Mapping cortical anatomy in preschool aged children with autism using surface-based morphometry

Common and distinct cortical thickness alterations in youth with autism spectrum disorder and attention-deficit/hyperactivity disorder

BACKGROUND

Autism spectrum disorder (ASD) and attention-deficit/hyperactivity disorder (ADHD) are neurodevelopmental disorders with overlapping behavioral features and genetic etiology. While brain cortical thickness (CTh) alterations have been reported in ASD and ADHD separately, the degree to which ASD and ADHD are associated with common and distinct patterns of CTh changes is unclear.

METHODS

We searched PubMed, Web of Science, Embase, and Science Direct from inception to 8 December 2023 and included studies of cortical thickness comparing youth (age less than 18) with ASD or ADHD with typically developing controls (TDC). We conducted a comparative meta-analysis of vertex-based studies to identify common and distinct CTh alterations in ASD and ADHD.

RESULTS

Twelve ASD datasets involving 458 individuals with ASD and 10 ADHD datasets involving 383 individuals with ADHD were included in the analysis. Compared to TDC, ASD showed increased CTh in bilateral superior frontal gyrus, left middle temporal gyrus, and right superior parietal lobule (SPL) and decreased CTh in right temporoparietal junction (TPJ). ADHD showed decreased CTh in bilateral precentral gyri, right postcentral gyrus, and right TPJ relative to TDC. Conjunction analysis showed both disorders shared reduced TPJ CTh located in default mode network (DMN). Comparative analyses indicated ASD had greater CTh in right SPL and TPJ located in dorsal attention network and thinner CTh in right TPJ located in ventral attention network than ADHD.

CONCLUSIONS

These results suggest shared thinner TPJ located in DMN is an overlapping neurobiological feature of ASD and ADHD. This alteration together with SPL alterations might be related to altered biological motion processing in ASD, while abnormalities in sensorimotor systems may contribute to behavioral control problems in ADHD. The disorder-specific thinner TPJ located in disparate attention networks provides novel insight into distinct symptoms of attentional deficits associated with the two neurodevelopmental disorders.

TRIAL REGISTRATION

PROSPERO CRD42022370620. Registered on November 9, 2022.

Cortical thickness abnormalities in autism spectrum disorder

The pathological mechanism of autism spectrum disorder (ASD) remains unclear. Nowadays, surface-based morphometry (SBM) based on structural magnetic resonance imaging (sMRI) techniques have reported cortical thickness (CT) variations in ASD. However, the findings were inconsistent and heterogeneous. This current meta-analysis conducted a whole-brain vertex-wise coordinate-based meta-analysis (CBMA) on CT studies to explore the most noticeable and robust CT changes in ASD individuals by applying the seed-based d mapping (SDM) program. A total of 26 investigations comprised 27 datasets were included, containing 1,635 subjects with ASD and 1470 HC, along with 94 coordinates. Individuals with ASD exhibited significantly altered CT in several regions compared to HC, including four clusters with thicker CT in the right superior temporal gyrus (STG.R), the left middle temporal gyrus (MTG.L), the left anterior cingulate/paracingulate gyri, the right superior frontal gyrus (SFG.R, medial orbital parts), as well as three clusters with cortical thinning including the left parahippocampal gyrus (PHG.L), the right precentral gyrus (PCG.R) and the left middle frontal gyrus (MFG.L). Adults with ASD only demonstrated CT thinning in the right parahippocampal gyrus (PHG.R), revealed by subgroup meta-analyses. Meta-regression analyses found that CT in STG.R was positively correlated with age. Meanwhile, CT in MFG.L and PHG.L had negative correlations with the age of ASD individuals. These results suggested a complicated and atypical cortical development trajectory in ASD, and would provide a deeper understanding of the neural mechanism underlying the cortical morphology in ASD.

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.

Altered Sex Chromosome Dosage Induces Coordinated Shifts in Cortical Anatomy and Anatomical Covariance

Sex chromosome dosage (SCD) variation increases risk for neuropsychiatric impairment, which may reflect direct SCD effects on brain organization. Here, we 1) map cumulative X- and Y-chromosome dosage effects on regional cortical thickness (CT) and investigate potential functional implications of these effects using Neurosynth, 2) test if this map is organized by patterns of CT covariance that are evident in health, and 3) characterize SCD effects on CT covariance itself. We modeled SCD effects on CT and CT covariance for 308 equally sized regions of the cortical sheet using structural neuroimaging data from 301 individuals with varying numbers of sex chromosomes (169 euploid, 132 aneuploid). Mounting SCD increased CT in the rostral frontal cortex and decreased CT in the lateral temporal cortex, bilaterally. Regions targeted by SCD were associated with social functioning, language processing, and comprehension. Cortical regions with a similar degree of SCD-sensitivity showed heightened CT covariance in health. Finally, greater SCD also increased covariance among regions similarly affected by SCD. Our study both 1) develops novel methods for comparing typical and disease-related structural covariance networks in the brain and 2) uses these techniques to resolve and identify organizing principles for SCD effects on regional cortical anatomy and anatomical covariance.

Dissociating regional gray matter density and gray matter volume in autism spectrum condition

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Local gray matter structure can be separated into density and volume.

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Gray matter density increased and volume decreased with age in adolescence.

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Increased gray matter density but reduced volume in girls relative to boys.

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Autism is associated with increased gray matter volume, but not density.

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Regions with increased volume align with prior studies in autistic youth.

Background

Despite decades of research, there is continued uncertainty regarding whether autism is associated with a specific profile of gray matter (GM) structure. This inconsistency may stem from the widespread use of voxel-based morphometry (VBM) methods that combine indices of GM density and GM volume. If GM density or volume, but not both, prove different in autism, the traditional VBM approach of combining the two indices may obscure the difference. The present study measures GM density and volume separately to examine whether autism is associated with alterations in GM volume, density, or both.

Methods

Differences in MRI-based GM density and volume were examined in 6–25 year-olds with a diagnosis of autism spectrum disorder (n = 213, 80.8% male, IQ 47–154) and a typically developing (TD) sample (n = 190, 71.6% male, IQ 67–155). High-resolution T1-weighted anatomical images were collected on a single MRI scanner. Regional density and volume were estimated via whole-brain parcellation comprised of 1625 parcels. Parcel-wise analyses were conducted using generalized additive models while controlling the false discovery rate (FDR, q < 0.05). Volume differences in the 68-region Desikan-Killiany atlas derived from Freesurfer were also examined, to establish the generalizability of findings across methods.

Results

No density differences were observed between the autistic and TD groups, either in individual parcels or whole brain mean density. Increased volume was observed in autism compared to the TD group when controlling for Age, Sex, and IQ, both at the level of the whole brain (total volume) and in 45 parcels (2.8% of total parcels). Parcels with greater volume included inferior, middle, and superior temporal gyrus, inferior and superior frontal gyrus, precuneus, and fusiform gyrus. Converging evidence from a standard Freesurfer pipeline also identified greater volume in a number of overlapping regions.

Limitations

The method for determining “density” is not a direct measure of neuronal density, and this study cannot reveal underlying cellular differences. While this study represents possibly the largest single-site sample of its kind, it is underpowered to detect very small differences.

Conclusions

These results provide compelling evidence that autism is associated with regional GM volumetric differences, which are more prominent than density differences. This underscores the importance of examining volume and density separately, and suggests that direct measures of volume (e.g. region-of-interest or tensor-based morphometry approaches) may be more sensitive to autism-relevant differences in neuroanatomy than concentration/density-based approaches.

Autism Spectrum Disorder and Childhood Apraxia of Speech: Early Language-Related Hallmarks across Structural MRI Study

Autism Spectrum Disorder (ASD) and Childhood Apraxia of Speech (CAS) are developmental disorders with distinct diagnostic criteria and different epidemiology. However, a common genetic background as well as overlapping clinical features between ASD and CAS have been recently reported. To date, brain structural language-related abnormalities have been detected in both the conditions, but no study directly compared young children with ASD, CAS and typical development (TD). In the current work, we aim: (i) to test the hypothesis that ASD and CAS display neurostructural differences in comparison with TD through morphometric Magnetic Resonance Imaging (MRI)-based measures (ASD vs. TD and CAS vs. TD); (ii) to investigate early possible disease-specific brain structural patterns in the two clinical groups (ASD vs. CAS); (iii) to evaluate predictive power of machine-learning (ML) techniques in differentiating the three samples (ASD, CAS, TD). We retrospectively analyzed the T1-weighted brain MRI scans of 68 children (age range: 34-74 months) grouped into three cohorts: (1) 26 children with ASD (mean age ± standard deviation: 56 ± 11 months); (2) 24 children with CAS (57 ± 10 months); (3) 18 children with TD (55 ± 13 months). Furthermore, a ML analysis based on a linear-kernel Support Vector Machine (SVM) was performed. All but one brain structures displayed significant higher volumes in both ASD and CAS children than TD peers. Specifically, ASD alterations involved fronto-temporal regions together with basal ganglia and cerebellum, while CAS alterations are more focused and shifted to frontal regions, suggesting a possible speech-related anomalies distribution. Caudate, superior temporal and hippocampus volumes directly distinguished the two conditions in terms of greater values in ASD compared to CAS. The ML analysis identified significant differences in brain features between ASD and TD children, whereas only some trends in the ML classification capability were detected in CAS as compared to TD peers. Similarly, the MRI structural underpinnings of two clinical groups were not significantly different when evaluated with linear-kernel SVM. Our results may represent the first step towards understanding shared and specific neural substrate in ASD and CAS conditions, which subsequently may contribute to early differential diagnosis and tailoring specific early intervention.

Evidence against the "normalization" prediction of the early brain overgrowth hypothesis of autism

BACKGROUND

The frequently cited Early Overgrowth Hypothesis of autism spectrum disorder (ASD) postulates that there is overgrowth of the brain in the first 2 years of life, which is followed by a period of arrested growth leading to normalized brain volume in late childhood and beyond. While there is consistent evidence for early brain overgrowth, there is mixed evidence for normalization of brain volume by middle childhood. The outcome of this debate is important to understanding the etiology and neurodevelopmental trajectories of ASD.

METHODS

Brain volume was examined in two very large single-site samples of children, adolescents, and adults. The primary sample comprised 456 6-25-year-olds (ASD n = 240, typically developing controls (TDC) n = 216), including a large number of females (n = 102) and spanning a wide IQ range (47-158). The replication sample included 175 males. High-resolution T1-weighted anatomical MRI images were examined for group differences in total brain, cerebellar, ventricular, gray, and white matter volumes.

RESULTS

The ASD group had significantly larger total brain, cerebellar, gray matter, white matter, and lateral ventricular volumes in both samples, indicating that brain volume remains enlarged through young adulthood, rather than normalizing. There were no significant age or sex interactions with diagnosis in these measures. However, a significant diagnosis-by-IQ interaction was detected in the larger sample, such that increased brain volume was related to higher IQ in the TDCs, but not in the ASD group. Regions-of-significance analysis indicated that total brain volume was larger in ASD than TDC for individuals with IQ less than 115, providing a potential explanation for prior inconsistent brain size results. No relationships were found between brain volume and measures of autism symptom severity within the ASD group.

LIMITATIONS

Our cross-sectional sample may not reflect individual changes over time in brain volume and cannot quantify potential changes in volume prior to age 6.

CONCLUSIONS

These findings challenge the "normalization" prediction of the brain overgrowth hypothesis by demonstrating that brain enlargement persists across childhood into early adulthood. The findings raise questions about the clinical implications of brain enlargement, since we find that it neither confers cognitive benefits nor predicts increased symptom severity in ASD.

Large-scale analyses of the relationship between sex, age and intelligence quotient heterogeneity and cortical morphometry in autism spectrum disorder

Significant heterogeneity across aetiologies, neurobiology and clinical phenotypes have been observed in individuals with autism spectrum disorder (ASD). Neuroimaging-based neuroanatomical studies of ASD have often reported inconsistent findings which may, in part, be attributable to an insufficient understanding of the relationship between factors influencing clinical heterogeneity and their relationship to brain anatomy. To this end, we performed a large-scale examination of cortical morphometry in ASD, with a specific focus on the impact of three potential sources of heterogeneity: sex, age and full-scale intelligence (FIQ). To examine these potentially subtle relationships, we amassed a large multi-site dataset that was carefully quality controlled (yielding a final sample of 1327 from the initial dataset of 3145 magnetic resonance images; 491 individuals with ASD). Using a meta-analytic technique to account for inter-site differences, we identified greater cortical thickness in individuals with ASD relative to controls, in regions previously implicated in ASD, including the superior temporal gyrus and inferior frontal sulcus. Greater cortical thickness was observed in sex specific regions; further, cortical thickness differences were observed to be greater in younger individuals and in those with lower FIQ, and to be related to overall clinical severity. This work serves as an important step towards parsing factors that influence neuroanatomical heterogeneity in ASD and is a potential step towards establishing individual-specific biomarkers.

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.

Quantifying individual differences in brain morphometry underlying symptom severity in Autism Spectrum Disorders

The neurobiology of heterogeneous neurodevelopmental disorders such as autism spectrum disorders (ASD) are still unclear. Despite extensive efforts, most findings are difficult to reproduce due to high levels of individual variance in phenotypic expression. To quantify individual differences in brain morphometry in ASD, we implemented a novel subject-level, distance-based method on subject-specific attributes. In a large multi-cohort sample, each subject with ASD (n = 100; n = 84 males; mean age: 11.43 years; mean IQ: 110.58) was strictly matched to a control participant (n = 100; n = 84 males; mean age: 11.43 years; mean IQ: 110.70). Intrapair Euclidean distance of MRI brain morphometry and symptom severity measures (Social Responsiveness Scale) were entered into a regularised machine learning pipeline for feature selection, with rigorous out-of-sample validation and permutation testing. Subject-specific structural morphometry features significantly predicted individual variation in ASD symptom severity (19 cortical thickness features, p = 0.01, n = 5000 permutations; 10 surface area features, p = 0.006, n = 5000 permutations). Findings remained robust across subjects and were replicated in validation samples. Identified cortical regions implicate key hubs of the salience and default mode networks as neuroanatomical features of social impairment in ASD. Present results highlight the importance of subject-level markers in ASD, and offer an important step forward in understanding the neurobiology of heterogeneous disorders.

Neuroanatomical deficits shared by youth with autism spectrum disorders and psychotic disorders

Autism spectrum disorders (ASD) and early-onset psychosis (EOP) are neurodevelopmental disorders that share genetic, clinical and cognitive facets; it is unclear if these disorders also share spatially overlapping cortical thickness (CT) and surface area (SA) abnormalities. MRI scans of 30 ASD, 29 patients with early-onset first-episode psychosis (EO-FEP) and 26 typically developing controls (TD) (age range 10-18 years) were analyzed by the FreeSurfer suite to calculate vertex-wise estimates of CT, SA, and cortical volume. Two publicly available datasets of ASD and EOP (age range 7-18 years and 5-17 years, respectively) were used for replication analysis. ASD and EO-FEP had spatially overlapping areas of cortical thinning and reduced SA in the bilateral insula (all p's < .00002); 37% of all left insular vertices presenting with significant cortical thinning and 20% (left insula) and 61% (right insula) of insular vertices displaying decreased SA overlapped across both disorders. In both disorders, SA deficits contributed more to cortical volume decreases than reductions in CT did. This finding, as well as the novel finding of an absence of spatial overlap (for ASD) or marginal overlap (for EOP) of deficits in CT and SA, was replicated in the two nonoverlapping independent samples. The insula appears to be a region with transdiagnostic vulnerability for deficits in CT and SA. The finding of nonexistent or small spatial overlap between CT and SA deficits in young people with ASD and psychosis may point to the involvement of common aberrant early neurodevelopmental mechanisms in their pathophysiology.

Longitudinally Mapping Childhood Socioeconomic Status Associations with Cortical and Subcortical Morphology

Childhood socioeconomic status (SES) impacts cognitive development and mental health, but its association with human structural brain development is not yet well characterized. Here, we analyzed 1243 longitudinally acquired structural MRI scans from 623 youth (299 female/324 male) to investigate the relation between SES and cortical and subcortical morphology between ages 5 and 25 years. We found positive associations between SES and total volumes of the brain, cortical sheet, and four separate subcortical structures. These associations were stable between ages 5 and 25. Surface-based shape analysis revealed that higher SES is associated with areal expansion of lateral prefrontal, anterior cingulate, lateral temporal, and superior parietal cortices and ventrolateral thalamic, and medial amygdalo-hippocampal subregions. Meta-analyses of functional imaging data indicate that cortical correlates of SES are centered on brain systems subserving sensorimotor functions, language, memory, and emotional processing. We further show that anatomical variation within a subset of these cortical regions partially mediates the positive association between SES and IQ. Finally, we identify neuroanatomical correlates of SES that exist above and beyond accompanying variation in IQ. Although SES is clearly a complex construct that likely relates to development through diverse, nondeterministic processes, our findings elucidate potential neuroanatomical mediators of the association between SES and cognitive outcomes.SIGNIFICANCE STATEMENT Childhood socioeconomic status (SES) has been associated with developmental disparities in mental health, cognitive ability, and academic achievement, but efforts to understand underlying SES-brain relationships are ongoing. Here, we leverage a unique developmental neuroimaging dataset to longitudinally map the associations between SES and regional brain anatomy at high spatiotemporal resolution. We find widespread associations between SES and global cortical and subcortical volumes and surface area and localize these correlations to a distributed set of cortical, thalamic, and amygdalo-hippocampal subregions. Anatomical variation within a subset of these regions partially mediates the positive relationship between SES and IQ. Our findings help to localize cortical and subcortical systems that represent candidate biological substrates for the known relationships between SES and cognition.

Social Responsiveness Scale (SRS) in Relation to Longitudinal Cortical Thickness Changes in Autism Spectrum Disorder

The relationship between brain development and clinical heterogeneity in autism (ASD) is unknown. This study examines the Social Responsiveness Scale (SRS) in relation to the longitudinal development of cortical thickness. Participants (N = 91 ASD, N = 56 TDC; 3-39 years at first scan) were scanned up to three times over a 7-year period. Mixed-effects models examined cortical thickness in relation to SRS score. ASD participants with higher SRS scores showed regionally increased age-related cortical thinning. Regional thickness differences and reduced age-related cortical thinning were found in predominantly right lateralized regions in ASD with decreasing SRS scores over time. Our findings emphasize the importance of examining clinical phenotypes in brain-based studies of ASD.

Atypical auditory language processing in adolescents with autism spectrum disorder

OBJECTIVE

Individuals with autism spectrum disorder (ASD) often show characteristic differences in auditory processing. To clarify the mechanisms underlying communication impairment in ASD, we examined auditory language processing with both anatomical and functional methods.

METHODS

We assessed the language abilities of adolescents with ASD and typically developing (TD) adolescents, and analyzed the surface-based morphometric structure between the groups using magnetic resonance imaging. Furthermore, we measured cortical responses to an auditory word comprehension task with magnetoencephalography and performed network-based statistics using the phase locking values.

RESULTS

We observed no structural differences between the groups. However, the volume of the left ventral central sulcus (vCS) showed a significant correlation with linguistic scores in ASD. Moreover, adolescents with ASD showed weaker cortical activation in the left vCS and superior temporal sulcus. Furthermore, these regions showed differential correlations with linguistic scores between the groups. Moreover, the ASD group had an atypical gamma band (25-40 Hz) network centered on the left vCS.

CONCLUSIONS

Adolescents with ASD showed atypical responses on the auditory word comprehension task and functional brain differences.

SIGNIFICANCE

Our results suggest that phonological processing and gamma band cortical activity play a critical role in auditory language processing-related pathophysiology in adolescents with ASD.

Autism spectrum disorder: Consensus guidelines on assessment, treatment and research from the British Association for Psychopharmacology

An expert review of the aetiology, assessment, and treatment of autism spectrum disorder, and recommendations for diagnosis, management and service provision was coordinated by the British Association for Psychopharmacology, and evidence graded. The aetiology of autism spectrum disorder involves genetic and environmental contributions, and implicates a number of brain systems, in particular the gamma-aminobutyric acid, serotonergic and glutamatergic systems. The presentation of autism spectrum disorder varies widely and co-occurring health problems (in particular epilepsy, sleep disorders, anxiety, depression, attention deficit/hyperactivity disorder and irritability) are common. We did not recommend the routine use of any pharmacological treatment for the core symptoms of autism spectrum disorder. In children, melatonin may be useful to treat sleep problems, dopamine blockers for irritability, and methylphenidate, atomoxetine and guanfacine for attention deficit/hyperactivity disorder. The evidence for use of medication in adults is limited and recommendations are largely based on extrapolations from studies in children and patients without autism spectrum disorder. We discuss the conditions for considering and evaluating a trial of medication treatment, when non-pharmacological interventions should be considered, and make recommendations on service delivery. Finally, we identify key gaps and limitations in the current evidence base and make recommendations for future research and the design of clinical trials.

Predicting symptom severity in autism spectrum disorder based on cortical thickness measures in agglomerative data

Machine learning approaches have been widely used for the identification of neuropathology from neuroimaging data. However, these approaches require large samples and suffer from the challenges associated with multi-site, multi-protocol data. We propose a novel approach to address these challenges, and demonstrate its usefulness with the Autism Brain Imaging Data Exchange (ABIDE) database. We predict symptom severity based on cortical thickness measurements from 156 individuals with autism spectrum disorder (ASD) from four different sites. The proposed approach consists of two main stages: a domain adaptation stage using partial least squares regression to maximize the consistency of imaging data across sites; and a learning stage combining support vector regression for regional prediction of severity with elastic-net penalized linear regression for integrating regional predictions into a whole-brain severity prediction. The proposed method performed markedly better than simpler alternatives, better with multi-site than single-site data, and resulted in a considerably higher cross-validated correlation score than has previously been reported in the literature for multi-site data. This demonstration of the utility of the proposed approach for detecting structural brain abnormalities in ASD from the multi-site, multi-protocol ABIDE dataset indicates the potential of designing machine learning methods to meet the challenges of agglomerative data.

Neuroanatomical variation in autism spectrum disorder: A comprehensive review

Autism Spectrum Disorder (ASD) is a neurodevelopmental disorder characterized by impairments in socialization, communication, and behavior. Many investigators have described the anatomical abnormalities in autistic brains, in an attempt to correlate them with the manifestations of ASD. Herein, we reviewed all the available literature about the neuroanatomical findings in ASD available via "PubMed" and "Google Scholar." References found in review articles were also searched manually. There was substantial discrepancy throughout the literature regarding the reported presence and significance of neuroanatomical findings in ASD, and this is thoroughly discussed in the present review.

Cortical thickness change in autism during early childhood

Structural magnetic resonance imaging (MRI) scans at high spatial resolution can detect potential foci of early brain dysmaturation in children with autism spectrum disorders (ASD). In addition, comparison between MRI and behavior measures over time can identify patterns of brain change accompanying specific outcomes. We report structural MRI data from two time points for a total of 84 scans in children with ASD and 30 scans in typical controls (mean age time one = 4.1 years, mean age at time two = 6.6 years). Surface-based cortical morphometry and linear mixed effects models were used to link changes in cortical anatomy to both diagnostic status and individual differences in changes in language and autism severity. Compared with controls, children with ASD showed accelerated gray matter volume gain with age, which was driven by a lack of typical age-related cortical thickness (CT) decrease within 10 cortical regions involved in language, social cognition, and behavioral control. Greater expressive communication gains with age in children with ASD were associated with greater CT gains in a set of right hemisphere homologues to dominant language cortices, potentially identifying a compensatory system for closer translational study. Hum Brain Mapp 37:2616-2629, 2016. © 2016 Wiley Periodicals, Inc.

Preliminary Findings Show Maternal Hypothyroidism May Contribute to Abnormal Cortical Morphology in Offspring

In rodents, insufficient thyroid hormone (TH) gestationally has adverse effects on cerebral cortex development. Comparable studies of humans examining how TH insufficiency affects cortical morphology are limited to children with congenital hypothyroidism or offspring of hypothyroxinemic women; effects on cortex of children born to women with clinically diagnosed hypothyroidism are not known. We studied archived MRI scans from 22 children aged 10-12 years born to women treated for preexisting or de novo hypothyroidism in pregnancy (HYPO) and 24 similar age and sex controls from euthyroid women. FreeSurfer Image Analysis Suite software was used to measure cortical thickness (CT) and a vertex-based approach served to compare HYPO versus control groups and Severe versus Mild HYPO subgroups as well as to perform regression analyses examining effects of trimester-specific maternal TSH on CT. Results showed that relative to controls, HYPO had multiple regions of both cortical thinning and thickening, which differed for left and right hemispheres. In HYPO, thinning was confined to medial and mid-lateral regions of each hemisphere and thickening to superior regions (primarily frontal) of the left hemisphere and inferior regions (particularly occipital and temporal) of the right. The Severe HYPO subgroup showed more thinning than Mild in frontal and temporal regions and more thickening in bilateral posterior and frontal regions. Maternal TSH values predicted degree of thinning and thickening within multiple brain regions, with the pattern and direction of correlations differing by trimester. Notably, some correlations remained when cases born to women with severe hypothyroidism were removed from the analyses, suggesting that mild variations of maternal TH may permanently affect offspring cortex. We conclude that maternal hypothyroidism during pregnancy has long-lasting manifestations on the cortical morphology of their offspring with specific effects reflecting both severity and timing of maternal TH insufficiency.

Cortical morphological markers in children with autism: a structural magnetic resonance imaging study of thickness, area, volume, and gyrification

Background

Individuals with autism spectrum disorder (ASD) have been characterized by altered cerebral cortical structures; however, the field has yet to identify consistent markers and prior studies have included mostly adolescents and adults. While there are multiple cortical morphological measures, including cortical thickness, surface area, cortical volume, and cortical gyrification, few single studies have examined all these measures. The current study analyzed all of the four measures and focused on pre-adolescent children with ASD.

Methods

We employed the FreeSurfer pipeline to examine surface-based morphometry in 60 high-functioning boys with ASD (mean age = 8.35 years, range = 4–12 years) and 41 gender-, age-, and IQ-matched typically developing (TD) peers (mean age = 8.83 years), while testing for age-by-diagnosis interaction and between-group differences.

Results

During childhood and in specific regions, ASD participants exhibited a lack of normative age-related cortical thinning and volumetric reduction and an abnormal age-related increase in gyrification. Regarding surface area, ASD and TD exhibited statistically comparable age-related development during childhood. Across childhood, ASD relative to TD participants tended to have higher mean levels of gyrification in specific regions. Within ASD, those with higher Social Responsiveness Scale total raw scores tended to have greater age-related increase in gyrification in specific regions during childhood.

Conclusions

ASD is characterized by cortical neuroanatomical abnormalities that are age-, measure-, statistical model-, and region-dependent. The current study is the first to examine the development of all four cortical measures in one of the largest pre-adolescent samples. Strikingly, Neurosynth-based quantitative reverse inference of the surviving clusters suggests that many of the regions identified above are related to social perception, language, self-referential, and action observation networks—those frequently found to be functionally altered in individuals with ASD. The comprehensive, multilevel analyses across a wide range of cortical measures help fill a knowledge gap and present a complex but rich picture of neuroanatomical developmental differences in children with ASD.

Electronic supplementary material

The online version of this article (doi:10.1186/s13229-016-0076-x) contains supplementary material, which is available to authorized users.

The effect of gender on the neuroanatomy of children with autism spectrum disorders: a support vector machine case-control study

Background

Genetic, hormonal, and environmental factors contribute since infancy to sexual dimorphism in regional brain structures of subjects with typical development. However, the neuroanatomical differences between male and female children with autism spectrum disorders (ASD) are an intriguing and still poorly investigated issue. This study aims to evaluate whether the brain of young children with ASD exhibits sex-related structural differences and if a correlation exists between clinical ASD features and neuroanatomical underpinnings.

Methods

A total of 152 structural MRI scans were analysed. Specifically, 76 young children with ASD (38 males and 38 females; 2–7 years of age; mean = 53 months, standard deviation = 17 months) were evaluated employing a support vector machine (SVM)-based analysis of the grey matter (GM). Group comparisons consisted of 76 age-, gender- and non-verbal-intelligence quotient-matched children with typical development or idiopathic developmental delay without autism.

Results

For both genders combined, SVM showed a significantly increased GM volume in young children with ASD with respect to control subjects, predominantly in the bilateral superior frontal gyrus (Brodmann area –BA– 10), bilateral precuneus (BA 31), bilateral superior temporal gyrus (BA 20/22), whereas less GM in patients with ASD was found in right inferior temporal gyrus (BA 37). For the within gender comparisons (i.e., females with ASD vs. controls and males with ASD vs. controls), two overlapping regions in bilateral precuneus (BA 31) and left superior frontal gyrus (BA 9/10) were detected. Sex-by-group analyses revealed in males with ASD compared to matched controls two male-specific regions of increased GM volume (left middle occipital gyrus—BA 19—and right superior temporal gyrus—BA 22). Comparisons in females with and without ASD demonstrated increased GM volumes predominantly in the bilateral frontal regions. Additional regions of significantly increased GM volume in the right anterior cingulate cortex (BA 32) and right cerebellum were typical only of females with ASD.

Conclusions

Despite the specific behavioural correlates of sex-dimorphism in ASD, brain morphology as yet remains unclear and requires future dedicated investigations. This study provides evidence of structural brain gender differences in young children with ASD that possibly contribute to the different phenotypic disease manifestations in males and females.

Electronic supplementary material

The online version of this article (doi:10.1186/s13229-015-0067-3) contains supplementary material, which is available to authorized users.

Localized Misfolding Within Broca's Area as a Distinctive Feature of Autistic Disorder

BACKGROUND

Recent neuroimaging studies suggest that autism spectrum disorder results from abnormalities in the cortical folding pattern. Usual morphometric measurements have failed to provide reliable neuroanatomic markers. Here, we propose that sulcal pits, which are the deepest points in each fold, are suitable candidates to uncover this atypical cortical folding.

METHODS

Sulcal pits were extracted from a magnetic resonance imaging database of 102 children (1.5-10 years old) distributed in three groups: children with autistic disorder (n = 59), typically developing children (n = 22), and children with pervasive developmental disorder not otherwise specified (n = 21). The geometrical properties of sulcal pits were compared between these three groups.

RESULTS

Fold-level analyses revealed a reduced pit depth in the left ascending ramus of the Sylvian fissure in children with autistic disorder only. The depth of this central fold of Broca's area was correlated with the social communication impairments that are characteristic of the pathology.

CONCLUSIONS

Our findings support an atypical gyrogenesis of this specific fold in autistic disorder that could be used for differential diagnosis. Sulcal pits constitute valuable markers of the cortical folding dynamics and could help for the early detection of atypical brain maturation.

Neonatal brain abnormalities associated with autism spectrum disorder in children born very preterm

Very preterm (VP) survivors are at increased risk of autism spectrum disorder (ASD) compared with term-born children. This study explored whether neonatal magnetic resonance (MR) brain features differed in VP children with and without ASD at 7 years. One hundred and seventy-two VP children (<30 weeks' gestation or <1250 g birth weight) underwent structural brain MR scans at term equivalent age (TEA; 40 weeks' gestation ±2 weeks) and were assessed for ASD at 7 years of age. The presence and severity of white matter, cortical gray matter, deep nuclear gray matter, and cerebellar abnormalities were assessed, and total and regional brain volumes were measured. ASD was diagnosed using a standardized parent report diagnostic interview and confirmed via an independent assessment. Eight VP children (4.7%) were diagnosed with ASD. Children with ASD had more cystic lesions in the cortical white matter at TEA compared with those without ASD (odds ratio [OR] 8.7, 95% confidence interval [CI] 1.5, 51.3, P = 0.02). There was also some evidence for smaller cerebellar volumes in children with ASD compared with those without ASD (OR = 0.82, CI = 0.66, 1.00, P = 0.06). Overall, the results suggest that VP children with ASD have different brain structure in the neonatal period compared with those who do not have ASD. Autism Res 2016, 9: 543-552. © 2015 International Society for Autism Research, Wiley Periodicals, Inc.

Gray Matter Alterations in Young Children with Autism Spectrum Disorders: Comparing Morphometry at the Voxel and Regional Level

BACKGROUND AND PURPOSE

Sophisticated algorithms to infer disease diagnosis, pathology progression and patient outcome are increasingly being developed to analyze brain MRI data. They have been successfully implemented in a variety of diseases and are currently investigated in the field of neuropsychiatric disorders, including autism spectrum disorder (ASD). We aim to test the ability to predict ASD from subtle morphological changes in structural magnetic resonance imaging (sMRI).

METHODS

The analysis of sMRI of a cohort of male ASD children and controls matched for age and nonverbal intelligence quotient (NVIQ) has been carried out with two widely used preprocessing software packages (SPM and Freesurfer) to extract brain morphometric information at different spatial scales. Then, support vector machines have been implemented to classify the brain features and to localize which brain regions contribute most to the ASD-control separation.

RESULTS

The features extracted from the gray matter subregions provide the best classification performance, reaching an area under the receiver operating characteristic curve (AUC) of 74%. This value is enhanced to 80% when considering only subjects with NVIQ over 70.

CONCLUSIONS

Despite the subtle impact of ASD on brain morphology and a limited cohort size, results from sMRI-based classifiers suggest a consistent network of altered brain regions.

Increased Surface Area, but not Cortical Thickness, in a Subset of Young Boys With Autism Spectrum Disorder

The Autism Phenome Project is the largest, single site, longitudinal magnetic resonance imaging (MRI) study of young children with autism spectrum disorder (ASD). Previous analyses from this cohort have shown that the children with autism have a total brain volume at time 1 (∼3 years of age) that is 6% larger than typically developing (TD) children. This finding is driven primarily by 15% of the boys with ASD that have disproportionate megalencephaly (ASD-DM) or brain size that is 1.5 standard deviations above what would be expected for the child's height. In the current study, cerebral cortical grey matter volume, thickness, and surface area were assayed from MRI scans of 112, 3-year-old boys with ASD and 50 age-matched TD boys. The boys with ASD-DM (n = 17) were analyzed separately from the boys with normal brain size (ASD-N, n = 95). Previous studies of cortical thickness and surface area for ASD children in this age range have come to diametrically different conclusions concerning the significance of cortical thickness vs. surface area. Current analyses indicate that cortical thickness was comparable across the ASD and TD groups. However, surface area was significantly greater in the ASD group compared to the TD group. This result was driven largely by the children with ASD-DM. Even in the ASD-DM group, not all cortical regions demonstrated increased surface area. These results provide strong evidence that the early cortical overgrowth associated with ASD is due primarily to increased surface area and not to increased cortical thickness.

Longitudinal cortical development during adolescence and young adulthood in autism spectrum disorder: increased cortical thinning but comparable surface area changes

OBJECTIVE

Prior reports suggest that autism spectrum disorder (ASD) is associated with atypically excessive early brain growth. Recent cross-sectional studies suggest that later cortical development during adolescence/adulthood might also be aberrant, although longitudinal designs are required to evaluate atypical growth trajectories. The present study sought to examine longitudinal changes in cortical thickness and surface area among adolescents and young adults with ASD.

METHOD

Two high-resolution anatomic magnetic resonance imaging scans approximately 2 years apart were acquired from 17 adolescents with ASD and 18 typically developing (TD) adolescents, matched on age (range = 14-24 years), IQ, sex ratio, and handedness (70 scans total). The FreeSurfer image analysis suite was used to quantify longitudinal changes in cortical thickness and surface area.

RESULTS

Accelerated cortical thinning for the ASD group as compared to the TD group was found in 2 areas in the left hemisphere, the posterior portion of ventral temporal cortex and superior parietal cortex (cluster corrected p < .01). For ventral temporal cortex, cortical thinning was associated with everyday executive function impairments, and thinner cortex at time 2 was correlated with ASD social symptoms. Differences in surface area changes were not detected.

CONCLUSION

The present longitudinal study extends prior cross-sectional research by demonstrating increased cortical thinning (in portions of temporal and parietal cortex) but comparable surface area growth rates in participants with ASD compared to TD controls during adolescence and into young adulthood. These findings provide further evidence for atypical cortical development beyond the early years in ASD, marked by increased cortical thinning in late adolescence/young adulthood.

Brain imaging research in autism spectrum disorders: in search of neuropathology and health across the lifespan

PURPOSE OF REVIEW

Advances in brain imaging research in autism spectrum disorders (ASD) are rapidly occurring, and the amount of neuroimaging research has dramatically increased over the past 5 years. In this review, advances during the past 12 months and longitudinal studies are highlighted.

RECENT FINDINGS

Cross-sectional neuroimaging research provides evidence that the neural underpinnings of the behavioral signs of ASD involve not only dysfunctional integration of information across distributed brain networks but also basic dysfunction in primary cortices.Longitudinal studies of ASD show abnormally enlarged brain volumes and increased rates of brain growth during early childhood in only a small minority of ASD children. There is evidence of disordered development of white matter microstructure and amygdala growth, and at 2 years of age, network inefficiencies in posterior cerebral regions.From older childhood into adulthood, atypical age-variant and age-invariant changes in the trajectories of total and regional brain volumes and cortical thickness are apparent at the group level.

SUMMARY

There is evidence of abnormalities in posterior lobes and posterior brain networks during the first 2 years of life in ASD and, even in older children and adults, dysfunction in primary cortical areas.

Atypical sulcal anatomy in young children with autism spectrum disorder

Autism spectrum disorder is associated with an altered early brain development. However, the specific cortical structure abnormalities underlying this disorder remain largely unknown. Nonetheless, atypical cortical folding provides lingering evidence of early disruptions in neurodevelopmental processes and identifying changes in the geometry of cortical sulci is of primary interest for characterizing these structural abnormalities in autism and their evolution over the first stages of brain development. Here, we applied state-of-the-art sulcus-based morphometry methods to a large highly-selective cohort of 73 young male children of age spanning from 18 to 108 months. Moreover, such large cohort was selected through extensive behavioral assessments and stringent inclusion criteria for the group of 59 children with autism. After manual labeling of 59 different sulci in each hemisphere, we computed multiple shape descriptors for each single sulcus element, hereby separating the folding measurement into distinct factors such as the length and depth of the sulcus. We demonstrated that the central, intraparietal and frontal medial sulci showed a significant and consistent pattern of abnormalities across our different geometrical indices. We also found that autistic and control children exhibited strikingly different relationships between age and structural changes in brain morphology. Lastly, the different measures of sulcus shapes were correlated with the CARS and ADOS scores that are specific to the autistic pathology and indices of symptom severity. Inherently, these structural abnormalities are confined to regions that are functionally relevant with respect to cognitive disorders in ASD. In contrast to those previously reported in adults, it is very unlikely that these abnormalities originate from general compensatory mechanisms unrelated to the primary pathology. Rather, they most probably reflect an early disruption on developmental trajectory that could be part of the primary pathology.

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A new single-site cohort of 73 young children (1.5–11 years) with autism and controls

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State-of-the-art methodology used to compare geometrical attributes of sulci

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Combination of automatic extraction of descriptors with manual identification of sulci

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Clearly evidence localized sulcal shape abnormalities in the autism group

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Different relationships between age and structural changes in brain morphology

Heterogeneity within Autism Spectrum Disorders: What have We Learned from Neuroimaging Studies?

Autism spectrum disorders (ASD) display significant heterogeneity. Although most neuroimaging studies in ASD have been designed to identify commonalities among affected individuals, rather than differences, some studies have explored variation within ASD. There have been two general types of approaches used for this in the neuroimaging literature to date: comparison of subgroups within ASD, and analyses using dimensional measures to link clinical variation to brain differences. This review focuses on structural and functional magnetic resonance imaging studies that have used these approaches to begin to explore heterogeneity between individuals with ASD. Although this type of data is yet sparse, recognition is growing of the limitations of behaviorally defined categorical diagnoses for understanding neurobiology. Study designs that are more informative regarding the sources of heterogeneity in ASD have the potential to improve our understanding of the neurobiological processes underlying ASD.