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Introduction Advancing research and support for neurologically diverse populations requires novel data harmonisation methods that are capable of aligning with contemporary approaches to understanding health and disability.Objectives We present the International Classification of Functioning, Disability and Health (ICF) as a conceptual framework to support harmonisation of mental health data and present a proof of principle within the Risk and Resilience in Developmental Diversity and Mental Health (R2D2-MH) consortium.Method 138 measures from various mental health datasets were linked to the ICF following the WHO’s established linking rules.Findings Findings support the notion that the ICF can assist in the harmonisation of mental health data. The high level of shared ICF codes provides indications of where items may be readily harmonised to develop datasets that may align more readily with contemporary approaches to understanding health and disability. Although the linking process necessarily entails an element of subjectivity, the application of established rules can increase rigour and transparency of the harmonisation process.Conclusions We present the first steps towards data harmonisation in mental health that is compatible with contemporary approaches in psychiatry, being more capable of capturing diversity and aligning with more transdiagnostic and neurodiversity-affirmative ways of understanding data.Clinical implications Our findings show promise, but future work is needed to address quantitative harmonisation. Similarly, issues related to the traditionally ‘pathophysiological’ frameworks that existing datasets are often embedded in can hinder the full potential of harmonisation based on the ICF.

Abstract Studies report that the microstructural integrity of the uncinate fasciculus (UF; connecting the anterior temporal lobe to the orbitofrontal cortex) is abnormal in adults with psychopathy and children with conduct problems (CP), especially those with high callous-unemotional (CU) traits. However, it is unknown if these abnormalities are ‘fixed’ or ‘reversible’. Therefore, we tested the hypothesis that a reduction in CP symptoms, following a parenting intervention, would be associated with altered microstructural integrity in the UF. Using diffusion tensor imaging tractography we studied microstructural differences (mean diffusivity (MD) and radial diffusivity (RD)) in the UF of 43 typically developing (TD) and 67 boys with CP before and after a 14-week parenting intervention. We also assessed whether clinical response in CP symptoms or CU traits explained changes in microstructure following the intervention. Prior to intervention, measures of MD and RD in the UF were increased in CP compared to TD boys. Following intervention, we found that the CP group had a significant reduction in RD and MD. Further, these microstructural changes were driven by the group of children whose CU traits improved (but not CP symptoms as hypothesized). No significant microstructural changes were observed in the TD group. Our findings suggest, for the first time, that microstructural abnormalities in the brains of children with CP may be reversible following parenting intervention.

Abstract Background Autism spectrum disorders (ASD) are neurodevelopmental conditions accompanied by differences in brain development. Neuroanatomical differences in autism are variable across individuals and likely underpin distinct clinical phenotypes. To parse heterogeneity, it is essential to establish how the neurobiology of ASD is modulated by differences associated with co-occurring conditions, such as attention-deficit/hyperactivity disorder (ADHD). This study aimed to (1) investigate between-group differences in autistic individuals with and without co-occurring ADHD, and to (2) link these variances to putative genomic underpinnings. Methods We examined differences in cortical thickness (CT) and surface area (SA) and their genomic associations in a sample of 533 individuals from the Longitudinal European Autism Project. Using a general linear model including main effects of autism and ADHD, and an ASD-by-ADHD interaction, we examined to which degree ADHD modulates the autism-related neuroanatomy. Further, leveraging the spatial gene expression data of the Allen Human Brain Atlas, we identified genes whose spatial expression patterns resemble our neuroimaging findings. Results In addition to significant main effects for ASD and ADHD in fronto-temporal, limbic, and occipital regions, we observed a significant ASD-by-ADHD interaction in the left precentral gyrus and the right frontal gyrus for measures of CT and SA, respectively. Moreover, individuals with ASD + ADHD differed in CT to those without. Both main effects and the interaction were enriched for ASD—but not for ADHD-related genes. Limitations Although we employed a multicenter design to overcome single-site recruitment limitations, our sample size of N = 25 individuals in the ADHD only group is relatively small compared to the other subgroups, which limits the generalizability of the results. Also, we assigned subjects into ADHD positive groupings according to the DSM-5 rating scale. While this is sufficient for obtaining a research diagnosis of ADHD, our approach did not take into account for how long the symptoms have been present, which is typically considered when assessing ADHD in the clinical setting. Conclusion Thus, our findings suggest that the neuroanatomy of ASD is significantly modulated by ADHD, and that autistic individuals with co-occurring ADHD may have specific neuroanatomical underpinnings potentially mediated by atypical gene expression.

Abstract 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, p adj = 0.02). This was driven (99%) by variance of the right fusiform gyrus connectopic map 2. While there were multiple nominal (uncorrected p

Abstract Background Attenuated social attention is a key marker of autism spectrum disorder (ASD). Recent neuroimaging findings also emphasize an altered processing of sensory salience in ASD. The locus coeruleus–norepinephrine system (LC-NE) has been established as a modulator of this sensory salience processing (SSP). We tested the hypothesis that altered LC-NE functioning contributes to different SSP and results in diverging social attention in ASD. Methods We analyzed the baseline eye-tracking data of the EU-AIMS Longitudinal European Autism Project (LEAP) for subgroups of autistic participants (n = 166, age = 6–30 years, IQ = 61–138, gender [female/male] = 41/125) or neurotypical development (TD; n = 166, age = 6–30 years, IQ = 63–138, gender [female/male] = 49/117) that were matched for demographic variables and data quality. Participants watched brief movie scenes (k = 85) depicting humans in social situations (human) or without humans (non-human). SSP was estimated by gazes on physical and motion salience and a corresponding pupillary response that indexes phasic activity of the LC-NE. Social attention is estimated by gazes on faces via manual areas of interest definition. SSP is compared between groups and related to social attention by linear mixed models that consider temporal dynamics within scenes. Models are controlled for comorbid psychopathology, gaze behavior, and luminance. Results We found no group differences in gazes on salience, whereas pupillary responses were associated with altered gazes on physical and motion salience. In ASD compared to TD, we observed pupillary responses that were higher for non-human scenes and lower for human scenes. In ASD, we observed lower gazes on faces across the duration of the scenes. Crucially, this different social attention was influenced by gazes on physical salience and moderated by pupillary responses. Limitations The naturalistic study design precluded experimental manipulations and stimulus control, while effect sizes were small to moderate. Covariate effects of age and IQ indicate that the findings differ between age and developmental subgroups. Conclusions Pupillary responses as a proxy of LC-NE phasic activity during visual attention are suggested to modulate sensory salience processing and contribute to attenuated social attention in ASD.

Abstract The excitatory/inhibitory (E/I) imbalance hypothesis posits that imbalance between excitatory (glutamatergic) and inhibitory (GABAergic) mechanisms underlies the behavioral characteristics of autism. However, how E/I imbalance arises and how it may differ across autism symptomatology and brain regions is not well understood. We used innovative analysis methods—combining competitive gene-set analysis and gene-expression profiles in relation to cortical thickness (CT) to investigate relationships between genetic variance, brain structure and autism symptomatology of participants from the AIMS-2-TRIALS LEAP cohort (autism = 359, male/female = 258/101; neurotypical control participants = 279, male/female = 178/101) aged 6–30 years. Using competitive gene-set analyses, we investigated whether aggregated genetic variation in glutamate and GABA gene-sets could be associated with behavioral measures of autism symptoms and brain structural variation. Further, using the same gene-sets, we corelated expression profiles throughout the cortex with differences in CT between autistic and neurotypical control participants, as well as in separate sensory subgroups. The 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. In adolescents and adults, brain regions with greater gene-expression of glutamate and GABA genes showed greater differences in CT between autistic and neurotypical control participants although in opposing directions. Additionally, the gene expression profiles were associated with CT profiles in separate sensory subgroups. Our results suggest complex relationships between E/I related genetics and autism symptom profiles as well as brain structure alterations, where there may be differential roles for glutamate and GABA.

Autism has been associated with differences in the developmental trajectories of multiple neuroanatomical features, including cortical thickness, surface area, cortical volume, measures of gyrification, and the gray-white matter tissue contrast. These neuroimaging features have been proposed as intermediate phenotypes on the gradient from genomic variation to behavioral symptoms. Hence, examining what these proxy markers represent, i.e., disentangling their associated molecular and genomic underpinnings, could provide crucial insights into the etiology and pathophysiology of autism. In line with this, an increasing number of studies are exploring the association between neuroanatomical, cellular/molecular, and (epi)genetic variation in autism, both indirectly and directly in vivo and across age. In this review, we aim to summarize the existing literature in autism (and neurotypicals) to chart a putative pathway from (i) imaging-derived neuroanatomical cortical phenotypes to (ii) underlying (neuropathological) biological processes, and (iii) associated genomic variation.

Abstract Background Understanding the development of the neuronal circuitry underlying autism spectrum disorder (ASD) is critical to shed light into its etiology and for the development of treatment options. Resting state EEG provides a window into spontaneous local and long-range neuronal synchronization and has been investigated in many ASD studies, but results are inconsistent. Unbiased investigation in large and comprehensive samples focusing on replicability is needed. Methods We quantified resting state EEG alpha peak metrics, power spectrum (PS, 2–32 Hz) and functional connectivity (FC) in 411 children, adolescents and adults (n = 212 ASD, n = 199 neurotypicals [NT], all with IQ > 75). We performed analyses in source-space using individual head models derived from the participants’ MRIs. We tested for differences in mean and variance between the ASD and NT groups for both PS and FC using linear mixed effects models accounting for age, sex, IQ and site effects. Then, we used machine learning to assess whether a multivariate combination of EEG features could better separate ASD and NT participants. All analyses were embedded within a train-validation approach (70%–30% split). Results In the training dataset, we found an interaction between age and group for the reactivity to eye opening (p = .042 uncorrected), and a significant but weak multivariate ASD vs. NT classification performance for PS and FC (sensitivity 0.52–0.62, specificity 0.59–0.73). None of these findings replicated significantly in the validation dataset, although the effect size in the validation dataset overlapped with the prediction interval from the training dataset. Limitations The statistical power to detect weak effects—of the magnitude of those found in the training dataset—in the validation dataset is small, and we cannot fully conclude on the reproducibility of the training dataset’s effects. Conclusions This suggests that PS and FC values in ASD and NT have a strong overlap, and that differences between both groups (in both mean and variance) have, at best, a small effect size. Larger studies would be needed to investigate and replicate such potential effects.

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.

Abstract Background Autism spectrum disorder (ASD) is characterized by impaired social communication and interaction, and stereotyped, repetitive behaviour and sensory interests. To date, there is no effective medication that can improve social communication and interaction in ASD, and effect sizes of behaviour-based psychotherapy remain in the low to medium range. Consequently, there is a clear need for new treatment options. ASD is associated with altered activation and connectivity patterns in brain areas which process social information. Transcranial direct current stimulation (tDCS) is a technique that applies a weak electrical current to the brain in order to modulate neural excitability and alter connectivity. Combined with specific cognitive tasks, it allows to facilitate and consolidate the respective training effects. Therefore, application of tDCS in brain areas relevant to social cognition in combination with a specific cognitive training is a promising treatment approach for ASD. Methods A phase-IIa pilot randomized, double-blind, sham-controlled, parallel-group clinical study is presented, which aims at investigating if 10 days of 20-min multi-channel tDCS stimulation of the bilateral tempo-parietal junction (TPJ) at 2.0 mA in combination with a computer-based cognitive training on perspective taking, intention and emotion understanding, can improve social cognitive abilities in children and adolescents with ASD. The main objectives are to describe the change in parent-rated social responsiveness from baseline (within 1 week before first stimulation) to post-intervention (within 7 days after last stimulation) and to monitor safety and tolerability of the intervention. Secondary objectives include the evaluation of change in parent-rated social responsiveness at follow-up (4 weeks after end of intervention), change in other ASD core symptoms and psychopathology, social cognitive abilities and neural functioning post-intervention and at follow-up in order to explore underlying neural and cognitive mechanisms. Discussion If shown, positive results regarding change in parent-rated social cognition and favourable safety and tolerability of the intervention will confirm tDCS as a promising treatment for ASD core-symptoms. This may be a first step in establishing a new and cost-efficient intervention for individuals with ASD. Trial registration The trial is registered with the German Clinical Trials Register (DRKS), DRKS00014732 . Registered on 15 August 2018. Protocol version This study protocol refers to protocol version 1.2 from 24 May 2019.

Abstract 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

Abstract 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.

Abstract 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.

Abstract Background A crucial step to understanding the mechanistic underpinnings of autism spectrum disorder (ASD), is to examine if the biological underpinnings of ASD in genetic high-risk conditions, like 22q11.2 deletion syndrome (22q11.2DS), are similar to those in idiopathic illness. This study aimed to examine if ASD symptomatology in 22q11.2DS is underpinned by the same—or distinct—neural systems that mediate these symptoms in non-deletion carriers. Methods We examined vertex-wise estimates of cortical volume (CV), surface area (SA), and cortical thickness across 131 individuals between 6 and 25 years of age including (1) 50 individuals with 22q11.2DS, out of which n = 25 had a diagnosis of ASD, (2) 40 non-carriers of the microdeletion with a diagnosis of ASD (i.e., idiopathic ASD), and (3) 41 typically developing (TD) controls. We employed a 2-by-2 factorial design to identify neuroanatomical variability associated with the main effects of 22q11.2DS and ASD, as well as their interaction. Further, using canonical correlation analysis (CCA), we compared neuroanatomical variability associated with the complex (i.e., multivariate) clinical phenotype of ASD between 22q11.2 deletion carriers and non-carriers. Results The set of brain regions associated with the main effect of 22q11.2DS was distinct from the neuroanatomical underpinnings of the main effect of ASD. Moreover, significant 22q11.2DS-by-ASD interactions were observed for CV and SA in the dorsolateral prefrontal cortex, precentral gyrus, and posterior cingulate cortex, suggesting that the neuroanatomy of ASD is significantly modulated by 22q11.2DS (p < 0.01). We further established that the multivariate patterns of neuroanatomical variability associated with differences in symptom profiles significantly differed between 22q11.2 deletion carriers and non-carriers. Limitations We employed a multicenter design to overcome single-site recruitment limitations; however, FreeSurfer-derived measures of surface anatomy have been shown to be highly reliable across scanner platforms and field strengths. Further, we controlled for gender to address the differing distribution between idiopathic ASD individuals and the other groups. Nonetheless, the gender distribution in our sample reflects that of the respective populations, adding to the generalizability of our results. Last, we included individuals with a relatively wide age range (i.e., 6–25 years). Conclusions Our findings indicate that neuroanatomical correlates of ASD symptomatology in carriers of the 22q11.2 microdeletion diverge from those in idiopathic ASD.

Abstract Background Autism spectrum condition (ASC) is accompanied by developmental differences in brain anatomy and connectivity. White matter differences in ASC have been widely studied with diffusion imaging but results are heterogeneous and vary across the age range of study participants and varying methodological approaches. To characterize the neurodevelopmental trajectory of white matter maturation, it is necessary to examine a broad age range of individuals on the autism spectrum and typically developing controls, and investigate age × group interactions. Methods Here, we employed a spatially unbiased tract-based spatial statistics (TBSS) approach to examine age-related differences in white matter connectivity in a sample of 41 individuals with ASC, and 41 matched controls between 7–17 years of age. Results We found significant age-related differences between the ASC and control group in widespread brain regions. This included age-related differences in the uncinate fasciculus, corticospinal tract, inferior longitudinal fasciculus, inferior fronto-occipital fasciculus, anterior thalamic radiation, superior longitudinal fasciculus and forceps major. Measures of fractional anisotropy (FA) were significantly positively associated with age in both groups. However, this relationship was significantly stronger in the ASC group relative to controls. Measures of radial diffusivity (RD) were significantly negatively associated with age in both groups, but this relationship was significantly stronger in the ASC group relative to controls. Limitations The generalisability of our findings is limited by the restriction of the sample to right-handed males with an IQ > 70. Furthermore, a longitudinal design would be required to fully investigate maturational processes across this age group. Conclusions Taken together, our findings suggest that autistic males have an altered trajectory of white matter maturation relative to controls. Future longitudinal analyses are required to further characterize the extent and time course of these differences.

Abstract Background Autism spectrum disorder (ASD) is a neurodevelopmental condition with key deficits in social functioning. It is widely assumed that the biological underpinnings of social impairment are neurofunctional alterations in the “social brain,” a neural circuitry involved in inferring the mental state of a social partner. However, previous evidence comes from small-scale studies and findings have been mixed. We therefore carried out the to-date largest study on neural correlates of mentalizing in ASD. Methods As part of the Longitudinal European Autism Project, we performed functional magnetic resonance imaging at six European sites in a large, well-powered, and deeply phenotyped sample of individuals with ASD (N = 205) and typically developing (TD) individuals (N = 189) aged 6 to 30 years. We presented an animated shapes task to assess and comprehensively characterize social brain activation during mentalizing. We tested for effects of age, diagnosis, and their association with symptom measures, including a continuous measure of autistic traits. Results We observed robust effects of task. Within the ASD sample, autistic traits were moderately associated with functional activation in one of the key regions of the social brain, the dorsomedial prefrontal cortex. However, there were no significant effects of diagnosis on task performance and no effects of age and diagnosis on social brain responses. Besides a lack of mean group differences, our data provide no evidence for meaningful differences in the distribution of brain response measures. Extensive control analyses suggest that the lack of case-control differences was not due to a variety of potential confounders. Conclusions Contrary to prior reports, this large-scale study does not support the assumption that altered social brain activation during mentalizing forms a common neural marker of ASD, at least with the paradigm we employed. Yet, autistic individuals show socio-behavioral deficits. Our work therefore highlights the need to interrogate social brain function with other brain measures, such as connectivity and network-based approaches, using other paradigms, or applying complementary analysis approaches to assess individual differences in this heterogeneous condition.

Background: 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. Methods: 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. Results: 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. Conclusion: 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.

Changes in brain structure asymmetry have been reported in autism spectrum disorder. Here the authors investigate this issue using a large-scale sample consisting of 54 data sets.

Abstract Background Histological evidence suggests that autism spectrum disorder (ASD) is accompanied by a reduced integrity of the grey-white matter boundary. This has also recently been confirmed by a structural neuroimaging study in vivo reporting significantly reduced grey-white matter tissue contrast (GWC) in adult individuals (18–42 years of age) with ASD relative to typically developing (TD) controls. However, it remains unknown whether the neuroanatomical differences in ASD at the grey-white matter boundary are stable across development or are age-dependent. Methods Here, we examined differences in the neurodevelopmental trajectories of GWC in a cross-sectional sample of 77 male ASD individuals and 76 typically developing (TD) controls across childhood and early adulthood (from 7 to 25 years). Results Using nested model comparisons, we first established that the developmental trajectory of GWC is complex in many regions across the cortex and includes linear and non-linear effects of age. Second, while ASD individuals have significantly reduced GWC overall, these differences are age-dependent and are most prominent during childhood (

Abstract Background The EU-AIMS Longitudinal European Autism Project (LEAP) is to date the largest multi-centre, multi-disciplinary observational study on biomarkers for autism spectrum disorder (ASD). The current paper describes the clinical characteristics of the LEAP cohort and examines age, sex and IQ differences in ASD core symptoms and common co-occurring psychiatric symptoms. A companion paper describes the overall design and experimental protocol and outlines the strategy to identify stratification biomarkers. Methods From six research centres in four European countries, we recruited 437 children and adults with ASD and 300 controls between the ages of 6 and 30 years with IQs varying between 50 and 148. We conducted in-depth clinical characterisation including a wide range of observational, interview and questionnaire measures of the ASD phenotype, as well as co-occurring psychiatric symptoms. Results The cohort showed heterogeneity in ASD symptom presentation, with only minimal to moderate site differences on core clinical and cognitive measures. On both parent-report interview and questionnaire measures, ASD symptom severity was lower in adults compared to children and adolescents. The precise pattern of differences varied across measures, but there was some evidence of both lower social symptoms and lower repetitive behaviour severity in adults. Males had higher ASD symptom scores than females on clinician-rated and parent interview diagnostic measures but not on parent-reported dimensional measures of ASD symptoms. In contrast, self-reported ASD symptom severity was higher in adults compared to adolescents, and in adult females compared to males. Higher scores on ASD symptom measures were moderately associated with lower IQ. Both inattentive and hyperactive/impulsive ADHD symptoms were lower in adults than in children and adolescents, and males with ASD had higher levels of inattentive and hyperactive/impulsive ADHD symptoms than females. Conclusions The established phenotypic heterogeneity in ASD is well captured in the LEAP cohort. Variation both in core ASD symptom severity and in commonly co-occurring psychiatric symptoms were systematically associated with sex, age and IQ. The pattern of ASD symptom differences with age and sex also varied by whether these were clinician ratings or parent- or self-reported which has important implications for establishing stratification biomarkers and for their potential use as outcome measures in clinical trials.

Abstract Background The tremendous clinical and aetiological diversity among individuals with autism spectrum disorder (ASD) has been a major obstacle to the development of new treatments, as many may only be effective in particular subgroups. Precision medicine approaches aim to overcome this challenge by combining pathophysiologically based treatments with stratification biomarkers that predict which treatment may be most beneficial for particular individuals. However, so far, we have no single validated stratification biomarker for ASD. This may be due to the fact that most research studies primarily have focused on the identification of mean case-control differences, rather than within-group variability, and included small samples that were underpowered for stratification approaches. The EU-AIMS Longitudinal European Autism Project (LEAP) is to date the largest multi-centre, multi-disciplinary observational study worldwide that aims to identify and validate stratification biomarkers for ASD. Methods LEAP includes 437 children and adults with ASD and 300 individuals with typical development or mild intellectual disability. Using an accelerated longitudinal design, each participant is comprehensively characterised in terms of clinical symptoms, comorbidities, functional outcomes, neurocognitive profile, brain structure and function, biochemical markers and genomics. In addition, 51 twin-pairs (of which 36 had one sibling with ASD) are included to identify genetic and environmental factors in phenotypic variability. Results Here, we describe the demographic characteristics of the cohort, planned analytic stratification approaches, criteria and steps to validate candidate stratification markers, pre-registration procedures to increase transparency, standardisation and data robustness across all analyses, and share some ‘lessons learnt’. A clinical characterisation of the cohort is given in the companion paper (Charman et al., accepted). Conclusion We expect that LEAP will enable us to confirm, reject and refine current hypotheses of neurocognitive/neurobiological abnormalities, identify biologically and clinically meaningful ASD subgroups, and help us map phenotypic heterogeneity to different aetiologies.

Background: Autism spectrum disorder (ASD) and attention deficit hyperactivity disorder (ADHD) frequently persist into adolescence and young adulthood. However, there are few clinical services that support those with these disorders through adulthood. Objective: Our aim was to determine if clinical services meet the needs of people with ASD and ADHD, who are ‘at transition’ from childhood to adulthood. Design: A longitudinal study of individuals with ASD and ADHD, the impact of services and treatments. Methods: Our research methods included (1) interviewing > 180 affected individuals (and their families) with a confirmed diagnosis of ASD and/or ADHD, (2) screening for ASD and ADHD in approximately 1600 patients and (3) surveying general practitioner prescribing to 5651 ASD individuals across the UK. In addition, we tested the effectiveness of (1) new ASD diagnostic interview measures in 169 twins, 145 familes and 150 non-twins, (2) a magnetic resonance imaging-based diagnostic aid in 40 ASD individuals, (3) psychological treatments in 46 ASD individuals and (4) the feasability of e-learning in 28 clinicians. Setting: NHS clinical services and prisons. Participants: Focus – young people with ASD and ADHD as they ‘transition’ from childhood and adolescence into early adulthood. Interventions: Testing the utility of diagnostic measures and services, web-based learning interventions, pharmacological prescribing and cognitive–behavioural treatments. Main outcome measures: Symptom severity, service provision and met/unmet need. Results: People with ASD and ADHD have very significant unmet needs as they transition through adolescence and young adulthood. A major contributor to this is the presence of associated mental health symptoms. However, these are mostly undiagnosed (and untreated) by clinical services. Furthermore, the largest determinant of service provision was age and not severity of symptoms. We provide new tools to help diagnose both the core disorders and their associated symptoms. We also provide proof of concept for the effectiveness of simple psychological interventions to treat obsessional symptoms, the potential to run treatment trials in prisons and training interventions. Limitations: Our findings only apply to clinical service settings. Conclusions: As individuals ‘transition’ their contact with treatment and support services reduces significantly. Needs-led services are required, which can both identify individuals with the ‘core symptoms’ of ASD and ADHD and treat their residual symptoms and associated conditions. Future work: To test our new diagnostic measures and treatment approaches in larger controlled trials. Trial registration: Current Controlled Trials ISRCTN87114880. Funding: The National Institute for Health Research Programme Grants for Applied Research programme.

The present study investigated the relationship between different attitudes toward inclusive education. It draws from the Framework of Inclusive Education by assuming a reciprocal relationship between learning theory beliefs, models of disability, and the assessment of joined education, resulting in consistent attitudes toward inclusion. The study investigated attitudes toward inclusion by applying a person-centered approach (latent profile analysis; LPA) to a sample of N = 138 student teachers. The results suggest a two-class solution: firstly, a consistent exclusive profile combining higher transmissive beliefs of learning and teaching and a preference for exclusion; secondly, a general inclusive profile that combines support for functional and full inclusion, relational and social models of disability, and a cognitive, constructivist learning theory. The profile distribution appeared to be related to teacher self-efficacy, but not to gender or the educational stage of prospective teaching practice.

This study reports on a newly developed framework of inclusive education, which sets out from three distinct models of disability (medical, relational, and social) and incorporates matching learning theory (behaviourist, cognitivist, and constructivist) and the placement of children with disabilities (exclusive, functional inclusive, full inclusive). Central to the framework is the contradiction between functional and full inclusive concepts, which are traced back to the conflict between a deterministic (medical and relational) and social model of disability. Applied to a complementary review of the literature published between 2006 and 2021, the framework sets the basis for structuring content analysis. An analysis of N = 685 reports shows the coherence of the framework as well as an increase in total publications, especially with full inclusive concepts. Additionally, analysis of the applied methodology shows a predominant role of qualitative methods, which is coherent with the constructivist perception of full inclusion. Implications are discussed regarding inconsistencies and barriers to inclusive education.