Search

Abstract Sensory atypicalities are particularly common in autism spectrum disorders (ASD). Nevertheless, our knowledge about the divergent functioning of the underlying somatosensory region and its association with ASD phenotype features is limited. We applied a data-driven approach to map the fine-grained variations in functional connectivity of the primary somatosensory cortex (S1) to the rest of the brain in 240 autistic and 164 neurotypical individuals from the EU-AIMS LEAP dataset, aged between 7 and 30. We estimated the S1 connection topography (‘connectopy’) at rest and during the emotional face-matching (Hariri) task, an established measure of emotion reactivity, and accessed its association with a set of clinical and behavioral variables. We first demonstrated that the S1 connectopy is organized along a dorsoventral axis, mapping onto the S1 somatotopic organization. We then found that its spatial characteristics were linked to the individuals’ adaptive functioning skills, as measured by the Vineland Adaptive Behavior Scales, across the whole sample. Higher functional differentiation characterized the S1 connectopies of individuals with higher daily life adaptive skills. Notably, we detected significant differences between rest and the Hariri task in the S1 connectopies, as well as their projection maps onto the rest of the brain suggesting a task-modulating effect on S1 due to emotion processing. All in all, variation of adaptive skills appears to be reflected in the brain’s mesoscale neural circuitry, as shown by the S1 connectivity profile, which is also differentially modulated during rest and emotional processing.

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 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 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.

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.

Imaging studies have implicated altered functional connectivity in adults with major depressive disorder (MDD). Whether similar dysfunction is present in adolescent patients is unclear. The degree of resting-state functional connectivity (rsFC) may reflect abnormalities within emotional (‘hot’) and cognitive control (‘cold’) neural systems. Here, we investigate rsFC of these systems in adolescent patients and changes following cognitive behavioral therapy (CBT). Functional Magnetic Resonance Imaging (fMRI) was acquired from adolescent patients before CBT, and 24-weeks later following completed therapy. Similar data were obtained from control participants. Cross-sectional Cohort: From 82 patients and 34 controls at baseline, rsFC of the amygdala, anterior cingulate cortex (ACC), and pre-frontal cortex (PFC) was calculated for comparison. Longitudinal Cohort: From 17 patients and 30 controls with longitudinal data, treatment effects were tested on rsFC. Patients demonstrated significantly greater rsFC to left amygdala, bilateral supragenual ACC, but not with PFC. Treatment effects were observed in right insula connected to left supragenual ACC, with baseline case-control differences reduced. rsFC changes were significantly correlated with changes in depression severity. Depressed adolescents exhibited heightened connectivity in regions of ‘hot’ emotional processing, known to be associated with depression, where treatment exposure exerted positive effects, without concomitant differences in areas of ‘cold’ cognition.

Introduction: Major Depressive Disorder (MDD) is a leading cause of disease burden worldwide. Mood-congruent biases in memory tasks are frequently reported in MDD patients, with facilitated memory for negative stimuli. Most functional MRI studies to date have examined the neural correlates of these biases in depressed adults, with fewer studies in adolescents with MDD. Investigation of MDD in adolescence may aid greater understanding of the aetiology and development of the disorder. Methods: Cognitive biases were investigated in 56 MDD patients aged 11–17 years and a matched group of 30 healthy control participants with a self-referential memory task. Behavioural performance and BOLD fMRI data were collected during both encoding and retrieval stages. Results: The neural response to encoding in adolescents with MDD was found to differ significantly from controls. Additionally, neural responses during encoding and retrieval showed differential relationships with age between patient and control groups, specifically in medial, temporal, and prefrontal regions. Conclusions: These findings suggest that during adolescence neurophysiological activity associated with emotional memory differs in those with depression compared to controls and may be age sensitive.

Compared to female major depressive disorder (MDD), male MDD often receives less attention. However, research is warranted since there are significant sex differences in the clinical presentation of MDD and a higher rate of suicide in depressed men. To the best of our knowledge, this is the first functional magnetic resonance imaging (fMRI) study with a large sample addressing putative sex differences in MDD during adolescence, a period when one of the most robust findings in psychiatric epidemiology emerges; that females are twice as likely to suffer from MDD than males. Twenty-four depressed and 10 healthy male adolescents, together with 82 depressed and 24 healthy female adolescents, aged 11–18 years, undertook an affective go/no-go task during fMRI acquisition. In response to sad relative to neutral distractors, significant sex differences (in the supramarginal gyrus) and group-by-sex interactions (in the supramarginal gyrus and the posterior cingulate cortex) were found. Furthermore, in contrast to the healthy male adolescents, depressed male adolescents showed decreased activation in the cerebellum with a significant group-by-age interaction in connectivity. Future research may consider altered developmental trajectories and the possible implications of sex-specific treatment and prevention strategies for MDD.

The "Reading the Mind in the Eyes" test (Eyes test) is an advanced test of theory of mind. Typical sex difference has been reported (i.e., female advantage). Individuals with autism show more difficulty than do typically developing individuals, yet it remains unclear how this is modulated by sex, as females with autism have been under-represented. Here in a large, non-male-biased sample we test for the effects of sex, diagnosis, and their interaction. The Eyes test (revised version) was administered online to 395 adults with autism (178 males, 217 females) and 320 control adults (152 males, 168 females). Two-way ANOVA showed a significant sex-by-diagnosis interaction in total correct score (F(1,711) = 5.090, p = 0.024, ηp2 = 0.007) arising from a significant sex difference between control males and females (p < 0.001, Cohen's d = 0.47), and an absence of a sex difference between males and females with autism (p = 0.907, d = 0.01); significant case-control differences were observed across sexes, with effect sizes of d = 0.35 in males and d = 0.69 in females. Group-difference patterns fit with the extreme-male-brain (EMB) theory predictions. Eyes test-Empathy Quotient and Eyes test-Autism Spectrum Quotient correlations were significant only in females with autism (r = 0.35, r = -0.32, respectively), but not in the other 3 groups. Support vector machine (SVM) classification based on response pattern across all 36 items classified autism diagnosis with a relatively higher accuracy for females (72.2%) than males (65.8%). Nevertheless, an SVM model trained within one sex generalized equally well when applied to the other sex. Performance on the Eyes test is a sex-independent phenotypic characteristic of adults with autism, reflecting sex-common social difficulties, and provides support for the EMB theory predictions for both males and females. Performance of females with autism differed from same-sex controls more than did that of males with autism. Females with autism also showed stronger coherence between self-reported dispositional traits and Eyes test performance than all other groups.