Publications by authors named "Eva Loth"

75 Publications

Social attention in anorexia nervosa and autism spectrum disorder: Role of social motivation.

Autism 2021 Nov 30:13623613211060593. Epub 2021 Nov 30.

King's College London, UK.

Lay Abstract: Research suggests a relationship between autism and anorexia nervosa. For example, rigid and inflexible behaviour, a preference for routine and social difficulties are seen in both conditions. In this study, we examined whether people with anorexia and people with autism show similarities in social attention (where they look while engaging in social interactions or watching a scene with people interacting). This could help us understand why people with anorexia and autism experience difficulties in social situations. Participants with either anorexia or autism, as well as participants with no mental health problems watched a video of a social scene while we recorded which parts of the scene they looked at with an eye-tracker. Participants also completed questionnaires to assess characteristics of autism. We found that autistic participants looked at faces less than typically developing participants. However, participants with anorexia did not show a similar reduction in attention to faces, contrary to our predictions. Autistic features were not related to attention in either group. The results suggest that autistic people may miss important social cues (like facial expressions), potentially contributing to social difficulties. However, this mechanism does not appear explain social difficulties in people with anorexia.
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http://dx.doi.org/10.1177/13623613211060593DOI Listing
November 2021

The meaning of significant mean group differences for biomarker discovery.

PLoS Comput Biol 2021 Nov 18;17(11):e1009477. Epub 2021 Nov 18.

Mila-Quebec Artificial Intelligence Institute, Montreal, Canada.

Over the past decade, biomarker discovery has become a key goal in psychiatry to aid in the more reliable diagnosis and prognosis of heterogeneous psychiatric conditions and the development of tailored therapies. Nevertheless, the prevailing statistical approach is still the mean group comparison between "cases" and "controls," which tends to ignore within-group variability. In this educational article, we used empirical data simulations to investigate how effect size, sample size, and the shape of distributions impact the interpretation of mean group differences for biomarker discovery. We then applied these statistical criteria to evaluate biomarker discovery in one area of psychiatric research-autism research. Across the most influential areas of autism research, effect size estimates ranged from small (d = 0.21, anatomical structure) to medium (d = 0.36 electrophysiology, d = 0.5, eye-tracking) to large (d = 1.1 theory of mind). We show that in normal distributions, this translates to approximately 45% to 63% of cases performing within 1 standard deviation (SD) of the typical range, i.e., they do not have a deficit/atypicality in a statistical sense. For a measure to have diagnostic utility as defined by 80% sensitivity and 80% specificity, Cohen's d of 1.66 is required, with still 40% of cases falling within 1 SD. However, in both normal and nonnormal distributions, 1 (skewness) or 2 (platykurtic, bimodal) biologically plausible subgroups may exist despite small or even nonsignificant mean group differences. This conclusion drastically contrasts the way mean group differences are frequently reported. Over 95% of studies omitted the "on average" when summarising their findings in their abstracts ("autistic people have deficits in X"), which can be misleading as it implies that the group-level difference applies to all individuals in that group. We outline practical approaches and steps for researchers to explore mean group comparisons for the discovery of stratification biomarkers.
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http://dx.doi.org/10.1371/journal.pcbi.1009477DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8601419PMC
November 2021

A Phase II Randomized, Double-Blind, Placebo-Controlled Study of the Efficacy, Safety, and Tolerability of Arbaclofen Administered for the Treatment of Social Function in Children and Adolescents With Autism Spectrum Disorders: Study Protocol for AIMS-2-TRIALS-CT1.

Front Psychiatry 2021 24;12:701729. Epub 2021 Aug 24.

Institute of Psychiatry and Mental Health, Hospital General Universitario Gregorio Marañón, Madrid, Spain.

Autism Spectrum Disorder (ASD or autism) is characterized by difficulties in social communication and interaction, which negatively impact on individuals and their families' quality of life. Currently no pharmacological interventions have been shown to be effective for improving social communication in autism. Previous trials have indicated the potential of arbaclofen for improving social function among autistic children and adolescents with fluent speech. The AIMS2TRIALS-Clinical Trial 1 (AIMS-CT1) will examine whether arbaclofen is superior to placebo in improving social function and other secondary outcomes over 16 weeks, along with safety and tolerability profiles. AIMS-CT1 is an international, multi-site, double-blind, parallel group Phase II randomized clinical trial. It will include 130 males and females aged 5:0-17:11 years, with a diagnosis of ASD and fluent speech. Eligible participants will be randomized on a ratio of 1:1 for a 16-week treatment period. Medication will be titrated over 5 weeks. The primary outcome is the effect on social function from weeks 0 to 16 measured on the Socialization domain of the Vineland Adaptive Behavior Scales, 3rd edition. Secondary outcome measures include the CGI-S (Clinical Global Impression-Severity), CGI-I (Clinical Global Impression-Improvement), other areas of adaptive function, social communication and other autism symptoms, co-occurring behavior problems and health-related quality of life. Genetic and electrophysiological markers will be examined as potential stratifiers for treatment response. Exploratory novel digital technologies will also be used to measure change, examining simultaneously the validity of digital biomarkers in natural environments. The safety and tolerability of the drug will also be examined. Our protocol is very closely aligned with a parallel Canadian trial of 90 participants (ARBA Study, US NCT number: NCT03887676) to allow for secondary combined analyses. Outcomes will be compared using both an Intent-to-reat and Per Protocol approach. The outcomes of this trial, combined with the parallel Canadian trial, will contribute to the evidence base for medications used to help social difficulties among young autistic individuals; demonstrate the capabilities of the AIMS-2-TRIALS network of academic centers to deliver clinical trials; and support future drug development. EudraCT number: 2018-000942-21 and ClinicalTrials.gov registry number: NCT03682978. Currently under protocol v.7.2, dated 20.11.2020.
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http://dx.doi.org/10.3389/fpsyt.2021.701729DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8421761PMC
August 2021

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

Am J Psychiatry 2021 Sep 10:appiajp202120050630. Epub 2021 Sep 10.

Department of Child and Adolescent Psychiatry, University Hospital, Goethe University, Frankfurt am Main, Germany (Ecker, Bletsch, Mann, Schaefer, Yousaf, Chiocchetti, Bast, Freitag).

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.
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http://dx.doi.org/10.1176/appi.ajp.2021.20050630DOI Listing
September 2021

The Monash Autism-ADHD genetics and neurodevelopment (MAGNET) project design and methodologies: a dimensional approach to understanding neurobiological and genetic aetiology.

Mol Autism 2021 08 5;12(1):55. Epub 2021 Aug 5.

Turner Institute for Brain and Mental Health, School of Psychological Sciences, Monash University, 18 Innovation Walk, Melbourne, VIC, 3800, Australia.

Background: ASD and ADHD are prevalent neurodevelopmental disorders that frequently co-occur and have strong evidence for a degree of shared genetic aetiology. Behavioural and neurocognitive heterogeneity in ASD and ADHD has hampered attempts to map the underlying genetics and neurobiology, predict intervention response, and improve diagnostic accuracy. Moving away from categorical conceptualisations of psychopathology to a dimensional approach is anticipated to facilitate discovery of data-driven clusters and enhance our understanding of the neurobiological and genetic aetiology of these conditions. The Monash Autism-ADHD genetics and neurodevelopment (MAGNET) project is one of the first large-scale, family-based studies to take a truly transdiagnostic approach to ASD and ADHD. Using a comprehensive phenotyping protocol capturing dimensional traits central to ASD and ADHD, the MAGNET project aims to identify data-driven clusters across ADHD-ASD spectra using deep phenotyping of symptoms and behaviours; investigate the degree of familiality for different dimensional ASD-ADHD phenotypes and clusters; and map the neurocognitive, brain imaging, and genetic correlates of these data-driven symptom-based clusters.

Methods: The MAGNET project will recruit 1,200 families with children who are either typically developing, or who display elevated ASD, ADHD, or ASD-ADHD traits, in addition to affected and unaffected biological siblings of probands, and parents. All children will be comprehensively phenotyped for behavioural symptoms, comorbidities, neurocognitive and neuroimaging traits and genetics.

Conclusion: The MAGNET project will be the first large-scale family study to take a transdiagnostic approach to ASD-ADHD, utilising deep phenotyping across behavioural, neurocognitive, brain imaging and genetic measures.
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http://dx.doi.org/10.1186/s13229-021-00457-3DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8340366PMC
August 2021

Neural Biomarkers Distinguish Severe From Mild Autism Spectrum Disorder Among High-Functioning Individuals.

Front Hum Neurosci 2021 6;15:657857. Epub 2021 May 6.

Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China.

Several previous studies have reported atypicality in resting-state functional connectivity (FC) in autism spectrum disorder (ASD), yet the relatively small effect sizes prevent us from using these characteristics for diagnostic purposes. Here, canonical correlation analysis (CCA) and hierarchical clustering were used to partition the high-functioning ASD group (i.e., the ASD discovery group) into subgroups. A support vector machine (SVM) model was trained through the 10-fold strategy to predict Autism Diagnostic Observation Schedule (ADOS) scores within the ASD discovery group ( = 0.30, < 0.001, = 260), which was further validated in an independent sample (i.e., the ASD validation group) ( = 0.35, = 0.031, = 29). The neuroimage-based partition derived two subgroups representing severe versus mild autistic patients. We identified FCs that show graded changes in strength from ASD-severe, through ASD-mild, to controls, while the same pattern cannot be observed in partitions based on ADOS score. We also identified FCs that are specific for ASD-mild, similar to a partition based on ADOS score. The current study provided multiple pieces of evidence with replication to show that resting-state functional magnetic resonance imaging (rsfMRI) FCs could serve as neural biomarkers in partitioning high-functioning autistic individuals based on their symptom severity and showing advantages over traditional partition based on ADOS score. Our results also indicate a compensatory role for a frontocortical network in patients with mild ASD, indicating potential targets for future clinical treatments.
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http://dx.doi.org/10.3389/fnhum.2021.657857DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8134539PMC
May 2021

Imbalanced social-communicative and restricted repetitive behavior subtypes of autism spectrum disorder exhibit different neural circuitry.

Commun Biol 2021 05 14;4(1):574. Epub 2021 May 14.

Roche Pharma Research and Early Development, Neuroscience, Ophthalmology and Rare Diseases, Roche Innovation Center Basel, Basel, Switzerland.

Social-communication (SC) and restricted repetitive behaviors (RRB) are autism diagnostic symptom domains. SC and RRB severity can markedly differ within and between individuals and may be underpinned by different neural circuitry and genetic mechanisms. Modeling SC-RRB balance could help identify how neural circuitry and genetic mechanisms map onto such phenotypic heterogeneity. Here, we developed a phenotypic stratification model that makes highly accurate (97-99%) out-of-sample SC = RRB, SC > RRB, and RRB > SC subtype predictions. Applying this model to resting state fMRI data from the EU-AIMS LEAP dataset (n = 509), we find that while the phenotypic subtypes share many commonalities in terms of intrinsic functional connectivity, they also show replicable differences within some networks compared to a typically-developing group (TD). Specifically, the somatomotor network is hypoconnected with perisylvian circuitry in SC > RRB and visual association circuitry in SC = RRB. The SC = RRB subtype show hyperconnectivity between medial motor and anterior salience circuitry. Genes that are highly expressed within these networks show a differential enrichment pattern with known autism-associated genes, indicating that such circuits are affected by differing autism-associated genomic mechanisms. These results suggest that SC-RRB imbalance subtypes share many commonalities, but also express subtle differences in functional neural circuitry and the genomic underpinnings behind such circuitry.
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http://dx.doi.org/10.1038/s42003-021-02015-2DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8121854PMC
May 2021

Are we ready for precision medicine for Autism? And who wants it?

Authors:
Eva Loth

Eur Neuropsychopharmacol 2021 Jul 11;48:32-33. Epub 2021 Apr 11.

Institute of Psychiatry, Psychology and Neuroscience, King's College London, London SE5 8AF, United Kingdom. Electronic address:

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http://dx.doi.org/10.1016/j.euroneuro.2021.03.009DOI Listing
July 2021

Towards robust and replicable sex differences in the intrinsic brain function of autism.

Mol Autism 2021 03 1;12(1):19. Epub 2021 Mar 1.

Autism Center, The Child Mind Institute, 101 E 56 Street, New York City, New York, 10026, USA.

Background: Marked sex differences in autism prevalence accentuate the need to understand the role of biological sex-related factors in autism. Efforts to unravel sex differences in the brain organization of autism have, however, been challenged by the limited availability of female data.

Methods: We addressed this gap by using a large sample of males and females with autism and neurotypical (NT) control individuals (ABIDE; Autism: 362 males, 82 females; NT: 409 males, 166 females; 7-18 years). Discovery analyses examined main effects of diagnosis, sex and their interaction across five resting-state fMRI (R-fMRI) metrics (voxel-level Z > 3.1, cluster-level P < 0.01, gaussian random field corrected). Secondary analyses assessed the robustness of the results to different pre-processing approaches and their replicability in two independent samples: the EU-AIMS Longitudinal European Autism Project (LEAP) and the Gender Explorations of Neurogenetics and Development to Advance Autism Research.

Results: Discovery analyses in ABIDE revealed significant main effects of diagnosis and sex across the intrinsic functional connectivity of the posterior cingulate cortex, regional homogeneity and voxel-mirrored homotopic connectivity (VMHC) in several cortical regions, largely converging in the default network midline. Sex-by-diagnosis interactions were confined to the dorsolateral occipital cortex, with reduced VMHC in females with autism. All findings were robust to different pre-processing steps. Replicability in independent samples varied by R-fMRI measures and effects with the targeted sex-by-diagnosis interaction being replicated in the larger of the two replication samples-EU-AIMS LEAP.

Limitations: Given the lack of a priori harmonization among the discovery and replication datasets available to date, sample-related variation remained and may have affected replicability.

Conclusions: Atypical cross-hemispheric interactions are neurobiologically relevant to autism. They likely result from the combination of sex-dependent and sex-independent factors with a differential effect across functional cortical networks. Systematic assessments of the factors contributing to replicability are needed and necessitate coordinated large-scale data collection across studies.
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http://dx.doi.org/10.1186/s13229-021-00415-zDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7923310PMC
March 2021

Towards robust and replicable sex differences in the intrinsic brain function of autism.

Mol Autism 2021 03 1;12(1):19. Epub 2021 Mar 1.

Autism Center, The Child Mind Institute, 101 E 56 Street, New York City, New York, 10026, USA.

Background: Marked sex differences in autism prevalence accentuate the need to understand the role of biological sex-related factors in autism. Efforts to unravel sex differences in the brain organization of autism have, however, been challenged by the limited availability of female data.

Methods: We addressed this gap by using a large sample of males and females with autism and neurotypical (NT) control individuals (ABIDE; Autism: 362 males, 82 females; NT: 409 males, 166 females; 7-18 years). Discovery analyses examined main effects of diagnosis, sex and their interaction across five resting-state fMRI (R-fMRI) metrics (voxel-level Z > 3.1, cluster-level P < 0.01, gaussian random field corrected). Secondary analyses assessed the robustness of the results to different pre-processing approaches and their replicability in two independent samples: the EU-AIMS Longitudinal European Autism Project (LEAP) and the Gender Explorations of Neurogenetics and Development to Advance Autism Research.

Results: Discovery analyses in ABIDE revealed significant main effects of diagnosis and sex across the intrinsic functional connectivity of the posterior cingulate cortex, regional homogeneity and voxel-mirrored homotopic connectivity (VMHC) in several cortical regions, largely converging in the default network midline. Sex-by-diagnosis interactions were confined to the dorsolateral occipital cortex, with reduced VMHC in females with autism. All findings were robust to different pre-processing steps. Replicability in independent samples varied by R-fMRI measures and effects with the targeted sex-by-diagnosis interaction being replicated in the larger of the two replication samples-EU-AIMS LEAP.

Limitations: Given the lack of a priori harmonization among the discovery and replication datasets available to date, sample-related variation remained and may have affected replicability.

Conclusions: Atypical cross-hemispheric interactions are neurobiologically relevant to autism. They likely result from the combination of sex-dependent and sex-independent factors with a differential effect across functional cortical networks. Systematic assessments of the factors contributing to replicability are needed and necessitate coordinated large-scale data collection across studies.
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http://dx.doi.org/10.1186/s13229-021-00415-zDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7923310PMC
March 2021

Temporal Profiles of Social Attention Are Different Across Development in Autistic and Neurotypical People.

Biol Psychiatry Cogn Neurosci Neuroimaging 2021 08 12;6(8):813-824. Epub 2020 Sep 12.

Centre of Brain and Cognitive Development, Birkbeck College, University of London, London, United Kingdom.

Background: Sociocommunicative difficulties, including abnormalities in eye contact, are core diagnostic features of autism spectrum disorder (ASD). Many studies have used eye tracking to measure reduced attention to faces in autistic people; however, most of this work has not taken advantage of eye-tracking temporal resolution to examine temporal profiles of attention.

Methods: We used growth curve analysis to model attention to static social scenes as a function of time in a large (N = 650) sample of autistic participants and neurotypical participants across a wide age range (6-30 years).

Results: The model yielded distinct temporal profiles of attention to faces in the groups. Initially, both groups showed a relatively high probability of attending to faces, followed by decline after several seconds. The neurotypical participants, however, were significantly more likely to return their attention to faces in the latter part of each 20-second trial, with increasing probability with age. In contrast, the probability of returning to the face in the autistic participants remained low across development. In participants with ASD, more atypical profiles of attention were associated with lower Vineland Adaptive Behavior Scales communication scores and a higher curvature in one data-driven cluster correlated with symptom severity.

Conclusions: These findings show that social attention not only is reduced in ASD, but also differs in its temporal dynamics. The neurotypical participants became more sophisticated in how they deployed their social attention across age, a pattern that was significantly reduced in the participants with ASD, possibly reflecting delayed acquisition of social expertise.
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http://dx.doi.org/10.1016/j.bpsc.2020.09.004DOI Listing
August 2021

Fractionating autism based on neuroanatomical normative modeling.

Transl Psychiatry 2020 11 6;10(1):384. Epub 2020 Nov 6.

Donders Institute for Brain, Cognition and Behavior, Radboud University Nijmegen, Nijmegen, The Netherlands.

Autism is a complex neurodevelopmental condition with substantial phenotypic, biological, and etiologic heterogeneity. It remains a challenge to identify biomarkers to stratify autism into replicable cognitive or biological subtypes. Here, we aim to introduce a novel methodological framework for parsing neuroanatomical subtypes within a large cohort of individuals with autism. We used cortical thickness (CT) in a large and well-characterized sample of 316 participants with autism (88 female, age mean: 17.2 ± 5.7) and 206 with neurotypical development (79 female, age mean: 17.5 ± 6.1) aged 6-31 years across six sites from the EU-AIMS multi-center Longitudinal European Autism Project. Five biologically based putative subtypes were derived using normative modeling of CT and spectral clustering. Three of these clusters showed relatively widespread decreased CT and two showed relatively increased CT. These subtypes showed morphometric differences from one another, providing a potential explanation for inconsistent case-control findings in autism, and loaded differentially and more strongly onto symptoms and polygenic risk, indicating a dilution of clinical effects across heterogeneous cohorts. Our results provide an important step towards parsing the heterogeneous neurobiology of autism.
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http://dx.doi.org/10.1038/s41398-020-01057-0DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7648836PMC
November 2020

Gray matter covariations and core symptoms of autism: the EU-AIMS Longitudinal European Autism Project.

Mol Autism 2020 10 30;11(1):86. Epub 2020 Oct 30.

Department of Cognitive Neuroscience, Donders Institute for Brain, Cognition and Behaviour, Radboud University Nijmegen Medical Centre, Nijmegen, The Netherlands.

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.
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http://dx.doi.org/10.1186/s13229-020-00389-4DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7596954PMC
October 2020

Modeling flexible behavior in childhood to adulthood shows age-dependent learning mechanisms and less optimal learning in autism in each age group.

PLoS Biol 2020 10 27;18(10):e3000908. Epub 2020 Oct 27.

Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, United Kingdom.

Flexible behavior is critical for everyday decision-making and has been implicated in restricted, repetitive behaviors (RRB) in autism spectrum disorder (ASD). However, how flexible behavior changes developmentally in ASD remains largely unknown. Here, we used a developmental approach and examined flexible behavior on a probabilistic reversal learning task in 572 children, adolescents, and adults (ASD N = 321; typical development [TD] N = 251). Using computational modeling, we quantified latent variables that index mechanisms underlying perseveration and feedback sensitivity. We then assessed these variables in relation to diagnosis, developmental stage, core autism symptomatology, and associated psychiatric symptoms. Autistic individuals showed on average more perseveration and less feedback sensitivity than TD individuals, and, across cases and controls, older age groups showed more feedback sensitivity than younger age groups. Computational modeling revealed that dominant learning mechanisms underpinning flexible behavior differed across developmental stages and reduced flexible behavior in ASD was driven by less optimal learning on average within each age group. In autistic children, perseverative errors were positively related to anxiety symptoms, and in autistic adults, perseveration (indexed by both task errors and model parameter estimates) was positively related to RRB. These findings provide novel insights into reduced flexible behavior in relation to clinical symptoms in ASD.
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http://dx.doi.org/10.1371/journal.pbio.3000908DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7591042PMC
October 2020

Atypical Brain Asymmetry in Autism-A Candidate for Clinically Meaningful Stratification.

Biol Psychiatry Cogn Neurosci Neuroimaging 2021 08 25;6(8):802-812. Epub 2020 Aug 25.

Donders Institute for Brain, Cognition, and Behavior, Radboud University Nijmegen, Nijmegen, The Netherlands; Department for Cognitive Neuroscience, Radboud University Medical Center Nijmegen, Nijmegen, The Netherlands; Centre for Functional MRI of the Brain, University of Oxford, Oxford, United Kingdom.

Background: Autism spectrum disorder ("autism") is a highly heterogeneous neurodevelopmental condition with few effective treatments for core and associated features. To make progress we need to both identify and validate neural markers that help to parse heterogeneity to tailor therapies to specific neurobiological profiles. Atypical hemispheric lateralization is a stable feature across studies in autism, but its potential as a neural stratification marker has not been widely examined.

Methods: In order to dissect heterogeneity in lateralization in autism, we used the large EU-AIMS (European Autism Interventions-A Multicentre Study for Developing New Medications) Longitudinal European Autism Project dataset comprising 352 individuals with autism and 233 neurotypical control subjects as well as a replication dataset from ABIDE (Autism Brain Imaging Data Exchange) (513 individuals with autism, 691 neurotypical subjects) using a promising approach that moves beyond mean group comparisons. We derived gray matter voxelwise laterality values for each subject and modeled individual deviations from the normative pattern of brain laterality across age using normative modeling.

Results: Individuals with autism had highly individualized patterns of both extreme right- and leftward deviations, particularly in language, motor, and visuospatial regions, associated with symptom severity. Language delay explained most variance in extreme rightward patterns, whereas core autism symptom severity explained most variance in extreme leftward patterns. Follow-up analyses showed that a stepwise pattern emerged, with individuals with autism with language delay showing more pronounced rightward deviations than individuals with autism without language delay.

Conclusions: Our analyses corroborate the need for novel (dimensional) approaches to delineate the heterogeneous neuroanatomy in autism and indicate that atypical lateralization may constitute a neurophenotype for clinically meaningful stratification in autism.
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http://dx.doi.org/10.1016/j.bpsc.2020.08.008DOI Listing
August 2021

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

Psychol Med 2020 Oct 8:1-13. Epub 2020 Oct 8.

Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology & Neuroscience, King's College London, De Crespigny Park, LondonSE5 8AF, UK.

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.
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http://dx.doi.org/10.1017/S0033291720003244DOI Listing
October 2020

How do core autism traits and associated symptoms relate to quality of life? Findings from the Longitudinal European Autism Project.

Autism 2021 02 7;25(2):389-404. Epub 2020 Oct 7.

King's College London, UK.

Lay Abstract: Previous studies suggest that some autistic individuals report lower satisfaction, or well-being, with different aspects of everyday life than those without autism. It is unclear whether this might be partly explained by symptoms of anxiety and/or depression, which affect at least 20%-50% of autistic people. In this study, we measured individual differences in well-being in 573 six to thirty-year-olds with and without a diagnosis of autism. We investigated whether individual differences in well-being were explained by autism traits (e.g. social-communication difficulties) and/or anxiety and depression symptoms. We showed that, though well-being was lower for some autistic individuals, compared to those without autism, many autistic individuals reported good well-being. Where well-being was reduced, this was particularly explained by depression symptoms, across all ages. For children/adolescents, anxiety and social-communication difficulties were also related to some aspects of well-being. Our study suggests that support and services for improving mental health, especially depression symptoms, may also improve broader outcomes for autistic people.
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http://dx.doi.org/10.1177/1362361320959959DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7874383PMC
February 2021

Effect Sizes of Deletions and Duplications on Autism Risk Across the Genome.

Am J Psychiatry 2021 01 11;178(1):87-98. Epub 2020 Sep 11.

Université de Montréal, Montreal (Douard, Zeribi, Schramm, Tamer, Loum, Nowak, Lord, Moreau, Huguet, Jacquemont); UHC Sainte-Justine Research Center, Montreal (Douard, Zeribi, Schramm, Tamer, Loum, Nowak, Saci, Lord, Rodríguez-Herreros, Jean-Louis, Moreau, Huguet, Jacquemont); Lady Davis Institute for Medical Research, Jewish General Hospital, Montreal (Schramm, Greenwood); Sensory-Motor Laboratory, Jules-Gonin Eye Hospital, University of Lausanne, Lausanne, Switzerland (Rodríguez-Herreros); Department of Forensic and Neurodevelopmental Sciences (Loth) and Center for Population Neuroscience and Stratified Medicine (Schumann), Institute of Psychiatry, Psychology, and Neuroscience, King's College London; Hospital for Sick Children and Departments of Physiology and Nutritional Sciences, University of Toronto, Toronto (Pausova); Departments of Neurology and Neurosurgery, Montreal Neurological Institute and Hospital, McGill University, Montreal (Elsabbagh); Department of Biomedical and Health Informatics, Children's Hospital of Philadelphia, Philadelphia, and Department of Genetics, University of Pennsylvania Perelman School of Medicine, Philadelphia (Almasy); Department of Psychiatry, Boston Children's Hospital and Harvard Medical School, Boston (Glahn); Human Genetics and Cognitive Functions, Institut Pasteur, Université de Paris, Paris (Bourgeron); Département de Sciences de la Décision, HEC Montreal, Montreal (Labbe); Bloorview Research Institute, Holland Bloorview Kids Rehabilitation Hospital, Toronto (Paus); Departments of Psychology and Psychiatry, University of Toronto, Toronto (Paus); Centre de Recherche de CIUSSS-NIM, Montreal (Mottron); Département de Psychiatrie, Université de Montréal, Montreal (Mottron); Department of Epidemiology, Biostatistics, and Occupational Health, Gerald Bronfman Department of Oncology, and Department of Human Genetics, McGill University, Montreal (Greenwood).

Objective: Deleterious copy number variants (CNVs) are identified in up to 20% of individuals with autism. However, levels of autism risk conferred by most rare CNVs remain unknown. The authors recently developed statistical models to estimate the effect size on IQ of all CNVs, including undocumented ones. In this study, the authors extended this model to autism susceptibility.

Methods: The authors identified CNVs in two autism populations (Simons Simplex Collection and MSSNG) and two unselected populations (IMAGEN and Saguenay Youth Study). Statistical models were used to test nine quantitative variables associated with genes encompassed in CNVs to explain their effects on IQ, autism susceptibility, and behavioral domains.

Results: The "probability of being loss-of-function intolerant" (pLI) best explains the effect of CNVs on IQ and autism risk. Deleting 1 point of pLI decreases IQ by 2.6 points in autism and unselected populations. The effect of duplications on IQ is threefold smaller. Autism susceptibility increases when deleting or duplicating any point of pLI. This is true for individuals with high or low IQ and after removing de novo and known recurrent neuropsychiatric CNVs. When CNV effects on IQ are accounted for, autism susceptibility remains mostly unchanged for duplications but decreases for deletions. Model estimates for autism risk overlap with previously published observations. Deletions and duplications differentially affect social communication, behavior, and phonological memory, whereas both equally affect motor skills.

Conclusions: Autism risk conferred by duplications is less influenced by IQ compared with deletions. The model applied in this study, trained on CNVs encompassing >4,500 genes, suggests highly polygenic properties of gene dosage with respect to autism risk and IQ loss. These models will help to interpret CNVs identified in the clinic.
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http://dx.doi.org/10.1176/appi.ajp.2020.19080834DOI Listing
January 2021

Interferon-γ signaling in human iPSC-derived neurons recapitulates neurodevelopmental disorder phenotypes.

Sci Adv 2020 Aug 19;6(34):eaay9506. Epub 2020 Aug 19.

Department of Basic and Clinical Neuroscience, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK.

Maternal immune activation increases the risk of neurodevelopmental disorders. Elevated cytokines, such as interferon-γ (IFN-γ), in offspring's brains play a central role. IFN-γ activates an antiviral cellular state, limiting viral entry and replication. Moreover, IFN-γ is implicated in brain development. We tested the hypothesis that IFN-γ signaling contributes to molecular and cellular phenotypes associated with neurodevelopmental disorders. Transient IFN-γ treatment of neural progenitors derived from human induced pluripotent stem cells increased neurite outgrowth. RNA sequencing analysis revealed that major histocompatibility complex class I (MHCI) genes were persistently up-regulated through neuronal differentiation-an effect that was mediated by IFN-γ-induced promyelocytic leukemia protein (PML) nuclear bodies. Critically, IFN-γ-induced neurite outgrowth required both PML and MHCI. We also found evidence that IFN-γ disproportionately altered the expression of genes associated with schizophrenia and autism, suggesting convergence between genetic and environmental risk factors. Together, these data implicate IFN-γ signaling in neurodevelopmental disorder etiology.
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http://dx.doi.org/10.1126/sciadv.aay9506DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7438100PMC
August 2020

Atypical Neurogenesis in Induced Pluripotent Stem Cells From Autistic Individuals.

Biol Psychiatry 2021 03 23;89(5):486-496. Epub 2020 Jun 23.

Autism Research Centre, Department of Psychiatry, University of Cambridge, Cambridge, United Kingdom.

Background: Autism is a heterogeneous collection of disorders with a complex molecular underpinning. Evidence from postmortem brain studies have indicated that early prenatal development may be altered in autism. Induced pluripotent stem cells (iPSCs) generated from individuals with autism with macrocephaly also indicate prenatal development as a critical period for this condition. But little is known about early altered cellular events during prenatal stages in autism.

Methods: iPSCs were generated from 9 unrelated individuals with autism without macrocephaly and with heterogeneous genetic backgrounds, and 6 typically developing control individuals. iPSCs were differentiated toward either cortical or midbrain fates. Gene expression and high throughput cellular phenotyping was used to characterize iPSCs at different stages of differentiation.

Results: A subset of autism-iPSC cortical neurons were RNA-sequenced to reveal autism-specific signatures similar to postmortem brain studies, indicating a potential common biological mechanism. Autism-iPSCs differentiated toward a cortical fate displayed impairments in the ability to self-form into neural rosettes. In addition, autism-iPSCs demonstrated significant differences in rate of cell type assignment of cortical precursors and dorsal and ventral forebrain precursors. These cellular phenotypes occurred in the absence of alterations in cell proliferation during cortical differentiation, differing from previous studies. Acquisition of cell fate during midbrain differentiation was not different between control- and autism-iPSCs.

Conclusions: Taken together, our data indicate that autism-iPSCs diverge from control-iPSCs at a cellular level during early stage of neurodevelopment. This suggests that unique developmental differences associated with autism may be established at early prenatal stages.
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http://dx.doi.org/10.1016/j.biopsych.2020.06.014DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7843956PMC
March 2021

Emotion Recognition Abilities in Adults with Anorexia Nervosa are Associated with Autistic Traits.

J Clin Med 2020 Apr 8;9(4). Epub 2020 Apr 8.

Department of Psychological Medicine, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London SE5 8AB, UK.

Difficulties in socio-emotional functioning are proposed to contribute to the development and maintenance of anorexia nervosa (AN). This study aimed to examine emotion recognition abilities in individuals in the acute and recovered stages of AN compared to healthy controls (HCs). A second aim was to examine whether attention to faces and comorbid psychopathology predicted emotion recognition abilities. The films expressions task was administered to 148 participants (46 AN, 51 recovered AN, 51 HC) to assess emotion recognition, during which attention to faces was recorded using eye-tracking. Comorbid psychopathology was assessed using self-report questionnaires and the Autism Diagnostic Observation Schedule-2nd edition (ADOS-2). No significant differences in emotion recognition abilities or attention to faces were found between groups. However, individuals with a lifetime history of AN who scored above the clinical cut-off on the ADOS-2 displayed poorer emotion recognition performance than those scoring below cut-off and HCs. ADOS-2 scores significantly predicted emotion recognition abilities while controlling for group membership and intelligence. Difficulties in emotion recognition appear to be associated with high autism spectrum disorder (ASD) traits, rather than a feature of AN. Whether individuals with AN and high ASD traits may require different treatment strategies or adaptations is a question for future research.
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http://dx.doi.org/10.3390/jcm9041057DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7230901PMC
April 2020

Social brain activation during mentalizing in a large autism cohort: the Longitudinal European Autism Project.

Mol Autism 2020 02 22;11(1):17. Epub 2020 Feb 22.

Department of Child and Adolescent Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim / University of Heidelberg, Mannheim, Germany.

Background: Autism spectrum disorder (ASD) is a neurodevelopmental condition with key deficits in social functioning. It is widely assumed that the biological underpinnings of social impairment are neurofunctional alterations in the "social brain," a neural circuitry involved in inferring the mental state of a social partner. However, previous evidence comes from small-scale studies and findings have been mixed. We therefore carried out the to-date largest study on neural correlates of mentalizing in ASD.

Methods: As part of the Longitudinal European Autism Project, we performed functional magnetic resonance imaging at six European sites in a large, well-powered, and deeply phenotyped sample of individuals with ASD (N = 205) and typically developing (TD) individuals (N = 189) aged 6 to 30 years. We presented an animated shapes task to assess and comprehensively characterize social brain activation during mentalizing. We tested for effects of age, diagnosis, and their association with symptom measures, including a continuous measure of autistic traits.

Results: We observed robust effects of task. Within the ASD sample, autistic traits were moderately associated with functional activation in one of the key regions of the social brain, the dorsomedial prefrontal cortex. However, there were no significant effects of diagnosis on task performance and no effects of age and diagnosis on social brain responses. Besides a lack of mean group differences, our data provide no evidence for meaningful differences in the distribution of brain response measures. Extensive control analyses suggest that the lack of case-control differences was not due to a variety of potential confounders.

Conclusions: Contrary to prior reports, this large-scale study does not support the assumption that altered social brain activation during mentalizing forms a common neural marker of ASD, at least with the paradigm we employed. Yet, autistic individuals show socio-behavioral deficits. Our work therefore highlights the need to interrogate social brain function with other brain measures, such as connectivity and network-based approaches, using other paradigms, or applying complementary analysis approaches to assess individual differences in this heterogeneous condition.
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http://dx.doi.org/10.1186/s13229-020-0317-xDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7036196PMC
February 2020

From pattern classification to stratification: towards conceptualizing the heterogeneity of Autism Spectrum Disorder.

Neurosci Biobehav Rev 2019 09 19;104:240-254. Epub 2019 Jul 19.

Donders Center for Brain, Cognition and Behavior, Radboud University Nijmegen, Nijmegen, the Netherlands; Department for Cognitive Neuroscience, Radboud University Medical Center Nijmegen, Nijmegen, the Netherlands; Centre for Functional MRI of the Brain (FMRIB), University of Oxford, Oxford, United Kingdom.

Pattern classification and stratification approaches have increasingly been used in research on Autism Spectrum Disorder (ASD) over the last ten years with the goal of translation towards clinical applicability. Here, we present an extensive scoping literature review on those two approaches. We screened a total of 635 studies, of which 57 pattern classification and 19 stratification studies were included. We observed large variance across pattern classification studies in terms of predictive performance from about 60% to 98% accuracy, which is among other factors likely linked to sampling bias, different validation procedures across studies, the heterogeneity of ASD and differences in data quality. Stratification studies were less prevalent with only two studies reporting replications and just a few showing external validation. While some identified strata based on cognition and intelligence reappear across studies, biology as a stratification marker is clearly underexplored. In summary, mapping biological differences at the level of the individual with ASD is a major challenge for the field now. Conceptualizing those mappings and individual trajectories that lead to the diagnosis of ASD, will become a major challenge in the near future.
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http://dx.doi.org/10.1016/j.neubiorev.2019.07.010DOI Listing
September 2019

Converting tests of fundamental social, cognitive, and affective processes into clinically useful bio-behavioral markers for neurodevelopmental conditions.

Wiley Interdiscip Rev Cogn Sci 2019 Sep 3;10(5):e1499. Epub 2019 Apr 3.

Department of Psychology, Bucknell University, Lewisburg, Pennsylvania.

Biomarker discovery has become a central topic in neurodevelopmental research. A validated biomarker could be any objective measure or test that has clinical utility for diagnostic, stratification, or predictive purposes, or that can be used to objectively measure therapeutic efficacy. Here we discuss the potential and challenges of converting tests of fundamental social, cognitive, emotional and motivational processes into clinically useful bio-behavioral markers for neurodevelopmental conditions. Given the broad clinical and etiological heterogeneity of many neurodevelopmental conditions, we propose moving the focus from identifying group-defining characteristics to creating cross-domain bio-behavioral profiles at the individual level. We outline steps to develop tests that reflect the relevant domains and that are comparable, engaging and sensitive across large age and ability ranges. Analytical validation of these tests requires creating age norms, and optimizing psychometric properties. Individual bio-behavioral fingerprints of strengths and difficulties across domains can then be combined with multivariate approaches to identify "subgroups." This may help researchers and clinicians to compare individuals with and without intellectual disability, track developmental stability versus changes, and facilitate family genetic studies. Clinical validation requires including these tests in multidisciplinary, longitudinal and/ or intervention studies to ascertain whether particular subgroups differ in terms of their etiology, clinical symptom profile, prognosis or therapeutic benefit. Potential advantages of bio-behavioral tests over other biomarker methodologies, such as neuroimaging measures, include the low cost, ease of administration and analysis, low risk, and scalability through on-line assessments or tablet applications. This article is categorized under: Neuroscience > Development Psychology > Theory and Methods Neuroscience > Clinical Neuroscience Neuroscience > Cognition.
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http://dx.doi.org/10.1002/wcs.1499DOI Listing
September 2019

Patients with autism spectrum disorders display reproducible functional connectivity alterations.

Sci Transl Med 2019 02;11(481)

Hôpitaux Universitaires Mondor, DHU PePSY, Pôle de psychiatrie, Faculté de Médecine, Université Paris Est, INSERM U955, IMRB, Equipe 15, Psychiatrie Translationnelle, Fondation FondaMental, 94000 Créteil, France.

Despite the high clinical burden, little is known about pathophysiology underlying autism spectrum disorder (ASD). Recent resting-state functional magnetic resonance imaging (rs-fMRI) studies have found atypical synchronization of brain activity in ASD. However, no consensus has been reached on the nature and clinical relevance of these alterations. Here, we addressed these questions in four large ASD cohorts. Using rs-fMRI, we identified functional connectivity alterations associated with ASD. We tested for associations of these imaging phenotypes with clinical and demographic factors such as age, sex, medication status, and clinical symptom severity. Our results showed reproducible patterns of ASD-associated functional hyper- and hypoconnectivity. Hypoconnectivity was primarily restricted to sensory-motor regions, whereas hyperconnectivity hubs were predominately located in prefrontal and parietal cortices. Shifts in cortico-cortical between-network connectivity from outside to within the identified regions were shown to be a key driver of these abnormalities. This reproducible pathophysiological phenotype was partially associated with core ASD symptoms related to communication and daily living skills and was not affected by age, sex, or medication status. Although the large effect sizes in standardized cohorts are encouraging with respect to potential application as a treatment and for patient stratification, the moderate link to clinical symptoms and the large overlap with healthy controls currently limit the usability of identified alterations as diagnostic or efficacy readout.
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http://dx.doi.org/10.1126/scitranslmed.aat9223DOI Listing
February 2019

Dissecting the Heterogeneous Cortical Anatomy of Autism Spectrum Disorder Using Normative Models.

Biol Psychiatry Cogn Neurosci Neuroimaging 2019 06 19;4(6):567-578. Epub 2018 Dec 19.

Department of Cognitive Neuroscience, Radboud University Medical Center, Nijmegen, the Netherlands; Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, the Netherlands; Department of Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience King's College London, London, United Kingdom.

Background: The neuroanatomical basis of autism spectrum disorder (ASD) has remained elusive, mostly owing to high biological and clinical heterogeneity among diagnosed individuals. Despite considerable effort toward understanding ASD using neuroimaging biomarkers, heterogeneity remains a barrier, partly because studies mostly employ case-control approaches, which assume that the clinical group is homogeneous.

Methods: Here, we used an innovative normative modeling approach to parse biological heterogeneity in ASD. We aimed to dissect the neuroanatomy of ASD by mapping the deviations from a typical pattern of neuroanatomical development at the level of the individual and to show the necessity to look beyond the case-control paradigm to understand the neurobiology of ASD. We first estimated a vertexwise normative model of cortical thickness development using Gaussian process regression, then mapped the deviation of each participant from the typical pattern. For this, we employed a heterogeneous cross-sectional sample of 206 typically developing individuals (127 males) and 321 individuals with ASD (232 males) (6-31 years of age).

Results: We found few case-control differences, but the ASD cohort showed highly individualized patterns of deviations in cortical thickness that were widespread across the brain. These deviations correlated with severity of repetitive behaviors and social communicative symptoms, although only repetitive behaviors survived corrections for multiple testing.

Conclusions: Our results 1) reinforce the notion that individuals with ASD show distinct, highly individualized trajectories of brain development and 2) show that by focusing on common effects (i.e., the "average ASD participant"), the case-control approach disguises considerable interindividual variation crucial for precision medicine.
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http://dx.doi.org/10.1016/j.bpsc.2018.11.013DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6551348PMC
June 2019

Investigating the factors underlying adaptive functioning in autism in the EU-AIMS Longitudinal European Autism Project.

Autism Res 2019 04 11;12(4):645-657. Epub 2019 Feb 11.

Department of Psychology, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK.

Individuals with autism spectrum disorder (ASD) exhibit significant impairments in adaptive functioning that impact on their ability to meet the demands of everyday life. A recurrent finding is that there is a pronounced discrepancy between level of cognitive ability and adaptive functioning, and this is particularly prominent among higher-ability individuals. However, the key clinical and demographic associations of these discrepancies remain unclear. This study included a sample of 417 children, adolescents, and adults with ASD as part of the EU-AIMS LEAP cohort. We examined how age, sex, IQ, levels of ASD symptom and autistic trait severity and psychiatric symptomatology are associated with adaptive functioning as measured by the Vineland Adaptive Behavior Scales-Second Edition and IQ-adaptive functioning discrepancies. Older age, lower IQ and higher social-communication symptoms were associated with lower adaptive functioning. Results also demonstrate that older age, higher IQ and higher social-communication symptoms are associated with greater IQ-adaptive functioning discrepancy scores. By contrast, sensory ASD symptoms, repetitive and restricted behaviors, as well as symptoms of attention deficit/hyperactivity disorder (ADHD), anxiety and depression, were not associated with adaptive functioning or IQ-adaptive functioning discrepancy scores. These findings suggest that it is the core social communication problems that define ASD that contribute to adaptive function impairments that people with ASD experience. They show for the first time that sensory symptoms, repetitive behavior and associated psychiatric symptoms do not independently contribute to adaptive function impairments. Individuals with ASD require supportive interventions across the lifespan that take account of social-communicative ASD symptom severity. Autism Res 2019, 12: 645-657. © 2019 The Authors. Autism Research published by International Society for Autism Research published by Wiley Periodicals, Inc. LAY SUMMARY: This study investigated key clinical and demographic associations of adaptive functioning impairments in individuals with autism. We found that older age, lower IQ and more severe social-communicative symptoms, but not sensory or repetitive symptoms or co-occurring psychiatric symptoms, are associated with lower adaptive functioning and greater ability-adaptive function discrepancies. This suggests that interventions targeting adaptive skills acquisition should be flexible in their timing and intensity across developmental periods, levels of cognitive ability and take account of social-communicative ASD symptom severity.
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http://dx.doi.org/10.1002/aur.2081DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6519242PMC
April 2019

Altered Connectivity Between Cerebellum, Visual, and Sensory-Motor Networks in Autism Spectrum Disorder: Results from the EU-AIMS Longitudinal European Autism Project.

Biol Psychiatry Cogn Neurosci Neuroimaging 2019 03 5;4(3):260-270. Epub 2018 Dec 5.

Department of Cognitive Neuroscience, Radboud University Medical Center, the Netherlands; Donders Institute for Brain, Cognition, and Behavior, Radboud University, the Netherlands; Karakter Child and Adolescent Psychiatry University Centre, Nijmegen, the Netherlands.

Background: Resting-state functional magnetic resonance imaging-based studies on functional connectivity in autism spectrum disorder (ASD) have generated inconsistent results. Interpretation of findings is further hampered by small samples and a focus on a limited number of networks, with networks underlying sensory processing being largely underexamined. We aimed to comprehensively characterize ASD-related alterations within and between 20 well-characterized resting-state networks using baseline data from the EU-AIMS (European Autism Interventions-A Multicentre Study for Developing New Medications) Longitudinal European Autism Project.

Methods: Resting-state functional magnetic resonance imaging data was available for 265 individuals with ASD (7.5-30.3 years; 73.2% male) and 218 typically developing individuals (6.9-29.8 years; 64.2% male), all with IQ > 70. We compared functional connectivity within 20 networks-obtained using independent component analysis-between the ASD and typically developing groups, and related functional connectivity within these networks to continuous (overall) autism trait severity scores derived from the Social Responsiveness Scale Second Edition across all participants. Furthermore, we investigated case-control differences and autism trait-related alterations in between-network connectivity.

Results: Higher autism traits were associated with increased connectivity within salience, medial motor, and orbitofrontal networks. However, we did not replicate previously reported case-control differences within these networks. The between-network analysis did reveal case-control differences showing on average 1) decreased connectivity of the visual association network with somatosensory, medial, and lateral motor networks, and 2) increased connectivity of the cerebellum with these sensory and motor networks in ASD compared with typically developing subjects.

Conclusions: We demonstrate ASD-related alterations in within- and between-network connectivity. The between-network alterations broadly affect connectivity between cerebellum, visual, and sensory-motor networks, potentially underlying impairments in multisensory and visual-motor integration frequently observed in ASD.
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http://dx.doi.org/10.1016/j.bpsc.2018.11.010DOI Listing
March 2019

EU-AIMS Longitudinal European Autism Project (LEAP): the autism twin cohort.

Mol Autism 2018 13;9:26. Epub 2018 Apr 13.

1Department of Women's and Children's Health, Division of Neuropsychiatry Unit, Center of Neurodevelopmental Disorders (KIND), Karolinska Institutet, Stockholm, Sweden.

EU-AIMS is the largest European research program aiming to identify stratification biomarkers and novel interventions for autism spectrum disorder (ASD). Within the program, the Longitudinal European Autism Project (LEAP) has recruited and comprehensively phenotyped a rare sample of 76 monozygotic and dizygotic twins, discordant, or concordant for ASD plus 30 typically developing twins. The aim of this letter is to complete previous descriptions of the LEAP case-control sample, clinically characterize, and investigate the suitability of the sample for ASD twin-control analyses purposes and share some 'lessons learnt.' Among the twins, a diagnosis of ASD is associated with increased symptom levels of ADHD, higher rates of intellectual disability, and lower family income. For the future, we conclude that the LEAP twin cohort offers multiple options for analyses of genetic and shared and non-shared environmental factors to generate new hypotheses for the larger cohort of LEAP singletons, but particularly cross-validate and refine evidence from it.
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http://dx.doi.org/10.1186/s13229-018-0212-xDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5899373PMC
October 2018

Measuring and Estimating the Effect Sizes of Copy Number Variants on General Intelligence in Community-Based Samples.

JAMA Psychiatry 2018 05;75(5):447-457

Department of Pediatrics, Université de Montréal, Montreal, Quebec, Canada.

Importance;: Copy number variants (CNVs) classified as pathogenic are identified in 10% to 15% of patients referred for neurodevelopmental disorders. However, their effect sizes on cognitive traits measured as a continuum remain mostly unknown because most of them are too rare to be studied individually using association studies.

Objective: To measure and estimate the effect sizes of recurrent and nonrecurrent CNVs on IQ.

Design, Setting, And Participants: This study identified all CNVs that were 50 kilobases (kb) or larger in 2 general population cohorts (the IMAGEN project and the Saguenay Youth Study) with measures of IQ. Linear regressions, including functional annotations of genes included in CNVs, were used to identify features to explain their association with IQ. Validation was performed using intraclass correlation that compared IQ estimated by the model with empirical data.

Main Outcomes And Measures: Performance IQ (PIQ), verbal IQ (VIQ), and frequency of de novo CNV events.

Results: The study included 2090 European adolescents from the IMAGEN study and 1983 children and parents from the Saguenay Youth Study. Of these, genotyping was performed on 1804 individuals from IMAGEN and 977 adolescents, 445 mothers, and 448 fathers (484 families) from the Saguenay Youth Study. We observed 4928 autosomal CNVs larger than 50 kb across both cohorts. For rare deletions, size, number of genes, and exons affect IQ, and each deleted gene is associated with a mean (SE) decrease in PIQ of 0.67 (0.19) points (P = 6 × 10-4); this is not so for rare duplications and frequent CNVs. Among 10 functional annotations, haploinsufficiency scores best explain the association of any deletions with PIQ with a mean (SE) decrease of 2.74 (0.68) points per unit of the probability of being loss-of-function intolerant (P = 8 × 10-5). Results are consistent across cohorts and unaffected by sensitivity analyses removing pathogenic CNVs. There is a 0.75 concordance (95% CI, 0.39-0.91) between the effect size on IQ estimated by our model and IQ loss calculated in previous studies of 15 recurrent CNVs. There is a close association between effect size on IQ and the frequency at which deletions occur de novo (odds ratio, 0.86; 95% CI, 0.84-0.87; P = 2.7 × 10-88). There is a 0.76 concordance (95% CI, 0.41-0.91) between de novo frequency estimated by the model and calculated using data from the DECIPHER database.

Conclusions And Relevance: Models trained on nonpathogenic deletions in the general population reliably estimate the effect size of pathogenic deletions and suggest omnigenic associations of haploinsufficiency with IQ. This represents a new framework to study variants too rare to perform individual association studies and can help estimate the cognitive effect of undocumented deletions in the neurodevelopmental clinic.
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http://dx.doi.org/10.1001/jamapsychiatry.2018.0039DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5875373PMC
May 2018
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