Altered corpus callosum morphology associated with autism over the first 2 years of life

Gut-Brain Axis in the Early Postnatal Years of Life: A Developmental Perspective

Emerging evidence suggests that alterations in the development of the gastrointestinal (GI) tract during the early postnatal period can influence brain development and vice-versa. It is increasingly recognized that communication between the GI tract and brain is mainly driven by neural, endocrine, immune, and metabolic mediators, collectively called the gut-brain axis (GBA). Changes in the GBA mediators occur in response to the developmental changes in the body during this period. This review provides an overview of major developmental events in the GI tract and brain in the early postnatal period and their parallel developmental trajectories under physiological conditions. Current knowledge of GBA mediators in context to brain function and behavioral outcomes and their synthesis and metabolism (site, timing, etc.) is discussed. This review also presents hypotheses on the role of the GBA mediators in response to the parallel development of the GI tract and brain in infants.

Atypical visual processing in a mouse model of autism

Human social cognition relies heavily on the processing of various visual cues, such as eye contact and facial expressions. Atypical visual perception and integration have been recognized as key phenotypes in individuals diagnosed with autism spectrum disorder (ASD), and may potentially contribute to impediments in normal social development, a hallmark of ASD. Meanwhile, increasing studies on visual function in ASD have pointed to detail-oriented perception, which has been hypothesized to result from heightened response to information of high spatial frequency. However, mixed results of human studies have led to much debate, and investigations using animal models have been limited. Here, using BTBR mice as a model of idiopathic ASD, we assessed retinal stimulus processing by full-field electroretinogram and found impaired photoreceptor function and retina-based alterations mostly in the cone pathway. Using the optokinetic reflex to evaluate visual function, we observed robustly enhanced visual response to finer spatial details and more subtle contrasts at only higher spatial frequencies in the BTBR mice, under both photopic and scotopic conditions. These behavioral results, which are similar to findings in a subset of ASD patients, indicate a bias toward processing information of high spatial frequencies. Together, these findings also suggest that, while enhancement of visual behaviors under both photopic and scotopic conditions might be due to alterations in visual processing common to both rod and cone pathways, these mechanisms are probably downstream of photoreceptor function.

Neuroimaging Markers of Risk and Pathways to Resilience in Autism Spectrum Disorder

Autism spectrum disorder is a complex, heterogeneous neurodevelopmental condition of largely unknown etiology. This heterogeneity of symptom presentation, combined with high rates of comorbidity with other developmental disorders and a lack of reliable biomarkers, makes diagnosing and evaluating life outcomes for individuals with autism spectrum disorder a challenge. We review the growing literature on neuroimaging-based biomarkers of risk for the development of autism and explore evidence for resilience in some autistic individuals. The current literature suggests that neuroimaging during early infancy, in combination with prebirth and early genetic studies, is a promising tool for identifying biomarkers of risk, while studies of gene expression and DNA methylation have provided some key insights into mechanisms of resilience. With genetics and the environment contributing to both risk for the development of autism spectrum disorder and conditions for resilience, additional studies are needed to understand how risk and resilience interact mechanistically, whereby factors of risk may engender conditions for adaptation. Future studies should prioritize longitudinal designs in global cohorts, with the involvement of the autism community as partners in research to help identify domains of functioning that hold value and importance to the community.

Sleep Onset Problems and Subcortical Development in Infants Later Diagnosed With Autism Spectrum Disorder

OBJECTIVE

Sleep patterns in children with autism spectrum disorder (ASD) appear to diverge from typical development in the second or third year of life. Little is known, however, about the occurrence of sleep problems in infants who later develop ASD and possible effects on early brain development. In a longitudinal neuroimaging study of infants at familial high or low risk for ASD, parent-reported sleep onset problems were examined in relation to subcortical brain volumes in the first 2 years of life.

METHODS

A total of 432 infants were included across three study groups: infants at high risk who developed ASD (N=71), infants at high risk who did not develop ASD (N=234), and infants at low risk (N=127). Sleep onset problem scores (derived from an infant temperament measure) were evaluated in relation to longitudinal high-resolution T₁ and T₂ structural imaging data acquired at 6, 12, and 24 months of age.

RESULTS

Sleep onset problems were more common at 6-12 months among infants who later developed ASD. Infant sleep onset problems were related to hippocampal volume trajectories from 6 to 24 months only for infants at high risk who developed ASD. Brain-sleep relationships were specific to the hippocampus; no significant relationships were found with volume trajectories of other subcortical structures examined (the amygdala, caudate, globus pallidus, putamen, and thalamus).

CONCLUSIONS

These findings provide initial evidence that sleep onset problems in the first year of life precede ASD diagnosis and are associated with altered neurodevelopmental trajectories in infants at high familial risk who go on to develop ASD. If replicated, these findings could provide new insights into a potential role of sleep difficulties in the development of ASD.

A methodological review of fetal neurosonographic studies: New directions in assessment of neurodevelopmental risk for mental health problems

Most mental disorders are now considered to have neurodevelopmental origins, with a growing body of research pointing to neural alterations that predate birth. However, lack of established methods for reliable investigation of fetal brain development has limited research into early neural vulnerability. Using a systematic approach and quantitative evaluation of study methodology, we review neurosonographic studies of fetal brain structure with objective quality measures. A total of 81 studies were identified. High quality studies were identified for measurement of the corpus callosum, cerebellum, vermis, ventricles and frontal cortex, with reference ranges provided to facilitate future clinical research. Fewer and lower quality studies were available for subcortical structures, prompting a need for further research to create reliable reference ranges. Development and adoption of reference ranges for fetal brain structures should facilitate future research in neurosonographic evaluation of fetal brain development and lead to a better understanding of neurodevelopmental risk and resilience processes for mental disorders.

Sex differences associated with corpus callosum development in human infants: A longitudinal multimodal imaging study

The corpus callosum (CC) is the largest connective pathway in the human brain, linking cerebral hemispheres. There is longstanding debate in the scientific literature whether sex differences are evident in this structure, with many studies indicating the structure is larger in females. However, there are few data pertaining to this issue in infancy, during which time the most rapid developmental changes to the CC occur. In this study, we examined longitudinal brain imaging data collected from 104 infants at ages 6, 12, and 24 months. We identified sex differences in brain-size adjusted CC area and thickness characterized by a steeper rate of growth in males versus females from ages 6-24 months. In contrast to studies of older children and adults, CC size was larger for male compared to female infants. Based on diffusion tensor imaging data, we found that CC thickness is significantly associated with underlying microstructural organization. However, we observed no sex differences in the association between microstructure and thickness, suggesting that the role of factors such as axon density and/or myelination in determining CC size is generally equivalent between sexes. Finally, we found that CC length was negatively associated with nonverbal ability among females.

Loss of Cntnap2 Causes Axonal Excitability Deficits, Developmental Delay in Cortical Myelination, and Abnormal Stereotyped Motor Behavior

Contactin-associated protein-like 2 (Caspr2) is found at the nodes of Ranvier and has been associated with physiological properties of white matter conductivity. Genetic variation in CNTNAP2, the gene encoding Caspr2, has been linked to several neurodevelopmental conditions, yet pathophysiological effects of CNTNAP2 mutations on axonal physiology and brain myelination are unknown. Here, we have investigated mouse mutants for Cntnap2 and found profound deficiencies in the clustering of Kv1-family potassium channels in the juxtaparanodes of brain myelinated axons. These deficits are associated with a change in the waveform of axonal action potentials and increases in postsynaptic excitatory responses. We also observed that the normal process of myelination is delayed in Cntnap2 mutant mice. This later phenotype is a likely modulator of the developmental expressivity of the stereotyped motor behaviors that characterize Cntnap2 mutant mice. Altogether, our results reveal a mechanism linked to white matter conductivity through which mutation of CNTNAP2 may affect neurodevelopmental outcomes.

In Vivo Imaging of Gray Matter Microstructure in Major Psychiatric Disorders: Opportunities for Clinical Translation

Postmortem studies reveal that individuals with major neuropsychiatric disorders such as schizophrenia and autism spectrum disorder have gray matter microstructural abnormalities. These include abnormalities in neuropil organization, expression of proteins supporting neuritic and synaptic integrity, and myelination. Genetic and postmortem studies suggest that these changes may be causally linked to the pathogenesis of these disorders. Advances in diffusion-weighted magnetic resonance image (dMRI) acquisition techniques and biophysical modeling allow for the quantification of gray matter microstructure in vivo. While several biophysical models for imaging microstructural properties are available, one in particular, neurite orientation dispersion and density imaging (NODDI), holds great promise for clinical applications. NODDI can be applied to both gray and white matter and requires only a single extra shell beyond a standard dMRI acquisition. Since its development only a few years ago, the NODDI algorithm has been used to characterize gray matter microstructure in schizophrenia, Alzheimer's disease, healthy aging, and development. These investigations have shown that microstructural findings in vivo, using NODDI, align with postmortem findings. Not only do NODDI and other advanced dMRI-based modeling methods provide a window into the brain previously only available postmortem, but they may be more sensitive to certain brain changes than conventional magnetic resonance imaging approaches. This opens up exciting new possibilities for clinicians to more rapidly detect disease signatures and allows earlier intervention in the course of the disease. Given that neurites and gray matter microstructure have the capacity to rapidly remodel, these novel dMRI-based methods represent an opportunity to noninvasively monitor neuroplastic changes posttherapy within much shorter time scales.

Breastfeeding Duration Is Associated with Regional, but Not Global, Differences in White Matter Tracts

Extended breastfeeding through infancy confers benefits on neurocognitive performance and intelligence tests, though few have examined the biological basis of these effects. To investigate correlations with breastfeeding, we examined the major white matter tracts in 4–8 year-old children using diffusion tensor imaging and volumetric measurements of the corpus callosum. We found a significant correlation between the duration of infant breastfeeding and fractional anisotropy scores in left-lateralized white matter tracts, including the left superior longitudinal fasciculus and left angular bundle, which is indicative of greater intrahemispheric connectivity. However, in contrast to expectations from earlier studies, no correlations were observed with corpus callosum size, and thus no correlations were observed when using such measures of global interhemispheric white matter connectivity development. These findings suggest a complex but significant positive association between breastfeeding duration and white matter connectivity, including in pathways known to be functionally relevant for reading and language development.

Role of deep learning in infant brain MRI analysis

Deep learning algorithms and in particular convolutional networks have shown tremendous success in medical image analysis applications, though relatively few methods have been applied to infant MRI data due numerous inherent challenges such as inhomogenous tissue appearance across the image, considerable image intensity variability across the first year of life, and a low signal to noise setting. This paper presents methods addressing these challenges in two selected applications, specifically infant brain tissue segmentation at the isointense stage and presymptomatic disease prediction in neurodevelopmental disorders. Corresponding methods are reviewed and compared, and open issues are identified, namely low data size restrictions, class imbalance problems, and lack of interpretation of the resulting deep learning solutions. We discuss how existing solutions can be adapted to approach these issues as well as how generative models seem to be a particularly strong contender to address them.

Early patterns of functional brain development associated with autism spectrum disorder in tuberous sclerosis complex

Tuberous sclerosis complex (TSC) is a rare genetic disorder that confers a high risk for autism spectrum disorders (ASD), with behavioral predictors of ASD emerging early in life. Deviations in structural and functional neural connectivity are highly implicated in both TSC and ASD. For the first time, we explore whether electroencephalographic (EEG) measures of neural network function precede or predict the emergence of ASD in TSC. We determine whether altered brain function (a) is present in infancy in TSC, (b) differentiates infants with TSC based on ASD diagnostic status, and (c) is associated with later cognitive function. We studied 35 infants with TSC (N = 35), and a group of typically developing infants (N = 20) at 12 and 24 months of age. Infants with TSC were later subdivided into ASD and non-ASD groups based on clinical evaluation. We measured features of spontaneous alpha oscillations (6-12 Hz) that are closely associated with neural network development: alpha power, alpha phase coherence (APC), and peak alpha frequency (PAF). Infants with TSC demonstrated reduced interhemispheric APC compared to controls at 12 months of age, and these differences were found to be most pronounced at 24 months in the infants who later developed ASD. Across all infants, PAF at 24 months was associated with verbal and nonverbal cognition at 36 months. Associations between early network function and later neurodevelopmental and cognitive outcomes highlight the potential utility of early scalable EEG markers to identify infants with TSC requiring additional targeted intervention initiated very early in life. Autism Res 2019, 12: 1758-1773. © 2019 International Society for Autism Research, Wiley Periodicals, Inc. LAY SUMMARY: Approximately half of infants with tuberous sclerosis complex (TSC) develop autism. Here, using EEG, we find that there is a reduction in communication between brain regions during infancy in TSC, and that the infants who show the largest reductions are those who later develop autism. Being able to identify infants who show early signs of disrupted brain development may improve the timing of early prediction and interventions in TSC, and also help us to understand how early brain changes lead to autism.

The Neurodevelopment of Autism from Infancy Through Toddlerhood

Autism spectrum disorder (ASD) emerges during early childhood and is marked by a relatively narrow window in which infants transition from exhibiting normative behavioral profiles to displaying the defining features of the ASD phenotype in toddlerhood. Prospective brain imaging studies in infants at high familial risk for autism have revealed important insights into the neurobiology and developmental unfolding of ASD. In this article, we review neuroimaging studies of brain development in ASD from birth through toddlerhood, relate these findings to candidate neurobiological mechanisms, and discuss implications for future research and translation to clinical practice.

Effects of prenatal exposure to particulate matter air pollution on corpus callosum and behavioral problems in children

OBJECTIVE

Air pollution (AP) may affect neurodevelopment, but studies about the effects of AP on the growing human brain are still scarce. We aimed to investigate the effects of prenatal exposure to AP on lateral ventricles (LV) and corpus callosum (CC) volumes in children and to determine whether the induced brain changes are associated with behavioral problems.

METHODS

Among the children recruited through a set of representative schools of the city of Barcelona, (Spain) in the Brain Development and Air Pollution Ultrafine Particles in School Children (BREATHE) study, 186 typically developing participants aged 8-12 years underwent brain MRI on the same 1.5 T MR unit over a 1.5-year period (October 2012-April 2014). Brain volumes were derived from structural MRI scans using automated tissue segmentation. Behavioral problems were assessed using the Strengths and Difficulties Questionnaire (SDQ) and the criteria of the Attention Deficit Hyperactivity Disorder DSM-IV list. Prenatal fine particle (PM_2.5) levels were retrospectively estimated at the mothers' residential addresses during pregnancy with land use regression (LUR) models. To determine whether brain structures might be affected by prenatal PM_2.5 exposure, linear regression models were run and adjusted for age, sex, intracranial volume (ICV), maternal education, home socioeconomic vulnerability index, birthweight and mothers' smoking status during pregnancy. To test for associations between brain changes and behavioral outcomes, negative binomial regressions were performed and adjusted for age, sex, ICV.

RESULTS

Prenatal PM_2.5 levels ranged from 11.8 to 39.5 μg/m³ during the third trimester of pregnancy. An interquartile range increase in PM_2.5 level (7 μg/m³) was significantly linked to a decrease in the body CC volume (mm³) (β = -53.7, 95%CI [-92.0, -15.5] corresponding to a 5% decrease of the mean body CC volume) independently of ICV, age, sex, maternal education, socioeconomic vulnerability index at home, birthweight and mothers' smoking status during the third trimester of pregnancy. A 50 mm³ decrease in the body CC was associated with a significant higher hyperactivity subscore (Rate Ratio (RR) = 1.09, 95%CI [1.01, 1.17) independently of age, sex and ICV. The statistical significance of these results did not survive to False Discovery Rate correction for multiple comparisons.

CONCLUSIONS

Prenatal exposure to PM_2.5 may be associated with CC volume decrease in children. The consequences might be an increase in behavioral problems.

Precocious myelination in a mouse model of autism

Autism spectrum disorder (ASD) has been hypothesized to be a result of altered connectivity in the brain. Recent imaging studies suggest accelerated maturation of the white matter in young children with ASD, with underlying mechanisms unknown. Myelin is an integral part of the white matter and critical for connectivity; however, its role in ASD remains largely unclear. Here, we investigated myelin development in a model of idiopathic ASD, the BTBR mice. Magnetic resonance imaging revealed that fiber tracts in the frontal brain of the BTBR mice had increased volume at postnatal day 6, but the difference reduced over time, reminiscent of the findings in young patients. We further identified that myelination in the frontal brain of both male and female neonatal BTBR mice was increased, associated with elevated levels of myelin basic protein. However, myelin pattern was unaltered in adult BTBR mice, revealing accelerated developmental trajectory of myelination. Consistently, we found that signaling of platelet-derived growth factor receptor alpha (PDGFRα) was reduced in the frontal brain of neonatal BTBR mice. However, levels of microRNA species known to regulate PDGFRα signaling and myelination were unaltered. Together, these results suggest that precocious myelination could potentially contribute to increased volume and connectivity of the white matter observed in young children with ASD.

TRActs constrained by UnderLying INfant anatomy (TRACULInA): An automated probabilistic tractography tool with anatomical priors for use in the newborn brain

The ongoing myelination of white-matter fiber bundles plays a significant role in brain development. However, reliable and consistent identification of these bundles from infant brain MRIs is often challenging due to inherently low diffusion anisotropy, as well as motion and other artifacts. In this paper we introduce a new tool for automated probabilistic tractography specifically designed for newborn infants. Our tool incorporates prior information about the anatomical neighborhood of white-matter pathways from a training data set. In our experiments, we evaluate this tool on data from both full-term and prematurely born infants and demonstrate that it can reconstruct known white-matter tracts in both groups robustly, even in the presence of differences between the training set and study subjects. Additionally, we evaluate it on a publicly available large data set of healthy term infants (UNC Early Brain Development Program). This paves the way for performing a host of sophisticated analyses in newborns that we have previously implemented for the adult brain, such as pointwise analysis along tracts and longitudinal analysis, in both health and disease.

Hierarchical Multi-Geodesic Model for Longitudinal Analysis of Temporal Trajectories of Anatomical Shape and Covariates

Longitudinal regression analysis for clinical imaging studies is essential to investigate unknown relationships between subject-wise changes over time and subject-specific characteristics, represented by covariates such as disease severity or a level of genetic risk. Image-derived data in medical image analysis, e.g. diffusion tensors or geometric shapes, are often represented on nonlinear Riemannian manifolds. Hierarchical geodesic models were suggested to characterize subject-specific changes of nonlinear data on Riemannian manifolds as extensions of a linear mixed effects model. We propose a new hierarchical multi-geodesic model to enable analysis of the relationship between subject-wise anatomical shape changes on a Riemannian manifold and multiple subject-specific characteristics. Each individual subject-wise shape change is represented by a univariate geodesic model. The effects of subject-specific covariates on the estimated subject-wise trajectories are then modeled by multivariate intercept and slope models which together form a multi-geodesic model. Validation was performed with a synthetic example on a S ² manifold. The proposed method was applied to a longitudinal set of 72 corpus callosum shapes from 24 autism spectrum disorder subjects to study the relationship between anatomical shape changes and the autism severity score, resulting in statistics for the population but also for each subject. To our knowledge, this is the first longitudinal framework to model anatomical developments over time as functions of both continuous and categorical covariates on a nonlinear shape space.

Exploring cortical activation and connectivity in infants with and without familial risk for autism during naturalistic social interactions: A preliminary study

Behavioral signs of Autism Spectrum Disorder (ASD) are typically observable by the second year of life and a reliable diagnosis of ASD is possible by 2 to 3 years of age. Studying infants with familial risk for ASD allows for the investigation of early signs of ASD risk within the first year. Brain abnormalities such as hyper-connectivity within the first year may precede the overt signs of ASD that emerge later in life. In this preliminary study, we use functional near-infrared spectroscopy (fNIRS), an infant-friendly neuroimaging tool that is relatively robust against motion artifacts, to examine functional activation and connectivity during naturalistic social interactions in 9 high-risk (HR; older sibling with ASD) and 6 low-risk (LR; no family history of ASD) infants from 6 to 9 months of age. We obtained two 30-second baseline periods and a 5-minute social interaction period. HR infants showed reduced right and left-hemispheric activation compared to LR infants based on oxy (HbO₂) and deoxy (HHb) signal trends. HR infants also had greater functional connectivity than LR infants during the pre- and post-social periods and showed a drop in connectivity during the social period. Our findings are consistent with previous work suggesting early differences in cortical activation associated with familial risk for ASD, and highlight the promise of fNIRS in evaluating potential markers of ASD risk during naturalistic social contexts.

Autism spectrum disorder: Trends in research exploring etiopathogenesis

Autism spectrum disorder is a neurodevelopmental condition in which affected individuals have difficulties while interacting and communicating socially, and repetitive behaviors. It has a multifactorial etiology. Various risk factors, including genetic and environmental influences, have been explored while trying to understand its causation. As older evidence was suggestive of a high heritability, a majority of research focused on finding the underlying genetic causes of autism. Due to these efforts, there have been advances in the knowledge of some of the genetic factors associated with autism. But a recent trend also shows an increasing interest in exploration of various potential environmental triggers. These efforts have brought us closer to understanding the elusive disorder more so than ever before. The current review discusses the recent trends in research exploring the etiopathogenesis of autism spectrum disorder.

White matter alterations in adult with autism spectrum disorder evaluated using diffusion kurtosis imaging

PURPOSE

Autism spectrum disorder (ASD) is related to impairment in various white matter (WM) pathways. Utility of the recently developed two-compartment model of diffusion kurtosis imaging (DKI) to analyse axial diffusivity of WM is restricted by several limitations. The present study aims to validate the utility of model-free DKI in the evaluation of WM alterations in ASD and analyse the potential relationship between DKI-evident WM alterations and personality scales.

METHODS

Overall, 15 participants with ASD and 15 neurotypical (NT) controls were scanned on a 3 T magnetic resonance (MR) scanner, and scores for autism quotient (AQ), systemising quotient (SQ) and empathising quotient (EQ) were obtained for both groups. Multishell diffusion-weighted MR data were acquired using two b-values (1000 and 2000 s/mm²). Differences in mean kurtosis (MK), radial kurtosis (RK) and axial kurtosis (AK) between the groups were evaluated using tract-based spatial statistics (TBSS). Finally, the relationships between the kurtosis indices and personality quotients were examined.

RESULTS

The ASD group demonstrated significantly lower AK in the body and splenium of corpus callosum than the NT group; however, no other significant differences were identified. Negative correlations were found between AK and AQ or SQ, predominantly in WM areas related to social-emotional processing such as uncinate fasciculus, inferior fronto-occipital fasciculus, and inferior and superior longitudinal fasciculi.

CONCLUSIONS

Model-free DKI and its indices may represent a novel, objective method for detecting the disease severity and WM alterations in patients with ASD.

Eurosibs: Towards robust measurement of infant neurocognitive predictors of autism across Europe

•

The Eurosibs consortium is a nine-site European neurocognitive study of infants with an older sibling with ASD.

•

Data quality assessments show that that neurocognitive measures hold promise for cross-site consistency in diverse populations.

•

We present robust data analysis pipelines and highlight challenges and opportunities for future multisite research efforts.

Autism Spectrum Disorder (ASD) is a neurodevelopmental disorder that affects social communication skills and flexible behaviour. Developing new treatment approaches for ASD requires early identification of the factors that influence later behavioural outcomes. One fruitful research paradigm has been the prospective study of infants with a first degree relative with ASD, who have around a 20% likelihood of developing ASD themselves. Early findings have identified a range of candidate neurocognitive markers for later ASD such as delayed attention shifting or neural responses to faces, but given the early stage of the field most sample sizes are small and replication attempts remain rare. The Eurosibs consortium is a European multisite neurocognitive study of infants with an older sibling with ASD conducted across nine sites in five European countries. In this manuscript, we describe the selection and standardization of our common neurocognitive testing protocol. We report data quality assessments across sites, showing that neurocognitive measures hold great promise for cross-site consistency in diverse populations. We discuss our approach to ensuring robust data analysis pipelines and boosting future reproducibility. Finally, we summarise challenges and opportunities for future multi-site research efforts.

Atypicalities of Gesture Form and Function in Autistic Adults

While well-represented on clinical measures, co-speech gesture production has never been formally studied in autistic adults. Twenty-one verbally fluent autistic adults and 21 typically developing controls engaged in a controlled conversational task. Group differences were observed in both semantic/pragmatic and motoric features of spontaneously produced co-speech gestures. Autistic adults prioritized different functions of co-speech gesture. Specifically, they used gesture more than controls to facilitate conversational turn-taking, demonstrating a novel nonverbal strategy for regulating conversational dynamics. Autistic adults were more likely to gesture unilaterally than bilaterally, a motoric feature of gesture that was individually associated with autism symptoms. Co-speech gestures may provide a link between nonverbal communication symptoms and known differences in motor performance in autism.

Familial risk of autism alters subcortical and cerebellar brain anatomy in infants and predicts the emergence of repetitive behaviors in early childhood

Autism spectrum disorder (ASD) is a common neurodevelopmental condition, and infant siblings of children with ASD are at a higher risk of developing autistic traits or an ASD diagnosis, when compared to those with typically developing siblings. Reports of differences in brain anatomy and function in high-risk infants which predict later autistic behaviors are emerging, but although cerebellar and subcortical brain regions have been frequently implicated in ASD, no high-risk study has examined these regions. Therefore, in this study, we compared regional MRI volumes across the whole brain in 4-6-month-old infants with (high-risk, n = 24) and without (low-risk, n = 26) a sibling with ASD. Within the high-risk group, we also examined whether any regional differences observed were associated with autistic behaviors at 36 months. We found that high-risk infants had significantly larger cerebellar and subcortical volumes at 4-6-months of age, relative to low-risk infants; and that larger volumes in high-risk infants were linked to more repetitive behaviors at 36 months. Our preliminary observations require replication in longitudinal studies of larger samples. If correct, they suggest that the early subcortex and cerebellum volumes may be predictive biomarkers for childhood repetitive behaviors. Autism Res 2019, 12: 614-627. © 2019 The Authors. Autism Research published by International Society for Autism Research published byWiley Periodicals, Inc. LAY SUMMARY: Individuals with a family history of autism spectrum disorder (ASD) are at risk of ASD and related developmental difficulties. This study revealed that 4-6-month-old infants at high-risk of ASD have larger cerebellum and subcortical volumes than low-risk infants, and that larger volumes in high-risk infants are associated with more repetitive behaviors in childhood.

Functional EEG connectivity in infants associates with later restricted and repetitive behaviours in autism; a replication study

We conducted a replication study of our prior report that increased alpha EEG connectivity at 14-months associates with later autism spectrum disorder (ASD) diagnosis, and dimensional variation in restricted interests/repetitive behaviours. 143 infants at high and low familial risk for ASD watched dynamic videos of spinning toys and women singing nursery rhymes while high-density EEG was recorded. Alpha functional connectivity (7-8 Hz) was calculated using the debiased weighted phase lag index. The final sample with clean data included low-risk infants (N = 20), and high-risk infants who at 36 months showed either typical development (N = 47), atypical development (N = 21), or met criteria for ASD (N = 13). While we did not replicate the finding that global EEG connectivity associated with ASD diagnosis, we did replicate the association between higher functional connectivity at 14 months and greater severity of restricted and repetitive behaviours at 36 months in infants who met criteria for ASD. We further showed that this association is strongest for the circumscribed interests subdomain. We propose that structural and/or functional abnormalities in frontal-striatal circuits underlie the observed association. This is the first replicated infant neural predictor of dimensional variation in later ASD symptoms.

Sex differences of brain and their implications for personalized therapy

Nowadays, it is known that the sex differences regard many organs, e.g., liver, vessels, pancreas, lungs, bronchi and also the brain. Sex differences are not just a matter of ethical and moral principles, as they are central to explain many still unknown diseases and their understanding is a prerequisite to develop an effective therapy for each individual. This review reports on those sex differences that are not only macroscopic and morphological, but also involve molecular and functional dimorphism in the brain. It will recapitulate the main structural differences between male and female brain including the neurotransmission systems; in particular, the main objective is to identify a correlation, already known or to be investigated in the future, between the differences that characterize male and female brains from a morphological and biochemical point of view and neurological syndromes. This correlation could provide a starting point for future scientific research aimed to investigate and define a personalized therapy.

A review on neuroimaging studies of genetic and environmental influences on early brain development

The past decades witnessed a surge of interest in neuroimaging study of normal and abnormal early brain development. Structural and functional studies of normal early brain development revealed massive structural maturation as well as sequential, coordinated, and hierarchical emergence of functional networks during the infancy period, providing a great foundation for the investigation of abnormal early brain development mechanisms. Indeed, studies of altered brain development associated with either genetic or environmental risks emerged and thrived. In this paper, we will review selected studies of genetic and environmental risks that have been relatively more extensively investigated-familial risks, candidate risk genes, and genome-wide association studies (GWAS) on the genetic side; maternal mood disorders and prenatal drug exposures on the environmental side. Emerging studies on environment-gene interactions will also be reviewed. Our goal was not to perform an exhaustive review of all studies in the field but to leverage some representative ones to summarize the current state, point out potential limitations, and elicit discussions on important future directions.

Enhanced cerebellar myelination with concomitant iron elevation and ultrastructural irregularities following prenatal exposure to ambient particulate matter in the mouse

Accumulating evidence indicates the developing central nervous system (CNS) is a target of air pollution toxicity. Epidemiological reports increasingly demonstrate that exposure to the particulate matter (PM) fraction of air pollution during neurodevelopment is associated with an increased risk of neurodevelopmental disorders (NDDs) such as autism spectrum disorder (ASD). These observations are supported by animal studies demonstrating prenatal exposure to concentrated ambient PM induces neuropathologies characteristic of ASD, including ventriculomegaly and aberrant corpus callosum (CC) myelination. Given the role of the CC and cerebellum in ASD etiology, this study tested whether prenatal exposure to concentrated ambient particles (CAPs) produced pathological features in offspring CC and cerebella consistent with ASD. Analysis of cerebellar myelin density revealed male-specific hypermyelination in CAPs-exposed offspring at postnatal days (PNDs) 11-15 without alteration of cerebellar area. Atomic absorption spectroscopy (AAS) revealed elevated iron (Fe) in the cerebellum of CAPs-exposed female offspring at PNDs 11-15, which connects with previously observed elevated Fe in the female CC. The presence of Fe inclusions, along with aluminum (Al) and silicon (Si) inclusions, were confirmed at nanoscale resolution in the CC along with ultrastructural myelin sheath damage. Furthermore, RNAseq and gene ontology (GO) enrichment analyses revealed cerebellar gene expression was significantly affected by sex and prenatal CAPs exposure with significant enrichment in inflammation and transmembrane transport processes that could underlie observed myelin and metal pathologies. Overall, this study highlights the ability of PM exposure to disrupt myelinogenesis and elucidates novel molecular targets of PM-induced developmental neurotoxicity.

Cerebrospinal fluid and the early brain development of autism

BACKGROUND

There is currently a renaissance of interest in the many functions of cerebrospinal fluid (CSF). Altered flow of CSF, for example, has been shown to impair the clearance of pathogenic inflammatory proteins involved in neurodegenerative diseases, such as amyloid-β. In addition, the role of CSF in the newly discovered lymphatic system of the brain has become a prominently researched area in clinical neuroscience, as CSF serves as a conduit between the central nervous system and immune system.

MAIN BODY

This article will review the importance of CSF in regulating normal brain development and function, from the prenatal period throughout the lifespan, and highlight recent research that CSF abnormalities in autism spectrum disorder (ASD) are present in infancy, are detectable by conventional structural MRI, and could serve as an early indicator of altered neurodevelopment.

CONCLUSION

The identification of early CSF abnormalities in children with ASD, along with emerging knowledge of the underlying pathogenic mechanisms, has the potential to serve as early stratification biomarkers that separate children with ASD into biological subtypes that share a common pathophysiology. Such subtypes could help parse the phenotypic heterogeneity of ASD and map on to targeted, biologically based treatments.

Role of Microtubule-Associated Protein in Autism Spectrum Disorder

Autism spectrum disorder (ASD) is a neurodevelopmental disorder characterized by deficits in social interaction and communication, along with repetitive and restrictive patterns of behaviors or interests. Normal brain development is crucial to behavior and cognition in adulthood. Abnormal brain development, such as synaptic and myelin dysfunction, is involved in the pathogenesis of ASD. Microtubules and microtubule-associated proteins (MAPs) are important in regulating the processes of brain development, including neuron production and synaptic formation, as well as myelination. Increasing evidence suggests that the level of MAPs are changed in autistic patients and mouse models of ASD. Here, we discuss the roles of MAPs.

Unsupervised Manifold Learning Using High-Order Morphological Brain Networks Derived From T1-w MRI for Autism Diagnosis

Brain disorders, such as Autism Spectrum Disorder (ASD), alter brain functional (from fMRI) and structural (from diffusion MRI) connectivities at multiple levels and in varying degrees. While unraveling such alterations have been the focus of a large number of studies, morphological brain connectivity has been out of the research scope. In particular, shape-to-shape relationships across brain regions of interest (ROIs) were rarely investigated. As such, the use of networks based on morphological brain data in neurological disorder diagnosis, while leveraging the advent of machine learning, could complement our knowledge on brain wiring alterations in unprecedented ways. In this paper, we use conventional T1-weighted MRI to define morphological brain networks (MBNs), each quantifying shape relationship between different cortical regions for a specific cortical attribute at both low-order and high-order levels. While typical brain connectomes investigate the relationship between two ROIs, we propose high-order MBN which better captures brain complex interactions by modeling the morphological relationship between pairs of ROIs. For ASD identification, we present a connectomic manifold learning framework, which learns multiple kernels to estimate a similarity measure between ASD and normal controls (NC) connectional features, to perform dimensionality reduction for clustering ASD and NC subjects. We benchmark our ASD identification method against both supervised and unsupervised state-of-the-art methods, while depicting the most discriminative high- and low-order relationships between morphological regions in the left and right hemispheres.

The effect of age on vertex-based measures of the grey-white matter tissue contrast in autism spectrum disorder

Background

Histological evidence suggests that autism spectrum disorder (ASD) is accompanied by a reduced integrity of the grey-white matter boundary. This has also recently been confirmed by a structural neuroimaging study in vivo reporting significantly reduced grey-white matter tissue contrast (GWC) in adult individuals (18–42 years of age) with ASD relative to typically developing (TD) controls. However, it remains unknown whether the neuroanatomical differences in ASD at the grey-white matter boundary are stable across development or are age-dependent.

Methods

Here, we examined differences in the neurodevelopmental trajectories of GWC in a cross-sectional sample of 77 male ASD individuals and 76 typically developing (TD) controls across childhood and early adulthood (from 7 to 25 years).

Results

Using nested model comparisons, we first established that the developmental trajectory of GWC is complex in many regions across the cortex and includes linear and non-linear effects of age. Second, while ASD individuals have significantly reduced GWC overall, these differences are age-dependent and are most prominent during childhood (< 15 years).

Conclusions

Taken together, our findings suggest that differences in GWC in ASD are unlikely to reflect atypical grey matter cytoarchitecture alone, but may also represent other aspects of the cortical architecture such as age-dependent variability in myelin integrity.

Electronic supplementary material

The online version of this article (10.1186/s13229-018-0232-6) contains supplementary material, which is available to authorized users.

Insights from perceptual, sensory, and motor functioning in autism and cerebellar primary disturbances: Are there reliable markers for these disorders?

The contribution of cerebellar circuitry alterations in the pathophysiology of Autism Spectrum Disorder (ASD) has been widely investigated in the last decades. Yet, experimental studies on neurocognitive markers of ASD have not been attentively compared with similar studies in patients with cerebellar primary disturbances (e.g., malformations, agenesis, degeneration, etc). Addressing this neglected issue could be useful to underline unexpected areas of overlap and/or underestimated differences between these sets of conditions. In fact, ASD and cerebellar primary disturbances (notably, Cerebellar Cognitive Affective Syndrome, CCAS) can share atypical manifestations in perceptual, sensory, and motor functions, but neural subcircuits involved in these anomalies/difficulties could be distinct. Here, we specifically deal with this issue focusing on four paradigmatic neurocognitive functions: visual and biological motion perception, multisensory integration, and high stages of the motor hierarchy. From a research perspective, this represents an essential challenge to more deeply understand neurocognitive markers of ASD and of cerebellar primary disturbances/CCAS. Although we cannot assume definitive conclusions, and beyond phenotypical similarities between ASD and CCAS, clinical and experimental evidence described in this work argues that ASD and CCAS are distinct phenomena. ASD and CCAS seem to be characterized by different pathophysiological mechanisms and mediated by distinct neural nodes. In parallel, from a clinical perspective, this characterization may furnish insights to tackle the distinction between autistic functioning/autistic phenotype (in ASD) and dysmetria of thought/autistic-like phenotype (in CCAS).

Prioritized High-Confidence Risk Genes for Intellectual Disability Reveal Molecular Convergence During Brain Development

Dissecting the genetic susceptibility to intellectual disability (ID) based on de novo mutations (DNMs) will aid our understanding of the neurobiological and genetic basis of ID. In this study, we identify 63 high-confidence ID genes with q-values < 0.1 based on four background DNM rates and coding DNM data sets from multiple sequencing cohorts. Bioinformatic annotations revealed a higher burden of these 63 ID genes in FMRP targets and CHD8 targets, and these genes show evolutionary constraint against functional genetic variation. Moreover, these ID risk genes were preferentially expressed in the cortical regions from the early fetal to late mid-fetal stages. In particular, a genome-wide weighted co-expression network analysis suggested that ID genes tightly converge onto two biological modules (M1 and M2) during human brain development. Functional annotations showed specific enrichment of chromatin modification and transcriptional regulation for M1 and synaptic function for M2, implying the divergent etiology of the two modules. In addition, we curated 12 additional strong ID risk genes whose molecular interconnectivity with known ID genes (q-values < 0.3) was greater than random. These findings further highlight the biological convergence of ID risk genes and help improve our understanding of the genetic architecture of ID.

Brain and behavior development in autism from birth through infancy

Autism spectrum disorder (ASD) is a heterogeneous condition that affects 1 in 68 children. Diagnosis is based on the presence of characteristic behavioral impairments that emerge in the second year of life and thus is not typically made until 3 to 4 years of age. Recent studies of early brain and behavior development have provided important new insights into the nature of this condition. Autism-specific brain imaging features have been identified as early as 6 months of age, and age-specific brain and behavior changes have been demonstrated across the first 2 years of life, highlighting the developmental nature of ASD. New findings demonstrate that early brain imaging in the first year of life holds great promise for presymptomatic prediction of ASD. There is a general understanding in medicine that earlier treatment has better outcomes than later treatment, and in autism, there is an emerging consensus that earlier intervention results in more successful outcomes for the child. Examining early brain and behavior trajectories also has the potential to parse the etiologic heterogeneity in ASD, a well-recognized impediment to developing targeted, mechanistic treatments. This review highlights the current state of the science in the pursuit of early brain and behavioral markers of autism during infancy and examines the potential implications of these findings for treatment of this condition.

Differences in Neural Correlates of Speech Perception in 3 Month Olds at High and Low Risk for Autism Spectrum Disorder

In this study, we investigated neural precursors of language acquisition as potential endophenotypes of autism spectrum disorder (ASD) in 3-month-old infants at high and low familial ASD risk. Infants were imaged using functional near-infrared spectroscopy while they listened to auditory stimuli containing syllable repetitions; their neural responses were analyzed over left and right temporal regions. While female low risk infants showed initial neural activation that decreased over exposure to repetition-based stimuli, potentially indicating a habituation response to repetition in speech, female high risk infants showed no changes in neural activity over exposure. This finding may indicate a potential neural endophenotype of language development or ASD specific to females at risk for the disorder.

Behavioral Phenotype of ASD Preschoolers with Gastrointestinal Symptoms or Food Selectivity

This study investigated the prevalence and type of gastrointestinal (GI) and food selectivity (FS) symptoms in 163 preschoolers with ASD, and their possible links with core ASD features and emotional/behavioural problems. 40.5% of children with ASD had at least one severe GI symptom or FS. Preschoolers with and without GI symptoms and with and without FS were significantly different on several emotional/behavioural problems and restrictive/repetitive behaviours, whereas they did not differ significantly on performance IQ and autistic severity. The GI plus FS group presented with Sleep Problems, Self-injurious Behaviors and Anxiety Problems. Results indicated the need for early identification of GI disturbances and FS in order to design tailored intervention for these symptoms frequently associated to challenging behaviours in ASD.

The neural circuitry of restricted repetitive behavior: Magnetic resonance imaging in neurodevelopmental disorders and animal models

Restricted, repetitive behaviors (RRBs) are patterns of behavior that exhibit little variation in form and have no obvious function. RRBs although transdiagonstic are a particularly prominent feature of certain neurodevelopmental disorders, yet relatively little is known about the neural circuitry of RRBs. Past work in this area has focused on isolated brain regions and neurotransmitter systems, but implementing a neural circuit approach has the potential to greatly improve understanding of RRBs. Magnetic resonance imaging (MRI) is well-suited to studying the structural and functional connectivity of the nervous system, and is a highly translational research tool. In this review, we synthesize MRI research from both neurodevelopmental disorders and relevant animal models that informs the neural circuitry of RRB. Together, these studies implicate distributed neural circuits between the cortex, basal ganglia, and cerebellum. Despite progress in neuroimaging of RRB, there are many opportunities for conceptual and methodological improvement. We conclude by suggesting future directions for MRI research in RRB, and how such studies can benefit from complementary approaches in neuroscience.

Development of White Matter Circuitry in Infants With Fragile X Syndrome

IMPORTANCE

Fragile X syndrome (FXS) is a genetic neurodevelopmental disorder and the most common inherited cause of intellectual disability in males. However, there are no published data on brain development in children with FXS during infancy.

OBJECTIVE

To characterize the development of white matter at ages 6, 12, and 24 months in infants with FXS compared with that of typically developing controls.

DESIGN, SETTING, AND PARTICIPANTS

Longitudinal behavioral and brain imaging data were collected at 1 or more time points from 27 infants with FXS and 73 typically developing controls between August 1, 2008, and June 14, 2016, at 2 academic medical centers. Infants in the control group had no first- or second-degree relatives with intellectual or psychiatric disorders, including FXS and autism spectrum disorder.

MAIN OUTCOMES AND MEASURES

Nineteen major white matter pathways were defined in common atlas space based on anatomically informed methods. Diffusion parameters, including fractional anisotropy, were compared between groups using linear mixed effects modeling. Fiber pathways showing group differences were subsequently examined in association with direct measures of verbal and nonverbal development.

RESULTS

There were significant differences in the development of 12 of 19 fiber tracts between the 27 infants with FXS (22 boys and 5 girls) and the 73 infants in the control group (46 boys and 27 girls), with lower fractional anisotropy in bilateral subcortical-frontal, occipital-temporal, temporal-frontal, and cerebellar-thalamic pathways, as well as 4 of 6 subdivisions of the corpus callosum. For all 12 of these pathways, there were significant main effects between groups but not for the interaction of age × group, indicating that lower fractional anisotropy was present and stable from age 6 months in infants with FXS. Lower fractional anisotropy values in the uncinate fasciculi were correlated with lower nonverbal developmental quotient in the FXS group (left uncinate, F = 10.06; false discovery rate-corrected P = .03; right uncinate, F = 21.8; P = .004).

CONCLUSIONS AND RELEVANCE

The results substantiate in human infants the essential role of fragile X gene expression in the early development of white matter. The findings also suggest that the neurodevelopmental effects of FXS are well established at 6 months of age.

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.

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.

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.

Loss of skills and onset patterns in neurodevelopmental disorders: Understanding the neurobiological mechanisms

Patterns of onset in Autism Spectrum Disorder, including a pattern that includes loss of previously acquired skills, have been identified since the first reports of the disorder. However, attempts to study such "regression" have been limited to clinical studies, that until recently mostly involved retrospective reports. The current report reflects discussion that occurred at an NIMH convened meeting in 2016 with the purpose of bridging clinical autism research with basic and translational work in this area. This summary describes the state of the field with respect to clinical studies, describing gaps in knowledge based on limited methods and prospective data collected. Biological mechanisms that have been shown to account for regression early in development in specific conditions are discussed, as well as potential mechanisms that have not yet been explored. Suggestions include use of model systems during the developmental period and cutting-edge methods, including non-invasive imaging that may afford opportunities for a better understanding of the neurobiological pathways that result in loss of previously-attained skills. Autism Res 2018, 11: 212-222. © 2017 International Society for Autism Research, Wiley Periodicals, Inc.

LAY SUMMARY

Loss of previously acquired skills, or regression, has been reported in Autism Spectrum Disorder since Kanner's reports in the 1950's. The current report reflects discussion from an NIMH convened meeting in 2016 with the purpose of bridging clinical autism research with basic and translational work in this area. This summary describes the state of the field regarding clinical studies and suggests use of model systems during the developmental period and cutting-edge methods, for a better understanding of the neurobiological pathways that result in loss of previously-attained skills.

Toddlers later diagnosed with autism exhibit multiple structural abnormalities in temporal corpus callosum fibers

Interhemispheric functional connectivity abnormalities are often reported in autism and it is thus not surprising that structural defects of the corpus callosum (CC) are consistently found using both traditional MRI and DTI techniques. Past DTI studies however, have subdivided the CC into 2 or 3 segments without regard for where fibers may project to within the cortex, thus placing limitations on our ability to understand the nature, timing and neurobehavioral impact of early CC abnormalities in autism. Leveraging a unique cohort of 97 toddlers (68 autism; 29 typical) we utilized a novel technique that identified seven CC tracts according to their cortical projections. Results revealed that younger (<2.5 years old), but not older toddlers with autism exhibited abnormally low mean, radial, and axial diffusivity values in the CC tracts connecting the occipital lobes and the temporal lobes. Fractional anisotropy and the cross sectional area of the temporal CC tract were significantly larger in young toddlers with autism. These findings indicate that water diffusion is more restricted and unidirectional in the temporal CC tract of young toddlers who develop autism. Such results may be explained by a potential overabundance of small caliber axons generated by excessive prenatal neural proliferation as proposed by previous genetic, animal model, and postmortem studies of autism. Furthermore, early diffusion measures in the temporal CC tract of the young toddlers were correlated with outcome measures of autism severity at later ages. These findings regarding the potential nature, timing, and location of early CC abnormalities in autism add to accumulating evidence, which suggests that altered inter-hemispheric connectivity, particularly across the temporal lobes, is a hallmark of the disorder.

Atypical age-dependency of executive function and white matter microstructure in children and adolescents with autism spectrum disorders

Executive function (EF) performance is associated with measurements of white matter microstructure (WMS) in typical individuals. Impaired EF is a hallmark symptom of autism spectrum disorders (ASD) but it is unclear how impaired EF relates to variability in WMS. Twenty-one male youth (8-18 years) with ASD and without intellectual disability and twenty-one typical male participants (TP) matched for age, intelligence quotient, handedness, race and parental socioeconomic status were recruited. Five EF domains were assessed and several DTI-based measurements of WMS [fractional anisotropy (FA), mean diffusivity (MD) and radial diffusivity (RD)] were estimated for eighteen white matter tracts. The ASD group had lower scores for attention (F = 8.37, p = 0.006) and response inhibition (F = 13.09, p = 0.001). Age-dependent changes of EF performance and WMS measurements were present in TP but attenuated in the ASD group. The strongest diagnosis-by-age effect was found for forceps minor, left anterior thalamic radiation and left cingulum angular bundle (all p's ≤ 0.002). In these tracts subjects with ASD tended to have equal or increased FA and/or reduced MD and/or RD at younger ages while controls had increased FA and/or reduced MD and/or RD thereafter. Only for TP individuals, increased FA in the left anterior thalamic radiation was associated with better response inhibition, while reduced RD in forceps minor and left cingulum angular bundle was related to better problem solving and working memory performance respectively. These findings provide novel insight into the age-dependency of EF performance and WMS in ASD, which can be instructive to cognitive training programs.

Ulk4 deficiency leads to hypomyelination in mice

Brain nerve fibers are insulated by myelin which is produced by oligodendrocytes. Defects in myelination are increasingly recognized as a common pathology underlying neuropsychiatric and neurodevelopmental disorders, which are associated with deletions of the Unc-51-like kinase 4 (ULK4) gene. Key transcription factors have been identified for oligodendrogenesis, but little is known about their associated regulators. Here we report that Ulk4 acts as a key regulator of myelination. Myelination is reduced by half in the Ulk4^tm1a/tm1a hypomorph brain, whereas expression of axonal marker genes Tubb3, Nefh, Nefl and Nefm remains unaltered. Transcriptome analyses reveal that 8 (Gfap, Mbp, Mobp, Plp1, Slc1a2, Ttr, Cnp, Scd2) of the 10 most significantly altered genes in the Ulk4^tm1a/tm1a brain are myelination-related. Ulk4 is co-expressed in Olig2⁺ (pan-oligodendrocyte marker) and CC1⁺ (mature myelinated oligodendrocyte marker) cells during postnatal development. Major oligodendrogeneic transcription factors, including Olig2, Olig1, Myrf, Sox10, Sox8, Sox6, Sox17, Nkx2-2, Nkx6-2 and Carhsp1, are significantly downregulated in the mutants. mRNA transcripts enriched in oligodendrocyte progenitor cells (OPCs), the newly formed oligodendrocytes (NFOs) and myelinating oligodendrocytes (MOs), are significantly attenuated. Expression of stage-specific oligodendrocyte factors including Cspg4, Sox17, Nfasc, Enpp6, Sirt2, Cnp, Plp1, Mbp, Ugt8, Mag and Mog are markedly decreased. Indirect effects of axon caliber and neuroinflammation may also contribute to the hypomyelination, as Ulk4 mutants display smaller axons and increased neuroinflammation. This is the first evidence demonstrating that ULK4 is a crucial regulator of myelination, and ULK4 may therefore become a novel therapeutic target for hypomyelination diseases.

Toward a conceptual framework for early brain and behavior development in autism

Studies of infant siblings of older autistic probands, who are at elevated risk for autism, have demonstrated that the defining features of autism are not present in the first year of life but emerge late in the first and into the second year. A recent longitudinal neuroimaging study of high-risk siblings revealed a specific pattern of brain development in infants later diagnosed with autism, characterized by cortical surface area hyper-expansion in the first year followed by brain volume overgrowth in the second year that is associated with the emergence of autistic social deficits. Together with new observations from genetically defined autism risk alleles and rodent model, these findings suggest a conceptual framework for the early, post-natal development of autism. This framework postulates that an increase in the proliferation of neural progenitor cells and hyper-expansion of cortical surface area in the first year, occurring during a pre-symptomatic period characterized by disrupted sensorimotor and attentional experience, leads to altered experience-dependent neuronal development and decreased elimination of neuronal processes. This process is linked to brain volume overgrowth and disruption of the refinement of neural circuit connections and is associated with the emergence of autistic social deficits in the second year of life. A better understanding of the timing of developmental brain and behavior mechanisms in autism during infancy, a period which precedes the emergence of the defining features of this disorder, will likely have important implications for designing rational approaches to early intervention.

Long-term outcome of autistic spectrum disorder: a retrospective case study in a southern italian region

Background

Autism Spectrum Disorder (ASD) is a complex neurodevelopmental disorder, characterized by impaired social communication and restricted and repetitive behaviours, as well as associated features including intellectual disability and impaired sensorimotor function.

Despite a growing interest in this devastating disorder for families and young parents, there are no certainties as regards its aetiology, although a significant genetic background is considered to be important.

Since there is little information about the social adaptation and quality of life of patients with Autism Spectrum Disorder, we decided to study and evaluate the long-term outcome and quality of life in a sample of children, adolescent and young adults.

Methods

This is a case study of subjects diagnosed with ASD and followed by clinics and rehabilitation centers in Campania region, in the south of Italy.

The study sample was composed by 110 patients (83 males, 27 females), aged between 8.1 and 28.0 years (mean 20.6; median 21.2; SD ± 4.85), recruited in 8 rehabilitation centers of Campania region.

A follow-up interview was performed by means of a questionnaire administered to the parents/caregivers of patients at a mean age of their son/daughter of 20.6 years (median 21.2 years; range 8.1-28.0).

Results

Reports from parents or caregivers show an overall improvement with regard to social and adaptive abilities in a group of teen-agers and young adults with ASD.

Major concerns on significant quality of life parameters such as independent living, work experiences, friendships and relationships, accommodation type, recreational activities and personal autonomy were persisting.

Conclusions

The present study shows an overall improvement with regard to social and adaptive abilities in a large number of subjects. Considerable problems are related to autonomy, employment opportunities and social relationships of these patients. Parents need more recreational activities and continuous support with facilities for families.

A Riemannian Framework for Linear and Quadratic Discriminant Analysis on the Tangent Space of Shapes

We present a Riemannian framework for linear and quadratic discriminant classification on the tangent plane of the shape space of curves. The shape space is infinite dimensional and is constructed out of square root velocity functions of curves. We introduce the notion of mean and covariance of shape-valued random variables and samples from a tangent space to the pre-shapes (invariant to translation and scaling) and then extend it to the full shape space (rotational invariance). The shape observations from the population are approximated by coefficients of a Fourier basis of the tangent space. The algorithms for linear and quadratic discriminant analysis are then defined using reduced dimensional features obtained by projecting the original shape observations on to the truncated Fourier basis. We show classification results on synthetic data and shapes of cortical sulci, corpus callosum curves, as well as facial midline curve profiles from patients with fetal alcohol syndrome (FAS).