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Item does not contain fulltext OBJECTIVE: The male preponderance in prevalence of autism is among the most pronounced sex ratios across neurodevelopmental conditions. The authors sought to elucidate the relationship between autism and typical sex-differential neuroanatomy, cognition, and related gene expression. METHODS: Using a novel deep learning framework trained to predict biological sex based on T(1)-weighted structural brain images, the authors compared sex prediction model performance across neurotypical and autistic males and females. Multiple large-scale data sets comprising T(1)-weighted MRI data were employed at four stages of the analysis pipeline: 1) pretraining, with the UK Biobank sample (>10,000 individuals); 2) transfer learning and validation, with the ABIDE data sets (1,412 individuals, 5-56 years of age); 3) test and discovery, with the EU-AIMS/AIMS-2-TRIALS LEAP data set (681 individuals, 6-30 years of age); and 4) specificity, with the NeuroIMAGE and ADHD200 data sets (887 individuals, 7-26 years of age). RESULTS: Across both ABIDE and LEAP, features positively predictive of neurotypical males were on average significantly more predictive of autistic males (ABIDE: Cohen's d=0.48; LEAP: Cohen's d=1.34). Features positively predictive of neurotypical females were on average significantly less predictive of autistic females (ABIDE: Cohen's d=1.25; LEAP: Cohen's d=1.29). These differences in sex prediction accuracy in autism were not observed in individuals with ADHD. In autistic females, the male-shifted neurophenotype was further associated with poorer social sensitivity and emotional face processing while also associated with gene expression patterns of midgestational cell types. CONCLUSIONS: The results demonstrate an increased resemblance in both autistic male and female individuals' neuroanatomy with male-characteristic patterns associated with typically sex-differential social cognitive features and related gene expression patterns. The findings hold promise for future research aimed at refining the quest for biological mechanisms underpinning the etiology of autism.

Neuroimaging analyses of brain structure and function in autism have typically been conducted in isolation, missing the sensitivity gains of linking data across modalities. Here we focus on the integration of structural and functional organisational properties of brain regions. We aim to identify novel brain-organisation phenotypes of autism. We utilised multimodal MRI (T1-, diffusion-weighted and resting state functional), behavioural and clinical data from the EU AIMS Longitudinal European Autism Project (LEAP) from autistic (n = 206) and non-autistic (n = 196) participants. Of these, 97 had data from 2 timepoints resulting in a total scan number of 466. Grey matter density maps, probabilistic tractography connectivity matrices and connectopic maps were extracted from respective MRI modalities and were then integrated with Linked Independent Component Analysis. Linear mixed-effects models were used to evaluate the relationship between components and group while accounting for covariates and non-independence of participants with longitudinal data. Additional models were run to investigate associations with dimensional measures of behaviour. We identified one component that differed significantly between groups (coefficient = 0.33, padj = 0.02). This was driven (99%) by variance of the right fusiform gyrus connectopic map 2. While there were multiple nominal associations with behavioural measures, none were significant following multiple comparison correction. Our analysis considered the relative contributions of both structural and functional brain phenotypes simultaneously, finding that functional phenotypes drive associations with autism. These findings expanded on previous unimodal studies by revealing the topographic organisation of functional connectivity patterns specific to autism and warrant further investigation.

Contains fulltext : 248865.pdf (Publisher’s version ) (Closed access) OBJECTIVE: Autism spectrum disorder (ASD) is accompanied by highly individualized neuroanatomical deviations that potentially map onto distinct genotypes and clinical phenotypes. This study aimed to link differences in brain anatomy to specific biological pathways to pave the way toward targeted therapeutic interventions. METHODS: The authors examined neurodevelopmental differences in cortical thickness and their genomic underpinnings in a large and clinically diverse sample of 360 individuals with ASD and 279 typically developing control subjects (ages 6-30 years) within the EU-AIMS Longitudinal European Autism Project (LEAP). The authors also examined neurodevelopmental differences and their potential pathophysiological mechanisms between clinical ASD subgroups that differed in the severity and pattern of sensory features. RESULTS: In addition to significant between-group differences in "core" ASD brain regions (i.e., fronto-temporal and cingulate regions), individuals with ASD manifested as neuroanatomical outliers within the neurotypical cortical thickness range in a wider neural system, which was enriched for genes known to be implicated in ASD on the genetic and/or transcriptomic level. Within these regions, the individuals' total (i.e., accumulated) degree of neuroanatomical atypicality was significantly correlated with higher polygenic scores for ASD and other psychiatric conditions, and it scaled with measures of symptom severity. Differences in cortical thickness deviations were also associated with distinct sensory subgroups, especially in brain regions expressing genes involved in excitatory rather than inhibitory neurotransmission. CONCLUSIONS: The study findings corroborate the link between macroscopic differences in brain anatomy and the molecular mechanisms underpinning heterogeneity in ASD, and provide future targets for stratification and subtyping.

Human brain mapping 43(1), 37-55 (2022). doi:10.1002/hbm.25029 special issue: "Special Issue: The ENIGMA Consortium: the first 10 years / Issue Edited by: P.M. Thompson, N. Jahanshad, L. Schmaal, J.A. Turner, A. Winkler, S.I. Thomopoulos, G.F. Egan, P. Kochunov", Published by Wiley-Liss, New York, NY

Contains fulltext : 293775.pdf (Publisher’s version ) (Open Access) BACKGROUND: Neuroimaging studies of functional connectivity (FC) in autism have been hampered by small sample sizes and inconsistent findings with regard to whether connectivity is increased or decreased in individuals with autism, whether these alterations affect focal systems or reflect a brain-wide pattern, and whether these are age and/or sex dependent. METHODS: The study included resting-state functional magnetic resonance imaging and clinical data from the EU-AIMS LEAP (European Autism Interventions Longitudinal European Autism Project) and the ABIDE (Autism Brain Imaging Data Exchange) 1 and 2 initiatives of 1824 (796 with autism) participants with an age range of 5-58 years. Between-group differences in FC were assessed, and associations between FC and clinical symptom ratings were investigated through canonical correlation analysis. RESULTS: Autism was associated with a brainwide pattern of hypo- and hyperconnectivity. Hypoconnectivity predominantly affected sensory and higher-order attentional networks and correlated with social impairments, restrictive and repetitive behavior, and sensory processing. Hyperconnectivity was observed primarily between the default mode network and the rest of the brain and between cortical and subcortical systems. This pattern was strongly associated with social impairments and sensory processing. Interactions between diagnosis and age or sex were not statistically significant. CONCLUSIONS: The FC alterations observed, which primarily involve hypoconnectivity of primary sensory and attention networks and hyperconnectivity of the default mode network and subcortex with the rest of the brain, do not appear to be age or sex dependent and correlate with clinical dimensions of social difficulties, restrictive and repetitive behaviors, and alterations in sensory processing. These findings suggest that the observed connectivity alterations are stable, trait-like features of autism that are related to the main symptom domains of the condition.

BACKGROUND AND PURPOSE: MR imaging studies and neuropathologic findings in individuals with 22q11.2 deletion syndrome show anomalous early brain development. We aimed to retrospectively evaluate cerebral abnormalities, focusing on gray matter heterotopia, and to correlate these with subjects’ neuropsychiatric impairments. MATERIALS AND METHODS: Three raters assessed gray matter heterotopia and other morphologic brain abnormalities on 3D T1WI and T2*WI in 75 individuals with 22q11.2 deletion syndrome (27 females, 15.5 [SD, 7.4] years of age) and 53 controls (24 females, 12.6 [SD, 4.7] years of age). We examined the association among the groups’ most frequent morphologic findings, general cognitive performance, and comorbid neuropsychiatric conditions. RESULTS: Heterotopia in the white matter were the most frequent finding in individuals with 22q11.2 deletion syndrome (n = 29; controls, n = 0; between-group difference, P < .001), followed by cavum septi pellucidi and/or vergae (n = 20; controls, n = 0; P < .001), periventricular cysts (n = 10; controls, n = 0; P = .007), periventricular nodular heterotopia (n = 10; controls, n = 0; P = .007), and polymicrogyria (n = 3; controls, n = 0; P = .3). However, individuals with these morphologic brain abnormalities did not differ significantly from those without them in terms of general cognitive functioning and psychiatric comorbidities. CONCLUSIONS: Taken together, our findings, periventricular nodular heterotopia or heterotopia in the white matter (possibly related to interrupted Arc cells migration), persistent cavum septi pellucidi and/or vergae, and formation of periventricular cysts, give clues to the brain development disorder induced by the 22q11.2 deletion syndrome. There was no evidence that these morphologic findings were associated with differences in psychiatric or cognitive presentation of the 22q11.2 deletion syndrome.

Background: Parenting interventions reduce antisocial behavior (ASB) in some children with conduct problems (CPs), but not others. Understanding the neural basis for this disparity is important because persistent ASB is associated with lifelong morbidity and places a huge burden on our health and criminal justice systems. One of the most highly replicated neural correlates of ASB is amygdala hypoactivity to another person's fear. We aimed to assess whether amygdala hypoactivity to fear in children with CPs is remediated following reduction in ASB after successful treatment and/or if it is a marker for persistent ASB. Methods: We conducted a prospective, case-control study of boys with CPs and typically developing (TD) boys. Both groups (ages 5–10 years) completed 2 magnetic resonance imaging sessions (18 ± 5.8 weeks apart) with ASB assessed at each visit. Participants included boys with CPs following referral to a parenting intervention group and TD boys recruited from the same schools and geographical regions. Final functional magnetic resonance imaging data were available for 36 TD boys and 57 boys with CPs. Boys with CPs were divided into those whose ASB improved (n = 27) or persisted (n = 30) following the intervention. Functional magnetic resonance imaging data assessing fear reactivity were then analyzed using a longitudinal group (TD/improving CPs/persistent CPs) × time point (pre/post) design. Results: Amygdala hypoactivity to fear was observed only in boys with CPs who had persistent ASB and was absent in those whose ASB improved following intervention. Conclusions: Our findings suggest that amygdala hypoactivity to fear is a marker for ASB that is resistant to change following a parenting intervention and a putative target for future treatments.

Background: Although many studies have explored atypicalities in gray matter (GM) and white matter (WM) morphology of autism, most of them relied on unimodal analyses that did not benefit from the likelihood that different imaging modalities may reflect common neurobiology. We aimed to establish brain patterns of modalities that differentiate between individuals with and without autism and explore associations between these brain patterns and clinical measures in the autism group. Methods: We studied 183 individuals with autism and 157 nonautistic individuals (age range, 6–30 years) in a large, deeply phenotyped autism dataset (EU-AIMS LEAP [European Autism Interventions—A Multicentre Study for Developing New Medications Longitudinal European Autism Project]). Linked independent component analysis was used to link all participants’ GM volume and WM diffusion tensor images, and group comparisons of modality shared variances were examined. Subsequently, we performed univariate and multivariate brain-behavior correlation analyses to separately explore the relationships between brain patterns and clinical profiles. Results: One multimodal pattern was significantly related to autism. This pattern was primarily associated with GM volume in bilateral insula and frontal, precentral and postcentral, cingulate, and caudate areas and co-occurred with altered WM features in the superior longitudinal fasciculus. The brain-behavior correlation analyses showed a significant multivariate association primarily between brain patterns that involved variation of WM and symptoms of restricted and repetitive behavior in the autism group. Conclusions: Our findings demonstrate the assets of integrated analyses of GM and WM alterations to study the brain mechanisms that underpin autism and show that the complex clinical autism phenotype can be interpreted by brain covariation patterns that are spread across the brain involving both cortical and subcortical areas.

Background Autism spectrum disorder (ASD) is associated with deficits in executive functioning (EF), and these have been suggested to contribute to core as well as co-occurring psychiatric symptoms. The biological basis of these deficits is unknown but may include the serotonergic system, which is involved both in regulating EF in neurotypical populations and in the pathophysiology of ASD. We previously demonstrated that reducing serotonin by acute tryptophan depletion (ATD) shifts differences in brain function during performance of EF tasks towards control levels. However, ATD cannot be easily used in the clinic, and we therefore need to adopt alternative approaches to challenge the serotonin system. Hence, we investigated the role of the serotonergic modulator tianeptine on EF networks in ASD. Method We conducted a pharmacological magnetic resonance imaging study, using a randomized double-blind crossover design, to compare the effect of an acute dosage of 12.5 mg tianeptine and placebo on brain activation during two EF tasks (of response inhibition and sustained attention) in 38 adult males: 19 with ASD and 19 matched controls. Results Under placebo, compared to controls, individuals with ASD had atypical brain activation in response inhibition regions including the inferior frontal cortex, premotor regions and cerebellum. During sustained attention, individuals with ASD had decreased brain activation in the right middle temporal cortex, right cuneus and left precuneus. Most of the case–control differences in brain function observed under placebo conditions were abolished by tianeptine administration. Also, within ASD individuals, brain functional differences were shifted significantly towards control levels during response inhibition in the inferior frontal and premotor cortices. Limitations We conducted a pilot study using a single dose of tianeptine, and therefore, we cannot comment on long-term outcome. Conclusions Our findings provide the first evidence that tianeptine can shift atypical brain activation during EF in adults with ASD towards control levels. Future studies should investigate whether this shift in the biology of ASD is maintained after prolonged treatment with tianeptine and whether it improves clinical symptoms.

Zusammenfassung. Theoretischer Hintergrund: Autismus-Spektrum-Störung (ASS) ist eine neuronale Entwicklungsstörung und tritt häufig gemeinsam mit der Aufmerksamkeitsdefizit-/Hyperaktivitätsstörung (ADHS) auf. Bisher wurde jedoch nur selten untersucht, wie sich Personen mit ASS von Personen mit ASS und komorbider ADHS, sowie von einer gesunden Kontrollgruppe (KG) auf neuroanatomischer Ebene unterscheiden. Fragestellung: In der vorliegenden Studie wurde an 101 Jugendlichen untersucht, ob die Kortexdicke bei ASS von komorbid auftretenden ADHS-Symptomen moduliert wird. Methode: Für jeden Proband_innen berechneten wir auf Basis struktureller T1-gewichteter Magnetresonanztomographie Scans die Kortexdicke an jedem Punkt der Gehirnoberfläche. Ergebnisse: Es zeigten sich signifikante Unterschiede zwischen autistischen Proband_innen mit und ohne ADHS im posterioren Cingulum, der Lingualwindung sowie dem Precuneus der linken Hemisphäre. Diskussion und Schlussfolgerung: Die Ergebnisse implizieren, dass die kortikale Dicke bei ASS durch das gleichzeitige Vorliegen einer ADHS moduliert wird. Diese Erkenntnisse könnten in zukünftigen Studien zur Untersuchung neuroanatomischer Ursachen von ASS und der Unterteilung von Proband_innen in homogenere Subgruppen von Nutzen sein und so der zukünftigen Entwicklung individualisierter Therapien dienen.

Autism spectrum disorder (ASD) is a highly complex neurodevelopmental condition that is accompanied by neuroanatomical differences on the macroscopic and microscopic level. Findings from histological, genetic, and more recently in vivo neuroimaging studies converge in suggesting that neuroanatomical abnormalities, specifically around the gray‐white matter (GWM) boundary, represent a crucial feature of ASD. However, no research has yet characterized the GWM boundary in ASD based on measures of diffusion. Here, we registered diffusion tensor imaging data to the structural T1‐weighted images of 92 adults with ASD and 92 matched neurotypical controls in order to examine between‐group differences and group‐by‐sex interactions in fractional anisotropy and mean diffusivity sampled at the GWM boundary, and at different sampling depths within the superficial white and into the gray matter. As hypothesized, we observed atypical diffusion at and around the GWM boundary in ASD, with between‐group differences and group‐by‐sex interactions depending on tissue class and sampling depth. Furthermore, we identified that altered diffusion at the GWM boundary partially (i.e., ~50%) overlapped with atypical gray‐white matter tissue contrast in ASD. Our study thus replicates and extends previous work highlighting the GWM boundary as a crucial target of neuropathology in ASD, and guides future work elucidating etiological mechanisms., The present study observed atypical diffusion at and around the gray‐white matter (GWM) boundary in individuals with autism spectrum disorder (ASD) relative to neurotypical controls, with between‐group differences and group‐by‐sex interactions depending on tissue class and sampling depth. Altered diffusion at the GWM boundary was further identified to partially (i.e., ~50%) and nonrandomly overlap with atypical gray‐white matter tissue contrast in ASD. The study thus replicates and extends previous work highlighting the GWM boundary as a crucial target of neuropathology in ASD, and guides future work elucidating etiological mechanisms.

Emotion processing—including signals from facial expressions—is often altered in individuals with autism spectrum disorder (ASD). The biological basis of this is poorly understood but may include neurochemically mediated differences in the responsivity of key ‘limbic’ regions (including amygdala, ventromedial prefrontal cortex (vmPFC) and nucleus accumbens (NAc)). Emerging evidence also suggests that ASD may be a disorder of brain temporal dynamics. Moreover, serotonin (5-HT) has been shown to be a key regulator of both facial-emotion processing and brain dynamics, and 5-HT abnormalities have been consistently implicated in ASD. To date, however, no one has examined how 5-HT influences the dynamics of facial-emotion processing in ASD. Therefore, we compared the influence of 5-HT on the responsivity of brain dynamics during facial-emotion processing in individuals with and without ASD. Participants completed a facial-emotion processing fMRI task at least 8 days apart using a randomised double-blind crossover design. At each visit they received either a single 20-mg oral dose of the selective serotonin reuptake inhibitor (SSRI) citalopram or placebo. We found that citalopram (which increases levels of 5-HT) caused sustained activation in key limbic regions during processing of negative facial emotions in adults with ASD—but not in neurotypical adults. The neurotypical adults’ limbic response reverted more rapidly to baseline following a 5-HT-challenge. Our results suggest that serotonergic homoeostatic control of the temporal dynamics in limbic regions is altered in adults with ASD, and provide a fresh perspective on the biology of ASD.

Contains fulltext : 251394.pdf (Publisher’s version ) (Open Access) Small average differences in the left-right asymmetry of cerebral cortical thickness have been reported in individuals with autism spectrum disorder (ASD) compared to typically developing controls, affecting widespread cortical regions. The possible impacts of these regional alterations in terms of structural network effects have not previously been characterized. Inter-regional morphological covariance analysis can capture network connectivity between different cortical areas at the macroscale level. Here, we used cortical thickness data from 1455 individuals with ASD and 1560 controls, across 43 independent datasets of the ENIGMA consortium's ASD Working Group, to assess hemispheric asymmetries of intra-individual structural covariance networks, using graph theory-based topological metrics. Compared with typical features of small-world architecture in controls, the ASD sample showed significantly altered average asymmetry of networks involving the fusiform, rostral middle frontal, and medial orbitofrontal cortex, involving higher randomization of the corresponding right-hemispheric networks in ASD. A network involving the superior frontal cortex showed decreased right-hemisphere randomization. Based on comparisons with meta-analyzed functional neuroimaging data, the altered connectivity asymmetry particularly affected networks that subserve executive functions, language-related and sensorimotor processes. These findings provide a network-level characterization of altered left-right brain asymmetry in ASD, based on a large combined sample. Altered asymmetrical brain development in ASD may be partly propagated among spatially distant regions through structural connectivity.

Contains fulltext : 288245.pdf (Publisher’s version ) (Open Access) BACKGROUND: The cerebellum contains more than 50% of the brain's neurons and is involved in social cognition. Cerebellar anatomical atypicalities have repeatedly been reported in individuals with autism. However, studies have yielded inconsistent findings, likely because of a lack of statistical power, and did not capture the clinical and neuroanatomical diversity of autism. Our aim was to better understand cerebellar anatomy and its diversity in autism. METHODS: We studied cerebellar gray matter morphology in 274 individuals with autism and 219 control subjects of a multicenter European cohort, EU-AIMS LEAP (European Autism Interventions-A Multicentre Study for Developing New Medications; Longitudinal European Autism Project). To ensure the robustness of our results, we conducted lobular parcellation of the cerebellum with 2 different pipelines in addition to voxel-based morphometry. We performed statistical analyses with linear, multivariate (including normative modeling), and meta-analytic approaches to capture the diversity of cerebellar anatomy in individuals with autism and control subjects. Finally, we performed a dimensional analysis of cerebellar anatomy in an independent cohort of 352 individuals with autism-related symptoms. RESULTS: We did not find any significant difference in the cerebellum when comparing individuals with autism and control subjects using linear models. In addition, there were no significant deviations in our normative models in the cerebellum in individuals with autism. Finally, we found no evidence of cerebellar atypicalities related to age, IQ, sex, or social functioning in individuals with autism. CONCLUSIONS: Despite positive results published in the last decade from relatively small samples, our results suggest that there is no striking difference in cerebellar anatomy of individuals with autism.

Contains fulltext : 282637.pdf (Publisher’s version ) (Closed access) Autism spectrum disorder (ASD) is a neurodevelopmental condition characterized by difficulties in social communication, but also great heterogeneity. To offer individualized medicine approaches, we need to better target interventions by stratifying autistic people into subgroups with different biological profiles and/or prognoses. We sought to validate neural responses to faces as a potential stratification factor in ASD by measuring neural (electroencephalography) responses to faces (critical in social interaction) in N = 436 children and adults with and without ASD. The speed of early-stage face processing (N170 latency) was on average slower in ASD than in age-matched controls. In addition, N170 latency was associated with responses to faces in the fusiform gyrus, measured with functional magnetic resonance imaging, and polygenic scores for ASD. Within the ASD group, N170 latency predicted change in adaptive socialization skills over an 18-month follow-up period; data-driven clustering identified a subgroup with slower brain responses and poor social prognosis. Use of a distributional data-driven cutoff was associated with predicted improvements of power in simulated clinical trials targeting social functioning. Together, the data provide converging evidence for the utility of the N170 as a stratification factor to identify biologically and prognostically defined subgroups in ASD.

Social-communication (SC) and restricted repetitive behaviors (RRB) are autism diagnostic symptom domains. SC and RRB severity can markedly differ within and between individuals and may be underpinned by different neural circuitry and genetic mechanisms. Modeling SC-RRB balance could help identify how neural circuitry and genetic mechanisms map onto such phenotypic heterogeneity. Here, we developed a phenotypic stratification model that makes highly accurate (97–99%) out-of-sample SC = RRB, SC > RRB, and RRB > SC subtype predictions. Applying this model to resting state fMRI data from the EU-AIMS LEAP dataset (n = 509), we find that while the phenotypic subtypes share many commonalities in terms of intrinsic functional connectivity, they also show replicable differences within some networks compared to a typically-developing group (TD). Specifically, the somatomotor network is hypoconnected with perisylvian circuitry in SC > RRB and visual association circuitry in SC = RRB. The SC = RRB subtype show hyperconnectivity between medial motor and anterior salience circuitry. Genes that are highly expressed within these networks show a differential enrichment pattern with known autism-associated genes, indicating that such circuits are affected by differing autism-associated genomic mechanisms. These results suggest that SC-RRB imbalance subtypes share many commonalities, but also express subtle differences in functional neural circuitry and the genomic underpinnings behind such circuitry., Natasha Bertelsen et al. develop a computational model to categorize patients with autism spectrum disorder (ASD) into distinct subgroups, based on social-communicative or restricted repetitive behaviors. By integrating publicly available neuroimaging and genetic data, they report neural and molecular signatures in two of these subgroups, altogether highlighting subtle differences in neural circuitry and genomic networks that could underlie phenotypic differences among ASD patients.

BackgroundThe excitatory/inhibitory (E/I) imbalance hypothesis posits that an imbalance between excitatory (glutamatergic) and inhibitory (GABAergic) mechanisms underlies the behavioral characteristics of autism spectrum disorder (autism). However, how E/I imbalance arises and how it may differ across autism symptomatology and brain regions is not well understood.MethodsWe used innovative analysis methods - combining competitive gene-set analysis and gene-expression profiles in relation to cortical thickness (CT)- to investigate the relationship between genetic variance, brain structure and autism symptomatology of participants from the EU-AIMS LEAP cohort (autism=360, male/female=259/101; neurotypical control participants=279, male/female=178/101) aged 6 to 30 years. Competitive gene-set analysis investigated associations between glutamatergic and GABAergic signaling pathway gene-sets and clinical measures, and CT. Additionally, we investigated expression profiles of the genes within those sets throughout the brain and how those profiles relate to differences in CT between autistic and neurotypical control participants in the same regions.ResultsThe glutamate gene-set was associated with all autism symptom severity scores on the Autism Diagnostic Observation Schedule-2 (ADOS-2) and the Autism Diagnostic Interview-Revised (ADI-R) within the autistic group, while the GABA set was associated with sensory processing measures (using the SSP subscales) across all participants. Brain regions with greater gene expression of both glutamate and GABA genes showed greater differences in CT between autistic and neurotypical control participants.ConclusionsOur results suggest crucial roles for glutamate and GABA genes in autism symptomatology as well as CT, where GABA is more strongly associated with sensory processing and glutamate more with autism symptom severity.

Autism spectrum disorder (ASD) is a group of neurodevelopmental conditions associated with quantitative differences in cortical and subcortical brain morphometry. Qualitative assessment of brain morphology provides complementary information on the possible underlying neurobiology. Studies of neuroradiological findings in ASD have rendered mixed results, and await robust replication in a sizable and independent sample.We systematically and comprehensively assessed neuroradiological findings in a large cohort of participants with ASD and age-matched controls (total N = 620, 348 ASD and 272 controls), including 70 participants with intellectual disability (47 ASD, 23 controls). We developed a comprehensive scoring system, augmented by standardized biometric measures.There was a higher incidence of neuroradiological findings in individuals with ASD (89.4 %) compared to controls (83.8 %, p = .042). Certain findings were also more common in ASD, in particular opercular abnormalities (OR 1.9, 95 % CI 1.3-3.6) and mega cisterna magna (OR 2.4, 95 % CI 1.4-4.0) reached significance when using FDR, whereas increases in macrocephaly (OR 2.0, 95 % CI 1.2-3.2), cranial deformities (OR 2.4, 95 % CI: 1.0-5.8), calvarian / dural thickening (OR 1.5, 95 % CI 1.0-2.3), ventriculomegaly (OR 3.4, 95 % CI 1.3-9.2), and hypoplasia of the corpus callosum (OR 2.7, 95 % CI 1.1-6.3) did not survive this correction. Furthermore, neuroradiological findings were more likely to occur in isolation in controls, whereas they clustered more frequently in ASD. The incidence of neuroradiological findings was higher in individuals with mild intellectual disability (95.7 %), irrespective of ASD diagnosis.There was a subtly higher prevalence of neuroradiological findings in ASD, which did not appear to be specific to the condition. Individual findings or clusters of findings may point towards the neurodevelopmental mechanisms involved in individual cases. As such, clinical MRI assessments may be useful to guide further etiopathological (genetic) investigations, and are potentially valuable to fundamental ASD research.

The neuroanatomy of autism spectrum disorder (ASD) shows highly heterogeneous developmental trajectories across individuals. Mapping atypical brain development onto clinical phenotypes, and establishing their molecular underpinnings, is therefore crucial for patient stratification and subtyping. In this longitudinal study we examined intra- and inter-individual differences in the developmental trajectory of cortical thickness (CT) in childhood and adolescence, and their genomic underpinnings, in 33 individuals with ASD and 37 typically developing controls (aged 11–18 years). Moreover, we aimed to link regional atypical CT development to intra-individual variations in restricted and repetitive behavior (RRB) over a two-year time period. Individuals with ASD showed significantly reduced cortical thinning in several of the brain regions functionally related to wider autism symptoms and traits (e.g., fronto-temporal and cingulate cortices). The spatial patterns of the neuroanatomical differences in CT were enriched for genes known to be associated with ASD at a genetic and transcriptomic level. Further, intra-individual differences in CT correlated with within-subject variability in the severity of RRBs. Our findings represent an important step towards characterizing the neuroanatomical underpinnings of ASD across development based upon measures of CT. Moreover, our findings provide important novel insights into the link between microscopic and macroscopic pathology in ASD, as well as their relationship with different clinical ASD phenotypes.

Studying the neural processing of faces can illuminate the mechanisms of compromised social expertise in autism. To resolve a longstanding debate, we examined whether differences in configural face processing in autism are underpinned by quantitative differences in the activation of typical face processing pathways, or the recruitment of non-typical neural systems.We investigated spatial and temporal characteristics of event-related EEG responses to upright and inverted faces in a large sample of children, adolescents, and adults with and without autism. We examined topographic analyses of variance and global field power to identify group differences in the spatial and temporal response to face inversion. We then examined how quasi-stable spatiotemporal profiles - microstates - are modulated by face orientation and diagnostic group.Upright and inverted faces produced distinct profiles of topography and strength in the topographical analyses. These topographical profiles differed between diagnostic groups in adolescents, but not in children or adults. In the microstate analysis, the autistic group showed differences in the activation strength of normative microstates during early-stage processing at all ages, suggesting consistent quantitative differences in the operation of typical processing pathways; qualitative differences in microstate topographies during late-stage processing became prominent in adults, suggesting the increasing involvement of non-typical neural systems with processing time and over development.These findings suggest that early difficulties with configural face processing may trigger later compensatory processes in autism that emerge in later development.

Small average differences in the left-right asymmetry of cerebral cortical thickness have been reported in individuals with autism spectrum disorder (ASD) compared to typically developing controls. Although these alterations affect multiple and widespread cortical regional asymmetries, the extent to which specific structural networks might be affected remains unknown. Inter-regional morphological covariance analysis can capture network connectivity relations between different cortical areas at the macroscale level. Here, we used cortical thickness data from 1,455 individuals with ASD and 1,560 controls, across 43 independent datasets of the ENIGMA consortium’s ASD Working Group, to assess hemispheric asymmetries of intra-individual structural covariance networks, using graph theory-based topological metrics. Compared with typical features of small-world architecture in controls, the ASD sample showed significantly altered asymmetry of hemispheric networks involving the fusiform, rostral middle frontal, and medial orbitofrontal cortex, driven by shifts toward higher randomization of the corresponding right-hemispheric networks in ASD. A network involving the superior frontal cortex showed decreased right-hemisphere randomization. Based on comparisons with meta-analyzed functional neuroimaging data, the altered connectivity asymmetry particularly affected networks that subserve working memory, executive functions, language, reading, and sensorimotor processes. Taken together, these findings provide new insights into how altered brain left-right asymmetry in ASD affects specific structural and functional brain networks. Altered asymmetrical brain development in ASD may be partly propagated among spatially distant regions through structural connectivity.

Background Marked sex differences in autism prevalence accentuate the need to understand the role of biological sex-related factors in autism. Efforts to unravel sex differences in the brain organization of autism have, however, been challenged by the limited availability of female data. Methods We addressed this gap by using a large sample of males and females with autism and neurotypical (NT) control individuals (ABIDE; Autism: 362 males, 82 females; NT: 409 males, 166 females; 7–18 years). Discovery analyses examined main effects of diagnosis, sex and their interaction across five resting-state fMRI (R-fMRI) metrics (voxel-level Z > 3.1, cluster-level P Results Discovery analyses in ABIDE revealed significant main effects of diagnosis and sex across the intrinsic functional connectivity of the posterior cingulate cortex, regional homogeneity and voxel-mirrored homotopic connectivity (VMHC) in several cortical regions, largely converging in the default network midline. Sex-by-diagnosis interactions were confined to the dorsolateral occipital cortex, with reduced VMHC in females with autism. All findings were robust to different pre-processing steps. Replicability in independent samples varied by R-fMRI measures and effects with the targeted sex-by-diagnosis interaction being replicated in the larger of the two replication samples—EU-AIMS LEAP. Limitations Given the lack of a priori harmonization among the discovery and replication datasets available to date, sample-related variation remained and may have affected replicability. Conclusions Atypical cross-hemispheric interactions are neurobiologically relevant to autism. They likely result from the combination of sex-dependent and sex-independent factors with a differential effect across functional cortical networks. Systematic assessments of the factors contributing to replicability are needed and necessitate coordinated large-scale data collection across studies.

Autism spectrum disorder (ASD) is associated with atypical brain development. However, the phenotype of regionally specific increased cortical thickness observed in ASD may be driven by several independent biological processes that influence the gray/white matter boundary, such as synaptic pruning, myelination, or atypical migration. Here, we propose to use the boundary sharpness coefficient (BSC), a proxy for alterations in microstructure at the cortical gray/white matter boundary, to investigate brain differences in individuals with ASD, including factors that may influence ASD-related heterogeneity (age, sex, and intelligence quotient). Using a vertex-based meta-analysis and a large multicenter structural magnetic resonance imaging (MRI) dataset, with a total of 1136 individuals, 415 with ASD (112 female; 303 male), and 721 controls (283 female; 438 male), we observed that individuals with ASD had significantly greater BSC in the bilateral superior temporal gyrus and left inferior frontal gyrus indicating an abrupt transition (high contrast) between white matter and cortical intensities. Individuals with ASD under 18 had significantly greater BSC in the bilateral superior temporal gyrus and right postcentral gyrus; individuals with ASD over 18 had significantly increased BSC in the bilateral precuneus and superior temporal gyrus. Increases were observed in different brain regions in males and females, with larger effect sizes in females. BSC correlated with ADOS-2 Calibrated Severity Score in individuals with ASD in the right medial temporal pole. Importantly, there was a significant spatial overlap between maps of the effect of diagnosis on BSC when compared with cortical thickness. These results invite studies to use BSC as a possible new measure of cortical development in ASD and to further examine the microstructural underpinnings of BSC-related differences and their impact on measures of cortical morphology.

Funder: Autism Research Trust, Background: Voxel-based morphometry (VBM) studies in autism spectrum disorder (autism) have yielded diverging results. This might partly be attributed to structural alterations being associating with the combined influence of several regions rather than with a single region. Further, these structural covariation differences may relate to continuous measures of autism rather than with categorical case–control contrasts. The current study aimed to identify structural covariation alterations in autism, and assessed canonical correlations between brain covariation patterns and core autism symptoms. Methods: We studied 347 individuals with autism and 252 typically developing individuals, aged between 6 and 30 years, who have been deeply phenotyped in the Longitudinal European Autism Project. All participants’ VBM maps were decomposed into spatially independent components using independent component analysis. A generalized linear model (GLM) was used to examine case–control differences. Next, canonical correlation analysis (CCA) was performed to separately explore the integrated effects between all the brain sources of gray matter variation and two sets of core autism symptoms. Results: GLM analyses showed significant case–control differences for two independent components. The first component was primarily associated with decreased density of bilateral insula, inferior frontal gyrus, orbitofrontal cortex, and increased density of caudate nucleus in the autism group relative to typically developing individuals. The second component was related to decreased densities of the bilateral amygdala, hippocampus, and parahippocampal gyrus in the autism group relative to typically developing individuals. The CCA results showed significant correlations between components that involved variation of thalamus, putamen, precentral gyrus, frontal, parietal, and occipital lobes, and the cerebellum, and repetitive, rigid and stereotyped behaviors and abnormal sensory behaviors in autism individuals. Limitations: Only 55.9% of the participants with autism had complete questionnaire data on continuous parent-reported symptom measures. Conclusions: Covaried areas associated with autism diagnosis and/or symptoms are scattered across the whole brain and include the limbic system, basal ganglia, thalamus, cerebellum, precentral gyrus, and parts of the frontal, parietal, and occipital lobes. Some of these areas potentially subserve social-communicative behavior, whereas others may underpin sensory processing and integration, and motor behavior.

SummaryWe introduce fsbrain, an R package for the visualization of neuroimaging data. The package can be used to visualize vertex-wise and region-wise morphometry data, parcellations, labels and statistical results on brain surfaces in three dimensions (3D). Voxel data can be displayed in lightbox mode. The fsbrain package offers various customization options and produces publication quality plots which can be displayed interactively, saved as bitmap images, or integrated into R notebooks.Availability and ImplementationThe software, source code and documentation are available under the MIT license at https://github.com/dfsp-spirit/fsbrain. Releases can be installed directly from the Comprehensive R Archive Network (CRAN).Contacttim.schaefer@kgu.de