The EU-AIMS Longitudinal European Autism Project (LEAP): clinical characterisation

Mapping the link between socio-economic factors, autistic traits and mental health across different settings

LAY ABSTRACT

Autistic individuals are more likely than non-autistic individuals to experience a mental health condition in their lifetime, and this includes externalising and internalising symptoms. We know very little about how different environments and family conditions impact these symptoms for autistic individuals. Improving our understanding of these relationships is important so that we can identify individuals who may be in greater need of support. In this article, we seek to improve our understanding of how environmental and family conditions impact externalising and internalising symptoms in autistic and non-autistic people. To do this, we conducted analyses with two cohorts in very different settings - in Europe and South Africa - to ensure our findings are globally representative. We used advanced statistical methods to establish environmental and family conditions that were similar to each other, and which could be combined into specific 'factors'. We found that four similar 'factors' could be identified in the two cohorts. These were distinguished by personal characteristics and environmental conditions of individuals, and were named Person Characteristics, Family System, Parental and Material Resources. Interestingly, just 'Family System' was associated with internalising and externalising symptoms, and this was the same in both cohorts. We also found that having high traits of autism impacted this relationship between Family System and mental health conditions with opposite directions in the two settings. These results show that characteristics in the Family System are associated with internalising and externalising symptoms, and autistic persons are particularly impacted, reinforcing the notion that family stressors are important to consider when implementing policy and practice related to improving the mental health of autistic people.

Is There a Bias Towards Males in the Diagnosis of Autism? A Systematic Review and Meta-Analysis

Autism is more frequently diagnosed in males, with evidence suggesting that females are more likely to be misdiagnosed or underdiagnosed. Possibly, the male/female ratio imbalance relates to phenotypic and camouflaging differences between genders. Here, we performed a comprehensive approach to phenotypic and camouflaging research in autism addressed in two studies. First (Study 1 - Phenotypic Differences in Autism), we conducted a systematic review and meta-analysis of gender differences in autism phenotype. The electronic datasets Pubmed, Scopus, Web of Science, and PsychInfo were searched. We included 67 articles that compared females and males in autism core symptoms, and in cognitive, socioemotional, and behavioural phenotypes. Autistic males exhibited more severe symptoms and social interaction difficulties on standard clinical measures than females, who, in turn, exhibited more cognitive and behavioural difficulties. Considering the hypothesis of camouflaging possibly underlying these differences, we then conducted a meta-analysis of gender differences in camouflaging (Study 2 - Camouflaging Differences in Autism). The same datasets as the first study were searched. Ten studies were included. Females used more compensation and masking camouflage strategies than males. The results support the argument of a bias in clinical procedures towards males and the importance of considering a 'female autism phenotype'-potentially involving camouflaging-in the diagnostic process.

Gray matter covariations in autism: out-of-sample replication using the ENIGMA autism cohort

BACKGROUND

Autism spectrum disorder (henceforth autism) is a complex neurodevelopmental condition associated with differences in gray matter (GM) volume covariations, as reported in our previous study of the Longitudinal European Autism Project (LEAP) data. To make progress on the identification of potential neural markers and to validate the robustness of our previous findings, we aimed to replicate our results using data from the Enhancing Neuroimaging Genetics Through Meta-Analysis (ENIGMA) autism working group.

METHODS

We studied 781 autistic and 927 non-autistic individuals (6-30 years, IQ ≥ 50), across 37 sites. Voxel-based morphometry was used to quantify GM volume as before. Subsequently, we used spatial maps of the two autism-related independent components (ICs) previously identified in the LEAP sample as templates for regression analyses to separately estimate the ENIGMA-participant loadings to each of these two ICs. Between-group differences in participants' loadings on each component were examined, and we additionally investigated the relation between participant loadings and autistic behaviors within the autism group.

RESULTS

The two components of interest, previously identified in the LEAP dataset, showed significant between-group differences upon regressions into the ENIGMA cohort. The associated brain patterns were consistent with those found in the initial identification study. The first IC was primarily associated with increased volumes of bilateral insula, inferior frontal gyrus, orbitofrontal cortex, and caudate in the autism group relative to the control group (β = 0.129, p = 0.013). The second IC was related to increased volumes of the bilateral amygdala, hippocampus, and parahippocampal gyrus in the autism group relative to non-autistic individuals (β = 0.116, p = 0.024). However, when accounting for the site-by-group interaction effect, no significant main effect of the group can be identified (p > 0.590). We did not find significant univariate association between the brain measures and behavior in autism (p > 0.085).

LIMITATIONS

The distributions of age, IQ, and sex between LEAP and ENIGMA are statistically different from each other. Owing to limited access to the behavioral data of the autism group, we were unable to further our understanding of the neural basis of behavioral dimensions of the sample.

CONCLUSIONS

The current study is unable to fully replicate the autism-related brain patterns from LEAP in the ENIGMA cohort. The diverse group effects across ENIGMA sites demonstrate the challenges of generalizing the average findings of the GM covariation patterns to a large-scale cohort integrated retrospectively from multiple studies. Further analyses need to be conducted to gain additional insights into the generalizability of these two GM covariation patterns.

Differences in Intrinsic Gray Matter Connectivity and Their Genomic Underpinnings in Autism Spectrum Disorder

BACKGROUND

Autism is a heterogeneous neurodevelopmental condition accompanied by differences in brain connectivity. Structural connectivity in autism has mainly been investigated within the white matter. However, many genetic variants associated with autism highlight genes related to synaptogenesis and axonal guidance, thus also implicating differences in intrinsic (i.e., gray matter) connections in autism. Intrinsic connections may be assessed in vivo via so-called intrinsic global and local wiring costs.

METHODS

Here, we examined intrinsic global and local wiring costs in the brain of 359 individuals with autism and 279 healthy control participants ages 6 to 30 years from the EU-AIMS LEAP (Longitudinal European Autism Project). FreeSurfer was used to derive surface mesh representations to compute the estimated length of connections required to wire the brain within the gray matter. Vertexwise between-group differences were assessed using a general linear model. A gene expression decoding analysis based on the Allen Human Brain Atlas was performed to link neuroanatomical differences to putative underpinnings.

RESULTS

Group differences in global and local wiring costs were predominantly observed in medial and lateral prefrontal brain regions, in inferior temporal regions, and at the left temporoparietal junction. The resulting neuroanatomical patterns were enriched for genes that had been previously implicated in the etiology of autism at genetic and transcriptomic levels.

CONCLUSIONS

Based on intrinsic gray matter connectivity, the current study investigated the complex neuroanatomy of autism and linked between-group differences to putative genomic and/or molecular mechanisms to parse the heterogeneity of autism and provide targets for future subgrouping approaches.

Autism Is Associated With Interindividual Variations of Gray and White Matter Morphology

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.

Why it is so challenging to perform economic evaluations of interventions in autism and what to do about it

Economic evaluation is used to determine the optimal provision of services and programs under budget constraints and to inform public and private payer funding decisions. To maximize value-for-money in the design and delivery of programs and services for persons with autism spectrum disorder (ASD), it's essential to generate high-quality economic evidence to inform budget allocation. There is a paucity however, of economic evaluations of interventions for ASD. This is due in part to challenges in conducting economic evaluations in this population and the lack of guidance on suitable approaches. These challenges are related to the inherent heterogeneity of the autistic population; establishing short- and long-term effectiveness; measurement of costs and the availability of valid instruments for collecting economic data; the appropriateness of outcomes for use in economic evaluation; and achieving statistical power. This commentary addresses a lack of awareness and needed guidance on these issues by discussing the challenges and providing recommendations for how economic evaluations in ASD could be improved to generate high-quality evidence for program funding decision-making.

The neuroanatomical substrates of autism and ADHD and their link to putative genomic underpinnings

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.

Pathways to peer interaction in ASD and TD through individual and dyadic joint-action motor abilities

Purpose

Any social engagement, especially with peers, requires children's effective activation of social and motor mechanisms. Children and adolescents with autism spectrum disorder (ASD) often display dysfunctions both in individual motor functioning (e.g., fine/gross) and in dyadic joint action (JA), where two partners coordinate movement toward a shared goal. Yet, these mechanisms' contribution to peer interaction has been underexplored.

Method

This study examined the contribution of individual motor functioning and JA performance to peer interaction (cooperation, attentiveness, social engagement, and dyadic quality), while comparing children and adolescents' (youngsters) with ASD versus those with typical development (TD).

Results

Results indicated more competent peer interaction in TD than in ASD. Interestingly, only the ASD group showed significant maturation with age for social engagement and dyadic interaction quality, calls for further examination of developmental trajectories. However, even the oldest participants with ASD continued to lag behind the youngest TD group. Also, findings indicated that better individual motor functioning and JA performance explained better peer interactive competence; yet, the contribution of individual motor functioning to social cooperation and dyadic quality was moderated by JA performance. Thus, youngsters' individual motor system was found to be an important contributor to peer interaction in those with low to moderate JA coordination capabilities, but not for those with high JA.

Conclusion

Results emphasize possible distinct contributions of each motor mechanism and their interaction for facilitating social interaction, hence, encouraging incorporation of individual and dyadic motor skills explicitly into social interaction interventions for youngsters ASD.

Fine-grained topographic organization within somatosensory cortex during resting-state and emotional face-matching task and its association with ASD traits

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.

The Construct Validity of the Childhood Joint Attention Rating Scale (C-JARS) in School-Aged Autistic Children

Preliminary evidence from the Childhood Joint Attention Rating Scale (C-JARS; Mundy et al., 2017) suggests symptoms related to diminished joint attention and the spontaneous sharing of experience with others can be assessed with a parent-report measure in children and adolescents with autism. This study was designed to expand on the previous study by examining the validity of both a Social Symptom (SS) and a Prosocial (PS) scale of the C-JARS in a study of school-aged autistic children (n  = 89) with and without co-occurring intellectual disability (ID), as well as an age matched neurotypical sample (n  = 62). Results indicated that both C-JARS scales were sensitive and specific with respect to identifying the diagnostic status of the children. In addition, the PS scale was sensitive to differences in cognitive abilities (IQ) and sex differences in the autism group. These results are consistent with the hypothesis that joint attention and spontaneous sharing of experience symptoms are not only characteristic of preschool children with autism but may also constitute a developmentally continuous dimension of the social phenotype of autism that can be measured in school-aged children.

Prediction of Behavioral Improvement Through Resting-State Electroencephalography and Clinical Severity in a Randomized Controlled Trial Testing Bumetanide in Autism Spectrum Disorder

BACKGROUND

Mechanism-based treatments such as bumetanide are being repurposed for autism spectrum disorder. We recently reported beneficial effects on repetitive behavioral symptoms that might be related to regulating excitation-inhibition (E/I) balance in the brain. Here, we tested the neurophysiological effects of bumetanide and the relationship to clinical outcome variability and investigated the potential for machine learning-based predictions of meaningful clinical improvement.

METHODS

Using modified linear mixed models applied to intention-to-treat population, we analyzed E/I-sensitive electroencephalography (EEG) measures before and after 91 days of treatment in the double-blind, randomized, placebo-controlled Bumetanide in Autism Medication and Biomarker study. Resting-state EEG of 82 subjects out of 92 participants (7-15 years) were available. Alpha frequency band absolute and relative power, central frequency, long-range temporal correlations, and functional E/I ratio treatment effects were related to the Repetitive Behavior Scale-Revised (RBS-R) and the Social Responsiveness Scale 2 as clinical outcomes.

RESULTS

We observed superior bumetanide effects on EEG, reflected in increased absolute and relative alpha power and functional E/I ratio and in decreased central frequency. Associations between EEG and clinical outcome change were restricted to subgroups with medium to high RBS-R improvement. Using machine learning, medium and high RBS-R improvement could be predicted by baseline RBS-R score and EEG measures with 80% and 92% accuracy, respectively.

CONCLUSIONS

Bumetanide exerts neurophysiological effects related to clinical changes in more responsive subsets, in whom prediction of improvement was feasible through EEG and clinical measures.

IQ trajectories in autistic children through preadolescence

BACKGROUND

We extended our study of trajectories of intellectual development of autistic individuals in early (mean age 3 years; T1), and middle childhood (mean age 5 years, 7 months; T2) into later middle childhood/preadolescence (mean age 11 years, 6 months; T3) in the longitudinal Autism Phenome Project cohort. Participants included 373 autistic children (115 females).

METHODS

Multivariate latent class growth analysis was used to identify distinct IQ trajectory subgroups. Baseline and developmental course group differences and predictors of trajectory membership were assessed using linear mixed effects models with repeated measures with pairwise testing, multinomial logistic regression models, and sensitivity analyses.

RESULTS

We isolated three IQ trajectories between T1 and T3 for autistic youth that were similar to those found in our prior work. These included a group with persistent intellectual disability (ID; 45%), a group with substantial increases in IQ (CHG; 39%), and a group with persistently average or above IQs (P-High; 16%). By T3, the groups did not differ in ADOS-2 calibrated severity scores (CSS), and there were no group differences between Vineland (VABS) communication scores in CHG and P-High. T1-T3 externalizing behaviors declined significantly for CHG, however, there were no significant T3 group differences between internalizing or externalizing symptoms. T1 correlates for CHG and P-High versus ID group membership included higher VABS communication and lower ADOS-2 CSS. A T1 to T2 increase in VABS communication scores and a decline in externalizing predicted CHG versus ID group membership at T3, while T1 to T2 improvement in VABS communication and reduction in ADOS-2 CSS predicted P-High versus ID group membership.

CONCLUSIONS

Autistic youth exhibit consistent IQ developmental trajectories from early childhood through preadolescence. Factors associated with trajectory group membership may provide clues about prognosis, and the need for treatments that improve adaptive communication and externalizing symptoms.

Exploring developmental trajectories throughout adolescence of children with autism spectrum disorder without intellectual disability

Characterizing the developmental trajectories of children with autism spectrum disorder (ASD) throughout adolescence and across different domains of functioning offers opportunities to improve long-term outcomes. This prospective study explored, for the first time, the evolution of children with ASD-without intellectual disability (ID) in terms of socio-adaptative skills, learning behaviors, executive functioning (EF), and internalizing/externalizing problems, compared to typically developing (TD) peers. Forty-five children with ASD-without ID and 37 matched TD children (aged 7-11) were assessed at baseline and after 5 years. Parents and teachers completed measures on theory of mind (ToM), socialization, daily living skills, learning style, EF, and emotional/behavioural difficulties at both time points. On all the domains assessed, the ASD group performed significantly worse than the TD group, both in childhood and adolescence. Specific changes were noted between baseline and follow-up assessment on adaptive skills, prosocial behavior, emotional control, inhibit, working memory and monitoring. Group membership (ASD/TD) was influenced by peer relationships and inhibit EF variables. These findings have implications for clinical and school settings.

Processing of social and monetary rewards in autism spectrum disorders

BACKGROUND

Reward processing has been proposed to underpin the atypical social feature of autism spectrum disorder (ASD). However, previous neuroimaging studies have yielded inconsistent results regarding the specificity of atypicalities for social reward processing in ASD.

AIMS

Utilising a large sample, we aimed to assess reward processing in response to reward type (social, monetary) and reward phase (anticipation, delivery) in ASD.

METHOD

Functional magnetic resonance imaging during social and monetary reward anticipation and delivery was performed in 212 individuals with ASD (7.6-30.6 years of age) and 181 typically developing participants (7.6-30.8 years of age).

RESULTS

Across social and monetary reward anticipation, whole-brain analyses showed hypoactivation of the right ventral striatum in participants with ASD compared with typically developing participants. Further, region of interest analysis across both reward types yielded ASD-related hypoactivation in both the left and right ventral striatum. Across delivery of social and monetary reward, hyperactivation of the ventral striatum in individuals with ASD did not survive correction for multiple comparisons. Dimensional analyses of autism and attention-deficit hyperactivity disorder (ADHD) scores were not significant. In categorical analyses, post hoc comparisons showed that ASD effects were most pronounced in participants with ASD without co-occurring ADHD.

CONCLUSIONS

Our results do not support current theories linking atypical social interaction in ASD to specific alterations in social reward processing. Instead, they point towards a generalised hypoactivity of ventral striatum in ASD during anticipation of both social and monetary rewards. We suggest this indicates attenuated reward seeking in ASD independent of social content and that elevated ADHD symptoms may attenuate altered reward seeking in ASD.

Sensory salience processing moderates attenuated gazes on faces in autism spectrum disorder: a case-control study

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.

Candidate diagnostic biomarkers for neurodevelopmental disorders in children and adolescents: a systematic review

Neurodevelopmental disorders - including attention-deficit/hyperactivity disorder (ADHD), autism spectrum disorder, communication disorders, intellectual disability, motor disorders, specific learning disorders, and tic disorders - manifest themselves early in development. Valid, reliable and broadly usable biomarkers supporting a timely diagnosis of these disorders would be highly relevant from a clinical and public health standpoint. We conducted the first systematic review of studies on candidate diagnostic biomarkers for these disorders in children and adolescents. We searched Medline and Embase + Embase Classic with terms relating to biomarkers until April 6, 2022, and conducted additional targeted searches for genome-wide association studies (GWAS) and neuroimaging or neurophysiological studies carried out by international consortia. We considered a candidate biomarker as promising if it was reported in at least two independent studies providing evidence of sensitivity and specificity of at least 80%. After screening 10,625 references, we retained 780 studies (374 biochemical, 203 neuroimaging, 133 neurophysiological and 65 neuropsychological studies, and five GWAS), including a total of approximately 120,000 cases and 176,000 controls. While the majority of the studies focused simply on associations, we could not find any biomarker for which there was evidence - from two or more studies from independent research groups, with results going into the same direction - of specificity and sensitivity of at least 80%. Other important metrics to assess the validity of a candidate biomarker, such as positive predictive value and negative predictive value, were infrequently reported. Limitations of the currently available studies include mostly small sample size, heterogeneous approaches and candidate biomarker targets, undue focus on single instead of joint biomarker signatures, and incomplete accounting for potential confounding factors. Future multivariable and multi-level approaches may be best suited to find valid candidate biomarkers, which will then need to be validated in external, independent samples and then, importantly, tested in terms of feasibility and cost-effectiveness, before they can be implemented in daily clinical practice.

Tackling hypo and hyper sensory processing heterogeneity in autism: From clinical stratification to genetic pathways

As an integral part of autism spectrum symptoms, sensory processing issues including both hypo and hyper sensory sensitivities. These sensory specificities may result from an excitation/inhibition imbalance with a poorly understood of their level of convergence with genetic alterations in GABA-ergic and glutamatergic pathways. In our study, we aimed to characterize the hypo/hyper-sensory profile among autistic individuals. We then explored its link with the burden of deleterious mutations in a subset of individuals with available whole-genome sequencing data. To characterize the hypo/hyper-sensory profile, the differential Short Sensory Profile (dSSP) was defined as a normalized and centralized hypo/hypersensitivity ratio from the Short Sensory Profile (SSP). Including 1136 participants (533 autistic individuals, 210 first-degree relatives, and 267 controls) from two independent study samples (PARIS and LEAP), we observed a statistically significant dSSP mean difference between autistic individuals and controls, driven mostly by a high dSSP variability, with an intermediated profile represented by relatives. Our genetic analysis tended to associate the dSSP and the hyposensitivity with mutations of the GABAergic pathway. The major limitation was the dSSP difficulty to discriminate subjects with a similar quantum of hypo- and hyper-sensory symptoms to those with no such symptoms, resulting both in a similar ratio score of 0. However, the dSSP could be a relevant clinical score, and combined with additional sensory descriptions, genetics and endophenotypic substrates, will improve the exploration of the underlying neurobiological mechanisms of sensory processing differences in autism spectrum.

Quality of Life, Neurosensory Disorders and Co-Occurring Medical Conditions in Individuals on the Spectrum, with a Special Focus on Females Diagnosed with Autism: A Systematic Review

Autism Spectrum Disorder (ASD) is a neurodevelopmental disorder that has a high prevalence and a significant economic impact. Our knowledge regarding neurosensory disorders and co-occurring medical conditions in the ASD population is limited, particularly for autistic women. Most of the studies include male participants or do not make comparisons with their female counterparts. The objective of this systematic review article is to explore the quality of life as well as the prevalence of neurosensory disorders and co-occurring medical conditions in individuals on the spectrum, with a special focus on autistic females. The literature search was carried out in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) criteria. A protocol of this systematic review was designed a priori and was registered in the PROSPERO database (registration number: CRD42022330368). We concluded that numerous medical areas were of concern. Autistic females are more likely than their male counterparts with ASD to suffer from psychiatric conditions such as post-traumatic stress syndrome, depression, and eating disorders. They are also more likely to report GI-related disturbances and chronic pain. Further investigations are warranted to determine quality of life, as well as the prevalence and severity of neurosensory disorders in individuals with ASD, specifically studies comparing autistic females with their male counterparts. The information derived from these studies will help develop better support systems for individuals with autism, particularly females on the spectrum, in pursuit of improving their quality of life.

Excitatory/inhibitory imbalance in autism: the role of glutamate and GABA gene-sets in symptoms and cortical brain structure

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.

Associations Between Caregiver Stress and Language Outcomes in Infants With Autistic and Non-Autistic Siblings: An Exploratory Study

PURPOSE

Caregivers of autistic children present with high stress levels, which have been associated with poorer child outcomes in several domains, including language development. However, prior to this study, it was unknown whether elevated caregiver stress was associated with language development in infant siblings of autistic children (Sibs-autism), who are at increased likelihood of receiving a future diagnosis of autism and/or language impairment compared to infant siblings of non-autistic children. This study explored the degree to which, as well as the mechanisms by which, caregiver stress was linked with later language outcomes of Sibs-autism and infant siblings of non-autistic children (Sibs-NA).

METHOD

Participants were 50 infants (28 Sibs-autism; 22 Sibs-NA) aged 12-18 months at the first time point in this study (Time 1). Infants were seen again 9 months later, at 21-27 months of age (Time 2). Caregiver stress was measured via a validated self-report measure at Time 1. Caregiver language input, the putative mechanism by which caregiver stress may influence later language outcomes, was collected via two daylong recordings from digital recording (Language ENvironment Analysis) devices worn by the child at this same time point. Child language outcomes were measured via standardized and caregiver report measures at Time 2.

RESULTS

Several models testing hypothesized indirect effects of caregiver stress on later child language outcomes through caregiver language input were statistically significant. Specifically, significant indirect effects suggest that (a) caregivers with increased stress tend to speak less to their infants, and (b) this reduced language input tends to covary with reduced child language outcomes later in life for Sibs-autism and Sibs-NA.

CONCLUSIONS

This study provides new insights into links between caregiver stress, caregiver language input, and language outcomes in Sibs-autism and Sibs-NA. Further work is necessary to understand how to best support caregivers and optimize the language learning environments for infants.

SUPPLEMENTAL MATERIAL

https://doi.org/10.23641/asha.21714368.

The Link Between Autism and Sex-Related Neuroanatomy, and Associated Cognition and Gene Expression

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 T₁-weighted structural brain images, the authors compared sex prediction model performance across neurotypical and autistic males and females. Multiple large-scale data sets comprising T₁-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.

Does the current state of biomarker discovery in autism reflect the limits of reductionism in precision medicine? Suggestions for an integrative approach that considers dynamic mechanisms between brain, body, and the social environment

Over the past decade, precision medicine has become one of the most influential approaches in biomedical research to improve early detection, diagnosis, and prognosis of clinical conditions and develop mechanism-based therapies tailored to individual characteristics using biomarkers. This perspective article first reviews the origins and concept of precision medicine approaches to autism and summarises recent findings from the first "generation" of biomarker studies. Multi-disciplinary research initiatives created substantially larger, comprehensively characterised cohorts, shifted the focus from group-comparisons to individual variability and subgroups, increased methodological rigour and advanced analytic innovations. However, although several candidate markers with probabilistic value have been identified, separate efforts to divide autism by molecular, brain structural/functional or cognitive markers have not identified a validated diagnostic subgroup. Conversely, studies of specific monogenic subgroups revealed substantial variability in biology and behaviour. The second part discusses both conceptual and methodological factors in these findings. It is argued that the predominant reductionist approach, which seeks to parse complex issues into simpler, more tractable units, let us to neglect the interactions between brain and body, and divorce individuals from their social environment. The third part draws on insights from systems biology, developmental psychology and neurodiversity approaches to outline an integrative approach that considers the dynamic interaction between biological (brain, body) and social mechanisms (stress, stigma) to understanding the origins of autistic features in particular conditions and contexts. This requires 1) closer collaboration with autistic people to increase face validity of concepts and methodologies; (2) development of measures/technologies that enable repeat assessment of social and biological factors in different (naturalistic) conditions and contexts, (3) new analytic methods to study (simulate) these interactions (including emergent properties), and (4) cross-condition designs to understand which mechanisms are transdiagnostic or specific for particular autistic sub-populations. Tailored support may entail both creating more favourable conditions in the social environment and interventions for some autistic people to increase well-being.

Predictors of individual differences in minimally verbal peer communication exchanges following peer-oriented social intervention

School-age children on the autism spectrum who are minimally verbal (MVAS) use a limited repertoire of spontaneous communicative spoken words and reveal large heterogeneity in cognitive functioning. Despite the challenges to form peer social engagement posed by their unique social-communicative profile, few interventions have targeted peer interactions in the MVAS population. This study explored predictors of individual differences in treatment response among 54 school-age minimally verbal autistic children (8-16 years) following an RCT "school-based peer social intervention" (S-PSI) that compared two peer-oriented intervention modalities (conversation versus collaboration) versus a waitlisted control group. We examined autistic-symptom severity, age, verbal and nonverbal IQ, executive functions, and sensory-processing profile for their contribution to children's ability to form relevant spontaneous communication exchanges with a peer partner. Main findings revealed that larger deficits in sensory-processing (sensory-avoidance and sensory low-registration) and in executive functions contributed to greater growth in "relevant" (i.e., adequately attuned, participatory, reciprocal) communication following both interventions, but not for the waitlisted controls. Additionally, older participants with lower verbal and nonverbal IQ improved communication's relevancy more after the conversation intervention, whereas the collaboration intervention was more beneficial for younger participants. Lower autistic-symptom severity contributed to larger growth in relevancy for all groups. By identifying individual-level predictors of spontaneous, attuned, participatory, and reciprocal (i.e., "relevant") communication exchanges with peers, we optimized S-PSI personalization for this uniquely nonverbal, heterogeneous MVAS population. These new channels for tailoring peer interventions to better meet individuals' needs may result in reduced social isolation and loneliness and enhanced well-being.

Patterns of connectome variability in autism across five functional activation tasks: findings from the LEAP project

BACKGROUND

Autism spectrum disorder (autism) is a complex neurodevelopmental condition with pronounced behavioral, cognitive, and neural heterogeneities across individuals. Here, our goal was to characterize heterogeneity in autism by identifying patterns of neural diversity as reflected in BOLD fMRI in the way individuals with autism engage with a varied array of cognitive tasks.

METHODS

All analyses were based on the EU-AIMS/AIMS-2-TRIALS multisite Longitudinal European Autism Project (LEAP) with participants with autism (n = 282) and typically developing (TD) controls (n = 221) between 6 and 30 years of age. We employed a novel task potency approach which combines the unique aspects of both resting state fMRI and task-fMRI to quantify task-induced variations in the functional connectome. Normative modelling was used to map atypicality of features on an individual basis with respect to their distribution in neurotypical control participants. We applied robust out-of-sample canonical correlation analysis (CCA) to relate connectome data to behavioral data.

RESULTS

Deviation from the normative ranges of global functional connectivity was greater for individuals with autism compared to TD in each fMRI task paradigm (all tasks p < 0.001). The similarity across individuals of the deviation pattern was significantly increased in autistic relative to TD individuals (p < 0.002). The CCA identified significant and robust brain-behavior covariation between functional connectivity atypicality and autism-related behavioral features.

CONCLUSIONS

Individuals with autism engage with tasks in a globally atypical way, but the particular spatial pattern of this atypicality is nevertheless similar across tasks. Atypicalities in the tasks originate mostly from prefrontal cortex and default mode network regions, but also speech and auditory networks. We show how sophisticated modeling methods such as task potency and normative modeling can be used toward unravelling complex heterogeneous conditions like autism.

Connectome-wide Mega-analysis Reveals Robust Patterns of Atypical Functional Connectivity in Autism

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.

Comparing the test-retest reliability of resting-state functional magnetic resonance imaging metrics across single band and multiband acquisitions in the context of healthy aging

The identification of meaningful functional magnetic resonance imaging (fMRI) biomarkers requires measures that reliably capture brain performance across different subjects and over multiple scanning sessions. Recent developments in fMRI acquisition, such as the introduction of multiband (MB) protocols and in-plane acceleration, allow for increased scanning speed and improved temporal resolution. However, they may also lead to reduced temporal signal to noise ratio and increased signal leakage between simultaneously excited slices. These methods have been adopted in several scanning modalities including diffusion weighted imaging and fMRI. To our knowledge, no study has formally compared the reliability of the same resting-state fMRI (rs-fMRI) metrics (amplitude of low-frequency fluctuations; seed-to-voxel and region of interest [ROI]-to-ROI connectivity) across conventional single-band fMRI and different MB acquisitions, with and without in-plane acceleration, across three sessions. In this study, 24 healthy older adults were scanned over three visits, on weeks 0, 1, and 4, and, on each occasion, underwent a conventional single band rs-fMRI scan and three different rs-fMRI scans with MB factors 4 and 6, with and without in-plane acceleration. Across all three rs-fMRI metrics, the reliability scores were highest with MB factor 4 with no in-plane acceleration for cortical areas and with conventional single band for subcortical areas. Recommendations for future research studies are discussed.

Unique dynamic profiles of social attention in autistic females

BACKGROUND

Social attention affords learning opportunities across development and may contribute to individual differences in developmental trajectories, such as between male and female individuals, and in neurodevelopmental conditions, such as autism.

METHODS

Using eye-tracking, we measured social attention in a large cohort of autistic (n = 123) and nonautistic females (n = 107), and autistic (n = 330) and nonautistic males (n = 204), aged 6-30 years. Using mixed Growth Curve Analysis, we modelled sex and diagnostic effects on the temporal dynamics of proportional looking time to three types of social stimuli (lean-static, naturalistic-static, and naturalistic-dynamic) and examined the link between individual differences and dimensional social and nonsocial autistic traits in autistic females and males.

RESULTS

In the lean-static stimulus, average face-looking was higher in females than in males of both autistic and nonautistic groups. Differences in the dynamic pattern of face-looking were seen in autistic vs. nonautistic females, but not males, with face-looking peaking later in the trial in autistic females. In the naturalistic-dynamic stimulus, average face-looking was higher in females than in males of both groups; changes in the dynamic pattern of face looking were seen in autistic vs. nonautistic males, but not in females, with a steeper peak in nonautistic males. Lower average face-looking was associated with higher observer-measured autistic characteristics in autistic females, but not in males.

CONCLUSIONS

Overall, we found stronger social attention in females to a similar degree in both autistic and nonautistic groups. Nonetheless, the dynamic profiles of social attention differed in different ways in autistic females and males compared to their nonautistic peers, and autistic traits predicted trends of average face-looking in autistic females. These findings support the role of social attention in the emergence of sex-related differences in autistic characteristics, suggesting an avenue to phenotypic stratification.

Test-retest reliability of time-varying patterns of brain activity across single band and multiband resting-state functional magnetic resonance imaging in healthy older adults

Leading Eigenvector Dynamics Analysis (LEiDA) is an analytic approach that characterizes brain activity recorded with functional Magnetic Resonance Imaging (fMRI) as a succession of discrete phase-locking patterns, or states, that consistently recur over time across all participants. LEiDA allows for the extraction of three state-related measures which have previously been key to gaining a better understanding of brain dynamics in both healthy and clinical populations: the probability of occurrence of a given state, its lifetime and the probability of switching from one state to another. The degree to which test-retest reliability of the LEiDA measures may be affected by increasing MRI multiband (MB) factors in comparison with single band sequences is yet to be established. In this study, 24 healthy older adults were scanned over three sessions, on weeks 0, 1, and 4. On each visit, they underwent a conventional single band resting-state fMRI (rs-fMRI) scan and three different MB rs-fMRI scans, with MB factors of 4, with and without in-plane acceleration, and 6 without in-plane acceleration. We found test-retest reliability scores to be significantly higher with MB factor 4 with and without in-plane acceleration for most cortical networks. These findings will inform the choice of acquisition parameters for future studies and clinical trials.

Facial expression recognition is linked to clinical and neurofunctional differences in autism

BACKGROUND

Difficulties in social communication are a defining clinical feature of autism. However, the underlying neurobiological heterogeneity has impeded targeted therapies and requires new approaches to identifying clinically relevant bio-behavioural subgroups. In the largest autism cohort to date, we comprehensively examined difficulties in facial expression recognition, a key process in social communication, as a bio-behavioural stratification biomarker, and validated them against clinical features and neurofunctional responses.

METHODS

Between 255 and 488 participants aged 6-30 years with autism, typical development and/or mild intellectual disability completed the Karolinska Directed Emotional Faces task, the Reading the Mind in the Eyes Task and/or the Films Expression Task. We first examined mean-group differences on each test. Then, we used a novel intersection approach that compares two centroid and connectivity-based clustering methods to derive subgroups based on the combined performance across the three tasks. Measures and subgroups were then related to clinical features and neurofunctional differences measured using fMRI during a fearful face-matching task.

RESULTS

We found significant mean-group differences on each expression recognition test. However, cluster analyses showed that these were driven by a low-performing autistic subgroup (~ 30% of autistic individuals who performed below 2SDs of the neurotypical mean on at least one test), while a larger subgroup (~ 70%) performed within 1SD on at least 2 tests. The low-performing subgroup also had on average significantly more social communication difficulties and lower activation in the amygdala and fusiform gyrus than the high-performing subgroup.

LIMITATIONS

Findings of autism expression recognition subgroups and their characteristics require independent replication. This is currently not possible, as there is no other existing dataset that includes all relevant measures. However, we demonstrated high internal robustness (91.6%) of findings between two clustering methods with fundamentally different assumptions, which is a critical pre-condition for independent replication.

CONCLUSIONS

We identified a subgroup of autistic individuals with expression recognition difficulties and showed that this related to clinical and neurobiological characteristics. If replicated, expression recognition may serve as bio-behavioural stratification biomarker and aid in the development of targeted interventions for a subgroup of autistic individuals.

Cerebellar Atypicalities in Autism?

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.

Qualitative differences in the spatiotemporal brain states supporting configural face processing emerge in adolescence in autism

BACKGROUND

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.

METHODS

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.

RESULTS

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.

CONCLUSIONS

These findings suggest that early difficulties with configural face processing may trigger later compensatory processes in autism that emerge in later development.

Longitudinal Stability of Intellectual Functioning in Autism Spectrum Disorder: From Age 3 Through Mid-adulthood

Intelligence (IQ) scores are used in educational and vocational planning for individuals with autism spectrum disorder (ASD) yet little is known about the stability of IQ throughout development. We examined longitudinal age-related IQ stability in 119 individuals with ASD (3-36 years of age at first visit) and 128 typically developing controls. Intelligence measures were collected over a 20-year period. In ASD, Full Scale (FSIQ) and Verbal (VIQ) Intelligence started lower in childhood and increased at a greater rate with age relative to the control group. By early adulthood, VIQ and working memory stabilized, whereas nonverbal and perceptual scores continued to change. Our results suggest that in individuals with ASD, IQ estimates may be dynamic in childhood and young adulthood.

Genetic correlates of phenotypic heterogeneity in autism

The substantial phenotypic heterogeneity in autism limits our understanding of its genetic etiology. To address this gap, here we investigated genetic differences between autistic individuals (nmax = 12,893) based on core and associated features of autism, co-occurring developmental disabilities and sex. We conducted a comprehensive factor analysis of core autism features in autistic individuals and identified six factors. Common genetic variants were associated with the core factors, but de novo variants were not. We found that higher autism polygenic scores (PGS) were associated with lower likelihood of co-occurring developmental disabilities in autistic individuals. Furthermore, in autistic individuals without co-occurring intellectual disability (ID), autism PGS are overinherited by autistic females compared to males. Finally, we observed higher SNP heritability for autistic males and for autistic individuals without ID. Deeper phenotypic characterization will be critical in determining how the complex underlying genetics shape cognition, behavior and co-occurring conditions in autism.

Stratifying the autistic phenotype using electrophysiological indices of social perception

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.

Evaluation of data imputation strategies in complex, deeply-phenotyped data sets: the case of the EU-AIMS Longitudinal European Autism Project

An increasing number of large-scale multi-modal research initiatives has been conducted in the typically developing population, e.g. Dev. Cogn. Neur. 32:43-54, 2018; PLoS Med. 12(3):e1001779, 2015; Elam and Van Essen, Enc. Comp. Neur., 2013, as well as in psychiatric cohorts, e.g. Trans. Psych. 10(1):100, 2020; Mol. Psych. 19:659–667, 2014; Mol. Aut. 8:24, 2017; Eur. Child and Adol. Psych. 24(3):265–281, 2015. Missing data is a common problem in such datasets due to the difficulty of assessing multiple measures on a large number of participants. The consequences of missing data accumulate when researchers aim to integrate relationships across multiple measures. Here we aim to evaluate different imputation strategies to fill in missing values in clinical data from a large (total N = 764) and deeply phenotyped (i.e. range of clinical and cognitive instruments administered) sample of N = 453 autistic individuals and N = 311 control individuals recruited as part of the EU-AIMS Longitudinal European Autism Project (LEAP) consortium. In particular, we consider a total of 160 clinical measures divided in 15 overlapping subsets of participants. We use two simple but common univariate strategies—mean and median imputation—as well as a Round Robin regression approach involving four independent multivariate regression models including Bayesian Ridge regression, as well as several non-linear models: Decision Trees (Extra Trees., and Nearest Neighbours regression. We evaluate the models using the traditional mean square error towards removed available data, and also consider the Kullback–Leibler divergence between the observed and the imputed distributions. We show that all of the multivariate approaches tested provide a substantial improvement compared to typical univariate approaches. Further, our analyses reveal that across all 15 data-subsets tested, an Extra Trees regression approach provided the best global results. This not only allows the selection of a unique model to impute missing data for the LEAP project and delivers a fixed set of imputed clinical data to be used by researchers working with the LEAP dataset in the future, but provides more general guidelines for data imputation in large scale epidemiological studies.

Large multicenter randomized trials in autism: key insights gained from the balovaptan clinical development program

BACKGROUND

Autism spectrum disorder (ASD) is a common and heterogeneous neurodevelopmental condition that is characterized by the core symptoms of social communication difficulties and restricted and repetitive behaviors. At present, there is an unmet medical need for therapies to ameliorate these core symptoms in order to improve quality of life of autistic individuals. However, several challenges are currently faced by the ASD community relating to the development of pharmacotherapies, namely in the conduct of clinical trials. Balovaptan is a V1a receptor antagonist that has been investigated to improve social communication difficulties in individuals with ASD. In this viewpoint, we draw upon our recent first-hand experiences of the balovaptan clinical development program to describe current challenges of ASD trials.

DISCUSSION POINTS

The balovaptan trials were conducted in a wide age range of individuals with ASD with the added complexities associated with international trials. When summarizing all three randomized trials of balovaptan, a placebo response was observed across several outcome measures. Placebo response was predicted by greater baseline symptom severity, online recruitment of participants, and less experienced or non-academic trial sites. We also highlight challenges relating to selection of outcome measures in ASD, the impact of baseline characteristics, and the role of expectation bias in influencing trial results.

CONCLUSION

Taken together, the balovaptan clinical development program has advanced our understanding of the key challenges facing ASD treatment research. The insights gained can be used to inform and improve the design of future clinical trials with the collective aim of developing efficacious therapies to support individuals with ASD.

Developing Gene-Based Personalised Interventions in Autism Spectrum Disorders

Autism spectrum disorder (ASD) is a neurodevelopmental disorder with onset in early childhood [...]

Alexithymia in autism: cross-sectional and longitudinal associations with social-communication difficulties, anxiety and depression symptoms

BACKGROUND

Alexithymia (difficulties in identifying and describing emotion) is a transdiagnostic trait implicated in social-emotional and mental health problems in the general population. Many autistic individuals experience significant social-communication difficulties and elevated anxiety/depression and alexithymia. Nevertheless, the role of alexithymia in explaining individual variability in the quality/severity of social-communication difficulties and/or anxiety and depression symptoms in autism remains poorly understood.

METHODS

In total, 337 adolescents and adults (autism N = 179) were assessed for alexithymia on the Toronto Alexithymia Scale and for social-communication difficulties, anxiety and depression symptoms. A total of 135 individuals (autism N = 76) were followed up 12-24 months later. We used regression models to establish cross-sectional and longitudinal associations between alexithymia, social-communication difficulties, anxiety and depression symptoms.

RESULTS

Autistic individuals reported significantly higher alexithymia than comparison individuals (p < 0.001, r effect size = 0.48), with 47.3% of autistic females and 21.0% of autistic males meeting cut-off for clinically relevant alexithymia (score ⩾61). Difficulties in describing feelings were particularly associated with current self-reported social-communication difficulties [p < 0.001, β = 0.57, 95% confidence interval (CI) 0.44-0.67] and predicted later social-communication difficulties (p = 0.02, β = 0.43, 95% CI 0.07-0.82). Difficulties in identifying feelings were particularly associated with current anxiety symptom severity (p < 0.001, β = 0.54, 95% CI 0.41-0.77) and predicted later anxiety (p = 0.01; β = 0.31, 95% CI 0.08-0.62).

CONCLUSIONS

Our findings suggest that difficulties in identifying v. describing emotion are associated with differential clinical outcomes in autism. Psychological therapies targeting emotional awareness may improve social-communication and anxiety symptoms in autism, potentially conferring long-term benefits.

Resting state EEG power spectrum and functional connectivity in autism: a cross-sectional analysis

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.

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

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

Neurobiological Correlates of Change in Adaptive Behavior in Autism

OBJECTIVE

Autism spectrum disorder (ASD) is a lifelong neurodevelopmental condition that is associated with significant difficulties in adaptive behavior and variation in clinical outcomes across the life span. Some individuals with ASD improve, whereas others may not change significantly, or regress. Hence, the development of "personalized medicine" approaches is essential. However, this requires an understanding of the biological processes underpinning differences in clinical outcome, at both the individual and subgroup levels, across the lifespan.

METHODS

The authors conducted a longitudinal follow-up study of 483 individuals (204 with ASD and 279 neurotypical individuals, ages 6-30 years), with assessment time points separated by ∼12-24 months. Data collected included behavioral data (Vineland Adaptive Behavior Scale-II), neuroanatomical data (structural MRI), and genetic data (DNA). Individuals with ASD were grouped into clinically meaningful "increasers," "no-changers," and "decreasers" in adaptive behavior. First, the authors compared neuroanatomy between outcome groups. Next, they examined whether deviations from the neurotypical neuroanatomical profile were associated with outcome at the individual level. Finally, they explored the observed neuroanatomical differences' potential genetic underpinnings.

RESULTS

Outcome groups differed in neuroanatomical features (cortical volume and thickness, surface area), including in "social brain" regions previously implicated in ASD. Also, deviations of neuroanatomical features from the neurotypical profile predicted outcome at the individual level. Moreover, neuroanatomical differences were associated with genetic processes relevant to neuroanatomical phenotypes (e.g., synaptic development).

CONCLUSIONS

This study demonstrates, for the first time, that variation in clinical (adaptive) outcome is associated with both group- and individual-level variation in anatomy of brain regions enriched for genes relevant to ASD. This may facilitate the move toward better targeted/precision medicine approaches.

Sex- and age-related differences in autistic behaviours in children with neurofibromatosis type 1

This study investigated sex and age differences in autistic behaviours in children with neurofibromatosis type 1 (NF1) who scored within the clinical range on the Social Responsiveness Scale - Second Edition (T score ≥ 60). Thirty-four males and 28 females (3-16 years) were assessed with the Autism Diagnostic Observation Schedule - Second Edition and Autism Diagnostic Interview - Revised. Across both measures, males exhibited greater social communication deficits relative to females. Age-related abatement of social communication difficulties was observed for males but not females. Conversely, no sex differences were found for restricted/repetitive behaviours, which were stable over time for both males and females. The findings are discussed within the context of broader neurodevelopmental considerations that are common in NF1.

Interindividual Differences in Cortical Thickness and Their Genomic Underpinnings in Autism Spectrum Disorder

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.

Following Excitation/Inhibition Ratio Homeostasis from Synapse to EEG in Monogenetic Neurodevelopmental Disorders

Pharmacological options for neurodevelopmental disorders are limited to symptom suppressing agents that do not target underlying pathophysiological mechanisms. Studies on specific genetic disorders causing neurodevelopmental disorders have elucidated pathophysiological mechanisms to develop more rational treatments. Here, we present our concerted multi-level strategy ‘BRAINMODEL’, focusing on excitation/inhibition ratio homeostasis across different levels of neuroscientific interrogation. The aim is to develop personalized treatment strategies by linking iPSC-based models and novel EEG measurements to patient report outcome measures in individual patients. We focus our strategy on chromatin- and SNAREopathies as examples of severe genetic neurodevelopmental disorders with an unmet need for rational interventions.

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

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

Neural Transcriptomic Analysis of Sex Differences in Autism Spectrum Disorder: Current Insights and Future Directions

Autism spectrum disorder (ASD) is consistently diagnosed 3 to 5 times more frequently in males than females, a dramatically sex-biased prevalence that suggests the involvement of sex-differential biological factors in modulating risk. The genomic scale of transcriptomic analyses of human brain tissue can provide an unbiased approach for identifying genes and associated functional processes at the intersection of sex-differential and ASD-impacted neurobiology. Several studies characterizing gene expression changes in the ASD brain have been published in recent years with increasing sample size and cellular resolution. These studies report several convergent patterns across data sets and genetically heterogeneous samples in the ASD brain, including elevated expression of gene sets associated with glial and immune function, and reduced expression of gene sets associated with neuronal and synaptic functions. Assessment of neurotypical cortex tissue has reported parallel patterns by sex, with male-elevated expression of overlapping sets of glial/immune-related genes and female-biased expression of neuron-associated genes, suggesting potential roles for these cell types in sex-differential ASD risk mechanisms. However, validating and further exploring these mechanisms is challenged by the available data, as existing studies of ASD brain include a limited number of female ASD donors and focus predominantly on cortex regions not known to show pronounced sex-differential morphology or function. With this review, we summarize convergent findings from several landmark studies of the transcriptome in ASD brain and their relationship to sex-differential gene expression, and we discuss limitations and remaining questions regarding transcriptomic analysis of sex differences in ASD.

Preference for biological motion is reduced in ASD: implications for clinical trials and the search for biomarkers

BACKGROUND

The neurocognitive mechanisms underlying autism spectrum disorder (ASD) remain unclear. Progress has been largely hampered by small sample sizes, variable age ranges and resulting inconsistent findings. There is a pressing need for large definitive studies to delineate the nature and extent of key case/control differences to direct research towards fruitful areas for future investigation. Here we focus on perception of biological motion, a promising index of social brain function which may be altered in ASD. In a large sample ranging from childhood to adulthood, we assess whether biological motion preference differs in ASD compared to neurotypical participants (NT), how differences are modulated by age and sex and whether they are associated with dimensional variation in concurrent or later symptomatology.

METHODS

Eye-tracking data were collected from 486 6-to-30-year-old autistic (N = 282) and non-autistic control (N = 204) participants whilst they viewed 28 trials pairing biological (BM) and control (non-biological, CTRL) motion. Preference for the biological motion stimulus was calculated as (1) proportion looking time difference (BM-CTRL) and (2) peak look duration difference (BM-CTRL).

RESULTS

The ASD group showed a present but weaker preference for biological motion than the NT group. The nature of the control stimulus modulated preference for biological motion in both groups. Biological motion preference did not vary with age, gender, or concurrent or prospective social communicative skill within the ASD group, although a lack of clear preference for either stimulus was associated with higher social-communicative symptoms at baseline.

LIMITATIONS

The paired visual preference we used may underestimate preference for a stimulus in younger and lower IQ individuals. Our ASD group had a lower average IQ by approximately seven points. 18% of our sample was not analysed for various technical and behavioural reasons.

CONCLUSIONS

Biological motion preference elicits small-to-medium-sized case-control effects, but individual differences do not strongly relate to core social autism associated symptomatology. We interpret this as an autistic difference (as opposed to a deficit) likely manifest in social brain regions. The extent to which this is an innate difference present from birth and central to the autistic phenotype, or the consequence of a life lived with ASD, is unclear.

Neuroimaging brain growth charts: A road to mental health

Mental disorders are common health concerns and contribute to a heavy global burden on our modern society. It is challenging to identify and treat them timely. Neuroimaging evidence suggests the incidence of various psychiatric and behavioral disorders is closely related to the atypical development of brain structure and function. The identification and understanding of atypical brain development provide chances for clinicians to detect mental disorders earlier, perhaps even prior to onset, and treat them more precisely. An invaluable and necessary method in identifying and monitoring atypical brain development are growth charts of typically developing individuals in the population. The brain growth charts can offer a series of standard references on typical neurodevelopment, representing an important resource for the scientific and medical communities. In the present paper, we review the relationship between mental disorders and atypical brain development from a perspective of normative brain development by surveying the recent progress in the development of brain growth charts, including four aspects on growth chart utility: 1) cohorts, 2) measures, 3) mechanisms, and 4) clinical translations. In doing so, we seek to clarify the challenges and opportunities in charting brain growth, and to promote the application of brain growth charts in clinical practice.

The Diagnosis of Autism: From Kanner to DSM-III to DSM-5 and Beyond

In this paper we review the impact of DSM-III and its successors on the field of autism-both in terms of clinical work and research. We summarize the events leading up to the inclusion of autism as a "new" official diagnostic category in DSM-III, the subsequent revisions of the DSM, and the impact of the official recognition of autism on research. We discuss the uses of categorical vs. dimensional approaches and the continuing tensions around broad vs. narrow views of autism. We also note some areas of current controversy and directions for the future.