ASD and improve long-term outcomes, early detection is essential. Using prospective neuroimaging of 59 6-month-old infants with a high familial risk for ASD, we show that functional connectivity magnetic resonance imaging correctly identified which individual children would receive a research clinical best-estimate diagnosis of ASD at 24 months of age. Functional brain connections were defined in 6-month-old infants that correlated with 24-month scores on measures of social behavior, language, motor development, and repetitive behavior, which are all features common to the diagnosis of ASD. A fully cross-validated machine learning algorithm applied at age 6 months had a positive predictive value of 100% [95% confidence interval (CI), 62.9 to 100], correctly predicting 9 of 11 infants who received a diagnosis of ASD at 24 months (sensitivity, 81.8%; 95% CI, 47.8 to 96.8). All 48 6-month-old infants who were not diagnosed with ASD were correctly classified [specificity, 100% (95% CI, 90.8 to 100); negative predictive value, 96.0% (95% CI, 85.1 to 99.3)]. These findings have clinical implications for early risk assessment and the feasibility of developing early preventative interventions for ASD.

Early brain development in infants at high risk for autism spectrum disorder.

Brain enlargement has been observed in children with autism spectrum disorder (ASD), but the timing of this phenomenon, and the relationship between ASD and the appearance of behavioural symptoms, are unknown. Retrospective head circumference and longitudinal brain volume studies of two-year olds followed up at four years of age have provided evidence that increased brain volume may emerge early in development. Studies of infants at high familial risk of autism can provide insight into the early development of autism and have shown that characteristic social deficits in ASD emerge during the latter part of the first and in the second year of life. These observations suggest that prospective brain-imaging studies of infants at high familial risk of ASD might identify early postnatal changes in brain volume that occur before an ASD diagnosis. In this prospective neuroimaging study of 106 infants at high familial risk of ASD and 42 low-risk infants, we show that hyperexpansion of the cortical surface area between 6 and 12 months of age precedes brain volume overgrowth observed between 12 and 24 months in 15 high-risk infants who were diagnosed with autism at 24 months. Brain volume overgrowth was linked to the emergence and severity of autistic social deficits. A deep-learning algorithm that primarily uses surface area information from magnetic resonance imaging of the brain of 6-12-month-old individuals predicted the diagnosis of autism in individual high-risk children at 24 months (with a positive predictive value of 81% and a sensitivity of 88%). These findings demonstrate that early brain changes occur during the period in which autistic behaviours are first emerging.

Neural Connectivity Evidence for a Categorical-Dimensional Hybrid Model of Autism Spectrum Disorder.

BACKGROUND: Autism spectrum disorder (ASD) encompasses a complex manifestation of symptoms that include deficits in social interaction and repetitive or stereotyped interests and behaviors. In keeping with the increasing recognition of the dimensional characteristics of ASD symptoms and the categorical nature of a diagnosis, we sought to delineate the neural mechanisms of ASD symptoms based on the functional connectivity of four known neural networks (i.e., default mode network, dorsal attention network, salience network, and executive control network). METHODS: We leveraged an open data resource (Autism Brain Imaging Data Exchange) providing resting-state functional magnetic resonance imaging data sets from 90 boys with ASD and 95 typically developing boys. This data set also included the Social Responsiveness Scale as a dimensional measure of ASD traits. Seed-based functional connectivity was paired with linear regression to identify functional connectivity abnormalities associated with categorical effects of ASD diagnosis, dimensional effects of ASD-like behaviors, and their interaction. RESULTS: Our results revealed the existence of dimensional mechanisms of ASD uniquely affecting each network based on the presence of connectivity-behavioral relationships; these were independent of diagnostic category. However, we also found evidence of categorical differences (i.e., diagnostic group differences) in connectivity strength for each network as well as categorical differences in connectivity-behavioral relationships (i.e., diagnosis-by-behavior interactions), supporting the coexistence of categorical mechanisms of ASD. CONCLUSIONS: Our findings support a hybrid model for ASD characterization that includes a combination of categorical and dimensional brain mechanisms and provide a novel understanding of the neural underpinnings of ASD.

Longitudinal profiles of adaptive behavior in fragile X syndrome.

OBJECTIVE: To examine longitudinally the adaptive behavior patterns in fragile X syndrome. METHOD: Caregivers of 275 children and adolescents with fragile X syndrome and 225 typically developing children and adolescents (2-18 years) were interviewed with the Vineland Adaptive Behavior Scales every 2 to 4 years as part of a prospective longitudinal study. RESULTS: Standard scores of adaptive behavior in people with fragile X syndrome are marked by a significant decline over time in all domains for males and in communication for females. Socialization skills are a relative strength as compared with the other domains for males with fragile X syndrome. Females with fragile X syndrome did not show a discernible pattern of developmental strengths and weaknesses. CONCLUSIONS: This is the first large-scale longitudinal study to show that the acquisition of adaptive behavior slows as individuals with fragile X syndrome age. It is imperative to ensure that assessments of adaptive behavior skills are part of intervention programs focusing on childhood and adolescence in this condition.

Trajectories of early brain volume development in fragile X syndrome and autism.

OBJECTIVE: To examine patterns of early brain growth in young children with fragile X syndrome (FXS) compared with a comparison group (controls) and a group with idiopathic autism. METHOD: The study included 53 boys 18 to 42 months of age with FXS, 68 boys with idiopathic autism (autism spectrum disorder), and a comparison group of 50 typically developing and developmentally delayed controls. Structural brain volumes were examined using magnetic resonance imaging across two time points, at 2 to 3 and again at 4 to 5 years of age, and total brain volumes and regional (lobar) tissue volumes were examined. In addition, a selected group of subcortical structures implicated in the behavioral features of FXS (e.g., basal ganglia, hippocampus, amygdala) was studied. RESULTS: Children with FXS had larger global brain volumes compared with controls but were not different than children with idiopathic autism, and the rate of brain growth from 2 to 5 years of age paralleled that seen in controls. In contrast to children with idiopathic autism who had generalized cortical lobe enlargement, children with FXS showed specific enlargement in the temporal lobe white matter, cerebellar gray matter, and caudate nucleus, but a significantly smaller amygdala. CONCLUSIONS: This structural longitudinal magnetic resonance imaging study of preschoolers with FXS observed generalized brain overgrowth in children with FXS compared with controls, evident at age 2 and maintained across ages 4 to 5. In addition, different patterns of brain growth that distinguished boys with FXS from boys with idiopathic autism were found.

Brain volume findings in 6-month-old infants at high familial 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 significant group differences for head circumference, brain volume, or abnormalities in radiologic findings from a group of 6-month-old infants at high risk for autism. The authors are unable to conclude that these abnormalities are not present in infants who later go on to receive a diagnosis of autism; rather, abnormalities were not detected in a large group at high familial risk. Future longitudinal studies of the IBIS study group will examine whether brain volume differs in infants who go on to develop autism.

Automatic corpus callosum segmentation using a deformable active Fourier contour model.

The corpus callosum (CC) is a structure of interest in many neuroimaging studies of neuro-developmental pathology such as autism. It plays an integral role in relaying sensory, motor and cognitive information from homologous regions in both hemispheres. We have developed a framework that allows automatic segmentation of the corpus callosum and its lobar subdivisions. Our approach employs constrained elastic deformation of flexible Fourier contour model, and is an extension of Szekely's 2D Fourier descriptor based Active Shape Model. The shape and appearance model, derived from a large mixed population of 150+ subjects, is described with complex Fourier descriptors in a principal component shape space. Using MNI space aligned T1w MRI data, the CC segmentation is initialized on the mid-sagittal plane using the tissue segmentation. A multi-step optimization strategy, with two constrained steps and a final unconstrained step, is then applied. If needed, interactive segmentation can be performed via contour repulsion points. Lobar connectivity based parcellation of the corpus callosum can finally be computed via the use of a probabilistic CC subdivision model. Our analysis framework has been integrated in an open-source, end-to-end application called CCSeg both with a command line and Qt-based graphical user interface (available on NITRC). A study has been performed to quantify the reliability of the semi-automatic segmentation on a small pediatric dataset. Using 5 subjects randomly segmented 3 times by two experts, the intra-class correlation coefficient showed a superb reliability (0.99). CCSeg is currently applied to a large longitudinal pediatric study of brain development in autism.

Early brain overgrowth in autism associated with an increase in cortical surface area before age 2 years.

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.

Multi-object analysis of volume, pose, and shape using statistical discrimination.

One goal of statistical shape analysis is the discrimination between two populations of objects. Whereas traditional shape analysis was mostly concerned with single objects, analysis of multi-object complexes presents new challenges related to alignment and pose. In this paper, we present a methodology for discriminant analysis of multiple objects represented by sampled medial manifolds. Non-euclidean metrics that describe geodesic distances between sets of sampled representations are used for alignment and discrimination. Our choice of discriminant method is the distance-weighted discriminant because of its generalization ability in high-dimensional, low sample size settings. Using an unbiased, soft discrimination score, we associate a statistical hypothesis test with the discrimination results. We explore the effectiveness of different choices of features as input to the discriminant analysis, using measures like volume, pose, shape, and the combination of pose and shape. Our method is applied to a longitudinal pediatric autism study with 10 subcortical brain structures in a population of 70 subjects. It is shown that the choices of type of global alignment and of intrinsic versus extrinsic shape features, the latter being sensitive to relative pose, are crucial factors for group discrimination and also for explaining the nature of shape change in terms of the application domain.

Teasing apart the heterogeneity of autism: Same behavior, different brains in toddlers with fragile X syndrome and autism.

To examine brain volumes in substructures associated with the behavioral features of children with FXS compared to children with idiopathic autism and controls. A cross-sectional study of brain substructures was conducted at the first time-point as part of an ongoing longitudinal MRI study of brain development in FXS. The study included 52 boys between 18-42 months of age with FXS and 118 comparison children (boys with autism-non FXS, developmental-delay, and typical development). Children with FXS and autistic disorder had substantially enlarged caudate volume and smaller amygdala volume; whereas those children with autistic disorder without FXS (i.e., idiopathic autism) had only modest enlargement in their caudate nucleus volumes but more robust enlargement of their amygdala volumes. Although we observed this double dissociation among selected brain volumes, no significant differences in severity of autistic behavior between these groups were observed. This study offers a unique examination of early brain development in two disorders, FXS and idiopathic autism, with overlapping behavioral features, but two distinct patterns of brain morphology. We observed that despite almost a third of our FXS sample meeting criteria for autism, the profile of brain volume differences for children with FXS and autism differed from those with idiopathic autism. These findings underscore the importance of addressing heterogeneity in studies of autistic behavior.

Particle-based shape analysis of multi-object complexes.

This paper presents a new method for optimizing surface point correspondences for shape modeling of multiobject anatomy, or shape complexes. The proposed method is novel in that it optimizes correspondence positions in the full, joint shape space of the object complex. Researchers have previously only considered the correspondence problem separately for each structure, thus ignoring the interstructural shape correlations that are increasingly of interest in many clinical contexts, such as the study of the effects of disease on groups of neuroanatomical structures. The proposed method uses a nonparametric, dynamic particle system to simultaneously sample object surfaces and optimize correspondence point positions. This paper also suggests a principled approach to hypothesis testing using the Hotelling T2 test in the PCA space of the correspondence model, with a simulation-based choice of the number of PCA modes. We also consider statistical analysis of object poses. The modeling and analysis methods are illustrated on brain structure complexes from an ongoing clinical study of pediatric autism.

Morphometric spatial patterns differentiating boys with fragile X syndrome, typically developing boys, and developmentally delayed boys aged 1 to 3 years.

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.

User-guided 3D active contour segmentation of anatomical structures: significantly improved efficiency and reliability.

Active contour segmentation and its robust implementation using level set methods are well-established theoretical approaches that have been studied thoroughly in the image analysis literature. Despite the existence of these powerful segmentation methods, the needs of clinical research continue to be fulfilled, to a large extent, using slice-by-slice manual tracing. To bridge the gap between methodological advances and clinical routine, we developed an open source application called ITK-SNAP, which is intended to make level set segmentation easily accessible to a wide range of users, including those with little or no mathematical expertise. This paper describes the methods and software engineering philosophy behind this new tool and provides the results of validation experiments performed in the context of an ongoing child autism neuroimaging study. The validation establishes SNAP intrarater and interrater reliability and overlap error statistics for the caudate nucleus and finds that SNAP is a highly reliable and efficient alternative to manual tracing. Analogous results for lateral ventricle segmentation are provided.

Cortical gray and white brain tissue volume in adolescents and adults with autism.

BACKGROUND: A number of studies have found brain enlargement in autism, but there is disagreement as to whether this enlargement is limited to early development or continues into adulthood. In this study, cortical gray and white tissue volumes were examined in a sample of adolescents and adults with autism who had demonstrated total brain enlargement in a previous magnetic resonance imaging (MRI) study. METHODS: An automated tissue segmentation program was applied to structural MRI scans to obtain volumes of gray, white, and cerebrospinal fluid (CSF) tissue on a sample of adolescent and adult males ages 13-29 with autism (n = 23) and controls (n = 15). Regional differences for brain lobes and brain hemispheres were also examined. RESULTS: Significant enlargement in gray matter volume was found for the individuals with autism, with a disproportionate increase in left-sided gray matter volume. Lobe volume enlargements were detected for frontal and temporal, but not parietal or occipital lobes, in the subjects with autism. Age and nonverbal IQ effects on tissue volume were also observed. CONCLUSIONS: These findings give evidence for left-lateralized gray tissue enlargement in adolescents and adults with autism, and demonstrate a regional pattern of cortical lobe volumes underlying this effect.

Magnetic resonance imaging and head circumference study of brain size in autism: birth through age 2 years.

CONTEXT: While the neuroanatomical basis of autism is not yet known, evidence suggests that brain enlargement may be characteristic of this disorder. Inferences about the timing of brain enlargement have recently come from studies of head circumference (HC). OBJECTIVES: To examine brain volume and HC in individuals with autism as compared with control individuals. DESIGN: A cross-sectional study of brain volume was conducted at the first time point in an ongoing longitudinal magnetic resonance imaging study of brain development in autism. Retrospective longitudinal HC measurements were gathered from medical records on a larger sample of individuals with autism and local control individuals. SETTING: Clinical research center. PARTICIPANTS: The magnetic resonance imaging study included 51 children with autism and 25 control children between 18 and 35 months of age (the latter included both developmentally delayed and typically developing children). Retrospective, longitudinal HC data were examined from birth to age 3 years in 113 children with autism and 189 local control children. MAIN OUTCOME MEASURES: Cerebral cortical (including cortical lobes) and cerebellar gray and white matter magnetic resonance imaging brain volumes as well as retrospective HC data from medical records were studied. RESULTS: Significant enlargement was detected in cerebral cortical volumes but not cerebellar volumes in individuals with autism. Enlargement was present in both white and gray matter, and it was generalized throughout the cerebral cortex. Head circumference appears normal at birth, with a significantly increased rate of HC growth appearing to begin around 12 months of age. CONCLUSIONS: Generalized enlargement of gray and white matter cerebral volumes, but not cerebellar volumes, are present at 2 years of age in autism. Indirect evidence suggests that this increased rate of brain growth in autism may have its onset postnatally in the latter part of the first year of life.