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1. The EU-AIMS Longitudinal European Autism Project (LEAP): design and methodologies to identify and validate stratification biomarkers for autism spectrum disorders

Author

Eva Loth, Tony Charman, Luke Mason, Julian Tillmann, Emily J. H. Jones, Caroline Wooldridge, Jumana Ahmad, Bonnie Auyeung, Claudia Brogna, Sara Ambrosino, Tobias Banaschewski, Simon Baron-Cohen, Sarah Baumeister, Christian Beckmann, Michael Brammer, Daniel Brandeis, Sven Bölte, Thomas Bourgeron, Carsten Bours, Yvette de Bruijn, Bhismadev Chakrabarti, Daisy Crawley, Ineke Cornelissen, Flavio Dell’ Acqua, Guillaume Dumas, Sarah Durston, Christine Ecker, Jessica Faulkner, Vincent Frouin, Pilar Garces, David Goyard, Hannah Hayward, Lindsay M. Ham, Joerg Hipp, Rosemary J. Holt, Mark H. Johnson, Johan Isaksson, Prantik Kundu, Meng-Chuan Lai, Xavier Liogier D’ardhuy, Michael V. Lombardo, David J. Lythgoe, René Mandl, Andreas Meyer-Lindenberg, Carolin Moessnang, Nico Mueller, Laurence O’Dwyer, Marianne Oldehinkel, Bob Oranje, Gahan Pandina, Antonio M. Persico, Amber N. V. Ruigrok, Barbara Ruggeri, Jessica Sabet, Roberto Sacco, Antonia San José Cáceres, Emily Simonoff, Roberto Toro, Heike Tost, Jack Waldman, Steve C. R. Williams, Marcel P. Zwiers, Will Spooren, Declan G. M. Murphy, and Jan K. Buitelaar

Subjects
Biomarkers, Cognition, Neuroimaging, MRI, EEG, Eye-tracking, Neurology. Diseases of the nervous system, RC346-429
Abstract

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

Published
2017
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2. The EU-AIMS Longitudinal European Autism Project (LEAP): clinical characterisation

Author

Tony Charman, Eva Loth, Julian Tillmann, Daisy Crawley, Caroline Wooldridge, David Goyard, Jumana Ahmad, Bonnie Auyeung, Sara Ambrosino, Tobias Banaschewski, Simon Baron-Cohen, Sarah Baumeister, Christian Beckmann, Sven Bölte, Thomas Bourgeron, Carsten Bours, Michael Brammer, Daniel Brandeis, Claudia Brogna, Yvette de Bruijn, Bhismadev Chakrabarti, Ineke Cornelissen, Flavio Dell’ Acqua, Guillaume Dumas, Sarah Durston, Christine Ecker, Jessica Faulkner, Vincent Frouin, Pilar Garcés, Lindsay Ham, Hannah Hayward, Joerg Hipp, Rosemary J. Holt, Johan Isaksson, Mark H. Johnson, Emily J. H. Jones, Prantik Kundu, Meng-Chuan Lai, Xavier Liogier D’ardhuy, Michael V. Lombardo, David J Lythgoe, René Mandl, Luke Mason, Andreas Meyer-Lindenberg, Carolin Moessnang, Nico Mueller, Laurence O’Dwyer, Marianne Oldehinkel, Bob Oranje, Gahan Pandina, Antonio M. Persico, Barbara Ruggeri, Amber N. V. Ruigrok, Jessica Sabet, Roberto Sacco, Antonia San Jóse Cáceres, Emily Simonoff, Roberto Toro, Heike Tost, Jack Waldman, Steve C. R. Williams, Marcel P. Zwiers, Will Spooren, Declan G. M. Murphy, and Jan K. Buitelaar

Subjects
Autism, Autism spectrum disorder, Phenotype, Behaviours, Heterogeneity, Sex, Neurology. Diseases of the nervous system, RC346-429
Abstract

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

Published
2017
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3. Autism is associated with interindividual variations of gray and white matter morphology

Author

Ting Mei, Natalie J. Forde, Dorothea L. Floris, Flavio Dell’Acqua, Richard Stones, Iva Ilioska, Sarah Durston, Carolin Moessnang, Tobias Banaschewski, Rosemary J. Holt, Simon Baron-Cohen, Annika Rausch, Eva Loth, Bethany Oakley, Tony Charman, Christine Ecker, Declan G.M. Murphy, Christian F. Beckmann, Alberto Llera, Jan K. Buitelaar, Jumana Ahmad, Sara Ambrosino, Bonnie Auyeung, Sarah Baumeister, Sven Bölte, Thomas Bourgeron, Carsten Bours, Michael Brammer, Daniel Brandeis, Claudia Brogna, Yvette de Bruijn, Bhismadev Chakrabarti, Ineke Cornelissen, Daisy Crawley, Guillaume Dumas, Jessica Faulkner, Vincent Frouin, Pilar Garcés, David Goyard, Lindsay Ham, Hannah Hayward, Joerg Hipp, Rosemary Holt, Mark H. Johnson, Emily J.H. Jones, Prantik Kundu, Meng-Chuan Lai, Xavier Liogier d’Ardhuy, Michael V. Lombardo, David J. Lythgoe, René Mandl, Andre Marquand, Luke Mason, Maarten Mennes, Andreas Meyer-Lindenberg, Nico Mueller, Laurence O’Dwyer, Marianne Oldehinkel, Bob Oranje, Gahan Pandina, Antonio M. Persico, Barbara Ruggeri, Amber Ruigrok, Jessica Sabet, Roberto Sacco, Antonia San José Cáceres, Emily Simonoff, Will Spooren, Julian Tillmann, Roberto Toro, Heike Tost, Jack Waldman, Steve C.R. Williams, Caroline Wooldridge, and Marcel P. Zwiers

Subjects
multimodal analysis, multivariate analysis, Cognitive Neuroscience, autism, Radiology, Nuclear Medicine and imaging, Neurology (clinical), gray matter, white matter, Biological Psychiatry, canonical correlation analysis
Abstract

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.

Published
2022

4. A comparison of the content and nature of worries of autistic and neurotypical young people as they transition from school

Author

Jack Waldman, Ann McPaul, and Andrew Jahoda

Subjects
Developmental and Educational Psychology
Abstract

The prevalence of anxiety is higher in autistic young people, compared to neurotypical youths. However, the nature of worry in autistic young people is under-researched. Transition from secondary school is a time of change and can be challenging for autistic adolescents. This project explored the content and emotional impact of worries in neurotypical and autistic young people during transition. Twenty-two autistic people and 22 neurotypical people, aged 16–18, were recruited from mainstream schools. Participants completed a novel task to identify and explore the nature of their main worries. The participants’ worry frequency and distress levels in relation to their most salient concerns, and their anxiety levels, were measured. Content analysis highlighted similarities and differences between the two groups’ worries. Both groups worried about failure and their prospects of further education. Autistic people were more concerned about change and friendship, whereas more salient worries for neurotypical individuals were about work and money. Autistic people were more distressed by their worries than neurotypical individuals. Findings regarding the nature of autistic young people’s worries may help inform interventions. Moreover, asking autistic people about their worries as they leave school may help to address their concerns, ease their transition and reduce distress. Lay abstract Autistic young people experience higher levels of anxiety than neurotypical young people. Having worries is part of feeling anxious. This makes it surprising that very little research has looked at the kind of worries autistic young people have. Leaving school, in particular, can be a worrying time for young people. Twenty-two autistic young people and 22 neurotypical young people who were at mainstream secondary schools agreed to take part in the study. They were between 16 and 18 years of age. They were asked to sort through a series of pictures, showing the different types of worries that young people might experience. They were then asked to pick out their four main worries and say how much they thought about each worry and how upset the worry made them. They also completed a questionnaire about their level of anxiety. There were similarities and differences between the autistic and neurotypical young people’s worries. Both groups worried about failing and how they might get on in further education. The autistic young people were more worried about change and friendships. Work and money were particular concerns for the neurotypical young people. The autistic young people said that they found their worries more upsetting than the neurotypical young people. Having a better understanding of autistic young people’s worries at important points in their lives might mean that more timely help and support can be given to them. Simply knowing what to ask young autistic school leavers about may help them to express unspoken concerns.

Published
2022

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

Author

Dorothea L. Floris, Thomas Wolfers, Mariam Zabihi, Nathalie E. Holz, Marcel P. Zwiers, Tony Charman, Julian Tillmann, Christine Ecker, Flavio Dell’Acqua, Tobias Banaschewski, Carolin Moessnang, Simon Baron-Cohen, Rosemary Holt, Sarah Durston, Eva Loth, Declan G.M. Murphy, Andre Marquand, Jan K. Buitelaar, Christian F. Beckmann, Jumana Ahmad, Sara Ambrosino, Bonnie Auyeung, Sarah Baumeister, Sven Bölte, Thomas Bourgeron, Carsten Bours, Michael Brammer, Daniel Brandeis, Claudia Brogna, Yvette de Bruijn, Bhismadev Chakrabarti, Ineke Cornelissen, Daisy Crawley, Guillaume Dumas, Jessica Faulkner, Vincent Frouin, Pilar Garcés, David Goyard, Lindsay Ham, Hannah Hayward, Joerg Hipp, Mark H. Johnson, Emily J.H. Jones, Prantik Kundu, Meng-Chuan Lai, Xavier Liogier d’Ardhuy, Michael V. Lombardo, David J. Lythgoe, René Mandl, Luke Mason, Maarten Mennes, Andreas Meyer-Lindenberg, Nico Mueller, Bethany Oakley, Laurence O’Dwyer, Marianne Oldehinkel, Bob Oranje, Gahan Pandina, Antonio M. Persico, Barbara Ruggeri, Amber Ruigrok, Jessica Sabet, Roberto Sacco, Antonia San José Cáceres, Emily Simonoff, Will Spooren, Roberto Toro, Heike Tost, Jack Waldman, Steve C.R. Williams, and Caroline Wooldridge

Subjects
medicine.medical_specialty, Language delay, Autism Spectrum Disorder, Cognitive Neuroscience, Stress-related disorders Donders Center for Medical Neuroscience [Radboudumc 13], Audiology, behavioral disciplines and activities, 050105 experimental psychology, Lateralization of brain function, 150 000 MR Techniques in Brain Function, Functional Laterality, 03 medical and health sciences, 0302 clinical medicine, All institutes and research themes of the Radboud University Medical Center, mental disorders, medicine, Autism spectrum disorder, Brain asymmetry, Hemispheric specialization, Heterogeneity, Normative modeling, Humans, 0501 psychology and cognitive sciences, Radiology, Nuclear Medicine and imaging, Autistic Disorder, Biological Psychiatry, Neurodevelopmental disorders Donders Center for Medical Neuroscience [Radboudumc 7], 05 social sciences, 220 Statistical Imaging Neuroscience, Brain, medicine.disease, Magnetic Resonance Imaging, medicine.anatomical_structure, Laterality, Autism, Neurology (clinical), Psychology, 030217 neurology & neurosurgery, Neurotypical, Neuroanatomy
Abstract

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.

Published
2020

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

Author

Roberto Sacco, Jumana Ahmad, Daniel Brandeis, Steve C.R. Williams, Carsten Bours, Christine Ecker, Emily Simonoff, Caroline Wooldridge, Andreas Meyer-Lindenberg, Pilar Garcés, Vincent Frouin, Thomas Bourgeron, Eva Loth, Guillaume Dumas, Jan K. Buitelaar, Andre F. Marquand, Hannah Hayward, Bethany Oakley, Joerg F. Hipp, Simon Baron-Cohen, Lindsay Ham, Michael V. Lombardo, Yvette de Bruijn, Jessica Faulkner, Declan G. Murphy, René C.W. Mandl, Sarah Baumeister, Marianne Oldehinkel, Jessica Sabet, Mark H. Johnson, Laurence O'Dwyer, Claudia Brogna, Amber N. V. Ruigrok, Frederick Shic, Bob Oranje, Ineke Cornelissen, Christian F. Beckmann, Tobias Banaschewski, Rosemary Holt, David Goyard, Michael Brammer, Daisy Crawley, Carolin Moessnang, Barbara Ruggeri, Gahan Pandina, Teresa Del Bianco, Julian Tillman, Luke Mason, Antonio M. Persico, Emily J.H. Jones, Sarah Durston, Antonia San José Cáceres, Roberto Toro, Xavier Liogier d'Ardhuy, Jack Waldman, Tony Charman, Meng-Chuan Lai, Marcel P. Zwiers, Flavio Dell'Acqua, Heike Tost, Maarten Mennes, Sven Bölte, Will Spooren, Sara Ambrosino, David J. Lythgoe, and Nico Mueller

Subjects
Adult, Adolescent, Cognitive Neuroscience, Eye contact, Social attention, Disease cluster, 050105 experimental psychology, Developmental psychology, Young Adult, 03 medical and health sciences, 0302 clinical medicine, medicine, Humans, Attention, 0501 psychology and cognitive sciences, Radiology, Nuclear Medicine and imaging, Autistic Disorder, Autism spectrum disorder, Child, Biological Psychiatry, Probability, Eye tracking, 05 social sciences, Contrast (statistics), medicine.disease, Vineland Adaptive Behavior Scale, Social motivation, Neurology (clinical), Growth curve analysis, Stratification, Psychology, 030217 neurology & neurosurgery, Neurotypical
Abstract

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.

Published
2020

7. Altered connectivity between cerebellum, visual, and sensory-motor networks in autism spectrum disorder: Results from the EU-AIMS Longitudinal European Autism Project

Author

Marianne Oldehinkel, Maarten Mennes, Andre Marquand, Tony Charman, Julian Tillmann, Christine Ecker, Flavio Dell’Acqua, Daniel Brandeis, Tobias Banaschewski, Sarah Baumeister, Carolin Moessnang, Simon Baron-Cohen, Rosemary Holt, Sven Bölte, Sarah Durston, Prantik Kundu, Michael V. Lombardo, Will Spooren, Eva Loth, Declan G.M. Murphy, Christian F. Beckmann, Jan K. Buitelaar, Jumana Ahmad, Sara Ambrosino, Bonnie Auyeung, Thomas Bourgeron, Carsten Bours, Michael Brammer, Claudia Brogna, Yvette de Bruijn, Bhismadev Chakrabarti, Ineke Cornelissen, Daisy Crawley, Guillaume Dumas, Jessica Faulkner, Vincent Frouin, Pilar Garcés, David Goyard, Lindsay Ham, Hannah Hayward, Joerg Hipp, Mark H. Johnson, Emily J.H. Jones, Meng-Chuan Lai, Xavier Liogier D’ardhuy, David J. Lythgoe, René Mandl, Luke Mason, Andreas Meyer-Lindenberg, Nico Mueller, Bethany Oakley, Laurence O’Dwyer, Bob Oranje, Gahan Pandina, Antonio M. Persico, Barbara Ruggeri, Amber Ruigrok, Jessica Sabet, Roberto Sacco, Antonia San José Cáceres, Emily Simonoff, Roberto Toro, Heike Tost, Jack Waldman, Steve C.R. Williams, Caroline Wooldridge, Marcel P. Zwiers, Radboud University Medical Center [Nijmegen], Monash University [Melbourne], Donders Institute for Brain, Cognition and Behaviour, Radboud university [Nijmegen], Institute of Psychiatry, Psychology & Neuroscience, King's College London, King‘s College London, Goethe-University Frankfurt am Main, Universität Heidelberg [Heidelberg], Universität Zürich [Zürich] = University of Zurich (UZH), Eidgenössische Technische Hochschule - Swiss Federal Institute of Technology [Zürich] (ETH Zürich), Department of Child and Adolescent Psychiatry and Psychotherapy [Mannheim], University of Cambridge [UK] (CAM), Karolinska Institutet [Stockholm], Stockholm County Council, University Medical Center [Utrecht], Icahn School of Medicine at Mount Sinai [New York] (MSSM), University of Cyprus [Nicosia], Roche Pharma Research and Early Development [Basel] (pRED), F. Hoffmann-La Roche [Basel], University of Oxford [Oxford], University of Edinburgh, Génétique humaine et fonctions cognitives - Human Genetics and Cognitive Functions (GHFC (UMR_3571 / U-Pasteur_1)), Institut Pasteur [Paris]-Université Paris Diderot - Paris 7 (UPD7)-Centre National de la Recherche Scientifique (CNRS), Università Campus Bio-Medico di Roma / University Campus Bio-Medico of Rome ( UCBM), University of Reading (UOR), Département de Chimie Moléculaire (DCM), Institut de Chimie du CNRS (INC)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019]), University of Nottingham, UK (UON), University of Toronto, Centre for Brain and Cognitive Development [Birkbeck College], Birkbeck College [University of London], Janssen Research & Development, This work was supported EU-AIMS, which receives support from the Innovative Medicines Initiative Joint Undertaking under Grant Agreement No. 115300 and the Innovative Medicines Initiative 2 Joint Undertaking under Grant Agreement No. 777394, the resources of which are composed of financial contributions from the European Union’s Seventh Framework Programme (Grant No. FP7/2007-2013), from the European Federation of Pharmaceutical Industries and Associations companies’ in-kind contributions, and from Autism Speaks. This work was also supported by the Netherlands Organization for Scientific Research through Vidi grants (Grant No. 864.12.003 [to CFB] and Grant No. 016.156.415 [to AFM]), from the FP7 (Grant Nos. 602805) (AGGRESSOTYPE) (to JKB), 603016 (MATRICS), and 278948 (TACTICS), and from the European Community’s Horizon 2020 Programme (H2020/2014-2020) (Grant Nos. 643051 [MiND] and 642996 (BRAINVIEW). This work received funding from the Wellcome Trust UK Strategic Award (Award No. 098369/Z/12/Z) and from the National Institute for Health Research Maudsley Biomedical Research Centre (to DM)., European Project: 602805,EC:FP7:HEALTH,FP7-HEALTH-2013-INNOVATION-1,AGGRESSOTYPE(2013), European Project: 603016,EC:FP7:HEALTH,FP7-HEALTH-2013-INNOVATION-1,MATRICS(2014), European Project: 278948,EC:FP7:HEALTH,FP7-HEALTH-2011-two-stage,TACTICS(2012), European Project: 643051,H2020,H2020-MSCA-ITN-2014,MiND(2015), European Project: 642996,H2020,H2020-MSCA-ITN-2014,BRAINVIEW(2015), Radboud University [Nijmegen], Universität Heidelberg [Heidelberg] = Heidelberg University, University of Cyprus [Nicosia] (UCY), University of Oxford, Institut Pasteur [Paris] (IP)-Université Paris Diderot - Paris 7 (UPD7)-Centre National de la Recherche Scientifique (CNRS), University of Zurich, Oldehinkel, Marianne, University of Zürich [Zürich] (UZH), Eidgenössische Technische Hochschule - Swiss Federal Institute of Technology in Zürich [Zürich] (ETH Zürich), Centre National de la Recherche Scientifique (CNRS)-Université Paris Diderot - Paris 7 (UPD7)-Institut Pasteur [Paris], Université Joseph Fourier - Grenoble 1 (UJF)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA), and Lombardo, Michael V. [0000-0001-6780-8619]

Subjects
Male, Autism Spectrum Disorder, Autism, Functional connectivity, 0302 clinical medicine, Cerebellum, Neural Pathways, Longitudinal Studies, 10064 Neuroscience Center Zurich, Child, Visual-motor integration, Visual Cortex, Brain Mapping, medicine.diagnostic_test, 05 social sciences, Sensory networks, 220 Statistical Imaging Neuroscience, 10058 Department of Child and Adolescent Psychiatry, Magnetic Resonance Imaging, 2728 Neurology (clinical), Autism spectrum disorder, Radiology Nuclear Medicine and imaging, 10076 Center for Integrative Human Physiology, Female, [SDV.NEU]Life Sciences [q-bio]/Neurons and Cognition [q-bio.NC], Sensorimotor Cortex, Biological psychiatry, Psychology, 2803 Biological Psychiatry, Adult, 2805 Cognitive Neuroscience, Autism, Cerebellum, Functional connectivity, Resting-state fMRI, Sensory networks, Visual-motor integration, Radiology, Nuclear Medicine and Imaging, Cognitive Neuroscience, Neurology (clinical), Biological Psychiatry, Adolescent, Cognitive Neuroscience, Clinical Neurology, Sensory system, 610 Medicine & health, Cognitive neuroscience, 050105 experimental psychology, 03 medical and health sciences, Young Adult, Salience (neuroscience), mental disorders, medicine, Humans, 2741 Radiology, Nuclear Medicine and Imaging, 0501 psychology and cognitive sciences, Radiology, Nuclear Medicine and imaging, Resting-state fMRI, Biological Psychiatry, Radiology, Nuclear Medicine and Imaging, Neurology (clinical), Neurodevelopmental disorders Donders Center for Medical Neuroscience [Radboudumc 7], Resting state fMRI, medicine.disease, Case-Control Studies, Functional magnetic resonance imaging, Neuroscience, 030217 neurology & neurosurgery
Abstract

BackgroundResting-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.MethodsResting-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.ResultsHigher 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.ConclusionsWe 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.

Published
2019

8. Sex-specific impact of prenatal androgens on intrinsic functional connectivity between social brain default mode subsystems

Author

Amber N. V. Ruigrok, Jean-Louis Mandel, Tiziano Pramparo, Prantik Kundu, Natasha Mooney, Rosemary Holt, Jérémie Courraud, Amélie Piton, Jack Waldman, Edward T. Bullmore, Bonnie Auyeung, Michael V. Lombardo, Meng-Chuan Lai, Angélique Quartier, and Simon Baron-Cohen

Subjects
0303 health sciences, Mechanism (biology), medicine.drug_class, Cellular differentiation, Neurogenesis, Biology, Androgen, medicine.disease, Neural stem cell, 03 medical and health sciences, 0302 clinical medicine, Dihydrotestosterone, medicine, Autism, Neuroscience, 030217 neurology & neurosurgery, Default mode network, 030304 developmental biology, medicine.drug
Abstract

Many early-onset neurodevelopmental conditions such as autism affect males more frequently than females and affect corresponding domains such as social cognition, social-communication, language, emotion, and reward. Testosterone is well-known for its role as a sex-related biological mechanism and affects these conditions and domains of functioning. Developmentally, testosterone may sex-differentially impact early fetal brain development by influencing early neuronal development and synaptic mechanisms behind cortical circuit formation, particularly for circuits that later develop specialized roles in such cognitive domains. Here we find that variation in fetal testosterone (FT) exerts sex-specific effects on later adolescent functional connectivity between social brain default mode network (DMN) subsystems. Increased FT is associated with dampening of functional connectivity between DMN subsystems in adolescent males, but has no effect in females. To isolate specific prenatal neurobiological mechanisms behind this effect, we examined changes in gene expression identified following a treatment with a potent androgen, dihydrotestosterone (DHT) in an in-vitro model of human neural stem cell (hNSC). We previously showed that DHT-dysregulates genes enriched with known syndromic causes for autism and intellectual disability. DHT dysregulates genes in hNSCs involved in early neurodevelopmental processes such as neurogenesis, cell differentiation, regionalization, and pattern specification. A significant number of these DHT-dysregulated genes shows spatial expression patterns in the adult brain that highly correspond to the spatial layout of the cortical midline DMN subsystem. These DMN-related and DHT-affected genes (e.g., MEF2C) are involved in a number of synaptic processes, many of which impact excitation/inhibition imbalance. Focusing on MEF2C, we find replicable upregulation of expression after DHT treatment as well as dysregulated expression in induced pluripotent stem cells and neurons of individuals with autism. This work highlights sex-specific prenatal androgen influence on social brain DMN circuitry and autism-related mechanisms and suggests that such influence may impact early neurodevelopmental processes (e.g., neurogenesis, cell differentiation) and later developing synaptic processes.

Published
2018

9. The EU-AIMS Longitudinal European Autism Project (LEAP): design and methodologies to identify and validate stratification biomarkers for autism spectrum disorders

Author

Caroline Wooldridge, Marianne Oldehinkel, Claudia Brogna, Heike Tost, Eva Loth, Lindsay Ham, Laurence O'Dwyer, Thomas Bourgeron, Gahan Pandina, Amber N. V. Ruigrok, Antonio M. Persico, Sarah Durston, Michael V. Lombardo, Andreas Meyer-Lindenberg, Steve C.R. Williams, Julian Tillmann, Simon Baron-Cohen, Sarah Baumeister, Christian F. Beckmann, Tobias Banaschewski, Jumana Ahmad, Barbara Ruggeri, Jessica Sabet, Joerg F. Hipp, Daisy Crawley, Christine Ecker, Sara Ambrosino, Tony Charman, Antonia San José Cáceres, Xavier Liogier d'Ardhuy, Will Spooren, David J. Lythgoe, Nico Mueller, Guillaume Dumas, Luke Mason, Meng-Chuan Lai, Yvette de Bruijn, Sven Bölte, Prantik Kundu, Daniel Brandeis, David Goyard, Ineke Cornelissen, Emily Simonoff, Carsten Bours, Johan Isaksson, Pilar Garcés, Emily J.H. Jones, Rosemary Holt, Marcel P. Zwiers, Vincent Frouin, Roberto Sacco, Declan G. Murphy, Hannah Hayward, Roberto Toro, Jack Waldman, Bob Oranje, Carolin Moessnang, Flavio Dell' Acqua, Jessica Faulkner, René C.W. Mandl, Mark H. Johnson, Bonnie Auyeung, Jan K. Buitelaar, Bhismadev Chakrabarti, Michael Brammer, King‘s College London, Institute of Psychiatry, Psychology & Neuroscience, King's College London, Centre for Brain and Cognitive Development [Birkbeck College], Birkbeck College [University of London], University of Edinburgh, University of Cambridge [UK] (CAM), Università Campus Bio-Medico di Roma / University Campus Bio-Medico of Rome ( UCBM), University Medical Center [Utrecht], Department of Child and Adolescent Psychiatry and Psychotherapy [Mannheim], Universität Heidelberg [Heidelberg] = Heidelberg University, Radboud University Medical Center [Nijmegen], Karolinska Institutet [Stockholm], Génétique humaine et fonctions cognitives - Human Genetics and Cognitive Functions (GHFC (UMR_3571 / U-Pasteur_1)), Institut Pasteur [Paris] (IP)-Université Paris Diderot - Paris 7 (UPD7)-Centre National de la Recherche Scientifique (CNRS), University of Reading (UOR), Service NEUROSPIN (NEUROSPIN), Université Paris-Saclay-Direction de Recherche Fondamentale (CEA) (DRF (CEA)), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA), Roche Pharma Research and Early Development [Basel] (pRED), F. Hoffmann-La Roche [Basel], University of London [London], Uppsala University, Icahn School of Medicine at Mount Sinai [New York] (MSSM), University of Toronto, University of Cyprus [Nicosia] (UCY), Heidelberg University, Janssen Research & Development, University of Messina, Donders Institute for Brain, Cognition and Behaviour, Radboud University [Nijmegen], This work was supported by EU-AIMS (European Autism Interventions), which receives support from the Innovative Medicines Initiative Joint Undertaking under grant agreement no. 115300, the resources of which are composed of financial contributions from the European Union’s Seventh Framework Programme (grant FP7/2007-2013), from the European Federation of Pharmaceutical Industries and Associations companies’ in-kind contributions and from Autism Speaks., European Project: 115300,EC:FP7:SP1-JTI,IMI-JU-03-2010,EU-AIMS(2012), Loth, Eva [0000-0001-9458-9167], Charman, Tony [0000-0003-1993-6549], Tillmann, Julian [0000-0001-9574-9855], Jones, Emily JH [0000-0001-5747-9540], Ahmad, Jumana [0000-0001-5271-0731], Brogna, Claudia [0000-0002-9526-6367], Banaschewski, Tobias [0000-0003-4595-1144], Baron-Cohen, Simon [0000-0001-9217-2544], Crawley, Daisy [0000-0001-9901-1110], Dumas, Guillaume [0000-0002-2253-1844], Hayward, Hannah [0000-0001-5552-2146], Hipp, Joerg [0000-0002-7875-2988], Johnson, Mark [0000-0003-4229-2585], Isaksson, Johan [0000-0003-1033-2618], Lai, Meng-Chuan [0000-0002-9593-5508], Lythgoe, David J [0000-0002-5078-9025], Moessnang, Carolin [0000-0003-4357-2706], Ruigrok, Amber [0000-0001-7711-8056], Ruggeri, Barbara [0000-0002-6231-8829], Simonoff, Emily [0000-0002-5450-0823], Toro, Roberto [0000-0002-6671-858X], Williams, Steve CR [0000-0003-4299-1941], Murphy, Declan GM [0000-0002-6664-7451], Apollo - University of Cambridge Repository, Universität Heidelberg [Heidelberg], Institut Pasteur [Paris]-Université Paris Diderot - Paris 7 (UPD7)-Centre National de la Recherche Scientifique (CNRS), Direction de Recherche Fondamentale (CEA) (DRF (CEA)), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris-Saclay, University of Cyprus [Nicosia], Radboud university [Nijmegen], Autism Research Centre and Section of Developmental Psychiatry, University of Cambridge [UK] ( CAM ), Università Campus Bio-Medico di Roma / University Campus Bio-Medico of Rome ( UCBM ), Medizinische Fakultät Mannheim, University of Zürich [Zürich] ( UZH ), Génétique humaine et Fonctions cognitives - Human Genetics and Cognitive Functions, Institut Pasteur [Paris]-Centre National de la Recherche Scientifique ( CNRS ), University of Reading ( UOR ), Goethe-University Frankfurt am Main, Service NEUROSPIN ( NEUROSPIN ), Direction de Recherche Fondamentale (CEA) ( DRF (CEA) ), Commissariat à l'énergie atomique et aux énergies alternatives ( CEA ) -Université Paris-Saclay-Commissariat à l'énergie atomique et aux énergies alternatives ( CEA ) -Université Paris-Saclay, Roche Pharma Research and Early Development [Basel] ( pRED ), Icahn School of Medicine at Mount Sinai [New York], and European Project : 115300,EC:FP7:SP1-JTI,IMI-JU-03-2010,EU-AIMS ( 2012 )

Subjects
Male, cognition, Autism Spectrum Disorder, [ SDV.MHEP.PSM ] Life Sciences [q-bio]/Human health and pathology/Psychiatrics and mental health, [SDV]Life Sciences [q-bio], Stress-related disorders Donders Center for Medical Neuroscience [Radboudumc 13], Individuality, lcsh:RC346-429, Developmental psychology, psyc, 0302 clinical medicine, Cognition, Intellectual disability, molecular biology, genetics, Longitudinal Studies, EEG, Biomarkers, eye-tracking, MRI, neuroimaging, developmental neuroscience, developmental biology, psychiatry and mental health, Precision Medicine, Child, Eye Movement Measurements, Psychiatry, 05 social sciences, 220 Statistical Imaging Neuroscience, Brain, Magnetic Resonance Imaging, 3. Good health, Psychiatry and Mental health, Phenotype, Autism spectrum disorder, Cohort, Female, Psychology, 050104 developmental & child psychology, Clinical psychology, Adult, BF, Neuroimaging, eye tracking, Biomarkers, cognition, EEG, eye-tracking, genetics, MRI, neuroimaging, molecular biology, developmental neuroscience, developmental biology, psychiatry and mental health, Psykiatri, 150 000 MR Techniques in Brain Function, [ SHS.PSY ] Humanities and Social Sciences/Psychology, 03 medical and health sciences, Genetic Heterogeneity, Developmental Neuroscience, mental disorders, medicine, Journal Article, Genetics, Humans, 0501 psychology and cognitive sciences, Saliva, Molecular Biology, lcsh:Neurology. Diseases of the nervous system, Neurodevelopmental disorders Donders Center for Medical Neuroscience [Radboudumc 7], Genetic heterogeneity, Research, Siblings, Patient Selection, biomarkers, medicine.disease, Precision medicine, [ SDV.NEU ] Life Sciences [q-bio]/Neurons and Cognition [q-bio.NC], Autism, Observational study, Eye-tracking, [ SDV.GEN ] Life Sciences [q-bio]/Genetics, Neurocognitive, 030217 neurology & neurosurgery, Developmental Biology, Hair
Abstract

Background The tremendous clinical and aetiological diversity among individuals with autism spectrum disorder (ASD) has been a major obstacle to the development of new treatments, as many may only be effective in particular subgroups. Precision medicine approaches aim to overcome this challenge by combining pathophysiologically based treatments with stratification biomarkers that predict which treatment may be most beneficial for particular individuals. However, so far, we have no single validated stratification biomarker for ASD. This may be due to the fact that most research studies primarily have focused on the identification of mean case-control differences, rather than within-group variability, and included small samples that were underpowered for stratification approaches. The EU-AIMS Longitudinal European Autism Project (LEAP) is to date the largest multi-centre, multi-disciplinary observational study worldwide that aims to identify and validate stratification biomarkers for ASD. Methods LEAP includes 437 children and adults with ASD and 300 individuals with typical development or mild intellectual disability. Using an accelerated longitudinal design, each participant is comprehensively characterised in terms of clinical symptoms, comorbidities, functional outcomes, neurocognitive profile, brain structure and function, biochemical markers and genomics. In addition, 51 twin-pairs (of which 36 had one sibling with ASD) are included to identify genetic and environmental factors in phenotypic variability. Results Here, we describe the demographic characteristics of the cohort, planned analytic stratification approaches, criteria and steps to validate candidate stratification markers, pre-registration procedures to increase transparency, standardisation and data robustness across all analyses, and share some ‘lessons learnt’. A clinical characterisation of the cohort is given in the companion paper (Charman et al., accepted). Conclusion We expect that LEAP will enable us to confirm, reject and refine current hypotheses of neurocognitive/neurobiological abnormalities, identify biologically and clinically meaningful ASD subgroups, and help us map phenotypic heterogeneity to different aetiologies. Electronic supplementary material The online version of this article (doi:10.1186/s13229-017-0146-8) contains supplementary material, which is available to authorized users.

Published
2017

10. Improving effect size estimation and statistical power with multi-echo fMRI and its impact on understanding the neural systems supporting mentalizing

Author

Prantik Kundu, Edward T. Bullmore, Natasha Mooney, Jack Waldman, Amber N. V. Ruigrok, Bonnie Auyeung, Rosie Holt, Simon Baron-Cohen, Michael V. Lombardo, Ruigrok, Amber [0000-0001-7711-8056], Bullmore, Edward [0000-0002-8955-8283], Baron-Cohen, Simon [0000-0001-9217-2544], and Apollo - University of Cambridge Repository

Subjects
Male, Adolescent, Computer science, Cognitive Neuroscience, Theory of Mind, 050105 experimental psychology, Article, 03 medical and health sciences, 0302 clinical medicine, Theory of mind, Cerebellum, medicine, Image Processing, Computer-Assisted, Humans, 0501 psychology and cognitive sciences, Brain Mapping, Denoising, Resting state fMRI, medicine.diagnostic_test, Echo-Planar Imaging, 05 social sciences, Multi-echo EPI, Brain, Mentalizing, Power (physics), Mentalization, Neurology, Sample size determination, Data Interpretation, Statistical, Female, Noise (video), Statistical power, Task-fMRI, Functional magnetic resonance imaging, 030217 neurology & neurosurgery, Social cognitive theory, Cognitive psychology
Abstract

Functional magnetic resonance imaging (fMRI) research is routinely criticized for being statistically underpowered due to characteristically small sample sizes and much larger sample sizes are being increasingly recommended. Additionally, various sources of artifact inherent in fMRI data can have detrimental impact on effect size estimates and statistical power. Here we show how specific removal of non-BOLD artifacts can improve effect size estimation and statistical power in task-fMRI contexts, with particular application to the social-cognitive domain of mentalizing/theory of mind. Non-BOLD variability identification and removal is achieved in a biophysical and statistically principled manner by combining multi-echo fMRI acquisition and independent components analysis (ME-ICA). Without smoothing, group-level effect size estimates on two different mentalizing tasks were enhanced by ME-ICA at a median rate of 24% in regions canonically associated with mentalizing, while much more substantial boosts (40- 149%) were observed in non-canonical cerebellar areas. Effect size boosting occurs via reduction of non-BOLD noise at the subject-level and consequent reductions in betweensubject variance at the group-level. Smoothing can attenuate ME-ICA-related effect size improvements in certain circumstances. Power simulations demonstrate that ME-ICArelated effect size enhancements enable much higher-powered studies at traditional sample sizes. Cerebellar effects observed after applying ME-ICA may be unobservable with conventional imaging at traditional sample sizes. Thus, ME-ICA allows for principled design-agnostic non-BOLD artifact removal that can substantially improve effect size estimates and statistical power in task-fMRI contexts. ME-ICA could mitigate some issues regarding statistical power in fMRI studies and enable novel discovery of aspects of brain organization that are currently under-appreciated and not well understood., This work was supported by a Wellcome Trust project grant to SB-C and ETB. MVL was supported by the Wellcome Trust and fellowships from Jesus College, Cambridge and the British Academy. PK was supported by the National Institutes of Health–Cambridge Scholars Program. ETB is employed half-time by the University of Cambridge and halftime by GlaxoSmithKline (GSK)., This is the author accepted manuscript. It first appeared from Elseiver at http://dx.doi.org/10.1016/j.neuroimage.2016.07.022.

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11. Polygenic scores for intelligence, educational attainment and schizophrenia are differentially associated with core autism features, IQ, and adaptive behaviour in autistic individuals

Author

Warrier, Varun, Leblond, Claire, Cliquet, Freddy, Leap, Aims-2-Trials, Bourgeron, Thomas, Baron-Cohen, Simon, University of Cambridge [UK] (CAM), Génétique humaine et fonctions cognitives - Human Genetics and Cognitive Functions (GHFC (UMR_3571 / U-Pasteur_1)), Centre National de la Recherche Scientifique (CNRS)-Institut Pasteur [Paris]-Université de Paris (UP), V.W. is funded by St. Catharines College, Cambridge. This study was funded by grants to SBC from the Medical Research Council, the Wellcome Trust, the Autism Research Trust, the Templeton World Charity Foundation, and to T.B. from the Institut Pasteur, the CNRS, The Bettencourt-Schueller and the Cognacq-Jay Foundations, the APHP and the Universite de Paris. SBC was funded by the Autism Research Trust, the Wellcome Trust, the Templeton World Charitable Foundation, and the NIHR Biomedical Research Centre in Cambridge, during the period of this work., List of authors and their affiliations for the EU-AIMS LEAP group : KCL: Dr Antonia San Jose Caceres, Hannah Hayward, Daisy Crawley, Jessica Faulkner, Jessica Sabet, Claire Ellis, Bethany Oakley, Dr. Eva Loth, Prof. Tony Charman, Prof. Declan Murphy, University of Cambridge: Dr. Rosemary Holt , Jack Waldman, Jessica Upadhyay, Nicola Gunby, Dr. Meng-Chuan Lai, Gwilym Renouf, Dr. Amber Ruigrok, Emily Taylor, Dr. Hisham Ziauddeen, Dr. Julia Deakin, Professor Simon Baron-Cohen, UMC Utrecht: Sara Ambrosino di Bruttopilo, Sarai van Dijk, Yvonne Rijks, Tabitha Koops, Miriam Douma, Alyssia Spaan, Iris Selten, Maarten Steffers, Anna Ver Loren van Themaat, Central Institute of Mental Health Mannheim: Dr. Nico Bast, Dr. Sarah Baumeister, Radboudumc: Dr Larry O’Dwyer, Carsten Bours, Annika Rausch Dr. Daniel von Rhein, Ineke Cornelissen, Yvette de Bruin, Maartje Graauwmans, Karolinska Institutet: Elzbieta Kostrzewa, Elodie Cauvet, Dr. Kristiina Tammimies, Rouslan Sitnikow, Institut Pasteur: Dr. Guillaume Dumas, Dr. Yang-Min Kim, and Institut Pasteur [Paris] (IP)-Centre National de la Recherche Scientifique (CNRS)-Université Paris Cité (UPCité)

Subjects
[SDV.GEN.GH]Life Sciences [q-bio]/Genetics/Human genetics, [SDV.BBM.GTP]Life Sciences [q-bio]/Biochemistry, Molecular Biology/Genomics [q-bio.GN], [INFO.INFO-BI]Computer Science [cs]/Bioinformatics [q-bio.QM]
Abstract

Posté sur medRxiv le 24 juillet 2020.; ImportanceSchizophrenia, educational attainment, and intelligence are all genetically correlated with autism. However, autism is a complex condition, with several different core (such as social communication difficulties and repetitive and restricted behaviour) and associated features (such as IQ and adaptive behaviour) contributing to the underlying heterogeneity. It is unknown to what extent polygenic scores (PGS) for these three phenotypes are associated with the core and associated autism features.ObjectiveTo investigate the association of PGS for intelligence, educational attainment and schizophrenia on core autism features, IQ and adaptive behaviour in autistic individuals. To further investigate the effects of stratifying by sex and IQ on these associations.DesignPGS association for the three phenotypes with 12 different autism core and associated features in three cohorts followed by meta-analysis. We additionally conducted sensitivity analyses by stratifying for sex and IQ.Settings :Three cross-sectional, multi-centre cohorts comprising autistic with genotype data, and phenotypic information.ParticipantsAutistic individuals (total N: 2,512 – 3,681) from three different cohorts: Simons Simplex Collection (Nmax = 2,233), Autism Genetic Research Exchange (Nmax = 1,200), and AIMS-2- TRIALS LEAP (Nmax = 262)Main outcome measuresAssociation of PGS for intelligence, educational attainment, and schizophrenia with core autism features, measures of intelligence, and adaptive behaviour in autistic individualsResultsWe identified a similar pattern of correlation among core and associated autism features across all three cohorts. Cluster analyses of these features identified two broad clusters – one consisting of the core features, and another consisting of IQ and adaptive behaviour. PGS for intelligence were only associated with measures of intelligence and adaptive behaviour (e.g. for full-scale IQ, Beta = 0.08, 95%CI = 0.11 – 0.04) for PGS for educational attainment were associated for measures of intelligence, adaptive behaviour, and additionally, non-verbal communication as measured by ADI – a core-autism feature (e.g. for full-scale IQ, Beta = 0.05, 95%CI = 0.08 – 0.02; for ADI non-verbal communication, Beta = 0.05, 95%CI = 0.09 – 0.01). Finally, PGS for schizophrenia were associated with two core autism features: restricted and repetitive behaviour and verbal communication difficulties as measured by the ADI-R (e.g. for ADI restricted and repetitive behaviour: Beta = 0.06, 95%CI = 0.09 – 0.02). Most of these associations were also significant when restricting it to males only or to individuals with IQ > 70. We find limited evidence for heterogeneity between cohorts.Conclusion and relevanceWe identify specific and different patterns of association between PGS for the three phenotypes and core and associated autism features. This provides greater resolution into the shared genetics between autism and the three phenotypes, and suggests one method to investigate heterogeneity in autism and co-occurring conditions.

Published
2021

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

Author

Meng-Chuan Lai, Elena Maria Busuoli, Antonio M. Persico, Bonnie Auyeung, Eva Loth, Sarah Durston, Andreas Meyer-Lindenberg, Sven Bölte, Carolin Moessnang, Stavros Trakoshis, Marianne Oldehinkel, Prantik Kundu, Steve C.R. Williams, Jan K. Buitelaar, Sarah Baumeister, Tony Charman, Michael V. Lombardo, Isotta Landi, Richard A. I. Bethlehem, Rosemary Holt, Veronica Mandelli, Christine Ecker, Natasha Bertelsen, Julian Tillmann, Declan G. Murphy, Christian F. Beckmann, Jakob Seidlitz, Eleonora Satta, Mark H. Johnson, Will Spooren, Simon Baron-Cohen, Guillaume Dumas, Luke Mason, Emily J.H. Jones, Thomas Bourgeron, Istituto Italiano di Tecnologia (IIT), University of Trento [Trento], University of Cambridge [UK] (CAM), Children’s Hospital of Philadelphia (CHOP ), University of Pennsylvania, University of Cyprus [Nicosia] (UCY), University of Edinburgh, King‘s College London, Génétique humaine et fonctions cognitives - Human Genetics and Cognitive Functions (GHFC (UMR_3571 / U-Pasteur_1)), Institut Pasteur [Paris] (IP)-Centre National de la Recherche Scientifique (CNRS)-Université Paris Cité (UPCité), Universität Heidelberg [Heidelberg] = Heidelberg University, Radboud University Medical Center [Nijmegen], Karolinska Institutet [Stockholm], Stockholm Health Care Services (SLSO), Curtin University [Perth], Planning and Transport Research Centre (PATREC), University Medical Center [Utrecht], Goethe-Universität Frankfurt am Main, University of London [London], Monash University [Melbourne], University of Messina, Università Campus Bio-Medico di Roma / University Campus Bio-Medico of Rome ( UCBM), University of Vienna [Vienna], Roche Pharma Research and Early Development [Basel] (pRED), F. Hoffmann-La Roche [Basel], Centre for Addiction and Mental Health [Toronto] (CAMH), The Hospital for sick children [Toronto] (SickKids), University of Toronto, National Taiwan University [Taiwan] (NTU), This project has received funding from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme under grant agreement No 755816 (ERC Starting Grant to MVL). This work was also supported by EU-AIMS and EU AIMS-2-TRIALS, which both received support from the Innovative Medicines Initiative Joint Undertaking under Grant Agreement No. 115300 and the Innovative Medicines Initiative 2 Joint Undertaking under Grant Agreement No. 777394, the resources of which are composed of financial contributions from the European Union’s Seventh Framework Programme (Grant No. FP7/2007–2013), from the European Federation of Pharmaceutical Industries and Associations companies’ in-kind contributions, and from Autism Speaks, Autistica and the Simons Foundation for Autism Research Initiative. The views expressed are those of the author(s) and not necessarily those of the IMI 2JU. This work was also supported by the Netherlands Organization for Scientific Research through Vidi grants (Grant No. 864.12.003 [to CFB]), from the FP7 (Grant Nos. 602805) (AGGRESSOTYPE) (to JKB), 603016 (MATRICS), and 278948 (TACTICS), and from the European Community’s Horizon 2020 Programme (H2020/2014–2020) (Grant Nos. 643051 [MiND] and 642996 (BRAINVIEW). This work received funding from the Wellcome Trust UK Strategic Award (Award No. 098369/Z/12/Z) and from the National Institute for Health Research Maudsley Biomedical Research Centre (to DGMM). M-CL was supported by the Academic Scholars Award from the Department of Psychiatry, University of Toronto, the Slaight Family Child and Youth Mental Health Innovation Fund from the CAMH Foundation, the Ontario Brain Institute via the Province of Ontario Neurodevelopmental Disorders (POND) Network (IDS-I l-02), the Canadian Institutes of Health Research Sex and Gender Science Chair (GSB 171373), and the Innovation Fund of the Alternative Funding Plan for the Academic Health Sciences Centres of Ontario (CAM-20-004). R.A.I.B acknowledges research support by the Autism Research Trust and a British Academy Fellowship (PF2\180017). MHJ, TC, and EJHJ acknowledge support from a UK MRC Programme Grant., the EU-AIMS LEAP group : Jumana Ahmad, Sara Ambrosino, Bonnie Auyeung, Tobias Banaschewski, Simon Baron-Cohen, Sarah Baumeister, Christian F. Beckmann, Sven Bölte, Thomas Bourgeron, Carsten Bours, Michael Brammer, Daniel Brandeis, Claudia Brogna, Yvette de Bruijn, Jan K. Buitelaar, Bhismadev Chakrabarti, Tony Charman, Chris Chatham, Ineke Cornelissen, Daisy Crawley, Flavio Dell’Acqua, Guillaume Dumas, Sarah Durston, Christine Ecker, Jessica Faulkner, Vincent Frouin, Pilar Garcés, David Goyard, Lindsay Ham, Hannah Hayward, Joerg Hipp, Rosemary J. Holt, Mark H. Johnson, Emily J. H. Jones, Prantik Kundu, Meng-Chuan Lai, Xavier Liogier D’ardhuy, Michael V. Lombardo, Eva Loth, David J. Lythgoe, René Mandl, Andre Marquand, Luke Mason, Maarten Mennes, Andreas Meyer-Lindenberg, Carolin Moessnang, Nico Mueller, Declan G. M. Murphy, Bethany Oakley, Laurence O’Dwyer, Marianne Oldehinkel, Bob Oranje, Gahan Pandina, Antonio M. Persico, Barbara Ruggeri, Amber N. V. Ruigrok, Jessica Sabet, Roberto Sacco, Antonia San José Cáceres, Emily Simonoff, Will Spooren, Julian Tillmann, Roberto Toro, Heike Tost, Jack Waldman, Steve C. R. Williams, Caroline Wooldridge & Marcel P. Zwiers, European Project: 0755816(2008), European Project: 115300,EC:FP7:SP1-JTI,IMI-JU-03-2010,EU-AIMS(2012), European Project: 602805,EC:FP7:HEALTH,FP7-HEALTH-2013-INNOVATION-1,AGGRESSOTYPE(2013), European Project: 603016,EC:FP7:HEALTH,FP7-HEALTH-2013-INNOVATION-1,MATRICS(2014), European Project: 278948,EC:FP7:HEALTH,FP7-HEALTH-2011-two-stage,TACTICS(2012), European Project: 643051,H2020,H2020-MSCA-ITN-2014,MiND(2015), European Project: 642996,H2020,H2020-MSCA-ITN-2014,BRAINVIEW(2015), University of Pennsylvania [Philadelphia], University of Cyprus (UCY), Institut Pasteur [Paris]-Centre National de la Recherche Scientifique (CNRS)-Université de Paris (UP), Universität Heidelberg [Heidelberg], Bethlehem, Richard A I [0000-0002-0714-0685], Seidlitz, Jakob [0000-0002-8164-7476], Bourgeron, Thomas [0000-0001-8164-9220], Charman, Tony [0000-0003-1993-6549], Persico, Antonio M [0000-0001-8910-4479], Lombardo, Michael V [0000-0001-6780-8619], Apollo - University of Cambridge Repository, and Bethlehem, Richard AI [0000-0002-0714-0685]

Subjects
Male, 0301 basic medicine, Autism Spectrum Disorder, Stress-related disorders Donders Center for Medical Neuroscience [Radboudumc 13], Medicine (miscellaneous), MESH: Magnetic Resonance Imaging, 0302 clinical medicine, 130 000 Cognitive Neurology & Memory, MESH: Child, Neural Pathways, Biology (General), Child, MESH: Autism Spectrum Disorder, MESH: Child Behavior Disorders, Communication, 220 Statistical Imaging Neuroscience, Hyperconnectivity, Autism spectrum disorders, Magnetic Resonance Imaging, Autism spectrum disorder, Female, MESH: Communication, General Agricultural and Biological Sciences, MESH: Stereotyped Behavior, QH301-705.5, autism spectrum disorders, Child Behavior Disorders, Biology, Article, General Biochemistry, Genetics and Molecular Biology, 03 medical and health sciences, All institutes and research themes of the Radboud University Medical Center, Neuroimaging, mental disorders, medicine, Biological neural network, Humans, Association (psychology), MESH: Neurodevelopmental Disorders, Neurodevelopmental disorders Donders Center for Medical Neuroscience [Radboudumc 7], MESH: Humans, Resting state fMRI, Genetic heterogeneity, MESH: Neural Pathways, [SCCO.NEUR]Cognitive science/Neuroscience, medicine.disease, MESH: Male, 030104 developmental biology, Neurodevelopmental Disorders, Autism, Stereotyped Behavior, Neuroscience, MESH: Female, 030217 neurology & neurosurgery
Abstract

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

Published
2021

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

Author

Tillmann, Julian, San José Cáceres, Antonia, Chatham, Chris H., Crawley, Daisy, Holt, Rosemary, Oakley, Bethany, Banaschewski, Tobias, Baron-Cohen, Simon, Bölte, Sven, Buitelaar, Jan K., Durston, Sarah, Ham, Lindsay, Loth, Eva, Simonoff, Emily, Spooren, Will, Murphy, Declan G., Charman, Tony, Ahmad, Jumana, Ambrosino, Sara, Auyeung, Bonnie, Baumeister, Sarah, Beckmann, Christian, Bourgeron, Thomas, Bours, Carsten, Brammer, Michael, Brandeis, Daniel, Brogna, Claudia, de Bruijn, Yvette, Chakrabarti, Bhismadev, Cornelissen, Ineke, Dell’ Acqua, Flavio, Dumas, Guillaume, Ecker, Christine, Faulkner, Jessica, Frouin, Vincent, Garcés, Pilar, Goyard, David, Hayward, Hannah, Hipp, Joerg, Johnson, Mark H., Jones, Emily J. H., Kundu, Prantik, Lai, Meng-Chuan, D'Ardhuy, Xavier Liogier, Lombardo, Michael, Lythgoe, David J., Mandl, René, Mason, Luke, Meyer-Lindenberg, Andreas, Moessnang, Carolin, Mueller, Nico, O'Dwyer, Laurence, Oldehinkel, Marianne, Oranje, Bob, Pandina, Gahan, Persico, Antonio M., Ruggeri, Barbara, Ruigrok, Amber, Sabet, Jessica, Sacco, Roberto, Toro, Roberto, Tost, Heike, Waldman, Jack, Williams, Steve C. R., Wooldridge, Caroline, Zwiers, Marcel P., Institute of Psychiatry, Psychology & Neuroscience, King's College London, King‘s College London, University of Vienna [Vienna], F. Hoffmann-La Roche [Basel], University of Cambridge [UK] (CAM), Department of Child and Adolescent Psychiatry and Psychotherapy [Mannheim], Universität Heidelberg [Heidelberg] = Heidelberg University, Central Institute of Mental Health [Mannheim], University Hospital Mannheim | Universitätsmedizin Mannheim, Karolinska Institutet [Stockholm], Donders Institute for Brain, Cognition and Behaviour, Radboud University [Nijmegen], Stockholm County Council, University Medical Center [Utrecht], Karakter Child and Adolescent Psychiatry University Centre [Nijmegen], South London and Maudsley NHS Foundation Trust, This work was supported by EU‐AIMS (European Autism Interventions), which receives support from the Innovative Medicines Initiative Joint Undertaking under grant agreement no. 115300, the resources of which are composed of financial contributions from the European Union's Seventh Framework Programme (grant FP7/2007‐2013), from the European Federation of Pharmaceutical Industries and Associations companies' in‐kind contributions, and from Autism Speaks, The EU‐AIMS LEAP group : Jumana Ahmad, Sara Ambrosino, Bonnie Auyeung, Sarah Baumeister, Christian Beckmann, Thomas Bourgeron, Carsten Bours, Michael Brammer, Daniel Brandeis, Claudia Brogna, Yvette de Bruijn, Bhismadev Chakrabarti, Ineke Cornelissen, Flavio Dell’ Acqua, Guillaume Dumas, Christine Ecker, Jessica Faulkner, Vincent Frouin, Pilar Garcés, David Goyard, Hannah Hayward, Joerg Hipp, Mark H. Johnson, Emily J.H. Jones, Prantik Kundu, Meng‐Chuan Lai, Xavier Liogier D'ardhuy, Michael Lombardo, David J. Lythgoe, René Mandl, Luke Mason, Andreas Meyer‐Lindenberg, Carolin Moessnang, Nico Mueller, Laurence O'Dwyer, Marianne Oldehinkel, Bob Oranje, Gahan Pandina, Antonio M. Persico, Barbara Ruggeri, Amber Ruigrok, Jessica Sabet, Roberto Sacco, Roberto Toro, Heike Tost, Jack Waldman, Steve C.R. Williams, Caroline Wooldridge, and Marcel P. Zwiers., We thank all participants and their families for their efforts to participate in the study., European Project: 115300,EC:FP7:SP1-JTI,IMI-JU-03-2010,EU-AIMS(2012), Universität Heidelberg [Heidelberg], Medical Faculty [Mannheim], Radboud university [Nijmegen], Tillmann, Julian [0000-0001-9574-9855], Bölte, Sven [0000-0002-4579-4970], Charman, Tony [0000-0003-1993-6549], and Apollo - University of Cambridge Repository

Subjects
Male, Intelligence, Psychological intervention, Severity of Illness Index, Cohort Studies, 0302 clinical medicine, Borderline intellectual functioning, Activities of Daily Living, Psychology, Longitudinal Studies, Child, Genetics (clinical), Research Articles, Adaptive behavior, General Neuroscience, 05 social sciences, Age Factors, Cognition, Europe, symptom severity, Phenotype, Autism spectrum disorder, Cohort, Anxiety, Female, medicine.symptom, adaptive functioning, autism spectrum disorder, intellectual functioning, psychiatric symptoms, Neuroscience (all), Neurology (clinical), 050104 developmental & child psychology, Clinical psychology, Research Article, Adult, Adolescent, 03 medical and health sciences, Young Adult, Sex Factors, mental disorders, medicine, Humans, 0501 psychology and cognitive sciences, Neurodevelopmental disorders Donders Center for Medical Neuroscience [Radboudumc 7], medicine.disease, [SDV.MHEP.PSM]Life Sciences [q-bio]/Human health and pathology/Psychiatrics and mental health, Autism, 030217 neurology & neurosurgery
Abstract

Contains fulltext : 204820.pdf (Publisher’s version ) (Closed access) 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. (c) 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.

Published
2019

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