Increased rate of amygdala growth in children aged 2 to 4 years with autism spectrum disorders: a longitudinal study

Autism spectrum disorder risk prediction: A systematic review of behavioral and neural investigations

A reliable diagnosis of autism spectrum disorder (ASD) is difficult to make until after toddlerhood. Detection in an earlier age enables early intervention, which is typically more effective. Recent studies of the development of brain and behavior in infants and toddlers have provided important insights in the diagnosis of autism. This extensive review focuses on published studies of predicting the diagnosis of autism during infancy and toddlerhood younger than 3 years using behavioral and neuroimaging approaches. After screening a total of 782 papers, 17 neuroimaging and 43 behavioral studies were reviewed. The features for prediction consist of behavioral measures using screening tools, observational and experimental methods, brain volumetric measures, and neural functional activation and connectivity patterns. The classification approaches include logistic regression, linear discriminant function, decision trees, support vector machine, and deep learning based methods. Prediction performance has large variance across different studies. For behavioral studies, the sensitivity varies from 20% to 100%, and specificity ranges from 48% to 100%. The accuracy rates range from 61% to 94% in neuroimaging studies. Possible factors contributing to this inconsistency may be partially due to the heterogeneity of ASD, different targeted populations (i.e., high-risk group for ASD and general population), age when the features were collected, and validation procedures. The translation to clinical practice requires extensive further research including external validation with large sample size and optimized feature selection. The use of multi-modal features, e.g., combination of neuroimaging and behavior, is worth further investigation to improve the prediction accuracy.

Sex Differences in the Amygdala Resting-State Connectome of Children With Autism Spectrum Disorder

BACKGROUND

Multifactorial liability models predict greater dissimilarity in the neural phenotype of autism spectrum disorder (ASD) in female individuals than in male individuals, while gender incoherence and extreme male brain models predict attenuated sex differences in ASD. The amygdala is an informative target to explore these models because it is implicated in both the neurobiology of ASD and sex differences in typical development.

METHODS

This study investigated amygdala resting-state functional connectivity in a cohort of 116 children with ASD (36 female) and 58 typically developing children (27 female) 2 to 7 years of age during natural sleep. First, multivariate distance matrix regression assessed global sex and diagnostic differences across the amygdala connectome. Second, univariate general linear models identified regions with mean connectivity differences.

RESULTS

Multivariate distance matrix regression revealed greater differences between typically developing children and those with ASD in females than in males, consistent with multifactorial liability models, and attenuated sex differences in the left amygdala connectome of children with ASD in a pattern consistent with the gender incoherence model. Univariate analysis identified similar sex differences in dorsomedial and ventral prefrontal cortices, lingual gyrus, and posterior cingulate cortex, but also noted that lower amygdala connectivity with superior temporal sulcus is observed across sexes.

CONCLUSIONS

This study provides evidence that compared with sex-matched control subjects, ASD manifests differently in the brain at the time of diagnosis and prior to the influence of compensatory mechanisms in male and female children, consistent with multifactorial liability models, and that ASD is associated with reduced sex differences in a pattern consistent with gender incoherence models.

Increased hippocampal shape asymmetry and volumetric ventricular asymmetry in autism spectrum disorder

•

Found increased subcortical asymmetry associated with autism.

•

Utilized a new measure of shape asymmetry for analysis of structural differences.

•

Observed significantly increased shape asymmetry of the hippocampus.

•

Observed significantly increased volumetric asymmetry in the lateral ventricles.

•

Focalized abnormalities may result in detectable shape (but not volume) differences.

Autism spectrum disorder (ASD) is a prevalent and fast-growing pervasive neurodevelopmental disorder worldwide. Despite the increasing prevalence of ASD and the breadth of research conducted on the disorder, a conclusive etiology has yet to be established and controversy still exists surrounding the anatomical abnormalities in ASD. In particular, structural asymmetries have seldom been investigated in ASD, especially in subcortical regions. Additionally, the majority of studies for identifying structural biomarkers associated with ASD have focused on small sample sizes. Therefore, the present study utilizes a large-scale, multi-site database to investigate asymmetries in the amygdala, hippocampus, and lateral ventricles, given the potential involvement of these regions in ASD. Contrary to prior work, we are not only computing volumetric asymmetries, but also shape asymmetries, using a new measure of asymmetry based on spectral shape descriptors. This measure represents the magnitude of the asymmetry and therefore captures both directional and undirectional asymmetry. The asymmetry analysis is conducted on 437 individuals with ASD and 511 healthy controls using T1-weighted MRI scans from the Autism Brain Imaging Data Exchange (ABIDE) database. Results reveal significant asymmetries in the hippocampus and the ventricles, but not in the amygdala, in individuals with ASD. We observe a significant increase in shape asymmetry in the hippocampus, as well as increased volumetric asymmetry in the lateral ventricles in individuals with ASD. Asymmetries in these regions have not previously been reported, likely due to the different characterization of neuroanatomical asymmetry and smaller sample sizes used in previous studies. Given that these results were demonstrated in a large cohort, such asymmetries may be worthy of consideration in the development of neurodiagnostic classification tools for ASD.

Identification, Evaluation, and Management of Children With Autism Spectrum Disorder

Autism spectrum disorder (ASD) is a common neurodevelopmental disorder with reported prevalence in the United States of 1 in 59 children (approximately 1.7%). Core deficits are identified in 2 domains: social communication/interaction and restrictive, repetitive patterns of behavior. Children and youth with ASD have service needs in behavioral, educational, health, leisure, family support, and other areas. Standardized screening for ASD at 18 and 24 months of age with ongoing developmental surveillance continues to be recommended in primary care (although it may be performed in other settings), because ASD is common, can be diagnosed as young as 18 months of age, and has evidenced-based interventions that may improve function. More accurate and culturally sensitive screening approaches are needed. Primary care providers should be familiar with the diagnostic criteria for ASD, appropriate etiologic evaluation, and co-occurring medical and behavioral conditions (such as disorders of sleep and feeding, gastrointestinal tract symptoms, obesity, seizures, attention-deficit/hyperactivity disorder, anxiety, and wandering) that affect the child's function and quality of life. There is an increasing evidence base to support behavioral and other interventions to address specific skills and symptoms. Shared decision making calls for collaboration with families in evaluation and choice of interventions.  This single clinical report updates the 2007 American Academy of Pediatrics clinical reports on the evaluation and treatment of ASD in one publication with an online table of contents and section view available through the American Academy of Pediatrics Gateway to help the reader identify topic areas within the report.

Circuits for social learning: A unified model and application to Autism Spectrum Disorder

Early life social experiences shape neural pathways in infants to develop lifelong social skills. This review presents the first unified circuit-based model of social learning that can be applied to early life social development, drawing together unique human developmental milestones, sensitive learning periods, and behavioral and neural scaffolds. Circuit domains for social learning are identified governing Activation, Integration, Discrimination, Response and Reward (AIDRR) to sculpt and drive human social learning. This unified model can be used to identify social delays earlier in development. We propose social impairments observed in Autism Spectrum Disorder are underpinned by early mistimed sensitive periods in brain development and alterations in amygdala development to disrupt the AIDRR circuits. This model directs how interventions can target neural circuits for social development and be applied early in life. To illustrate, the role of oxytocin and its use as an intervention is explored. The AIDRR model shifts focus away from delivering broad treatments based only on diagnostic classifications, to specifying and targeting the relevant circuits, at the right time of development, to optimize social learning.

Longitudinal EEG power in the first postnatal year differentiates autism outcomes

An aim of autism spectrum disorder (ASD) research is to identify early biomarkers that inform ASD pathophysiology and expedite detection. Brain oscillations captured in electroencephalography (EEG) are thought to be disrupted as core ASD pathophysiology. We leverage longitudinal EEG power measurements from 3 to 36 months of age in infants at low- and high-risk for ASD to test how and when power distinguishes ASD risk and diagnosis by age 3-years. Power trajectories across the first year, second year, or first three years postnatally were submitted to data-driven modeling to differentiate ASD outcomes. Power dynamics during the first postnatal year best differentiate ASD diagnoses. Delta and gamma frequency power trajectories consistently distinguish infants with ASD diagnoses from others. There is also a developmental shift across timescales towards including higher-frequency power to differentiate outcomes. These findings reveal the importance of developmental timing and trajectory in understanding pathophysiology and classifying ASD outcomes.

Brain oscillations may be disrupted in children with autism spectrum disorder. The authors performed a longitudinal study of electroencephalography recordings and found that EEG recordings from the first year after birth can distinguish healthy children from children with autism spectrum disorder.

A network of networks approach for modeling interconnected brain tissue-specific networks

Motivation

Recent sequence-based analyses have identified a lot of gene variants that may contribute to neurogenetic disorders such as autism spectrum disorder and schizophrenia. Several state-of-the-art network-based analyses have been proposed for mechanical understanding of genetic variants in neurogenetic disorders. However, these methods were mainly designed for modeling and analyzing single networks that do not interact with or depend on other networks, and thus cannot capture the properties between interdependent systems in brain-specific tissues, circuits and regions which are connected each other and affect behavior and cognitive processes.

Results

We introduce a novel and efficient framework, called a ‘Network of Networks’ approach, to infer the interconnectivity structure between multiple networks where the response and the predictor variables are topological information matrices of given networks. We also propose Graph-Oriented SParsE Learning, a new sparse structural learning algorithm for network data to identify a subset of the topological information matrices of the predictors related to the response. We demonstrate on simulated data that propose Graph-Oriented SParsE Learning outperforms existing kernel-based algorithms in terms of F-measure. On real data from human brain region-specific functional networks associated with the autism risk genes, we show that the ‘Network of Networks’ model provides insights on the autism-associated interconnectivity structure between functional interaction networks and a comprehensive understanding of the genetic basis of autism across diverse regions of the brain.

Availability and implementation

Our software is available from https://github.com/infinite-point/GOSPEL.

Supplementary information

Supplementary data are available at Bioinformatics online.

[Abnormal brain structure in preschool and school-aged children with autism spectrum disorder]

OBJECTIVE

To investigate the prevalence and type of abnormal brain structure in preschool and school-aged children with autism spectrum disorder (ASD).

METHODS

A total of 74 252 preschool and school-aged children aged 3-12 years in Shanghai were enrolled as subjects. A questionnaire survey was performed to collect basic information, and their parents and teachers completed the Social Communication Questionnaire (SCQ) based on the children's conditions. ASD was diagnosed by specialist physicians according to the DSM-5 criteria. Brain magnetic resonance imaging (MRI) was performed according to their parents' desires.

RESULTS

The overall prevalence rate of ASD was 2.59‰ (192/74 252) in the preschool and school-aged children. Brain MRI data were collected from 73 children with ASD and 185 healthy children. Among the 73 children with ASD, 40 (55%) had abnormal brain structure, and the most common types were unilateral or bilateral ventriculomegaly in 32 children (80%) and unilateral or bilateral deep frontotemporal sulci in 12 children (30%). Children with ASD showed lower white matter signal in bilateral ventricular and unilateral or bilateral deep frontotemporal sulci, compared to their normal peers (P<0.05).

CONCLUSIONS

There is a high prevalence rate of abnormal brain structure in preschool and school-aged children with ASD, with major types of unilateral or bilateral ventriculomegaly and unilateral or bilateral deep frontotemporal sulci. It is speculated that abnormal brain structure might be associated with the pathogenesis of ASD, and further studies are needed to clarify the association between abnormal brain structure and symptoms in children with ASD.

Differential Altered Auditory Event-Related Potential Responses in Young Boys on the Autism Spectrum With and Without Disproportionate Megalencephaly

Autism spectrum disorder (ASD), characterized by impairments in social communication and repetitive behaviors, often includes altered responses to sensory inputs as part of its phenotype. The neurobiological basis for altered sensory processing is not well understood. The UC Davis Medical Investigation of Neurodevelopmental Disorders Institute Autism Phenome Project is a longitudinal, multidisciplinary study of young children with ASD and age-matched typically developing (TD) controls. Previous analyses of the magnetic resonance imaging data from this cohort have shown that ∼15% of boys with ASD have disproportionate megalencephaly (DM) or brain size to height ratio, that is 1.5 standard deviations above the TD mean. Here, we investigated electrophysiological responses to auditory stimuli of increasing intensity (50-80 dB) in young toddlers (27-48 months old). Analyses included data from 36 age-matched boys, of which 24 were diagnosed with ASD (12 with and 12 without DM; ASD-DM and ASD-N) and 12 TD controls. We found that the two ASD subgroups differed in their electrophysiological response patterns to sounds of increasing intensity. At early latencies (55-115 ms), ASD-N does not show a loudness-dependent response like TD and ASD-DM, but tends to group intensities by soft vs. loud sounds, suggesting differences in sensory sensitivity in this group. At later latencies (145-195 ms), only the ASD-DM group shows significantly higher amplitudes for loud sounds. Because no similar effects were found in ASD-N and TD groups, this may be related to their altered neuroanatomy. These results contribute to the effort to delineate ASD subgroups and further characterize physiological responses associated with observable phenotypes. Autism Res 2019, 12: 1236-1250. © 2019 International Society for Autism Research, Wiley Periodicals, Inc. LAY SUMMARY: Approximately 15% of boys with ASD have much bigger brains when compared to individuals with typical development. By recording brain waves (electroencephalography) we compared how autistic children, with or without big brains, react to sounds compared to typically developing controls. We found that brain responses in the big-brained group are different from the two other groups, suggesting that they represent a specific autism subgroup.

[Abnormal brain structure in preschool and school-aged children with autism spectrum disorder]

OBJECTIVE

To investigate the prevalence and type of abnormal brain structure in preschool and school-aged children with autism spectrum disorder (ASD).

METHODS

A total of 74 252 preschool and school-aged children aged 3-12 years in Shanghai were enrolled as subjects. A questionnaire survey was performed to collect basic information, and their parents and teachers completed the Social Communication Questionnaire (SCQ) based on the children's conditions. ASD was diagnosed by specialist physicians according to the DSM-5 criteria. Brain magnetic resonance imaging (MRI) was performed according to their parents' desires.

RESULTS

The overall prevalence rate of ASD was 2.59‰ (192/74 252) in the preschool and school-aged children. Brain MRI data were collected from 73 children with ASD and 185 healthy children. Among the 73 children with ASD, 40 (55%) had abnormal brain structure, and the most common types were unilateral or bilateral ventriculomegaly in 32 children (80%) and unilateral or bilateral deep frontotemporal sulci in 12 children (30%). Children with ASD showed lower white matter signal in bilateral ventricular and unilateral or bilateral deep frontotemporal sulci, compared to their normal peers (P<0.05).

CONCLUSIONS

There is a high prevalence rate of abnormal brain structure in preschool and school-aged children with ASD, with major types of unilateral or bilateral ventriculomegaly and unilateral or bilateral deep frontotemporal sulci. It is speculated that abnormal brain structure might be associated with the pathogenesis of ASD, and further studies are needed to clarify the association between abnormal brain structure and symptoms in children with ASD.

Amygdala growth from youth to adulthood in the macaque monkey

Emerging evidence suggests that the human amygdala undergoes extensive growth through adolescence, coinciding with the acquisition of complex socioemotional learning. Our objective was to longitudinally map volumetric growth of the nonhuman primate amygdala in a controlled, naturalistic social environment from birth to adulthood. Magnetic resonance images were collected at five time-points in 24 male and female rhesus macaques from 6 months to adulthood at 5 years. We then compared amygdala growth to other brain regions, including newly collected isocortical gray and white matter volumes, and previously published data on the same cohort. We found that amygdala volume increases by nearly 50% from age 6 months to 5 years. This dramatic growth is in contrast to overall brain and hippocampal volume, which peak near 3 years, white matter, which slows from 3 to 5 years, and isocortical gray, which has a net decrease. Similar to isocortical gray and hippocampal volumes, amygdala volume is ~8% larger in males than females. Rate of growth does not differ by sex. Although the underlying neurobiological substrate for protracted amygdala growth into adulthood is unclear, we propose it may be due in part to the unique cellular development of immature neurons in paralaminar nucleus that mature in size and connectivity with age. Prolonged amygdala maturation raises the possibility that environmental and genetic perturbations that disrupt this trajectory may contribute to the emergence of psychiatric disorders, such as anxiety, depression, schizophrenia, and autism; all in which the amygdala is strongly implicated.

Four Social Brain Regions, Their Dysfunctions, and Sequelae, Extensively Explain Autism Spectrum Disorder Symptomatology

Autism spectrum disorder (ASD) is a challenging neurodevelopmental disorder with symptoms in social, language, sensory, motor, cognitive, emotional, repetitive behavior, and self-sufficient living domains. The important research question examined is the elucidation of the pathogenic neurocircuitry that underlies ASD symptomatology in all its richness and heterogeneity. The presented model builds on earlier social brain research, and hypothesizes that four social brain regions largely drive ASD symptomatology: amygdala, orbitofrontal cortex (OFC), temporoparietal cortex (TPC), and insula. The amygdala's contributions to ASD largely derive from its major involvement in fine-grained intangible knowledge representations and high-level guidance of gaze. In addition, disrupted brain regions can drive disturbance of strongly interconnected brain regions to produce further symptoms. These and related effects are proposed to underlie abnormalities of the visual cortex, inferior frontal gyrus (IFG), caudate nucleus, and hippocampus as well as associated symptoms. The model is supported by neuroimaging, neuropsychological, neuroanatomical, cellular, physiological, and behavioral evidence. Collectively, the model proposes a novel, parsimonious, and empirically testable account of the pathogenic neurocircuitry of ASD, an extensive account of its symptomatology, a novel physiological biomarker with potential for earlier diagnosis, and novel experiments to further elucidate the mechanisms of brain abnormalities and symptomatology in ASD.

Alterations in volumes and MRI features of amygdala in Chinese autistic preschoolers associated with social and behavioral deficits

To examine the amygdala volume in 2–5-year-old preschool children with autism and explore the relationship between amygdala volumes based on MRI findings and clinical features. A total of 39 cases with clinically diagnosed autism were collected. The oblique coronal T1 weighted image (T1WI) sequence was used to measure the volume of amygdala and the MRI signals were measured and analyzed. The data were compared to that of 24 age-matched healthy children and correlated to the clinical manifestations. The autism and the control groups were subject to brain scanning in 1 week after Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition (DSM-IV) review. The 39 cases, diagnosed with autism, were associated with social and behavioral deficits through clinical observation, physical and neurological examination, and assessments according to DSM IV, and the range of ABC scores in the autism group was 47–124, with an average score of 84.7 ± 24.1. Abnormal MRI signals were found in 19/78 (24.4%) amygdala in the autism group, the amygdala lesions showed punctuate or flaky low signal, slightly low signal, low to iso-signal, slightly high signal, or iso to high-signal intensity on T1 weighted three-dimendional fast low angle shot(T1FL3D) images. The right amygdala volume average was 1.088 ± 0.38 cm³, while that of the left amygdala was 1.04 ± 0.41 cm³, without any statistically significant difference (t = 0.533, p = 0.596) in the autism group. Among the 24 cases in the control group, the right amygdala volume average was 0.754 ± 0.194 cm³, while that of the left amygdala was 0.666 ± 0.252 cm³; the autism group had a significantly larger right and left amygdala volumes as compared to the age-matched typically developing group with a significant positive correlation between age and right amygdala volume (r = 0.406, p = 0.01). The preschool children with autism had significantly larger bilateral amygdala volumes as compared to age-matched typically developing children, the amygdala lesions may show abnormal signal. A relationship between age and right amygdala volume in the preschool children with autism was established.

A perspective on pre-eclampsia and neurodevelopmental outcomes in the offspring: Does maternal inflammation play a role?

Pre-eclampsia is a leading cause of maternal death and maternal and perinatal morbidity. Whilst the clinical manifestations of pre-eclampsia often occur in late pregnancy, the molecular events leading into the onset of this disease are thought to originate in early pregnancy and result in insufficient placentation. Although the causative molecular basis of pre-eclampsia remains poorly understood, maternal inflammation is recognised as a core clinical feature. While the adverse effects of pre-eclampsia on maternal and fetal health in pregnancy is well-recognised, the long-term impact of pre-eclampsia exposure on the risk of autism spectrum disorder (ASD) in exposed offspring is a topic of on-going debate. In particular, a recent systematic review has reported an association between exposure to pre-eclampsia and increased risk of ASD, however the molecular basis of this association is unknown. Here we review recent evidence for; 1) maternal inflammation in pre-eclampsia; 2) epidemiological evidence for alterations in neurodevelopmental outcomes in offspring exposed to pre-eclampsia; 3) long-term changes in the brains of offspring exposed to pre-eclampsia; and 4) how maternal inflammation may lead to altered neurodevelopmental outcomes in pre-eclampsia exposed offspring. Finally, we discuss the implications of this for the development of future studies in this field.

Atypical Functional Connectivity of Amygdala Related to Reduced Symptom Severity in Children With Autism

OBJECTIVE

Converging evidence indicates that brain abnormalities in autism spectrum disorders (ASDs) involve atypical network connectivity. Given the central role of social deficits in the ASD phenotype, this investigation examined functional connectivity of the amygdala-a brain structure critically involved in processing of social information-in children and adolescents with ASDs, as well as age-dependent changes and links with clinical symptoms.

METHOD

Resting-state functional magnetic resonance imaging (rs-fMRI) data from 55 participants with ASDs and 50 typically developing (TD) controls, aged 7 to 17 years, were included. Groups were matched for age, gender, IQ, and head motion. Functional connectivity MRI (fcMRI) analysis was applied to examine intrinsic functional connectivity (iFC) of the amygdala, including cross-sectional tests of age-related changes.

RESULTS

Direct between-group comparisons revealed reduced functional connectivity between bilateral amygdalae and left inferior occipital cortex, accompanied by greater connectivity between right amygdala and right sensorimotor cortex in the ASD group. This atypical pattern of amygdala connectivity was associated with decreased symptom severity and better overall functioning, as specifically seen in an ASD subgroup with the most atypical amygdala iFC but the least impaired social functioning. Age-related strengthening of amygdala-prefrontal connectivity, as observed in the TD group, was not detected in children with ASDs.

CONCLUSION

Findings support aberrant network sculpting in ASDs, specifically atypical integration between amygdala and primary sensorimotor circuits. Paradoxical links between atypical iFC and behavioral measures suggest that abnormal amygdala functional connections may be compensatory in some individuals with ASDs.

Carriage of Supernumerary Sex Chromosomes Decreases the Volume and Alters the Shape of Limbic Structures

Sex chromosome aneuploidy (SCA) increases risk for several psychiatric disorders associated with the limbic system, including mood and autism spectrum disorders. Thus, SCA offers a genetics-first model for understanding the biological basis of psychopathology. Additionally, the sex-biased prevalence of many psychiatric disorders could potentially reflect sex chromosome dosage effects on brain development. To clarify how limbic anatomy varies across sex and sex chromosome complement, we characterized amygdala and hippocampus structure in a uniquely large sample of patients carrying supernumerary sex chromosomes (n = 132) and typically developing controls (n = 166). After adjustment for sex-differences in brain size, karyotypically normal males (XY) and females (XX) did not differ in volume or shape of either structure. In contrast, all SCAs were associated with lowered amygdala volume relative to gonadally-matched controls. This effect was robust to three different methods for total brain volume adjustment, including an allometric analysis that derived normative scaling rules for these structures in a separate, typically developing population (n = 79). Hippocampal volume was insensitive to SCA after adjustment for total brain volume. However, surface-based analysis revealed that SCA, regardless of specific karyotype, was consistently associated with a spatially specific pattern of shape change in both amygdala and hippocampus. In particular, SCA was accompanied by contraction around the basomedial nucleus of the amygdala and an area crossing the hippocampal tail. These results demonstrate the power of SCA as a model to understand how copy number variation can precipitate changes in brain systems relevant to psychiatric disease.

Amygdala and oxytocin functioning as keys to understanding and treating autism: Commentary on an RDoC based approach

The recent review by Hennessey, Andari and Rainnie (2018) utilizes the proposed Research Domain Criteria (RDoC) to classify amygdala functions and relate them to autism symptomatology. This approach has the potential to challenge the overarching autism diagnosis by furthering our knowledge of the mechanisms giving rise to autism psychopathology and generate novel treatment options. The purpose of this commentary is to provide additional information on a number of points raised in the review. Thus, (1) we discuss the issue of amygdala and brain overgrowth in children with autism and relate it to developmental oxytocin changes, (2) examine potential mechanisms that underlie amygdala overgrowth and dysfunction of the oxytocin system, (3) zoom in on the sexually dimorphic characteristics of the amygdala and potential parallels with the oxytocin system and (4) discuss how the interplay of oxytocin and vasopressin may explain the partially inconsistent findings of their effects on amygdala functioning.

RDoC-based categorization of amygdala functions and its implications in autism

Confusion endures as to the exact role of the amygdala in relation to autism. To help resolve this we turned to the NIMH's Research Domain Criteria (RDoC) which provides a classification schema that identifies different categories of behaviors that can turn pathologic in mental health disorders, e.g. autism. While RDoC incorporates all the known neurobiological substrates for each domain, this review will focus primarily on the amygdala. We first consider the amygdala from an anatomical, historical, and developmental perspective. Next, we examine the different domains and constructs of RDoC that the amygdala is involved in: Negative Valence Systems, Positive Valence Systems, Cognitive Systems, Social Processes, and Arousal and Regulatory Systems. Then the evidence for a dysfunctional amygdala in autism is presented with a focus on alterations in development, prenatal valproic acid exposure as a model for ASD, and changes in the oxytocin system therein. Finally, a synthesis of RDoC, the amygdala, and autism is offered, emphasizing the task of disambiguation and suggestions for future research.

The journey to autism: Insights from neuroimaging studies of infants and toddlers

By definition, autism spectrum disorder (ASD) is a neurodevelopmental disorder that emerges during early childhood. It is during this time that infants and toddlers transition from appearing typical across multiple domains to exhibiting the behavioral phenotype of ASD. Neuroimaging studies focused on this period of development have provided crucial knowledge pertaining to this process, including possible mechanisms underlying pathogenesis of the disorder and offering the possibility of prodromal or presymptomatic prediction of risk. In this paper, we review findings from structural and functional brain imaging studies of ASD focused on the first years of life and discuss implications for next steps in research and clinical applications.

Neural Mechanisms of Qigong Sensory Training Massage for Children With Autism Spectrum Disorder: A Feasibility Study

OBJECTIVES

Despite the enormous prevalence of autism spectrum disorder (ASD), its global impact has yet to be realized. Millions of families worldwide need effective treatments to help them get through everyday challenges like eating, sleeping, digestion, and social interaction. Qigong Sensory Training (QST) is a nonverbal, parent-delivered intervention recently shown to be effective at reducing these everyday challenges in children with ASD. This study tested the feasibility of a protocol for investigating QST's neural mechanism.

METHODS

During a single visit, 20 children, 4- to 7-year-old, with ASD viewed images of emotional faces before and after receiving QST or watching a video (controls). Heart rate variability was recorded throughout the visit, and power in the high frequency band (0.15-0.4 Hz) was calculated to estimate parasympathetic tone in 5-s nonoverlapping windows. Cerebral oximetry of prefrontal cortex was recorded during rest and while viewing emotional faces.

RESULTS

95% completion rate and 7.6% missing data met a priori standards confirming protocol feasibility for future studies. Preliminary data suggest: (1) during the intervention, parasympathetic tone increased more in children receiving massage (M = 2.9, SD = 0.3) versus controls (M = 2.5, SD = 0.5); (2) while viewing emotional faces post-intervention, parasympathetic tone was more affected (reduced) in the massage group (p = 0.036); and (3) prefrontal cortex response to emotional faces was greater after massage compared to controls. These results did not reach statistical significance in this small study powered to test feasibility.

DISCUSSION/CONCLUSION

This study demonstrates solid protocol feasibility. If replicated in a larger sample, these findings would provide important clues to the neural mechanism of action underlying QST's efficacy for improving sensory, social, and communication difficulties in children with autism.

Cortical and Subcortical Brain Morphometry Differences Between Patients With Autism Spectrum Disorder and Healthy Individuals Across the Lifespan: Results From the ENIGMA ASD Working Group

OBJECTIVE

Neuroimaging studies show structural differences in both cortical and subcortical brain regions in children and adults with autism spectrum disorder (ASD) compared with healthy subjects. Findings are inconsistent, however, and it is unclear how differences develop across the lifespan. The authors investigated brain morphometry differences between individuals with ASD and healthy subjects, cross-sectionally across the lifespan, in a large multinational sample from the Enhancing Neuroimaging Genetics Through Meta-Analysis (ENIGMA) ASD working group.

METHOD

The sample comprised 1,571 patients with ASD and 1,651 healthy control subjects (age range, 2-64 years) from 49 participating sites. MRI scans were preprocessed at individual sites with a harmonized protocol based on a validated automated-segmentation software program. Mega-analyses were used to test for case-control differences in subcortical volumes, cortical thickness, and surface area. Development of brain morphometry over the lifespan was modeled using a fractional polynomial approach.

RESULTS

The case-control mega-analysis demonstrated that ASD was associated with smaller subcortical volumes of the pallidum, putamen, amygdala, and nucleus accumbens (effect sizes [Cohen's d], 0.13 to -0.13), as well as increased cortical thickness in the frontal cortex and decreased thickness in the temporal cortex (effect sizes, -0.21 to 0.20). Analyses of age effects indicate that the development of cortical thickness is altered in ASD, with the largest differences occurring around adolescence. No age-by-ASD interactions were observed in the subcortical partitions.

CONCLUSIONS

The ENIGMA ASD working group provides the largest study of brain morphometry differences in ASD to date, using a well-established, validated, publicly available analysis pipeline. ASD patients showed altered morphometry in the cognitive and affective parts of the striatum, frontal cortex, and temporal cortex. Complex developmental trajectories were observed for the different regions, with a developmental peak around adolescence. These findings suggest an interplay in the abnormal development of the striatal, frontal, and temporal regions in ASD across the lifespan.

Advances, challenges, and promises in pediatric neuroimaging of neurodevelopmental disorders

Recent years have witnessed the proliferation of neuroimaging studies of neurodevelopmental disorders (NDDs), particularly of children with autism spectrum disorder (ASD), attention-deficit/hyperactivity disorder (ADHD), and Tourette's syndrome (TS). Neuroimaging offers immense potential in understanding the biology of these disorders, and how it relates to clinical symptoms. Neuroimaging techniques, in the long run, may help identify neurobiological markers to assist clinical diagnosis and treatment. However, methodological challenges have affected the progress of clinical neuroimaging. This paper reviews the methodological challenges involved in imaging children with NDDs. Specific topics include correcting for head motion, normalization using pediatric brain templates, accounting for psychotropic medication use, delineating complex developmental trajectories, and overcoming smaller sample sizes. The potential of neuroimaging-based biomarkers and the utility of implementing neuroimaging in a clinical setting are also discussed. Data-sharing approaches, technological advances, and an increase in the number of longitudinal, prospective studies are recommended as future directions. Significant advances have been made already, and future decades will continue to see innovative progress in neuroimaging research endeavors of NDDs.

Neuron numbers increase in the human amygdala from birth to adulthood, but not in autism

Remarkably little is known about the postnatal cellular development of the human amygdala. It plays a central role in mediating emotional behavior and has an unusually protracted development well into adulthood, increasing in size by 40% from youth to adulthood. Variation from this typical neurodevelopmental trajectory could have profound implications on normal emotional development. We report the results of a stereological analysis of the number of neurons in amygdala nuclei of 52 human brains ranging from 2 to 48 years of age [24 neurotypical and 28 autism spectrum disorder (ASD)]. In neurotypical development, the number of mature neurons in the basal and accessory basal nuclei increases from childhood to adulthood, coinciding with a decrease of immature neurons within the paralaminar nucleus. Individuals with ASD, in contrast, show an initial excess of amygdala neurons during childhood, followed by a reduction in adulthood across nuclei. We propose that there is a long-term contribution of mature neurons from the paralaminar nucleus to other nuclei of the neurotypical human amygdala and that this growth trajectory may be altered in ASD, potentially underlying the volumetric changes detected in ASD and other neurodevelopmental or neuropsychiatric disorders.

Structural connectivity of the amygdala in young adults with autism spectrum disorder

Autism spectrum disorder (ASD) is characterized by impairments in social cognition, a function associated with the amygdala. Subdivisions of the amygdala have been identified which show specificity of structure, connectivity, and function. Little is known about amygdala connectivity in ASD. The aim of this study was to investigate the microstructural properties of amygdala-cortical connections and their association with ASD behaviours, and whether connectivity of specific amygdala subregions is associated with particular ASD traits. The brains of 51 high-functioning young adults (25 with ASD; 26 controls) were scanned using MRI. Amygdala volume was measured, and amygdala-cortical connectivity estimated using probabilistic tractography. An iterative 'winner takes all' algorithm was used to parcellate the amygdala based on its primary cortical connections. Measures of amygdala connectivity were correlated with clinical scores. In comparison with controls, amygdala volume was greater in ASD (F(1,94) = 4.19; p = .04). In white matter (WM) tracts connecting the right amygdala to the right cortex, ASD subjects showed increased mean diffusivity (t = 2.35; p = .05), which correlated with the severity of emotion recognition deficits (rho = -0.53; p = .01). Following amygdala parcellation, in ASD subjects reduced fractional anisotropy in WM connecting the left amygdala to the temporal cortex was associated with with greater attention switching impairment (rho = -0.61; p = .02). This study demonstrates that both amygdala volume and the microstructure of connections between the amygdala and the cortex are altered in ASD. Findings indicate that the microstructure of right amygdala WM tracts are associated with overall ASD severity, but that investigation of amygdala subregions can identify more specific associations.

Maternal Systemic Interleukin-6 During Pregnancy Is Associated With Newborn Amygdala Phenotypes and Subsequent Behavior at 2 Years of Age

BACKGROUND

Maternal inflammation during pregnancy increases the risk for offspring psychiatric disorders and other adverse long-term health outcomes. The influence of inflammation on the developing fetal brain is hypothesized as one potential mechanism but has not been examined in humans.

METHODS

Participants were adult women (N = 86) who were recruited during early pregnancy and whose offspring were born after 34 weeks' gestation. A biological indicator of maternal inflammation (interleukin-6) that has been shown to influence fetal brain development in animal models was quantified serially in early, mid-, and late pregnancy. Structural and functional brain magnetic resonance imaging scans were acquired in neonates shortly after birth. Infants' amygdalae were individually segmented for measures of volume and as seeds for resting state functional connectivity. At 24 months of age, children completed a snack delay task to assess impulse control.

RESULTS

Higher average maternal interleukin-6 concentration during pregnancy was prospectively associated with larger right amygdala volume and stronger bilateral amygdala connectivity to brain regions involved in sensory processing and integration (fusiform, somatosensory cortex, and thalamus), salience detection (anterior insula), and learning and memory (caudate and parahippocampal gyrus). Larger newborn right amygdala volume and stronger left amygdala connectivity were in turn associated with lower impulse control at 24 months of age, and mediated the association between higher maternal interleukin-6 concentrations and lower impulse control.

CONCLUSIONS

These findings provide new evidence in humans linking maternal inflammation during pregnancy with newborn brain and emerging behavioral phenotypes relevant for psychiatric disorders. A better understanding of intrauterine conditions that influence offspring disease susceptibility is warranted to inform targeted early intervention and prevention efforts.

Inferior Frontal Gyrus Volume Loss Distinguishes Between Autism and (Comorbid) Attention-Deficit/Hyperactivity Disorder-A FreeSurfer Analysis in Children

Objective: Autism spectrum (ASD) and attention-deficit/hyperactivity disorder (ADHD) are neurodevelopmental disorders with a high rate of comorbidity. To date, diagnosis is based on clinical presentation and distinct reliable biomarkers have been identified neither for ASD nor ADHD. Most previous neuroimaging studies investigated ASD and ADHD separately. Method: To address the question of structural brain differences between ASD and ADHD, we performed FreeSurfer analysis in a sample of children with ADHD (n = 30), with high-functioning ASD (n = 14), with comorbid high-functioning ASD and ADHD (n = 15), and of typically developed controls (TD; n = 36). With FreeSurfer, an automated brain imaging processing and analyzing suite, we reconstructed the cerebral cortex and calculated gray matter volumes as well as cortical surface parameters in terms of cortical thickness and mean curvature. Results: A significant main effect of the factor ADHD was detected for the left inferior frontal gyrus (Pars orbitalis) volume, with the ADHD group exhibiting smaller Pars orbitalis volumes. Dimensional measures of autism (SRS total raw score) and ADHD (DISYPS-II FBB-ADHD score) had no significant influence on the left Pars orbitalis volume. Both, ASD and ADHD tended to have an effect on cortical thickness or mean curvature, which did not survive correction for multiple comparisons. Conclusion: Our results underline that ADHD rather than ASD is associated with volume loss in the left inferior frontal gyrus (Pars orbitalis). This area might play a relevant role in modulating symptoms of inattention and/or impulsivity in ADHD. The effect of comorbid ADHD in ASD samples and vice versa, on cortical thickness and mean curvature, requires further investigation in larger samples.

Using Pattern Classification to Identify Brain Imaging Markers in Autism Spectrum Disorder

Autism spectrum disorder (ASD) is a neurodevelopmental condition characterized by deficits in social interaction and communication, as well as repetitive and restrictive behaviours. The etiological and phenotypic complexity of ASD has so far hindered the development of clinically useful biomarkers for the condition. Neuroimaging studies have been valuable in establishing a biological basis for ASD. Increasingly, neuroimaging has been combined with 'machine learning'-based pattern classification methods to make individual diagnostic predictions. Moving forward, the hope is that these techniques may not only facilitate the diagnostic process but may also aid in fractionating the ASD phenotype into more biologically homogeneous sub-groups, with defined pathophysiology, predictable outcomes and/or responses to targeted treatments and/or interventions. This review chapter will first introduce 'machine learning' and pattern recognition methods in general, with a focus on their application to diagnostic classification. It will highlight why such approaches to biomarker discovery may have advantages over more conventional analytical methods. Magnetic resonance imaging (MRI) findings of atypical brain structure, function and connectivity in ASD will be briefly reviewed before we describe how pattern recognition has been applied to generate predictive models for ASD. Last, we will discuss some limitations and pitfalls of pattern recognition analyses in ASD and consider how the field can advance beyond the prediction of binary outcomes.

Identification of Transmembrane Protease Serine 2 and Forkhead Box A1 As the Potential Bisphenol A Responsive Genes in the Neonatal Male Rat Brain

Perinatal exposure of Bisphenol A (BPA) to rodents modifies their behavior in later life. To understand how BPA modifies their neurodevelopmental process, we first searched for BPA responsive genes from androgen and estrogen receptor signaling target genes by polymerase chain reaction array in the neonatal male rat brain. We used a transgenic strain of Wistar rats carrying enhanced green fluorescent protein tagged to gonadotropin-inhibitory hormone (GnIH) promoter to investigate the possible interaction of BPA responsive genes and GnIH neurons. We found upregulation of transmembrane protease serine 2 (Tmprss2), an androgen receptor signaling target gene, and downregulation of Forkhead box A1 (Foxa1), an ER signaling target gene, in the medial amygdala of male rats that were subcutaneously administered with BPA from day 1 to 3. Tmprss2-immunoreactive (ir) cells were distributed in the olfactory bulb, cerebral cortex, hippocampus, amygdala, and hypothalamus in 3 days old but not in 1-month-old male rats. Density of Tmprss2-ir cells in the medial amygdala was increased by daily administration of BPA from day 1 to 3. Tmprss2 immunoreactivity was observed in 26.5% of GnIH neurons clustered from the ventral region of the ventromedial hypothalamic nucleus to the dorsal region of the arcuate nucleus of 3-day-old male rat hypothalamus. However, Tmprss2 mRNA expression significantly decreased in the amygdala and hypothalamus of 1-month-old male rats. Foxa1 mRNA expression was higher in the hypothalamus than the amygdala in 3 days old male rats. Intense Foxa1-ir cells were only found in the peduncular part of lateral hypothalamus of 3-day-old male rats. Density of Foxa1-ir cells in the hypothalamus was decreased by daily administration of BPA from day 1 to 3. Foxa1 mRNA expression in the hypothalamus also significantly decreased at 1 month. These results suggest that BPA disturbs the neurodevelopmental process and behavior of rats later in their life by modifying Tmprss2 and Foxa1 expressions in the brain.

Protracted dendritic growth in the typically developing human amygdala and increased spine density in young ASD brains

The amygdala is a medial temporal lobe structure implicated in social and emotional regulation. In typical development (TD), the amygdala continues to increase volumetrically throughout childhood and into adulthood, while other brain structures are stable or decreasing in volume. In autism spectrum disorder (ASD), the amygdala undergoes rapid early growth, making it volumetrically larger in children with ASD compared to TD children. Here we explore: (a) if dendritic arborization in the amygdala follows the pattern of protracted growth in TD and early overgrowth in ASD and (b), if spine density in the amygdala in ASD cases differs from TD from youth to adulthood. The amygdala from 32 postmortem human brains (7-46 years of age) were stained using a Golgi-Kopsch impregnation. Ten principal neurons per case were selected in the lateral nucleus and traced using Neurolucida software in their entirety. We found that both ASD and TD individuals show a similar pattern of increasing dendritic length with age well into adulthood. However, spine density is (a) greater in young ASD cases compared to age-matched TD controls (<18 years old) and (b) decreases in the amygdala as people with ASD age into adulthood, a phenomenon not found in TD. Therefore, by adulthood, there is no observable difference in spine density in the amygdala between ASD and TD age-matched adults (≥18 years old). Our findings highlight the unique growth trajectory of the amygdala and suggest that spine density may contribute to aberrant development and function of the amygdala in children with ASD.

Neonatal and regressive forms of autism: Diseases with similar symptoms but a different etiology

Autistic Spectrum Disorder (ASD) can be a debilitating, life-long neurocognitive disease. ASD is caused by genetic and epigenetic factors and largely unknown and poorly understood environmental triggers. Signs and symptoms of ASD often appear in the first year of life while the disease strikes other infants who had previously been developing normally at around 2years of age. Ozonoff and her colleagues recently suggested that there are three different pathways or trajectories for the development of ASD in infants 6-24months of age. I hypothesize that pathway 1 is caused by in utero insult/injury, pathway 2 by obstetric complications at birth, and pathway 3 by environmental triggers of ASD affecting infants 0-3years of age. Faster progress can be made in elucidating the underlying causes of neonatal and regressive forms of ASD if the diseases are investigated separately, instead of being part of the same disorder.

Advances in nonhuman primate models of autism: Integrating neuroscience and behavior

Given the prevalence and societal impact of autism spectrum disorders (ASD), there is an urgent need to develop innovative preventative strategies and treatments to reduce the alarming number of cases and improve core symptoms for afflicted individuals. Translational efforts between clinical and preclinical research are needed to (i) identify and evaluate putative causes of ASD, (ii) determine the underlying neurobiological mechanisms, (iii) develop and test novel therapeutic approaches and (iv) ultimately translate basic research into safe and effective clinical practices. However, modeling a uniquely human brain disorder, such as ASD, will require sophisticated animal models that capitalize on unique advantages of diverse species including drosophila, zebra fish, mice, rats, and ultimately, species more closely related to humans, such as the nonhuman primate. Here we discuss the unique contributions of the rhesus monkey (Macaca mulatta) model to ongoing efforts to understand the neurobiology of the disorder, focusing on the convergence of brain and behavior outcome measures that parallel features of human ASD.

Developmental disruption of amygdala transcriptome and socioemotional behavior in rats exposed to valproic acid prenatally

Background

The amygdala controls socioemotional behavior and has consistently been implicated in the etiology of autism spectrum disorder (ASD). Precocious amygdala development is commonly reported in ASD youth with the degree of overgrowth positively correlated to the severity of ASD symptoms. Prenatal exposure to VPA leads to an ASD phenotype in both humans and rats and has become a commonly used tool to model the complexity of ASD symptoms in the laboratory. Here, we examined abnormalities in gene expression in the amygdala and socioemotional behavior across development in the valproic acid (VPA) rat model of ASD.

Methods

Rat dams received oral gavage of VPA (500 mg/kg) or saline daily between E11 and 13. Socioemotional behavior was tracked across development in both sexes. RNA sequencing and proteomics were performed on amygdala samples from male rats across development.

Results

Effects of VPA on time spent in social proximity and anxiety-like behavior were sex dependent, with social abnormalities presenting in males and heightened anxiety in females. Across time VPA stunted developmental and immune, but enhanced cellular death and disorder, pathways in the amygdala relative to saline controls. At postnatal day 10, gene pathways involved in nervous system and cellular development displayed predicted activations in prenatally exposed VPA amygdala samples. By juvenile age, however, transcriptomic and proteomic pathways displayed reductions in cellular growth and neural development. Alterations in immune pathways, calcium signaling, Rho GTPases, and protein kinase A signaling were also observed.

Conclusions

As behavioral, developmental, and genomic alterations are similar to those reported in ASD, these results lend support to prenatal exposure to VPA as a useful tool for understanding how developmental insults to molecular pathways in the amygdala give rise to ASD-related syndromes.

Electronic supplementary material

The online version of this article (doi:10.1186/s13229-017-0160-x) contains supplementary material, which is available to authorized users.

In pursuit of neurophenotypes: The consequences of having autism and a big brain

A consensus has emerged that despite common core features, autism spectrum disorder (ASD) has multiple etiologies and various genetic and biological characteristics. The fact that there are likely to be subtypes of ASD has complicated attempts to develop effective therapies. The UC Davis MIND Institute Autism Phenome Project is a longitudinal, multidisciplinary analysis of children with autism and age-matched typically developing controls; nearly 400 families are participating in this study. The overarching goal is to gather sufficient biological, medical, and behavioral data to allow definition of clinically meaningful subtypes of ASD. One reasonable hypothesis is that different subtypes of autism will demonstrate different patterns of altered brain organization or development i.e., different neurophenotypes. In this Commentary, we discuss one neurophenotype that is defined by megalencephaly, or having brain size that is large and disproportionate to body size. We have found that 15% of the boys with autism demonstrate this neurophenotype, though it is far less common in girls. We review behavioral and medical characteristics of the large-brained group of boys with autism in comparison to those with typically sized brains. While brain size in typically developing individuals is positively correlated with cognitive function, the children with autism and larger brains have more severe disabilities and poorer prognosis. This research indicates that phenotyping in autism, like genotyping, requires a very substantial cohort of subjects. Moreover, since brain and behavior relationships may emerge at different times during development, this effort highlights the need for longitudinal analyses to carry out meaningful phenotyping. Autism Res 2017, 10: 711-722. © 2017 International Society for Autism Research, Wiley Periodicals, Inc.

Neural correlates of language variability in preschool-aged boys with autism spectrum disorder

Children with autism vary widely in their language abilities, yet the neural correlates of this language variability remain unclear, especially early in development. Diffusion tensor imaging (DTI) was used to examine diffusivity measures along the length of 18 major fiber tracts in 104 preschool-aged boys with autism spectrum disorder (ASD). The boys were assigned to subgroups according to their level of language development (Low: no/low language, Middle: small vocabulary, High: large vocabulary and grammar), based on their raw scores on the expressive language (EL) and receptive language (RL) sections of the Mullen Scales of Early Learning (MSEL). Results indicate that the subgroups differed in fractional anisotropy (FA), mean diffusivity (MD), and radial diffusivity (RD) along the inferior longitudinal fasciculus (ILF) in both hemispheres. Moreover, FA correlated significantly with Mullen EL and RL raw scores, but not ADOS severity score, along the left and right ILF. Subgroups also differed in MD (but not FA) along the left superior longitudinal fasiculus and left corticospinal tract, but these differences were not correlated with language scores. These findings suggest that white matter microstructure in the left and right ILF varies in relation to lexical development in young males with ASD. The findings also support the use of raw scores on language-relevant standardized tests for assessing early language-brain relationships. Autism Res 2017. © 2017 International Society for Autism Research, Wiley Periodicals, Inc. Autism Res 2017, 10: 1107-1119. © 2017 International Society for Autism Research, Wiley Periodicals, Inc.

Candidate Biomarkers in Children with Autism Spectrum Disorder: A Review of MRI Studies

Searching for effective biomarkers is one of the most challenging tasks in the research field of Autism Spectrum Disorder (ASD). Magnetic resonance imaging (MRI) provides a non-invasive and powerful tool for investigating changes in the structure, function, maturation, connectivity, and metabolism of the brain of children with ASD. Here, we review the more recent MRI studies in young children with ASD, aiming to provide candidate biomarkers for the diagnosis of childhood ASD. The review covers structural imaging methods, diffusion tensor imaging, resting-state functional MRI, and magnetic resonance spectroscopy. Future advances in neuroimaging techniques, as well as cross-disciplinary studies and large-scale collaborations will be needed for an integrated approach linking neuroimaging, genetics, and phenotypic data to allow the discovery of new, effective biomarkers.

A Volumetric and Functional Connectivity MRI Study of Brain Arginine-Vasopressin Pathways in Autistic Children

Dysfunction of brain-derived arginine-vasopressin (AVP) systems may be involved in the etiology of autism spectrum disorder (ASD). Certain regions such as the hypothalamus, amygdala, and hippocampus are known to contain either AVP neurons or terminals and may play an important role in regulating complex social behaviors. The present study was designed to investigate the concomitant changes in autistic behaviors, circulating AVP levels, and the structure and functional connectivity (FC) of specific brain regions in autistic children compared with typically developing children (TDC) aged from 3 to 5 years. The results showed: (1) children with ASD had a significantly increased volume in the left amygdala and left hippocampus, and a significantly decreased volume in the bilateral hypothalamus compared to TDC, and these were positively correlated with plasma AVP level. (2) Autistic children had a negative FC between the left amygdala and the bilateral supramarginal gyri compared to TDC. The degree of the negative FC between amygdala and supramarginal gyrus was associated with a higher score on the clinical autism behavior checklist. (3) The degree of negative FC between left amygdala and left supramarginal gyrus was associated with a lowering of the circulating AVP concentration in boys with ASD. (4) Autistic children showed a higher FC between left hippocampus and right subcortical area compared to TDC. (5) The circulating AVP was negatively correlated with the visual and listening response score of the childhood autism rating scale. These results strongly suggest that changes in structure and FC in brain regions containing AVP may be involved in the etiology of autism.

Neuroanatomy and Neuropathology of Autism Spectrum Disorder in Humans

Autism spectrum disorder (ASD) is a lifelong heterogeneous neurodevelopmental condition that is associated with differences in brain anatomy and connectivity. Yet, the molecular and cellular mechanisms that underpin the atypical developmental of the brain in ASD remain poorly understood. Here, we review the findings of in vivo neuroimaging studies examining the time course of atypical brain development in ASD and relate the different neurodevelopmental stages that are atypical in ASD to the known neurobiological mechanisms that drive the maturation of the typically developing brain. In particular, we focus on the notion of 'early brain overgrowth' in ASD, which may lead to differences in the formation of the brain's micro- and macro-circuitry. Moreover, we attempt to link the in vivo reports describing differences in brain anatomy and connectivity on the macroscopic level to the increasing number of post-mortem studies examining the neural architecture of the brain in ASD on the microscopic level. In addition, we discuss future directions and outstanding questions in this particular field of research and highlight the need for establishing the link between micro- and macro-pathology in the same set of individuals with ASD based on advances in genetic, molecular and imaging techniques. In combination, these may proof to be invaluable for patient stratification and the development of novel pharmacotherapies in the future.

Categorical versus dimensional approaches to autism-associated intermediate phenotypes in 22q11.2 microdeletion syndrome

BACKGROUND

22q11.2 Microdeletion syndrome (22q11DS) is associated with elevated rates of autism spectrum disorders (ASDs), although the diagnosis is controversial. In order to determine whether there is a biological substrate of ASD in 22q11DS, we examined neurocognitive and structural neuroanatomic differences between those with 22q11DS and an ASD diagnosis (22q11DS-ASD+) and those with 22q11DS without ASD (22q11DS-ASD-); we then determined whether these differences were better characterized within a categorical or dimensional framework.

METHODS

We collected multiple neurocognitive measures and high-resolution T1-weighted scans on 116 individuals (29 22q11DS-ASD+, 32 22q11DS-ASD-, 55 typically developing controls) between 6 and 26 years of age. Measures of subcortical volume, cortical thickness (CT), and surface area were extracted using the FreeSurfer image analysis suite. Group differences in neurocognitive and neuroanatomic measures were assessed; regression analyses were then performed to determine whether a categorical or dimensional measure of ASD was a better predictor of neurocognitive impairment and/or neuroanatomic abnormalities observed in 22q11DS-ASD+.

RESULTS

In comparison to 22q11DS-ASD-, 22q11DS-ASD+ participants exhibited decreased bilateral hippocampal CT and decreased right amygdala volumes. Those with 22q11DS-ASD+ also showed slowed processing speed and impairments in visuospatial and facial memory. Neurocognitive impairments fit a dimensional model of ASD, whereas reductions in parahippocampal CT were best explained by a categorical measure of ASD.

CONCLUSIONS

A combination of categorical and dimensional measures of ASD may provide the most comprehensive understanding of ASDs in 22q11DS.

Associations between cytokines, endocrine stress response, and gastrointestinal symptoms in autism spectrum disorder

Many children and adolescents with autism spectrum disorder (ASD) have significant gastrointestinal (GI) symptoms, but the etiology is currently unknown. Some individuals with ASD show altered reactivity to stress and altered immune markers relative to typically-developing individuals, particularly stress-responsive cytokines including tumor necrosis factor alpha (TNF-α) and interleukin 6 (IL-6). Acute and chronic stress is associated with the onset and exacerbation of GI symptoms in those without ASD. The present study examined whether GI symptoms in ASD were associated with increases in cortisol, a stress-associated endocrine marker, and TNF-α and IL-6 in response to stress. As hypothesized, a greater amount of lower GI tract symptoms were significantly associated with post-stress cortisol concentration. The relationship between cortisol response to stress and GI functioning was greater for children who had a history of regressive autism. Exploratory analyses revealed significant correlations between cortisol response, intelligence, and inappropriate speech. In contrast, symptoms of the lower GI tract were not associated with levels of TNF-α or IL-6. Significant correlations were found, however, between TNF-α and IL-6 and irritability, socialization, and intelligence. These findings suggest that individuals with ASD and symptoms of the lower GI tract may have an increased response to stress, but this effect is not associated with concomitant changes in TNF-α and IL-6. The relationship between cortisol stress response and lower GI tract symptoms in children with regressive autism, as well as the relationships between cortisol, IL-6, and intelligence in ASD, warrant further investigation.

Maternal polycystic ovary syndrome and the risk of autism spectrum disorders in the offspring: a population-based nationwide study in Sweden

Although many studies indicate the interplay of genetic and environmental factors in the etiology of autism spectrum disorder (ASD), our limited understanding of the underlying mechanisms hampers the development of effective ways of detecting and preventing the disorder. Recent studies support the hypothesis that prenatal androgen exposure contributes to the development of ASD. This would suggest that maternal polycystic ovary syndrome (PCOS), a condition associated with excess androgens, would increase the risk of ASD in the offspring. We conducted a matched case-control study nested within the total population of Sweden (children aged 4-17 who were born in Sweden from 1984 to 2007). The sample consisted of 23 748 ASD cases and 208 796 controls, matched by birth month and year, sex and region of birth. PCOS and ASD were defined from ICD codes through linkage to health-care registers. Maternal PCOS increased the odds of ASD in the offspring by 59%, after adjustment for confounders (odds ratio (OR) 1.59, 95% confidence interval (CI) 1.34-1.88). The odds of offspring ASD were further increased among mothers with both PCOS and obesity, a condition common to PCOS that is related to more severe hyperandrogenemia (OR 2.13, 95% CI 1.46-3.10). Risk estimates did not differ between sexes. In conclusion, children of women with PCOS appear to have a higher risk of developing ASD. This finding awaits confirmation, and exploration of potentially underlying mechanisms, including the role of sex steroids in the etiology of ASD.

Functional Connectivity of the Amygdala Is Disrupted in Preschool-Aged Children With Autism Spectrum Disorder

OBJECTIVE

The objective of this study was to determine whether functional connectivity of the amygdala is altered in preschool-age children with autism spectrum disorder (ASD) and to assess the clinical relevance of observed alterations in amygdala connectivity.

METHOD

A resting-state functional connectivity magnetic resonance imaging study of the amygdala (and a parallel study of primary visual cortex) was conducted in 72 boys (mean age 3.5 years; n = 43 with ASD; n = 29 age-matched controls).

RESULTS

The ASD group showed significantly weaker connectivity between the amygdala and several brain regions involved in social communication and repetitive behaviors, including bilateral medial prefrontal cortex, temporal lobes, and striatum (p < .05, corrected). Weaker connectivity between the amygdala and frontal and temporal lobes was significantly correlated with increased autism severity in the ASD group (p < .05). In a parallel analysis examining the functional connectivity of primary visual cortex, the ASD group showed significantly weaker connectivity between visual cortex and sensorimotor regions (p < .05, corrected). Weaker connectivity between visual cortex and sensorimotor regions was not correlated with core autism symptoms, but instead was correlated with increased sensory hypersensitivity in the visual/auditory domain (p < .05).

CONCLUSION

These findings indicate that preschool-age children with ASD have disrupted functional connectivity between the amygdala and regions of the brain important for social communication and language, which might be clinically relevant because weaker connectivity was associated with increased autism severity. Moreover, although amygdala connectivity was associated with behavioral domains that are diagnostic of ASD, altered connectivity of primary visual cortex was related to sensory hypersensitivity.

The neuroanatomy of autism spectrum disorder: An overview of structural neuroimaging findings and their translatability to the clinical setting

Autism spectrum disorder is a complex neurodevelopmental disorder, which is accompanied by differences in brain anatomy, functioning and brain connectivity. Due to its neurodevelopmental character, and the large phenotypic heterogeneity among individuals on the autism spectrum, the neurobiology of autism spectrum disorder is inherently difficult to describe. Nevertheless, significant progress has been made in characterizing the neuroanatomical underpinnings of autism spectrum disorder across the human life span, and in identifying the molecular pathways that may be affected in autism spectrum disorder. Moreover, novel methodological frameworks for analyzing neuroimaging data are emerging that make it possible to characterize the neuroanatomy of autism spectrum disorder on the case level, and to stratify individuals based on their individual phenotypic make up. While these approaches are increasingly more often employed in the research setting, their applicability in the clinical setting remains a vision for the future. The aim of the current review is to (1) provide a general overview of recent structural neuroimaging findings examining the neuroanatomy of autism spectrum disorder across the human life span, and in males and females with the condition, (2) highlight potential neuroimaging (bio)markers that may in the future be used for the stratification of autism spectrum disorder individuals into biologically homogeneous subgroups and (3) inform treatment and intervention strategies.

Frontal networks in adults with autism spectrum disorder

It has been postulated that autism spectrum disorder is underpinned by an 'atypical connectivity' involving higher-order association brain regions. To test this hypothesis in a large cohort of adults with autism spectrum disorder we compared the white matter networks of 61 adult males with autism spectrum disorder and 61 neurotypical controls, using two complementary approaches to diffusion tensor magnetic resonance imaging. First, we applied tract-based spatial statistics, a 'whole brain' non-hypothesis driven method, to identify differences in white matter networks in adults with autism spectrum disorder. Following this we used a tract-specific analysis, based on tractography, to carry out a more detailed analysis of individual tracts identified by tract-based spatial statistics. Finally, within the autism spectrum disorder group, we studied the relationship between diffusion measures and autistic symptom severity. Tract-based spatial statistics revealed that autism spectrum disorder was associated with significantly reduced fractional anisotropy in regions that included frontal lobe pathways. Tractography analysis of these specific pathways showed increased mean and perpendicular diffusivity, and reduced number of streamlines in the anterior and long segments of the arcuate fasciculus, cingulum and uncinate--predominantly in the left hemisphere. Abnormalities were also evident in the anterior portions of the corpus callosum connecting left and right frontal lobes. The degree of microstructural alteration of the arcuate and uncinate fasciculi was associated with severity of symptoms in language and social reciprocity in childhood. Our results indicated that autism spectrum disorder is a developmental condition associated with abnormal connectivity of the frontal lobes. Furthermore our findings showed that male adults with autism spectrum disorder have regional differences in brain anatomy, which correlate with specific aspects of autistic symptoms. Overall these results suggest that autism spectrum disorder is a condition linked to aberrant developmental trajectories of the frontal networks that persist in adult life.

One-Class Support Vector Machines Identify the Language and Default Mode Regions As Common Patterns of Structural Alterations in Young Children with Autism Spectrum Disorders

The identification of reliable brain endophenotypes of autism spectrum disorders (ASD) has been hampered to date by the heterogeneity in the neuroanatomical abnormalities detected in this condition. To handle the complexity of neuroimaging data and to convert brain images in informative biomarkers of pathology, multivariate analysis techniques based on Support Vector Machines (SVM) have been widely used in several disease conditions. They are usually trained to distinguish patients from healthy control subjects by making a binary classification. Here, we propose the use of the One-Class Classification (OCC) or Data Description method that, in contrast to two-class classification, is based on a description of one class of objects only. This approach, by defining a multivariate normative rule on one class of subjects, allows recognizing examples from a different category as outliers. We applied the OCC to 314 regional features extracted from brain structural Magnetic Resonance Imaging (MRI) scans of young children with ASD (21 males and 20 females) and control subjects (20 males and 20 females), matched on age [range: 22-72 months of age; mean = 49 months] and non-verbal intelligence quotient (NVIQ) [range: 31-123; mean = 73]. We demonstrated that a common pattern of features characterize the ASD population. The OCC SVM trained on the group of ASD subjects showed the following performances in the ASD vs. controls separation: the area under the receiver operating characteristic curve (AUC) was 0.74 for the male and 0.68 for the female population, respectively. Notably, the ASD vs. controls discrimination results were maximized when evaluated on the subsamples of subjects with NVIQ ≥ 70, leading to AUC = 0.81 for the male and AUC = 0.72 for the female populations, respectively. Language regions and regions from the default mode network-posterior cingulate cortex, pars opercularis and pars triangularis of the inferior frontal gyrus, and transverse temporal gyrus-contributed most to distinguishing individuals with ASD from controls, arguing for the crucial role of these areas in the ASD pathophysiology. The observed brain patterns associate preschoolers with ASD independently of their age, gender and NVIQ and therefore they are expected to constitute part of the ASD brain endophenotype.