Longitudinal magnetic resonance imaging study of cortical development through early childhood in autism

Eigenvector Centrality Characterization on fMRI Data: Gender and Node Differences in Normal and ASD Subjects : Author name

With the budding interests of structural and functional network characteristics as potential parameters for abnormal brains, an essential and thus simpler representation and evaluations have become necessary. Eigenvector centrality measure of functional magnetic resonance imaging (fMRI) offer region wise network representations through fMRI diagnostic maps. The article investigates the suitability of network node centrality values to discriminate ASD subject groups compared to typically developing controls following a boxplot formalism and a classification and regression tree model. Region wise differences between normal and ASD subjects primarily belong to the frontoparietal, limbic, ventral attention, default mode and visual networks. The reduced number of regions-of-interests (ROI) clearly suggests the benefit of automated supervised machine learning algorithm over the manual classification method.

Differences in regional brain structure in toddlers with autism are related to future language outcomes

Language and social symptoms improve with age in some autistic toddlers, but not in others, and such outcome differences are not clearly predictable from clinical scores alone. Here we aim to identify early-age brain alterations in autism that are prognostic of future language ability. Leveraging 372 longitudinal structural MRI scans from 166 autistic toddlers and 109 typical toddlers and controlling for brain size, we find that, compared to typical toddlers, autistic toddlers show differentially larger or thicker temporal and fusiform regions; smaller or thinner inferior frontal lobe and midline structures; larger callosal subregion volume; and smaller cerebellum. Most differences are replicated in an independent cohort of 75 toddlers. These brain alterations improve accuracy for predicting language outcome at 6-month follow-up beyond intake clinical and demographic variables. Temporal, fusiform, and inferior frontal alterations are related to autism symptom severity and cognitive impairments at early intake ages. Among autistic toddlers, brain alterations in social, language and face processing areas enhance the prediction of the child's future language ability.

Systematic review and meta-analysis: multimodal functional and anatomical neural alterations in autism spectrum disorder

BACKGROUND

This meta-analysis aimed to explore the most robust findings across numerous existing resting-state functional imaging and voxel-based morphometry (VBM) studies on the functional and structural brain alterations in individuals with autism spectrum disorder (ASD).

METHODS

A whole-brain voxel-wise meta-analysis was conducted to compare the differences in the intrinsic functional activity and gray matter volume (GMV) between individuals with ASD and typically developing individuals (TDs) using Seed-based d Mapping software.

RESULTS

A total of 23 functional imaging studies (786 ASD, 710 TDs) and 52 VBM studies (1728 ASD, 1747 TDs) were included. Compared with TDs, individuals with ASD displayed resting-state functional decreases in the left insula (extending to left superior temporal gyrus [STG]), bilateral anterior cingulate cortex/medial prefrontal cortex (ACC/mPFC), left angular gyrus and right inferior temporal gyrus, as well as increases in the right supplementary motor area and precuneus. For VBM meta-analysis, individuals with ASD displayed decreased GMV in the ACC/mPFC and left cerebellum, and increased GMV in the left middle temporal gyrus (extending to the left insula and STG), bilateral olfactory cortex, and right precentral gyrus. Further, individuals with ASD displayed decreased resting-state functional activity and increased GMV in the left insula after overlapping the functional and structural differences.

CONCLUSIONS

The present multimodal meta-analysis demonstrated that ASD exhibited similar alterations in both function and structure of the insula and ACC/mPFC, and functional or structural alterations in the default mode network (DMN), primary motor and sensory regions. These findings contribute to further understanding of the pathophysiology of ASD.

Autism-associated brain differences can be observed in utero using MRI

Developmental changes that occur before birth are thought to be associated with the development of autism spectrum disorders. Identifying anatomical predictors of early brain development may contribute to our understanding of the neurobiology of autism spectrum disorders and allow for earlier and more effective identification and treatment of autism spectrum disorders. In this study, we used retrospective clinical brain magnetic resonance imaging data from fetuses who were diagnosed with autism spectrum disorders later in life (prospective autism spectrum disorders) in order to identify the earliest magnetic resonance imaging-based regional volumetric biomarkers. Our results showed that magnetic resonance imaging-based autism spectrum disorder biomarkers can be found as early as in the fetal period and suggested that the increased volume of the insular cortex may be the most promising magnetic resonance imaging-based fetal biomarker for the future emergence of autism spectrum disorders, along with some additional, potentially useful changes in regional volumes and hemispheric asymmetries.

Passive exposure to visual motion leads to short-term changes in the optomotor response of aging zebrafish

Numerous studies have shown that prior visual experiences play an important role in sensory processing and adapting behavior in a dynamic environment. A repeated and passive presentation of visual stimulus is one of the simplest procedures to manipulate acquired experiences. Using this approach, we aimed to investigate exposure-based visual learning of aging zebrafish and how cholinergic intervention is involved in exposure-induced changes. Our measurements included younger and older wild-type zebrafish and achesb55/+ mutants with decreased acetylcholinesterase activity. We examined both within-session and across-day changes in the zebrafish optomotor responses to repeated and passive exposure to visual motion. Our findings revealed short-term (within-session) changes in the magnitude of optomotor response (i.e., the amount of position shift by fish as a response to visual motion) rather than long-term and persistent effects across days. Moreover, the observed short-term changes were age- and genotype-dependent. Compared to the initial presentations of motion within a session, the magnitude of optomotor response to terminal presentations decreased in the older zebrafish. There was a similar robust decrease specific to achesb55/+ mutants. Taken together, these results point to short-term (within-session) alterations in the motion detection of adult zebrafish and suggest differential effects of neural aging and cholinergic system on the observed changes. These findings further provide important insights into adult zebrafish optomotor response to visual motion and contribute to understanding this reflexive behavior in the short- and long-term stimulation profiles.

Deep learning-based, fully automated, pediatric brain segmentation

The purpose of this study was to demonstrate the performance of a fully automated, deep learning-based brain segmentation (DLS) method in healthy controls and in patients with neurodevelopmental disorders, SCN1A mutation, under eleven. The whole, cortical, and subcortical volumes of previously enrolled 21 participants, under 11 years of age, with a SCN1A mutation, and 42 healthy controls, were obtained using a DLS method, and compared to volumes measured by Freesurfer with manual correction. Additionally, the volumes which were calculated with the DLS method between the patients and the control group. The volumes of total brain gray and white matter using DLS method were consistent with that volume which were measured by Freesurfer with manual correction in healthy controls. Among 68 cortical parcellated volume analysis, the volumes of only 7 areas measured by DLS methods were significantly different from that measured by Freesurfer with manual correction, and the differences decreased with increasing age in the subgroup analysis. The subcortical volume measured by the DLS method was relatively smaller than that of the Freesurfer volume analysis. Further, the DLS method could perfectly detect the reduced volume identified by the Freesurfer software and manual correction in patients with SCN1A mutations, compared with healthy controls. In a pediatric population, this new, fully automated DLS method is compatible with the classic, volumetric analysis with Freesurfer software and manual correction, and it can also well detect brain morphological changes in children with a neurodevelopmental disorder.

Autism Spectrum Disorder: Brain Areas Involved, Neurobiological Mechanisms, Diagnoses and Therapies

Autism spectrum disorder (ASD), affecting over 2% of the pre-school children population, includes an important fraction of the conditions accounting for the heterogeneity of autism. The disease was discovered 75 years ago, and the present review, based on critical evaluations of the recognized ASD studies from the beginning of 1990, has been further developed by the comparative analyses of the research and clinical reports, which have grown progressively in recent years up to late 2023. The tools necessary for the identification of the ASD disease and its related clinical pathologies are genetic and epigenetic mutations affected by the specific interaction with transcription factors and chromatin remodeling processes occurring within specific complexes of brain neurons. Most often, the ensuing effects induce the inhibition/excitation of synaptic structures sustained primarily, at dendritic fibers, by alterations of flat and spine response sites. These effects are relevant because synapses, established by specific interactions of neurons with glial cells, operate as early and key targets of ASD. The pathology of children is often suspected by parents and communities and then confirmed by ensuing experiences. The final diagnoses of children and mature patients are then completed by the combination of neuropsychological (cognitive) tests and electro-/magneto-encephalography studies developed in specialized centers. ASD comorbidities, induced by processes such as anxieties, depressions, hyperactivities, and sleep defects, interact with and reinforce other brain diseases, especially schizophrenia. Advanced therapies, prescribed to children and adult patients for the control of ASD symptoms and disease, are based on the combination of well-known brain drugs with classical tools of neurologic and psychiatric practice. Overall, this review reports and discusses the advanced knowledge about the biological and medical properties of ASD.

Diagnosing autism severity associated with physical fitness and gray matter volume in children with autism spectrum disorder: Explainable machine learning method

PURPOSE

This study aimed to investigate the relationship between physical fitness, gray matter volume (GMV), and autism severity in children with autism spectrum disorder (ASD). Besides, we sought to diagnose autism severity associated with physical fitness and GMV using machine learning methods.

METHODS

Ninety children diagnosed with ASD underwent physical fitness tests, magnetic resonance imaging scans, and autism severity assessments. Diagnosis models were established using extreme gradient boosting (XGB), random forest (RF), support vector machine (SVM), and decision tree (DT) algorithms. Hyperparameters were optimized through the grid search cross-validation method. The shapley additive explanation (SHAP) method was employed to explain the diagnosis results.

RESULTS

Our study revealed associations between muscular strength in physical fitness and GMV in specific brain regions (left paracentral lobule, bilateral thalamus, left inferior temporal gyrus, and cerebellar vermis I-II) with autism severity in children with ASD. The accuracy (95 % confidence interval) of the XGB, RF, SVM, and DT models were 77.9 % (77.3, 78.6 %), 72.4 % (71.7, 73.2 %), 71.9 % (71.1, 72.6 %), and 66.9 % (66.2, 67.7 %), respectively. SHAP analysis revealed that muscular strength and thalamic GMV significantly influenced the decision-making process of the XGB model.

CONCLUSION

Machine learning methods can effectively diagnose autism severity associated with physical fitness and GMV in children with ASD. In this respect, the XGB model demonstrated excellent performance across various indicators, suggesting its potential for diagnosing autism severity.

Reduced covariation between brain morphometry and local spontaneous activity in young children with ASD

While disruptions in brain maturation in the first years of life in ASD are well documented, little is known about how the brain structure and function are related in young children with ASD compared to typically developing peers. We applied a multivariate pattern analysis to examine the covariation patterns between brain morphometry and local brain spontaneous activity in 38 toddlers and preschoolers with ASD and 31 typically developing children using T1-weighted structural MRI and resting-state fMRI data acquired during natural sleep. The results revealed significantly reduced brain structure-function correlations in ASD. The resultant brain structure and function composite indices were associated with age among typically developing children, but not among those with ASD, suggesting mistiming of typical brain maturational trajectories early in life in autism. Additionally, the brain function composite indices were associated with the overall developmental and adaptive behavior skills in the ASD group, highlighting the neurodevelopmental significance of early local brain activity in autism.

Whole-brain gray matter maturation trajectories associated with autistic traits from adolescence to early adulthood

A growing number of evidence supports a continued distribution of autistic traits in the general population. However, brain maturation trajectories of autistic traits as well as the influence of sex on these trajectories remain largely unknown. We investigated the association of autistic traits in the general population, with longitudinal gray matter (GM) maturation trajectories during the critical period of adolescence. We assessed 709 community-based adolescents (54.7% women) at age 14 and 22. After testing the effect of sex, we used whole-brain voxel-based morphometry to measure longitudinal GM volumes changes associated with autistic traits measured by the Social Responsiveness Scale (SRS) total and sub-scores. In women, we observed that the SRS was associated with slower GM volume decrease globally and in the left parahippocampus and middle temporal gyrus. The social communication sub-score correlated with slower GM volume decrease in the left parahippocampal, superior temporal gyrus, and pallidum; and the social cognition sub-score correlated with slower GM volume decrease in the left middle temporal gyrus, the right ventromedial prefrontal and orbitofrontal cortex. No longitudinal association was found in men. Autistic traits in young women were found to be associated with specific brain trajectories in regions of the social brain and the reward circuit known to be involved in Autism Spectrum Disorder. These findings support both the hypothesis of an earlier GM maturation associated with autistic traits in adolescence and of protective mechanisms in women. They advocate for further studies on brain trajectories associated with autistic traits in women.

Brain-charting autism and attention deficit hyperactivity disorder reveals distinct and overlapping neurobiology

Background

Autism and attention deficit hyperactivity disorder (ADHD) are heterogeneous neurodevelopmental conditions with complex underlying neurobiology. Despite overlapping presentation and sex-biased prevalence, autism and ADHD are rarely studied together, and sex differences are often overlooked. Normative modelling provides a unified framework for studying age-specific and sex-specific divergences in neurodivergent brain development.

Methods

Here we use normative modelling and a large, multi-site neuroimaging dataset to characterise cortical anatomy associated with autism and ADHD, benchmarked against models of typical brain development based on a sample of over 75,000 individuals. We also examined sex and age differences, relationship with autistic traits, and explored the co-occurrence of autism and ADHD (autism+ADHD).

Results

We observed robust neuroanatomical signatures of both autism and ADHD. Overall, autistic individuals showed greater cortical thickness and volume localised to the superior temporal cortex, whereas individuals with ADHD showed more global effects of cortical thickness increases but lower cortical volume and surface area across much of the cortex. The autism+ADHD group displayed a unique pattern of widespread increases in cortical thickness, and certain decreases in surface area. We also found evidence that sex modulates the neuroanatomy of autism but not ADHD, and an age-by-diagnosis interaction for ADHD only.

Conclusions

These results indicate distinct cortical differences in autism and ADHD that are differentially impacted by age, sex, and potentially unique patterns related to their co-occurrence.

Investigating Sex-Based Neural Differences in Autism and Their Extended Reality Intervention Implications

Autism Spectrum Disorder (ASD) affects millions of individuals worldwide, and there is growing interest in the use of extended reality (XR) technologies for intervention. Despite the promising potential of XR interventions, there remain gaps in our understanding of the neurobiological mechanisms underlying ASD, particularly in relation to sex-based differences. This scoping review synthesizes the current research on brain activity patterns in ASD, emphasizing the implications for XR interventions and neurofeedback therapy. We examine the brain regions commonly affected by ASD, the potential benefits and drawbacks of XR technologies, and the implications of sex-specific differences for designing effective interventions. Our findings underscore the need for ongoing research into the neurobiological underpinnings of ASD and sex-based differences, as well as the importance of developing tailored interventions that consider the unique needs and experiences of autistic individuals.

Perinatal exposure to potential endocrine disrupting chemicals and autism spectrum disorder: From Norwegian birth cohort to zebrafish studies

BACKGROUND

The etiology of autism spectrum disorder (ASD) is multifactorial, involving genetic and environmental contributors such as endocrine-disrupting chemicals (EDCs).

OBJECTIVE

To evaluate the association between perinatal exposure to 27 potential EDCs and ASD among Norwegian children, and to further examine the neurodevelopmental toxicity of associated chemicals using zebrafish embryos and larvae.

METHOD

1,199 mothers enrolled in the prospective birth-cohort (HUMIS, 2002-2009) study. Breastmilk levels of 27 chemicals were measured: polychlorinated biphenyls, organochlorine pesticides, polybrominated diphenyl ethers, and perfluoroalkyl substances as a proxy for perinatal exposure. We employed multivariable logistic regression to determine association, utilized elastic net logistic regression as variable selection method, and conducted an in vivo study with zebrafish larvae to confirm the neurodevelopmental effect.

RESULTS

A total of 20 children had specialist confirmed diagnosis of autism among 1,199 mother-child pairs in this study. β-Hexachlorocyclohexane (β-HCH) was the only chemical associated with ASD, after adjusting for 26 other chemicals. Mothers with the highest levels of β-HCH in their milk had a significant increased risk of having a child with ASD (OR = 1.82, 95 % CI: 1.20, 2.77 for an interquartile range increase in ln-transformed β-HCH concentration). The median concentration of β-HCH in breast milk was 4.37 ng/g lipid (interquartile range: 2.92-6.47), and the estimated daily intake (EDI) for Norwegian children through breastfeeding was 0.03 µg/kg of body weight. The neurodevelopmental and social behavioral effects of β-HCH were established in zebrafish embryos and larvae across various concentrations, with further analysis suggesting that perturbation of dopaminergic neuron development may underlie the neurotoxicity associated with β-HCH.

CONCLUSIONS

Prenatal exposure to β-HCH was associated with an increased risk of specialist-confirmed diagnoses of ASD among Norwegian children, and the EDI surpasses the established threshold. Zebrafish experiments confirm β-HCH neurotoxicity, suggesting dopaminergic neuron disruption as a potential underlying mechanism.

Morphological and Functional Changes of Cerebral Cortex in Autism Spectrum Disorder

Autism spectrum disorder (ASD) is a complex neurodevelopmental disorder characterized by early-onset impairments in socialization, communication, repetitive behaviors, and restricted interests. ASD exhibits considerable heterogeneity, with clinical presentations varying across individuals and age groups. The pathophysiology of ASD is hypothesized to be due to abnormal brain development influenced by a combination of genetic and environmental factors. One of the most consistent morphological parameters for assessing the abnormal brain structures in patients with ASD is cortical thickness. Studies have shown changes in the cortical thickness within the frontal, temporal, parietal, and occipital lobes of individuals with ASD. These changes in cortical thickness often correspond to specific clinical features observed in individuals with ASD. Furthermore, the aberrant brain anatomical features and cortical thickness alterations may lead to abnormal brain connectivity and synaptic structure. Additionally, ASD is associated with cortical hyperplasia in early childhood, followed by a cortical plateau and subsequent decline in later stages of development. However, research in this area has yielded contradictory findings regarding the cortical thickness across various brain regions in ASD.

Zebrafish optomotor response to second-order motion illustrates that age-related changes in motion detection depend on the activated motion system

Various aspects of visual functioning, including motion perception, change with age. Yet, there is a lack of comprehensive understanding of age-related alterations at different stages of motion processing and in each motion system. To understand the effects of aging on second-order motion processing, we investigated optomotor responses (OMR) in younger and older wild-type (AB-strain) and acetylcholinesterase (achesb55/+) mutant zebrafish. The mutant fish with decreased levels of acetylcholinesterase have been shown to have delayed age-related cognitive decline. Compared to previous results on first-order motion, we found distinct changes in OMR to second-order motion. The polarity of OMR was dependent on age, such that second-order stimulation led to mainly negative OMR in the younger group while older zebrafish had positive responses. Hence, these findings revealed an overall aging effect on the detection of second-order motion. Moreover, neither the genotype of zebrafish nor the spatial frequency of motion significantly changed the response magnitude. Our findings support the view that age-related changes in motion detection depend on the activated motion system.

Application of Multimodal MRI in the Early Diagnosis of Autism Spectrum Disorders: A Review

Autism spectrum disorder (ASD) is a neurodevelopmental disorder in children. Early diagnosis and intervention can remodel the neural structure of the brain and improve quality of life but may be inaccurate if based solely on clinical symptoms and assessment scales. Therefore, we aimed to analyze multimodal magnetic resonance imaging (MRI) data from the existing literature and review the abnormal changes in brain structural-functional networks, perfusion, neuronal metabolism, and the glymphatic system in children with ASD, which could help in early diagnosis and precise intervention. Structural MRI revealed morphological differences, abnormal developmental trajectories, and network connectivity changes in the brain at different ages. Functional MRI revealed disruption of functional networks, abnormal perfusion, and neurovascular decoupling associated with core ASD symptoms. Proton magnetic resonance spectroscopy revealed abnormal changes in the neuronal metabolites during different periods. Decreased diffusion tensor imaging signals along the perivascular space index reflected impaired glymphatic system function in children with ASD. Differences in age, subtype, degree of brain damage, and remodeling in children with ASD led to heterogeneity in research results. Multimodal MRI is expected to further assist in early and accurate clinical diagnosis of ASD through deep learning combined with genomics and artificial intelligence.

White and gray matter correlates of theory of mind in autism: a voxel-based morphometry study

Autism spectrum disorder (ASD) is characterized by difficulties in theory of mind (ToM) and social communication. Studying structural and functional correlates of ToM in the brain and how autistic and nonautistic groups differ in terms of these correlates can help with diagnosis and understanding the biological mechanisms of ASD. In this study, we investigated white matter volume (WMV) and gray matter volume (GMV) differences between matching autistic and nonautistic samples, and how these structural features relate to age and ToM skills, indexed by the Reading the Mind in the Eyes (RMIE) measure. The results showed widespread GMV and WMV differences between the two groups in regions crucial for social processes. The autistic group did not express the typically observed negative GMV and positive WMV correlations with age at the same level as the nonautistic group, pointing to abnormalities in developmental structural changes. In addition, we found differences between the two groups in how GMV relates to ToM, particularly in the left frontal regions, and how WMV relates to ToM, mostly in the cingulate and corpus callosum. Finally, GMV in the left insula, a region that is part of the salience network, was found to be crucial in distinguishing ToM performance between the two groups.

Regional, circuit and network heterogeneity of brain abnormalities in psychiatric disorders

The substantial individual heterogeneity that characterizes people with mental illness is often ignored by classical case-control research, which relies on group mean comparisons. Here we present a comprehensive, multiscale characterization of the heterogeneity of gray matter volume (GMV) differences in 1,294 cases diagnosed with one of six conditions (attention-deficit/hyperactivity disorder, autism spectrum disorder, bipolar disorder, depression, obsessive-compulsive disorder and schizophrenia) and 1,465 matched controls. Normative models indicated that person-specific deviations from population expectations for regional GMV were highly heterogeneous, affecting the same area in <7% of people with the same diagnosis. However, these deviations were embedded within common functional circuits and networks in up to 56% of cases. The salience-ventral attention system was implicated transdiagnostically, with other systems selectively involved in depression, bipolar disorder, schizophrenia and attention-deficit/hyperactivity disorder. Phenotypic differences between cases assigned the same diagnosis may thus arise from the heterogeneous localization of specific regional deviations, whereas phenotypic similarities may be attributable to the dysfunction of common functional circuits and networks.

Gender effects on autism spectrum disorder: a multi-site resting-state functional magnetic resonance imaging study of transcriptome-neuroimaging

Introduction

The gender disparity in autism spectrum disorder (ASD) has been one of the salient features of condition. However, its relationship between the pathogenesis and genetic transcription in patients of different genders has yet to reach a reliable conclusion.

Methods

To address this gap, this study aimed to establish a reliable potential neuro-marker in gender-specific patients, by employing multi-site functional magnetic resonance imaging (fMRI) data, and to further investigate the role of genetic transcription molecules in neurogenetic abnormalities and gender differences in autism at the neuro-transcriptional level. To this end, age was firstly used as a regression covariate, followed by the use of ComBat to remove the site effect from the fMRI data, and abnormal functional activity was subsequently identified. The resulting abnormal functional activity was then correlated by genetic transcription to explore underlying molecular functions and cellular molecular mechanisms.

Results

Abnormal brain functional activities were identified in autism patients of different genders, mainly located in the default model network (DMN) and precuneus-cingulate gyrus-frontal lobe. The correlation analysis of neuroimaging and genetic transcription further found that heterogeneous brain regions were highly correlated with genes involved in signal transmission between neurons' plasma membranes. Additionally, we further identified different weighted gene expression patterns and specific expression tissues of risk genes in ASD of different genders.

Discussion

Thus, this work not only identified the mechanism of abnormal brain functional activities caused by gender differences in ASD, but also explored the genetic and molecular characteristics caused by these related changes. Moreover, we further analyzed the genetic basis of sex differences in ASD from a neuro-transcriptional perspective.

Social visual preference mediates the effect of cortical thickness on symptom severity in children with autism spectrum disorder

Background

Evidence suggests that there is a robust relationship between altered neuroanatomy and autistic symptoms in individuals with autism spectrum disorder (ASD). Social visual preference, which is regulated by specific brain regions, is also related to symptom severity. However, there were a few studies explored the potential relationships among brain structure, symptom severity, and social visual preference.

Methods

The current study investigated relationships among brain structure, social visual preference, and symptom severity in 43 children with ASD and 26 typically developing (TD) children (aged 2-6 years).

Results

Significant differences were found in social visual preference and cortical morphometry between the two groups. Decreased percentage of fixation time in digital social images (%DSI) was negatively related to not only the thickness of the left fusiform gyrus (FG) and right insula, but also the Calibrated Severity Scores for the Autism Diagnostic Observation Schedule-Social Affect (ADOS-SA-CSS). Mediation analysis showed that %DSI partially mediated the relationship between neuroanatomical alterations (specifically, thickness of the left FG and right insula) and symptom severity.

Conclusion

These findings offer initial evidence that atypical neuroanatomical alterations may not only result in direct effects on symptom severity but also lead to indirect effects on symptom severity through social visual preference. This finding enhances our understanding of the multiple neural mechanisms implicated in ASD.

Absence of associations with prefrontal cortex and cerebellum may link to early language and social deficits in preschool children with ASD

Introduction

Autism spectrum disorder (ASD) is a complex developmental disorder, characterized by language and social deficits that begin to appear in the first years of life. Research in preschool children with ASD has consistently reported increased global brain volume and abnormal cortical patterns, and the brain structure abnormalities have also been found to be clinically and behaviorally relevant. However, little is known regarding the associations between brain structure abnormalities and early language and social deficits in preschool children with ASD.

Methods

In this study, we collected magnetic resonance imaging (MRI) data from a cohort of Chinese preschool children with and without ASD (24 ASD/20 non-ASD) aged 12-52 months, explored group differences in brain gray matter (GM) volume, and examined associations between regional GM volume and early language and social abilities in these two groups, separately.

Results

We observed significantly greater global GM volume in children with ASD as compared to those without ASD, but there were no regional GM volume differences between these two groups. For children without ASD, GM volume in bilateral prefrontal cortex and cerebellum was significantly correlated with language scores; GM volume in bilateral prefrontal cortex was significantly correlated with social scores. No significant correlations were found in children with ASD.

Discussion

Our data demonstrate correlations of regional GM volume with early language and social abilities in preschool children without ASD, and the absence of these associations appear to underlie language and social deficits in children with ASD. These findings provide novel evidence for the neuroanatomical basis associated with language and social abilities in preschool children with and without ASD, which promotes a better understanding of early deficits in language and social functions in ASD.

Association of Sex With Neurobehavioral Markers of Executive Function in 2-Year-Olds at High and Low Likelihood of Autism

Importance

Children with autism and their siblings exhibit executive function (EF) deficits early in development, but associations between EF and biological sex or early brain alterations in this population are largely unexplored.

Objective

To investigate the interaction of sex, autism likelihood group, and structural magnetic resonance imaging alterations on EF in 2-year-old children at high familial likelihood (HL) and low familial likelihood (LL) of autism, based on having an older sibling with autism or no family history of autism in first-degree relatives.

Design, Setting, and Participants

This prospective cohort study assessed 165 toddlers at HL (n = 110) and LL (n = 55) of autism at 4 university-based research centers. Data were collected from January 1, 2007, to December 31, 2013, and analyzed between August 2021 and June 2022 as part of the Infant Brain Imaging Study.

Main Outcomes and Measures

Direct assessments of EF and acquired structural magnetic resonance imaging were performed to determine frontal lobe, parietal lobe, and total cerebral brain volume.

Results

A total of 165 toddlers (mean [SD] age, 24.61 [0.95] months; 90 [54%] male, 137 [83%] White) at HL for autism (n = 110; 17 diagnosed with ASD) and LL for autism (n = 55) were studied. The toddlers at HL for autism scored lower than the toddlers at LL for autism on EF tests regardless of sex (mean [SE] B = -8.77 [4.21]; 95% CI, -17.09 to -0.45; η2p = 0.03). With the exclusion of toddlers with autism, no group (HL vs LL) difference in EF was found in boys (mean [SE] difference, -7.18 [4.26]; 95% CI, 1.24-15.59), but EF was lower in HL girls than LL girls (mean [SE] difference, -9.75 [4.34]; 95% CI, -18.32 to -1.18). Brain-behavior associations were examined, controlling for overall cerebral volume and developmental level. Sex differences in EF-frontal (B [SE] = 16.51 [7.43]; 95% CI, 1.36-31.67; η2p = 0.14) and EF-parietal (B [SE] = 17.68 [6.99]; 95% CI, 3.43-31.94; η2p = 0.17) associations were found in the LL group but not the HL group (EF-frontal: B [SE] = -1.36 [3.87]; 95% CI, -9.07 to 6.35; η2p = 0.00; EF-parietal: B [SE] = -2.81 [4.09]; 95% CI, -10.96 to 5.34; η2p = 0.01). Autism likelihood group differences in EF-frontal (B [SE] = -9.93 [4.88]; 95% CI, -19.73 to -0.12; η2p = 0.08) and EF-parietal (B [SE] = -15.44 [5.18]; 95% CI, -25.86 to -5.02; η2p = 0.16) associations were found in girls not boys (EF-frontal: B [SE] = 6.51 [5.88]; 95% CI, -5.26 to 18.27; η2p = 0.02; EF-parietal: B [SE] = 4.18 [5.48]; 95% CI, -6.78 to 15.15; η2p = 0.01).

Conclusions and Relevance

This cohort study of toddlers at HL and LL of autism suggests that there is an association between sex and EF and that brain-behavior associations in EF may be altered in children at HL of autism. Furthermore, EF deficits may aggregate in families, particularly in girls.

Characterisation of ASD traits among a cohort of children with isolated fetal ventriculomegaly

Fetal ventriculomegaly is the most common antenatally-diagnosed brain abnormality. Imaging studies in antenatal isolated ventriculomegaly demonstrate enlarged ventricles and cortical overgrowth which are also present in children with autism-spectrum disorder/condition (ASD). We investigate the presence of ASD traits in a cohort of children (n = 24 [20 males/4 females]) with isolated fetal ventriculomegaly, compared with 10 controls (n = 10 [6 males/4 females]). Neurodevelopmental outcome at school age included IQ, ASD traits (ADOS-2), sustained attention, neurological functioning, behaviour, executive function, sensory processing, co-ordination, and adaptive behaviours. Pre-school language development was assessed at 2 years. 37.5% of children, all male, in the ventriculomegaly cohort scored above threshold for autism/ASD classification. Pre-school language delay predicted an ADOS-2 autism/ASD classification with 73.3% specificity/66.7% sensitivity. Greater pre-school language delay was associated with more ASD symptoms. In this study, the neurodevelopment of children with isolated fetal ventriculomegaly, associated with altered cortical development, includes ASD traits, difficulties in sustained attention, working memory and sensation-seeking behaviours.

Sex and gender in neurodevelopmental conditions

Health-related conditions often differ qualitatively or quantitatively between individuals of different birth-assigned sexes and gender identities, and/or with different gendered experiences, requiring tailored care. Studying the moderating and mediating effects of sex-related and gender-related factors on impairment, disability, wellbeing and health is of paramount importance especially for neurodivergent individuals, who are diagnosed with neurodevelopmental conditions with uneven sex/gender distributions. Researchers have become aware of the myriad influences that sex-related and gender-related variables have on the manifestations of neurodevelopmental conditions, and contemporary work has begun to investigate the mechanisms through which these effects are mediated. Here we describe topical concepts of sex and gender science, summarize current knowledge, and discuss research and clinical challenges related to autism, attention-deficit/hyperactivity disorder and other neurodevelopmental conditions. We consider sex and gender in the context of epidemiology, behavioural phenotypes, neurobiology, genetics, endocrinology and neighbouring disciplines. The available evidence supports the view that sex and gender are important contributors to the biological and behavioural variability in neurodevelopmental conditions. Methodological caveats such as frequent conflation of sex and gender constructs, inappropriate measurement of these constructs and under-representation of specific demographic groups (for example, female and gender minority individuals and people with intellectual disabilities) limit the translational potential of research so far. Future research and clinical implementation should integrate sex and gender into next-generation diagnostics, mechanistic investigations and support practices.

Review of Progress in Diagnostic Studies of Autism Spectrum Disorder Using Neuroimaging

This review article summarizes the recent advances in the diagnostic studies of autism spectrum disorders (ASDs) considering some of the most influential research articles from the last two decades. ASD is a heterogeneous neurodevelopmental disorder characterized by abnormalities in social interaction, communication, and behavioral patterns as well as some unique strengths and differences. The current diagnosis systems are based on autism diagnostic observation schedule (ADOS) or autism diagnostic interview-revised (ADI-R), but biological markers are also important for an effective diagnosis of ASDs. The amalgamation of neuroimaging techniques, such as structural and functional magnetic resonance imaging (sMRI and fMRI), with machine-learning and deep-learning approaches helps throw new light on typical biological markers of ASDs at the early stage of life. To assess the performance of a deep neural network, we develop a light-weighted CNN model for ASD classification. The overall accuracy, precision, and F1-score of the proposed model are 99.92%, 99.93% and 99.92%, respectively. All the neuroimaging studies we have reviewed can be divided into 3 categories, viz. thickness, volume and functional connectivity-based studies. We conclude with a discussion of the major findings of considered studies and promising directions for future research in this field.

The subcortical correlates of autistic traits in school-age children: a population-based neuroimaging study

BACKGROUND

There is emerging evidence that the neuroanatomy of autism forms a spectrum which extends into the general population. However, whilst several studies have identified cortical morphology correlates of autistic traits, it is not established whether morphological differences are present in the subcortical structures of the brain. Additionally, it is not clear to what extent previously reported structural associations may be confounded by co-occurring psychopathology. To address these questions, we utilised neuroimaging data from the Adolescent Brain Cognitive Development Study to assess whether a measure of autistic traits was associated with differences in child subcortical morphology, and if any observed differences persisted after adjustment for child internalising and externalising symptoms.

METHODS

Our analyses included data from 7005 children aged 9-10 years (female: 47.19%) participating in the Adolescent Brain Cognitive Development Study. Autistic traits were assessed using scores from the Social Responsiveness Scale (SRS). Volumes of subcortical regions of interest were derived from structural magnetic resonance imaging data.

RESULTS

Overall, we did not find strong evidence for an association of autistic traits with differences in subcortical morphology in this sample of school-aged children. Whilst lower absolute volumes of the nucleus accumbens and putamen were associated with higher scores of autistic traits, these differences did not persist once a global measure of brain size was accounted for.

LIMITATIONS

It is important to note that autistic traits were assessed using the SRS, of which higher scores are associated with general behavioural problems, and therefore may not be wholly indicative of autism-specific symptoms. In addition, individuals with a moderate or severe autism diagnosis were excluded from the ABCD study, and thus, the average level of autistic traits will be lower than in the general population which may bias findings towards the null.

CONCLUSIONS

These findings from our well-powered study suggest that other metrics of brain morphology, such as cortical morphology or shape-based phenotypes, may be stronger candidates to prioritise when attempting to identify robust neuromarkers of autistic traits.

Language, Social, and Face Regions Are Affected in Toddlers with Autism and Predictive of Language Outcome

Identifying prognostic early brain alterations is crucial for autism spectrum disorder (ASD). Leveraging structural MRI data from 166 ASD and 109 typical developing (TD) toddlers and controlling for brain size, we found that, compared to TD, ASD toddlers showed larger or thicker lateral temporal regions; smaller or thinner frontal lobe and midline structures; larger callosal subregion volume; and smaller cerebellum. Most of these differences were replicated in an independent cohort of 38 ASD and 37 TD toddlers. Moreover, the identified brain alterations were related to ASD symptom severity and cognitive impairments at intake, and, remarkably, they improved the accuracy for predicting later language outcome beyond intake clinical and demographic variables. In summary, brain regions involved in language, social, and face processing were altered in ASD toddlers. These early-age brain alterations may be the result of dysregulation in multiple neural processes and stages and are promising prognostic biomarkers for future language ability.

Structural brain abnormalities and their association with language impairment in school-aged children with Autism Spectrum Disorder

Language impairment is comorbid in most children with Autism Spectrum Disorder (ASD) but its neural basis is poorly understood. Using structural magnetic resonance imaging (MRI), the present study provides the whole-brain comparison of both volume- and surface-based characteristics between groups of children with and without ASD and investigates the relationships between these characteristics in language-related areas and the language abilities of children with ASD measured with standardized tools. A total of 36 school-aged children participated in the study: 18 children with ASD and 18 age- and sex-matched typically developing controls. The results revealed that multiple regions differed between groups of children in gray matter volume, gray matter thickness, gyrification, and cortical complexity (fractal dimension). White matter volume and sulcus depth did not differ between groups of children in any region. Importantly, gray matter thickness and gyrification of language-related areas were related to language functioning in children with ASD. Thus, the results of the present study shed some light on the structural brain abnormalities associated with language impairment in ASD.

Intellectual disabilities moderate sex/gender differences in autism spectrum disorder: a systematic review and meta-analysis

BACKGROUND

Girls/women with autism spectrum disorder (ASD) are suggested to exhibit different symptom profiles than boys/men with ASD. Accumulating evidence suggests that intellectual disability (ID) may affect sex/gender differences in ASD. However, a systematic review and meta-analysis on this topic is missing.

METHODS

Two databases (MEDLINE and PsycINFO) were used to search for studies reporting sex/gender differences (girls/women versus boys/men) in social communication and interaction, restrictive and repetitive behaviour and interests (RRBIs), sensory processing, and linguistic and motor abilities in ASD. The final sample consisted of 79 studies. The meta-analysis was performed with Review Manager using a random-effects model. Participants with ASD without and with ID were analysed as separate subgroups, and the effects in these two subgroups were also compared with each other.

RESULTS

Girls/women with ASD without ID displayed fewer RRBIs, more sensory symptoms and less problems in linguistic abilities than their boys/men counterparts. In contrast, girls/women with ASD with ID displayed more social difficulties and RRBIs, poorer linguistic abilities and more motor problems than boys/men with ASD with ID. Comparisons of groups of participants with ASD without ID versus participants with ASD with ID confirmed differences in sex/gender effects on social difficulties, sensory processing, linguistic abilities and motor abilities.

CONCLUSIONS

Our results clearly suggest that the female phenotype of ASD is moderated by ID. Among individuals with ASD with ID, girls/women seem to be more severely affected than boys/men, whereas among individuals with ASD without ID, girls/women with ASD may have less symptoms than boys/men. Such phenotypic differences could be a potential cause of underrecognition of girls/women with ASD, and it is also possible that observed phenotypic differences may reflect underdiagnosing of girls/women with ASD.

Repurposing SGLT2 Inhibitors for Neurological Disorders: A Focus on the Autism Spectrum Disorder

Autism spectrum disorder (ASD) is a neurodevelopmental disorder with a substantially increasing incidence rate. It is characterized by repetitive behavior, learning difficulties, deficits in social communication, and interactions. Numerous medications, dietary supplements, and behavioral treatments have been recommended for the management of this condition, however, there is no cure yet. Recent studies have examined the therapeutic potential of the sodium-glucose cotransporter 2 (SGLT2) inhibitors in neurodevelopmental diseases, based on their proved anti-inflammatory effects, such as downregulating the expression of several proteins, including the transforming growth factor beta (TGF-β), interleukin-6 (IL-6), C-reactive protein (CRP), nuclear factor κB (NF-κB), tumor necrosis factor alpha (TNF-α), and the monocyte chemoattractant protein (MCP-1). Furthermore, numerous previous studies revealed the potential of the SGLT2 inhibitors to provide antioxidant effects, due to their ability to reduce the generation of free radicals and upregulating the antioxidant systems, such as glutathione (GSH) and superoxide dismutase (SOD), while crossing the blood brain barrier (BBB). These properties have led to significant improvements in the neurologic outcomes of multiple experimental disease models, including cerebral oxidative stress in diabetes mellitus and ischemic stroke, Alzheimer's disease (AD), Parkinson's disease (PD), and epilepsy. Such diseases have mutual biomarkers with ASD, which potentially could be a link to fill the gap of the literature studying the potential of repurposing the SGLT2 inhibitors' use in ameliorating the symptoms of ASD. This review will look at the impact of the SGLT2 inhibitors on neurodevelopmental disorders on the various models, including humans, rats, and mice, with a focus on the SGLT2 inhibitor canagliflozin. Furthermore, this review will discuss how SGLT2 inhibitors regulate the ASD biomarkers, based on the clinical evidence supporting their functions as antioxidant and anti-inflammatory agents capable of crossing the blood-brain barrier (BBB).

Mediating effect of sequential memory on the relationship between visual-motor integration and self-care performance in young children with autism spectrum disorder

Objective

Visual perception is a skill that contributes to the performance of self-care and important development tasks in early childhood. The relationship between self-care and visual perception is especially significant for young children with autism spectrum disorder (ASD), who have been described as visual learners. However, this relationship is not clearly understood among young children with ASD. We investigated the role of motor-free visual perception on the relationship between self-care and visual-motor integration in young children with ASD.

Methods

A sample of 66 children with ASD aged 48 to 83 months were recruited. Measurements included the Assessment of Motor and Process Skills, the Developmental Test of Visual Perception—Third Edition, and Test of Visual-Perceptual Skills—Third Edition.

Results

The results indicated that self-care performance had significant positive correlations with visual-motor integration, visual discrimination, visual memory, visual spatial relationships, and visual sequential memory. Of these, visual sequential memory and visual spatial relationships were the main factors related to self-care performance. Sequential memory was a mediator of the relationship between visual-motor integration and self-care performance.

Conclusion

This study establishes a deeper understanding of self-care and motor-free visual perception among young children with ASD. Understanding the relationship between visual perception and self-care in young children with ASD may aid professionals in providing self-care interventions for this population.

A narrative review of MRI changes correlated to signs and symptoms of autism

Autism spectrum disorder (ASD) is a neurodevelopmental disorder that occurs during early childhood. The change from being normal across several contexts to displaying the behavioral phenotype of ASD occurs in infants and toddlers with autism. Findings provided by magnetic resonance imaging (MRI)-based research owing to the developmental phase, including potential pathways underlying the pathogenesis of the condition and the potential for signs and symptomatic risk prediction. The present study focuses on the characteristic features of magnetic resonance imaging autistic brain, how these changes are correlated to autism signs and symptoms and the implications of MRI as a potential tool for the early diagnosis of ASD. PRISMA style was used to conduct this review. Research articles related to the key concepts of this review, which is looking at MRI brain changes in autistic patients, were revised and incorporated with what is known with the pathophysiology of brain regions in relation to signs and symptoms of autism. Studies on brain MRI of autism were revied for major brain features and regions such as brain volume, cortex and hippocampus. This review reveals that brain changes seen in MRI are highly correlated with the signs and symptoms of autism. There are numerous distinct features noted in an autistic brain using MRI. Based on these findings, various developmental brain paths and autistic behavior culminate in a typical diagnosis, and it is possible that addressing these trajectories would improve the accuracy in which children are detected and provide the necessary treatment.

Individual Brain Morphological Connectome Indicator Based on Jensen-Shannon Divergence Similarity Estimation for Autism Spectrum Disorder Identification

Background

Structural magnetic resonance imaging (sMRI) reveals abnormalities in patients with autism spectrum syndrome (ASD). Previous connectome studies of ASD have failed to identify the individual neuroanatomical details in preschool-age individuals. This paper aims to establish an individual morphological connectome method to characterize the connectivity patterns and topological alterations of the individual-level brain connectome and their diagnostic value in patients with ASD.

Methods

Brain sMRI data from 24 patients with ASD and 17 normal controls (NCs) were collected; participants in both groups were aged 24-47 months. By using the Jensen-Shannon Divergence Similarity Estimation (JSSE) method, all participants's morphological brain network were ascertained. Student's t-tests were used to extract the most significant features in morphological connection values, global graph measurement, and node graph measurement.

Results

The results of global metrics' analysis showed no statistical significance in the difference between two groups. Brain regions with meaningful properties for consensus connections and nodal metric features are mostly distributed in are predominantly distributed in the basal ganglia, thalamus, and cortical regions spanning the frontal, temporal, and parietal lobes. Consensus connectivity results showed an increase in most of the consensus connections in the frontal, parietal, and thalamic regions of patients with ASD, while there was a decrease in consensus connectivity in the occipital, prefrontal lobe, temporal lobe, and pale regions. The model that combined morphological connectivity, global metrics, and node metric features had optimal performance in identifying patients with ASD, with an accuracy rate of 94.59%.

Conclusion

The individual brain network indicator based on the JSSE method is an effective indicator for identifying individual-level brain network abnormalities in patients with ASD. The proposed classification method can contribute to the early clinical diagnosis of ASD.

Sex Differences in Autism Spectrum Disorder: Diagnostic, Neurobiological, and Behavioral Features

Autism Spectrum Disorder (ASD) is a complex neurodevelopmental disorder with a worldwide prevalence of about 1%, characterized by impairments in social interaction, communication, repetitive patterns of behaviors, and can be associated with hyper- or hypo-reactivity of sensory stimulation and cognitive disability. ASD comorbid features include internalizing and externalizing symptoms such as anxiety, depression, hyperactivity, and attention problems. The precise etiology of ASD is still unknown and it is undoubted that the disorder is linked to some extent to both genetic and environmental factors. It is also well-documented and known that one of the most striking and consistent finding in ASD is the higher prevalence in males compared to females, with around 70% of ASD cases described being males. The present review looked into the most significant studies that attempted to investigate differences in ASD males and females thus trying to shade some light on the peculiar characteristics of this prevalence in terms of diagnosis, imaging, major autistic-like behavior and sex-dependent uniqueness. The study also discussed sex differences found in animal models of ASD, to provide a possible explanation of the neurological mechanisms underpinning the different presentation of autistic symptoms in males and females.

Neuroimaging Techniques as Descriptive and Diagnostic Tools for Infants at Risk for Autism Spectrum Disorder: A Systematic Review

Autism Spectrum Disorder (ASD) has traditionally been evaluated and diagnosed via behavioral assessments. However, increasing research suggests that neuroimaging as early as infancy can reliably identify structural and functional differences between autistic and non-autistic brains. The current review provides a systematic overview of imaging approaches used to identify differences between infants at familial risk and without risk and predictive biomarkers. Two primary themes emerged after reviewing the literature: (1) neuroimaging methods can be used to describe structural and functional differences between infants at risk and infants not at risk for ASD (descriptive), and (2) neuroimaging approaches can be used to predict ASD diagnosis among high-risk infants and developmental outcomes beyond infancy (predicting later diagnosis). Combined, the articles highlighted that several neuroimaging studies have identified a variety of neuroanatomical and neurological differences between infants at high and low risk for ASD, and among those who later receive an ASD diagnosis. Incorporating neuroimaging into ASD evaluations alongside traditional behavioral assessments can provide individuals with earlier diagnosis and earlier access to supportive resources.

Small Nucleus Accumbens and Large Cerebral Ventricles in Infants and Toddlers Prior to Receiving Diagnoses of Autism Spectrum Disorder

Early interventions for autism spectrum disorder (ASD) are increasingly available, while only 42-50% of ASD children are diagnosed before 3 years old (YO). To identify neuroimaging biomarkers for early ASD diagnosis, we evaluated surface- and voxel-based brain morphometry in participants under 3YO who were later diagnosed with ASD. Magnetic resonance imaging data were retrospectively obtained from patients later diagnosed with ASD at Boston Children's Hospital. The ASD participants with comorbidities such as congenital disorder, epilepsy, and global developmental delay/intellectual disability were excluded from statistical analyses. Eighty-five structural brain magnetic resonance imaging images were collected from 81 participants under 3YO and compared with 45 images from 45 gender- and age-matched nonautistic controls (non-ASD). Using an Infant FreeSurfer pipeline, 236 regionally distributed measurements were extracted from each scan. By t-tests and linear mixed models, the smaller nucleus accumbens and larger bilateral lateral, third, and fourth ventricles were identified in the ASD group. Vertex-wise t-statistical maps showed decreased thickness in the caudal anterior cingulate cortex and increased thickness in the right medial orbitofrontal cortex in ASD. The smaller bilateral accumbens nuclei and larger cerebral ventricles were independent of age, gender, or gestational age at birth, suggesting that there are MRI-based biomarkers in prospective ASD patients before they receive the diagnosis and that the volume of the nucleus accumbens and cerebral ventricles can be key MRI-based early biomarkers to predict the emergence of ASD.

The role of head circumference and cerebral volumes to phenotype male adults with autism spectrum disorder

BACKGROUND

Autism spectrum disorder (ASD) has been repeatedly associated with enlargements of head circumference in children with ASD. However, it is unclear if these enlargements persist into adulthood. This is the first study to investigate head circumference in a large sample of adults with ASD.

METHODS

We apply a fully automated magnetic resonance imaging (MRI) based measurement approach to compute head circumference by combining 3D and 2D image processing. Head circumference was compared between male adults with ASD (n = 120) and healthy male controls (n = 136), from the Autism Brain Imaging Data Exchange (ABIDE) database. To explain which brain alterations drive our results, secondary analyses were performed for 10 additional morphological brain metrics.

RESULTS

ASD subjects showed an increase in head circumference (p = .0018). In addition, ASD patients had increased ventricular surface area (SA) (p = .0013). Intracranial volume, subarachnoidal cerebrospinal fluid (CSF) volume, and gray matter volume explained 50% of head circumference variance. Using a linear support vector machine, we gained an ASD classification accuracy of 73% (sensitivity 92%, specificity 68%) using head circumference and brain-morphological metrics as input features. Head circumference, ventricular SA, ventricular CSF volume, and ventricular asymmetry index contributed to 85% of feature weighting relevant for classification.

CONCLUSION

Our results suggest that head circumference increases in males with ASD persist into adulthood. Results may be driven by morphological alterations of ventricular CSF. The presented approach for an automated head circumference measurement allows for the retrospective investigation of large MRI datasets in neuropsychiatric disorders.

Sex/gender differences in children with autism spectrum disorder: A brief overview on epidemiology, symptom profile, and neuroanatomy

Autism spectrum disorders (ASD) are a heterogeneous group of neurodevelopmental conditions whose shared core features are impairments in social interaction and communication as well as restricted patterns of behavior, interests, and activities. The significant and consistent male preponderance in ASD prevalence has historically affected the scientific knowledge of autism in females as regards, inter alia, the clinical presentation, the genetic architecture, and the structural brain underpinnings. Indeed, females with ASD are under-investigated as samples recruited for clinical research typically reflect the strong male bias of the disorder. In the last years, the study of the various aspects of sex/gender (s/g) differences in ASD is gaining increased clinical and research interest resulting in a growing number of investigations on this topic. Here, I review and discuss evidence emerged from epidemiological, clinical, and neuroimaging studies in the last decade focusing on s/g differences in children with ASD. These studies are the prerequisites for the development of assessment and treatment practices which take into consideration s/g differences in ASD. Ultimately, a better understanding of s/g differences aims at improving healthcare for both ASD males and females.

Psychopathy in women: insights from neuroscience and ways forward for research

Psychopathy is a severe form of personality disturbance, resulting in a detrimental impact on individuals, healthcare systems, and society as a whole. Until relatively recently, most research in psychopathy has focused on male samples, not least because of its link with criminal behavior and the large proportion of violent crime committed by men. However, psychopathy in women also leads to considerable problems at an individual and societal level, including substance misuse, poor treatment outcomes, and contribution to ever-increasing numbers of female prisoners. Despite this, due to relative neglect, most research into adult female psychopathy is underpowered and outdated. We argue that the field needs revitalizing, with a focus on the developmental nature of the condition and neurocognitive research. Recent work international consortia into conduct disorder in female youth-a precursor of psychopathy in female adults-gives cause for optimism. Here, we outline key strategies for enriching research in this important field with contemporary approaches to other psychiatric conditions.

A ketogenic diet affects brain volume and metabolome in juvenile mice

Ketogenic diet (KD) is a high-fat and low-carbohydrate therapy for medically intractable epilepsy, and its applications in other neurological conditions, including those occurring in children, have been increasingly tested. However, how KD affects childhood neurodevelopment, a highly sensitive and plastic process, is not clear. In this study, we explored structural, metabolic, and functional consequences of a brief treatment of a strict KD (weight ratio of fat to carbohydrate plus protein is approximately 6.3:1) in naive juvenile mice of different inbred strains, using a multidisciplinary approach. Systemic measurements using magnetic resonance imaging revealed that unexpectedly, the volumes of most brain structures in KD-fed mice were about 90% of those in mice of the same strain but fed a standard diet. The reductions in volumes were nonselective, including different regions throughout the brain, the ventricles, and the white matter. The relative volumes of different brain structures were unaltered. Additionally, as KD is a metabolism-based treatment, we performed untargeted metabolomic profiling to explore potential means by which KD affected brain growth and to identify metabolic changes in the brain. We found that brain metabolomic profile was significantly impacted by KD, through both distinct and common pathways in different mouse strains. To explore whether the volumetric and metabolic changes induced by this KD treatment were associated with functional consequences, we recorded spontaneous EEG to measure brain network activity. Results demonstrated limited alterations in EEG patterns in KD-fed animals. In addition, we observed that cortical levels of brain-derived neurotrophic factor (BDNF), a critical molecule in neurodevelopment, did not change in KD-fed animals. Together, these findings indicate that a strict KD could affect volumetric development and metabolic profile of the brain in inbred juvenile mice, while global network activities and BDNF signaling in the brain were mostly preserved. Whether the volumetric and metabolic changes are related to any core functional consequences during neurodevelopment and whether they are also observed in humans need to be further investigated. In addition, our results indicate that certain outcomes of KD are specific to the individual mouse strains tested, suggesting that the physiological profiles of individuals may need to be examined to maximize the clinical benefit of KD.

PTEN mutations in autism spectrum disorder and congenital hydrocephalus: developmental pleiotropy and therapeutic targets

The lack of effective treatments for autism spectrum disorder (ASD) and congenital hydrocephalus (CH) reflects the limited understanding of the biology underlying these common neurodevelopmental disorders. Although ASD and CH have been extensively studied as independent entities, recent human genomic and preclinical animal studies have uncovered shared molecular pathophysiology. Here, we review and discuss phenotypic, genomic, and molecular similarities between ASD and CH, and identify the PTEN-PI3K-mTOR (phosphatase and tensin homolog-phosphoinositide 3-kinase-mammalian target of rapamycin) pathway as a common underlying mechanism that holds diagnostic, prognostic, and therapeutic promise for individuals with ASD and CH.

Neuroplastin in Neuropsychiatric Diseases

Molecular mechanisms underlying neuropsychiatric and neurodegenerative diseases are insufficiently elucidated. A detailed understanding of these mechanisms may help to further improve medical intervention. Recently, intellectual abilities, creativity, and amnesia have been associated with neuroplastin, a cell recognition glycoprotein of the immunoglobulin superfamily that participates in synapse formation and function and calcium signaling. Data from animal models suggest a role for neuroplastin in pathways affected in neuropsychiatric and neurodegenerative diseases. Neuroplastin loss or disruption of molecular pathways related to neuronal processes has been linked to various neurological diseases, including dementia, schizophrenia, and Alzheimer's disease. Here, we review the molecular features of the cell recognition molecule neuroplastin, and its binding partners, which are related to neurological processes and involved in learning and memory. The emerging functions of neuroplastin may have implications for the treatment of diseases, particularly those of the nervous system.

Sex/gender differences in the human autistic brains: A systematic review of 20 years of neuroimaging research

Our current understanding of autism is largely based on clinical experiences and research involving male individuals given the male-predominance in prevalence and the under-inclusion of female individuals due to small samples, co-occurring conditions, or simply being missed for diagnosis. There is a significantly biased 'male lens' in this field with autistic females insufficiently understood. We therefore conducted a systematic review to examine how sex and gender modulate brain structure and function in autistic individuals. Findings from the past 20 years are yet to converge on specific brain regions/networks with consistent sex/gender-modulating effects. Despite at least three well-powered studies identifying specific patterns of significant sex/gender-modulation of autism-control differences, many other studies are likely underpowered, suggesting a critical need for future investigation into sex/gender-based heterogeneity with better-powered designs. Future research should also formally investigate the effects of gender, beyond biological sex, which is mostly absent in the current literature. Understanding the roles of sex and gender in the development of autism is an imperative step to extend beyond the 'male lens' in this field.

Longitudinal Evaluation of Cerebral Growth Across Childhood in Boys and Girls With Autism Spectrum Disorder

BACKGROUND

Cerebral overgrowth is frequently reported in children but not in adults with autism spectrum disorder (ASD). This suggests that early cerebral overgrowth is followed by normalization of cerebral volumes. However, this notion is predicated on cross-sectional research that is vulnerable to sampling bias. For example, autistic individuals with disproportionate megalencephaly, a subgroup with higher rates of intellectual disability and larger cerebral volumes, may be underrepresented in studies of adolescents and adults. Furthermore, extant studies have cohorts that are predominately male, thus limiting knowledge of cerebral growth in females with ASD.

METHODS

Growth of total cerebral volume, gray matter (GM) volume, and white matter volume as well as proportion of GM to total cerebral volume were examined in a longitudinal sample comprising 273 boys (199 with ASD) scanned at up to four time points (mean ages = 38, 50, 64, and 137 months, respectively) and 156 girls (95 with ASD) scanned at up to three time points (mean ages = 39, 53, and 65 months, respectively) using mixed-effects modeling.

RESULTS

In boys with ASD, cerebral overgrowth in the ASD with disproportionate megalencephaly subgroup was predominately driven by increases in GM and persisted throughout childhood without evidence of volumetric regression or normalization. In girls with ASD, cerebral volumes were similar to those in typically developing girls, but growth trajectories of GM and white matter were slower throughout early childhood. The proportion of GM to total cerebral volume declined with age at a slower rate in autistic boys and girls relative to typically developing control subjects.

CONCLUSIONS

Longitudinal evidence does not support the notion that early brain overgrowth is followed by volumetric regression, at least from early to late childhood.

Early or Late Gestational Exposure to Maternal Immune Activation Alters Neurodevelopmental Trajectories in Mice: An Integrated Neuroimaging, Behavioral, and Transcriptional Study

BACKGROUND

Exposure to maternal immune activation (MIA) in utero is a risk factor for neurodevelopmental disorders later in life. The impact of the gestational timing of MIA exposure on downstream development remains unclear.

METHODS

We characterized neurodevelopmental trajectories of mice exposed to the viral mimetic poly I:C (polyinosinic:polycytidylic acid) either on gestational day 9 (early) or on day 17 (late) using longitudinal structural magnetic resonance imaging from weaning to adulthood. Using multivariate methods, we related neuroimaging and behavioral variables for the time of greatest alteration (adolescence/early adulthood) and identified regions for further investigation using RNA sequencing.

RESULTS

Early MIA exposure was associated with accelerated brain volume increases in adolescence/early adulthood that normalized in later adulthood in the striatum, hippocampus, and cingulate cortex. Similarly, alterations in anxiety-like, stereotypic, and sensorimotor gating behaviors observed in adolescence normalized in adulthood. MIA exposure in late gestation had less impact on anatomical and behavioral profiles. Multivariate maps associated anxiety-like, social, and sensorimotor gating deficits with volume of the dorsal and ventral hippocampus and anterior cingulate cortex, among others. The most transcriptional changes were observed in the dorsal hippocampus, with genes enriched for fibroblast growth factor regulation, autistic behaviors, inflammatory pathways, and microRNA regulation.

CONCLUSIONS

Leveraging an integrated hypothesis- and data-driven approach linking brain-behavior alterations to the transcriptome, we found that MIA timing differentially affects offspring development. Exposure in late gestation leads to subthreshold deficits, whereas exposure in early gestation perturbs brain development mechanisms implicated in neurodevelopmental disorders.

Association Between Abnormal Fetal Head Growth and Autism Spectrum Disorder

OBJECTIVE

Despite evidence for the prenatal onset of abnormal head growth in children with autism spectrum disorder (ASD), studies on fetal ultrasound data in ASD are limited and controversial.

METHOD

We conducted a longitudinal matched case-sibling-control study on prenatal ultrasound biometric measures of children with ASD, and 2 control groups: (1) their own typically developed sibling (TDS) and (2) typically developed population (TDP). The cohort comprised 528 children (72.7% male), 174 with ASD, 178 TDS, and 176 TDP.

RESULTS

During the second trimester, ASD and TDS fetuses had significantly smaller biparietal diameter (BPD) than TDP fetuses (adjusted odds ratio for the z score of BPD [aOR_zBPD] = 0.685, 95% CI = 0.527-0.890, and aOR_zBPD = 0.587, 95% CI = 0.459-0.751, respectively). However, these differences became statistically indistinguishable in the third trimester. Interestingly, head biometric measures varied by sex, with male fetuses having larger heads than female fetuses within and across groups. A linear mixed-effect model assessing the effects of sex and group assignment on fetal longitudinal head growth indicated faster BPD growth in TDS versus both ASD and TDP in male fetuses (β = 0.084 and β = 0.100 respectively; p < .001) but not in female fetuses, suggesting an ASD-sex interaction in head growth during gestation. Finally, fetal head growth showed conflicting correlations with ASD severity in male and female children across different gestation periods, thus further supporting the sex effect on the association between fetal head growth and ASD.

CONCLUSION

Our findings suggest that abnormal fetal head growth is a familial trait of ASD, which is modulated by sex and is associated with the severity of the disorder. Thus, it could serve as an early biomarker for ASD.

Neuroinflammation in autism spectrum disorders: Exercise as a "pharmacological" tool

The worldwide prevalence of ASD is around 1%. Although the pathogenesis of ASD is not entirely understood, it is recognized that a combination of genetic, epigenetics, environmental factors and immune system dysfunction can play an essential role in its development. It has been suggested that autism results from the central nervous system derangements due to low-grade chronic inflammatory reactions associated with the immune system activation. ASD individuals have increased microglial activation, density, and increased proinflammatory cytokines in the several brain regions. Autism has no available pharmacological treatments, however there are pedagogical and psychotherapeutic therapies, and pharmacological treatment, that help to control behavioral symptoms. Recent data indicate that exercise intervention programs may improve cognitive and behavioral symptoms in children with ASD. Exercise can also modify inflammatory profiles that will ameliorate associated metabolic disorders. This review highlights the involvement of neuroinflammation in ASD and the beneficial effects of physical exercise on managing ASD symptoms and associated comorbidities.

Cortical Morphology in Autism: Findings from a Cortical Shape-Adaptive Approach to Local Gyrification Indexing

It has been challenging to elucidate the differences in brain structure that underlie behavioral features of autism. Prior studies have begun to identify patterns of changes in autism across multiple structural indices, including cortical thickness, local gyrification, and sulcal depth. However, common approaches to local gyrification indexing used in prior studies have been limited by low spatial resolution relative to functional brain topography. In this study, we analyze the aforementioned structural indices, utilizing a new method of local gyrification indexing that quantifies this index adaptively in relation to specific sulci/gyri, improving interpretation with respect to functional organization. Our sample included n = 115 autistic and n = 254 neurotypical participants aged 5-54, and we investigated structural patterns by group, age, and autism-related behaviors. Differing structural patterns by group emerged in many regions, with age moderating group differences particularly in frontal and limbic regions. There were also several regions, particularly in sensory areas, in which one or more of the structural indices of interest either positively or negatively covaried with autism-related behaviors. Given the advantages of this approach, future studies may benefit from its application in hypothesis-driven examinations of specific brain regions and/or longitudinal studies to assess brain development in autism.

Discharge Estimation Using Integrated Satellite Data and Hybrid Model in the Midstream Yangtze River

Remotely sensing data have advantages in filling spatiotemporal gaps of in situ observation networks, showing potential application for monitoring floods in data-sparse regions. By using the water level retrievals of Jason-2/3 altimetry satellites, this study estimates discharge at a 10-day timescale for the virtual station (VS) 012 and 077 across the midstream Yangtze River Basin during 2009–2016 based on the developed Manning formula. Moreover, we calibrate a hybrid model combined with Gravity Recovery and Climate Experiment (GRACE) data, by coupling the GR6J hydrological model with a machine learning model to simulate discharge. To physically capture the flood processes, the random forest (RF) model is employed to downscale the 10-day discharge into a daily scale. The results show that: (1) discharge estimates from the developed Manning formula show good accuracy for the VS012 and VS077 based on the improved Multi-subwaveform Multi-weight Threshold Retracker; (2) the combination of the GR6J and the LSTM models substantially improves the performance of the discharge estimates solely from either the GR6J or LSTM models; (3) RF-downscaled daily discharge demonstrates a general consistency with in situ data, where NSE/KGE between them are as high as 0.69/0.83. Our approach, based on multi-source remotely sensing data and machine learning techniques, may benefit flood monitoring in poorly gauged areas.