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1. Predicting depression onset in young people based on clinical, cognitive, environmental, and neurobiological data

Author

Yara J. Toenders, Akhil Kottaram, Richard Dinga, Christopher G. Davey, Tobias Banaschewski, Arun L.W. Bokde, Erin Burke Quinlan, Sylvane Desrivières, Herta Flor, Antoine Grigis, Hugh Garavan, Penny Gowland, Andreas Heinz, Rüdiger Brühl, Jean-Luc Martinot, Marie-Laure Paillère Martinot, Frauke Nees, Dimitri Papadopoulos Orfanos, Herve Lemaitre, Tomáš Paus, Luise Poustka, Sarah Hohmann, Juliane H. Fröhner, Michael N. Smolka, Henrik Walter, Robert Whelan, Argyris Stringaris, Betteke van Noort, Jani Penttilä, Yvonne Grimmer, Corinna Insensee, Andreas Becker, Gunter Schumann, Lianne Schmaal, Developmental Neuroscience in Society, University of Melbourne, Radboud University [Nijmegen], Heidelberg University, Trinity College Dublin, King‘s College London, Universität Mannheim, 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), University of Vermont [Burlington], University of Nottingham, UK (UON), Charité - UniversitätsMedizin = Charité - University Hospital [Berlin], Physikalisch-Technische Bundesanstalt [Braunschweig] (PTB), Trajectoires Développementales en Psychiatrie [Paris], Université Paris Descartes - Paris 5 (UPD5)-PRES Sorbonne Paris Cité-Institut National de la Santé et de la Recherche Médicale (INSERM), CB - Centre Borelli - UMR 9010 (CB), Service de Santé des Armées-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Ecole Normale Supérieure Paris-Saclay (ENS Paris Saclay)-Université Paris Cité (UPCité), CHU Pitié-Salpêtrière [AP-HP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU), Kiel University, Institut des Maladies Neurodégénératives [Bordeaux] (IMN), Université de Bordeaux (UB)-Centre National de la Recherche Scientifique (CNRS), University of Toronto, University Medical Center Göttingen (UMG), Technische Universität Dresden = Dresden University of Technology (TU Dresden), National Institute of Mental Health (NIMH), Leibniz Institute for Neurobiology [Magdeburg] (LIN), Fudan University [Shanghai], This work was supported by the MQ Brighter Futures Award (MQBFC/2 [to LS]), the National Institute of Mental Health of the National Institutes of Health (Award Number R01MH117601 [to LS]), a National Health and Medical Research Council (NHMRC) Career Development Fellowship (1140764 [to LS]), the Dame Kate Campbell Fellowship from the Faculty of Medicine, Dentistry and Health Sciences at The University of Melbourne, and an NHMRC Career Development Award (141738 [to CGD]).This work received support from the following sources: the European Union–funded FP6 Integrated Project IMAGEN (Reinforcement-related behavior in normal brain function and psychopathology) (LSHM-CT-2007-037286), the Horizon 2020–funded ERC Advanced Grant 'STRATIFY' (Brain network based stratification of reinforcement-related disorders) (695313), Human Brain Project (HBP SGA 2, 785907, and HBP SGA 3, 945539), the Medical Research Council Grant 'c-VEDA' (Consortium on Vulnerability to Externalizing Disorders and Addictions) (MR/N000390/1), the National Institutes of Health (NIH) (R01DA049238, A decentralized macro and micro gene-by-environment interaction analysis of substance use behavior and its brain biomarkers), the National Institute for Health Research Biomedical Research Centre at South London and Maudsley NHS Foundation Trust and King’s College London, the Bundesministerium für Bildung und Forschung (BMBF Grant Nos. 01GS08152, 01EV0711, Forschungsnetz AERIAL 01EE1406A, 01EE1406B, Forschungsnetz IMAC-Mind 01GL1745B), the Deutsche Forschungsgemeinschaft (DFG Grant Nos. SM 80/7-2, SFB 940, TRR 265, NE 1383/14-1), the Medical Research Foundation and Medical Research Council (Grant Nos. MR/R00465X/1 and MR/S020306/1), and the NIH-funded ENIGMA (Grant Nos. 5U54EB020403-05 and 1R56AG058854-01). Further support was provided by grants from the ANR (ANR-12-SAMA-0004, AAPG2019 – GeBra), the Eranet Neuron (AF12-NEUR0008-01 – WM2NA, and ANR-18-NEUR00002-01 – ADORe), the Fondation de France (00081242), the Fondation pour la Recherche Médicale (DPA20140629802), the Mission Interministérielle de Lutte-contre-les-Drogues-et-les-Conduites-Addictives (MILDECA), the Assistance-Publique-Hôpitaux-de-Paris and INSERM (interface grant), Paris Sud University IDEX 2012, the Fondation de l’Avenir (grant AP-RM-17-013), the Fédération pour la Recherche sur le Cerveau, the National Institutes of Health, Science Foundation Ireland (16/ERCD/3797), USA (Axon, Testosterone and Mental Health during Adolescence, RO1 MH085772-01A1), and by NIH Consortium grant U54 EB020403, supported by a cross-NIH alliance that funds Big Data to Knowledge Centres of Excellence., Project IMAGEN, Human Brain Project, ANR-12-SAMA-0004,ADODEP,Dépression à l'Adolescence: Structure cérébrale et myélinisation(2012), and ANR-18-NEUR-0002,ADORe,TARGETING ADOLESCENT NEUROCOGNITIVE PROCESSES IN DEPRESSION TO PROMOTE INTERVENTION RESPONSE(2018)

Subjects
Longitudinal study, Adolescent, Cognitive Neuroscience, MESH: Cognition, Major depressive disorder, Logistic regression, Adolescents, 050105 experimental psychology, 03 medical and health sciences, 0302 clinical medicine, Cognition, MESH: Risk Factors, Risk Factors, Machine learning, medicine, Humans, 0501 psychology and cognitive sciences, Radiology, Nuclear Medicine and imaging, Longitudinal Studies, Big Five personality traits, MESH: Longitudinal Studies, Biological Psychiatry, Depression (differential diagnoses), MESH: Adolescent, Depressive Disorder, Major, MESH: Humans, Receiver operating characteristic, business.industry, Depression, 05 social sciences, MESH: Depression / psychology, medicine.disease, Neuroticism, Penalized logistic regression, [SDV.NEU]Life Sciences [q-bio]/Neurons and Cognition [q-bio.NC], Female, Neurology (clinical), MESH: Depressive Disorder, Major* / diagnosis, business, Prediction, MESH: Female, 030217 neurology & neurosurgery, [SDV.MHEP]Life Sciences [q-bio]/Human health and pathology, Clinical psychology
Abstract

BackgroundAdolescent onset of depression is associated with long-lasting negative consequences. Identifying adolescents at risk for developing depression would enable the monitoring of risk factors and the development of early intervention strategies. Using machine learning to combine several risk factors from multiple modalities might allow prediction of depression onset at the individual level. MethodsA subsample of a multisite longitudinal study in adolescents, the IMAGEN study, was used to predict future (subthreshold) major depressive disorder onset in healthy adolescents. Based on 2-year and 5-year follow-up data, participants were grouped into the following: 1) those developing a diagnosis of major depressive disorder or subthreshold major depressive disorder and 2) healthy control subjects. Baseline measurements of 145 variables from different modalities (clinical, cognitive, environmental, and structural magnetic resonance imaging) at age 14 years were used as input to penalized logistic regression (with different levels of penalization) to predict depression onset in a training dataset (n = 407). The features contributing the highest to the prediction were validated in an independent hold-out sample (three independent IMAGEN sites; n = 137). ResultsThe area under the receiver operating characteristic curve for predicting depression onset ranged between 0.70 and 0.72 in the training dataset. Baseline severity of depressive symptoms, female sex, neuroticism, stressful life events, and surface area of the supramarginal gyrus contributed most to the predictive model and predicted onset of depression, with an area under the receiver operating characteristic curve between 0.68 and 0.72 in the independent validation sample. ConclusionsThis study showed that depression onset in adolescents can be predicted based on a combination multimodal data of clinical characteristics, life events, personality traits, and brain structure variables.

Published
2022
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2. Functional Connectivity Predicts Individual Development of Inhibitory Control during Adolescence

Author

Robert Whelan, Luise Poustka, Lingzhong Fan, Henrik Walter, Sylvane Desrivières, Arun L.W. Bokde, Erin Burke Quinlan, Bader Chaarani, Dongya Wu, Bing Liu, Gunter Schumann, Herta Flor, Haiyan Wang, Bernd Ittermann, Jin Li, Hugh Garavan, Marie-Laure Paillère Martinot, Antoine Grigis, Juliane H. Fröhner, Jean-Luc Martinot, Dimitri Papadopoulos Orfanos, Tianzi Jiang, Ming Song, Eric Artiges, Tobias Banaschewski, Penny A. Gowland, Ang Li, Rongtao Jiang, Michael N. Smolka, Frauke Nees, Sabina Millenet, and Andreas Heinz

Subjects
Male, Adolescent, Cognitive Neuroscience, Psychological intervention, Stop signal, Young Adult, 03 medical and health sciences, Cellular and Molecular Neuroscience, 0302 clinical medicine, Neural Pathways, Inhibitory control, Reaction Time, medicine, Humans, Longitudinal Studies, 030304 developmental biology, 0303 health sciences, medicine.diagnostic_test, Functional Neuroimaging, Functional connectivity, Brain, Individual development, Adolescent Development, medicine.disease, Magnetic Resonance Imaging, Substance abuse, Inhibition, Psychological, Biological Variation, Population, Female, Original Article, Psychology, Functional magnetic resonance imaging, 030217 neurology & neurosurgery, Predictive modelling, Cognitive psychology
Abstract

Derailment of inhibitory control (IC) underlies numerous psychiatric and behavioral disorders, many of which emerge during adolescence. Identifying reliable predictive biomarkers that place the adolescents at elevated risk for future IC deficits can help guide early interventions, yet the scarcity of longitudinal research has hindered the progress. Here, using a large-scale longitudinal dataset in which the same subjects performed a stop signal task during functional magnetic resonance imaging at ages 14 and 19, we tracked their IC development individually and tried to find the brain features predicting their development by constructing prediction models using 14-year-olds’ functional connections within a network or between a pair of networks. The participants had distinct between-subject trajectories in their IC development. Of the candidate connections used for prediction, ventral attention-subcortical network interconnections could predict the individual development of IC and formed a prediction model that generalized to previously unseen individuals. Furthermore, we found that connectivity between these two networks was related to substance abuse problems, an IC-deficit related problematic behavior, within 5 years. Our study reveals individual differences in IC development from mid- to late-adolescence and highlights the importance of ventral attention-subcortical network interconnections in predicting future IC development and substance abuse in adolescents.

Published
2020
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3. Neurobehavioural characterisation and stratification of reinforcement-related behaviour

Author

Alex Ing, Luise Poustka, Erin Burke Quinlan, Frauke Nees, Tianye Jia, Andreas Heinz, Bernd Ittermann, Biondo Francesca, Michael N. Smolka, Sylvane Desrivières, Tobias Banaschewski, Arun L.W. Bokde, Robert Whelan, Henrik Walter, Jianfeng Feng, Gareth J. Barker, Tomáš Paus, Qiang Luo, Jean-Luc Martinot, Uli Bromberg, Marie-Laure Paillère Martinot, Juliane H. Fröhner, Hugh Garavan, Nicole Tay, Penny A. Gowland, Dimitri Papadopoulos Orfanos, Herta Flor, Antoine Grigis, Christian Büchel, and Gunter Schumann

Subjects
Male, Elementary cognitive task, Adolescent, Social Psychology, Experimental and Cognitive Psychology, Emotional processing, Impulsivity, Developmental psychology, Reward processing, Functional brain, 03 medical and health sciences, Behavioral Neuroscience, Cognition, 0302 clinical medicine, Reward, Neuroimaging, Functional neuroimaging, medicine, Humans, Attention, Child, Reinforcement, 030304 developmental biology, 0303 health sciences, Facial expression, Functional Neuroimaging, Brain, Anticipation, Psychological, medicine.disease, Magnetic Resonance Imaging, Comorbidity, Anticipation, Facial Expression, Impulsive Behavior, Female, Nerve Net, medicine.symptom, Psychology, Reinforcement, Psychology, 030217 neurology & neurosurgery, Cognitive psychology
Abstract

Reinforcement-related cognitive processes, such as reward processing, inhibitory control and social–emotional regulation are critical components of externalising and internalising behaviours. It is unclear to what extent the deficit in each of these processes contributes to individual behavioural symptoms, how their neural substrates give rise to distinct behavioural outcomes and whether neural activation profiles across different reinforcement-related processes might differentiate individual behaviours. We created a statistical framework that enabled us to directly compare functional brain activation during reward anticipation, motor inhibition and viewing emotional faces in the European IMAGEN cohort of 2,000 14-year-old adolescents. We observe significant correlations and modulation of reward anticipation and motor inhibition networks in hyperactivity, impulsivity, inattentive behaviour and conduct symptoms, and we describe neural signatures across cognitive tasks that differentiate these behaviours. We thus characterise shared and distinct functional brain activation patterns underling different externalising symptoms and identify neural stratification markers, while accounting for clinically observed comorbidity. On the basis of the IMAGEN database of 2,000 Caucasian adolescents, Jia et al identify neural patterns of activity during reward anticipation and motor inhibition associated with different externalising symptoms for ADHD and conduct problems.

Published
2020
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4. Examination of the neural basis of psychotic-like experiences in adolescence during processing of emotional faces

Author

Sabina Millenet, Andreas Heinz, Sylvane Desrivières, Hugh Garavan, Philip A. Spechler, Arun L.W. Bokde, Robert Whelan, Celia Boussebaa, Gunter Schumann, Christian Büchel, Henrik Walter, Evangelos Papanastasiou, Penny A. Gowland, Sukhwinder S. Shergill, Marie-Laure Paillère Martinot, Michael N. Smolka, Tobias Banaschewski, Herta Flor, Antoine Grigis, Juliane H. Fröhner, Bernd Ittermann, Luise Poustka, Frauke Nees, Tomáš Paus, Elias Mouchlianitis, Dimitri Papadopoulos Orfanos, Dan W. Joyce, Erin Burke Quinlan, Philip McGuire, and Eric Artiges

Subjects
Male, Psychosis, Adolescent, Databases, Factual, media_common.quotation_subject, medicine.medical_treatment, Emotions, lcsh:Medicine, Amygdala, behavioral disciplines and activities, Article, 03 medical and health sciences, Young Adult, 0302 clinical medicine, Perception, Human behaviour, medicine, Humans, Young adult, 10. No inequality, Antipsychotic, lcsh:Science, media_common, Cerebral Cortex, Facial expression, Multidisciplinary, lcsh:R, Right insula, Brain, Cognitive neuroscience, Diagnostic markers, medicine.disease, Magnetic Resonance Imaging, 030227 psychiatry, Facial Expression, medicine.anatomical_structure, Psychotic Disorders, nervous system, Female, lcsh:Q, Psychology, Insula, 030217 neurology & neurosurgery, psychological phenomena and processes, Clinical psychology
Abstract

Contemporary theories propose that dysregulation of emotional perception is involved in the aetiology of psychosis. 298 healthy adolescents were assessed at age 14- and 19-years using fMRI while performing a facial emotion task. Psychotic-like experiences (PLEs) were assessed with the CAPE-42 questionnaire at age 19. The high PLEs group at age 19 years exhibited an enhanced response in right insular cortex and decreased response in right prefrontal, right parahippocampal and left striatal regions; also, a gradient of decreasing response to emotional faces with age, from 14 to 19 years, in the right parahippocampal region and left insular cortical area. The right insula demonstrated an increasing response to emotional faces with increasing age in the low PLEs group, and a decreasing response over time in the high PLEs group. The change in parahippocampal/amygdala and insula responses during the perception of emotional faces in adolescents with high PLEs between the ages of 14 and 19 suggests a potential ‘aberrant’ neurodevelopmental trajectory for critical limbic areas. Our findings emphasize the role of the frontal and limbic areas in the aetiology of psychotic symptoms, in subjects without the illness phenotype and the confounds introduced by antipsychotic medication.

Published
2020
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5. Immune-Related Genetic Overlap Between Regional Gray Matter Reductions and Psychiatric Symptoms in Adolescents, and Gene-Set Validation in a Translational Model

Author

Lukas Penninck, El Chérif Ibrahim, Eric Artiges, Victor Gorgievski, Sylvane Desrivières, Severine Farley, Irina Filippi, Carlos E. A. de Macedo, Raoul Belzeaux, Tobias Banaschewski, Arun L. W. Bokde, Erin Burke Quinlan, Herta Flor, Antoine Grigis, Hugh Garavan, Penny Gowland, Andreas Heinz, Rüdiger Brühl, Frauke Nees, Dimitri Papadopoulos Orfanos, Tomáš Paus, Luise Poustka, Juliane H. Fröhner, Michael N. Smolka, Henrik Walter, Robert Whelan, Julien Grenier, Gunter Schumann, Marie-Laure Paillère Martinot, Eleni T. Tzavara, Jean-Luc Martinot, for the IMAGEN Consortium, INSERM U1299 'Trajectoires développementales en Psychiatrie', Institut de Neurosciences de la Timone (INT), Aix Marseille Université (AMU)-Centre National de la Recherche Scientifique (CNRS), Centre Neurosciences intégratives et Cognition (INCC - UMR 8002), Centre National de la Recherche Scientifique (CNRS)-Université Paris Cité (UPCité), King‘s College London, Département Universitaire de Psychiatrie - [Hôpital Sainte Marguerite - APHM] (Hôpitaux Sud), Aix Marseille Université (AMU)-Assistance Publique - Hôpitaux de Marseille (APHM)-Hôpital Sainte-Marguerite [CHU - APHM] (Hôpitaux Sud ), Universität Heidelberg [Heidelberg] = Heidelberg University, Department of Child and Adolescent Psychiatry and Psychotherapy [Mannheim], Institute of Cognitive and Clinical Neuroscience, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Trinity College Dublin, 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), University of Vermont [Burlington], Sir Peter Mansfield Magnetic Resonance Centre [Nottingham], University of Nottingham, UK (UON), Medizinische Universität Wien = Medical University of Vienna, Physikalisch-Technische Bundesanstalt [Braunschweig] (PTB), Institute of Medical Psychology and Medical Sociology, Christian-Albrechts-University of Kiel, Germany., Université du Québec à Montréal = University of Québec in Montréal (UQAM), Georg-August-University = Georg-August-Universität Göttingen, Technische Universität Dresden = Dresden University of Technology (TU Dresden), Charité - UniversitätsMedizin = Charité - University Hospital [Berlin], Toxicité environnementale, cibles thérapeutiques, signalisation cellulaire (T3S - UMR_S 1124), Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Université Paris Cité (UPCité), ANR-12-SAMA-0004,ADODEP,Dépression à l'Adolescence: Structure cérébrale et myélinisation(2012), ANR-19-NEUR-0005,ANTaRES,Biomarkers of ANTidepressant RESponse : early indicators and novel targets(2019), ANR-18-NEUR-0002,ADORe,TARGETING ADOLESCENT NEUROCOGNITIVE PROCESSES IN DEPRESSION TO PROMOTE INTERVENTION RESPONSE(2018), European Project: SFRH/BPD/11566/2002,FCT::Pós-Doutoramento,SFRH/2002,SFRH/BPD/11566/2002(2003), Ibrahim, El Chérif, Santé Mentale et Addictions - Dépression à l'Adolescence: Structure cérébrale et myélinisation - - ADODEP2012 - ANR-12-SAMA-0004 - SAMENTA - VALID, Biomarkers of ANTidepressant RESponse : early indicators and novel targets - - ANTaRES2019 - ANR-19-NEUR-0005 - ERAnet NEURON - VALID, ERANET NEURON - TARGETING ADOLESCENT NEUROCOGNITIVE PROCESSES IN DEPRESSION TO PROMOTE INTERVENTION RESPONSE - - ADORe2018 - ANR-18-NEUR-0002 - ERAnet NEURON - VALID, APLICAÇÃO DE CONTADORES GASOSOS NA DETECÇÃO DE RAIOS X RESULTANTES DO DECAIMENTO DE ESTADOS EXCITADOS DE ÁTOMOS EXÓTICOS-II - SFRH/BPD/11566/2002 - - FCT::Pós-Doutoramento2003-05-01 - 9999-12-31 - SFRH/BPD/11566/2002 - VALID, Universität Heidelberg [Heidelberg], INSERM U1299 'Trajectoires développementales et Psychiatrie', Centre National de la Recherche Scientifique (CNRS)-Université de Paris (UP), Institute of Psychiatry, Psychology & Neuroscience, King's College London, INSERM U1299 'Trajectoires développemebntales et Psychiatrie', Hôpital Sainte-Marguerite [CHU - APHM] (Hôpitaux Sud )-Assistance Publique - Hôpitaux de Marseille (APHM)-Aix Marseille Université (AMU), 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, Department of Psychiatry, University of Vermont, Burlington 05401, VT, USA, School of Physics and Astronomy, University of Birmingham, Department of Psychiatry and Psychotherapy [Berlin], Centre Hospitalier Universitaire Sainte-Justine [Montréal, Québec, Canada], Department of Child and Adolescent Psychiatry and Psychotherapy, University Medical Centre Göttingen, Department of Psychiatry and Neuroimaging Center, Technische Universität Dresden, Centre for Population Neuroscience and Precision Medicine (PONS), Institute of Psychiatry, Psychology & Neuroscience, King's College London, INSERM - Université de Paris. (INSERM UMRS 1124 - Université de Paris.), AP-HP. Department of Child and Adolescent Psychiatry, Pitié-Salpêtrière Hospital, Fondation FondaMental [Créteil], CHU Sainte Justine [Montréal], Université Paris Cité (UPCité), CHU Pitié-Salpêtrière [AP-HP], and Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)

Subjects
medicine.medical_specialty, [SDV.IB.IMA]Life Sciences [q-bio]/Bioengineering/Imaging, Cognitive Neuroscience, [SDV]Life Sciences [q-bio], [SDV.MHEP.PSM] Life Sciences [q-bio]/Human health and pathology/Psychiatrics and mental health, childhood maltreatment, Neuroscience (miscellaneous), Single-nucleotide polymorphism, Neurosciences. Biological psychiatry. Neuropsychiatry, 03 medical and health sciences, Cellular and Molecular Neuroscience, 0302 clinical medicine, Developmental Neuroscience, [SDV.BBM.GTP]Life Sciences [q-bio]/Biochemistry, Molecular Biology/Genomics [q-bio.GN], medicine, Bipolar disorder, Psychiatry, Prefrontal cortex, Depression (differential diagnoses), immunity genes, Original Research, 030304 developmental biology, 0303 health sciences, business.industry, medicine.disease, 3. Good health, [SDV] Life Sciences [q-bio], psychiatric symptoms, [SDV.IB.IMA] Life Sciences [q-bio]/Bioengineering/Imaging, Mood disorders, Schizophrenia, [SDV.MHEP.PSM]Life Sciences [q-bio]/Human health and pathology/Psychiatrics and mental health, Etiology, [SDV.BBM.GTP] Life Sciences [q-bio]/Biochemistry, Molecular Biology/Genomics [q-bio.GN], Major depressive disorder, adolescence, business, 030217 neurology & neurosurgery, Neuroscience, MRI, RC321-571
Abstract

Adolescence is a period of vulnerability for the maturation of gray matter (GM) and also for the onset of psychiatric disorders such as major depressive disorder (MDD), bipolar disorder and schizophrenia. Chronic neuroinflammation is considered to play a role in the etiology of these illnesses. However, the involvement of neuroinflammation in the observed link between regional GM volume reductions and psychiatric symptoms is not established yet. Here, we investigated a possible common immune-related genetic link between these two phenomena in european adolescents recruited from the community. Hippocampal and medial prefrontal cortex (mPFC) were defined a priori as regions of interest (ROIs). Their GM volumes were extracted in 1,563 14-year-olds from the IMAGEN database. We found a set of 26 SNPs that correlated with the hippocampal volumes and 29 with the mPFC volumes at age 14. We formed two ROI-Related Immune-gene scores (RRI) with the inflammation SNPs that correlated to hippocampal GM volume and to mPFC GM volume. The predictive ability of both RRIs with regards to the presence of psychiatric symptoms at age 18 was investigated by correlating the RRIs with psychometric questionnaires obtained at age 18. The RRIs (but not control scores constructed with random SNPs) correlated with the presence of depressive symptoms, positive psychotic symptoms, and externalizing symptoms in later adolescence. In addition, the effect of childhood maltreatment, one of the major environmental risk factors for depression and other mental disorders, interacted with the RRI effect. We next sought to validate this finding by investigating our set of inflammatory genes in a translational animal model of early life adversity. Mice were subjected to a protocol of maternal separation at an early post-natal age. We evaluated depressive behaviors in separated and non-separated mice at adolescence and their correlations with the concomitant expression of our genes in whole blood samples. We show that in mice, early life adversity affected the expression of our set of genes in peripheral blood, and that levels of expression correlated with symptoms of negative affect in adolescence. Overall, our translational findings in adolescent mice and humans provide a novel validated gene-set of immune-related genes for further research in the early stages of mood disorders.

Published
2021
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6. Adolescent to young adult longitudinal development of subcortical volumes in two European sites with four waves

Author

Sticca F, Sylvane Desrivières, Lea L. Backhausen, MN Smolka, Herta Flor, Antoine Grigis, Tobias Banaschewski, Luise Poustka, Frauke Nees, J.L. Martinot, Eric Artiges, Robert Whelan, Ruediger Bruehl, P Gowland, Froehner Jh, Andreas Heinz, Megan M. Herting, Henrik Walter, Gareth J. Barker, Winterer J, G. Schumann, Hugh Garavan, Bokde Alw, Dimitri Papadopoulos-Orfanos, Lauren Robinson, Nora C. Vetter, Sarah Hohmann, Herve Lemaitre, and Marie-Laure Paillère-Martinot

Subjects
Brain development, 05 social sciences, 050105 experimental psychology, Developmental psychology, Longitudinal development, 03 medical and health sciences, Adolescent psychopathology, 0302 clinical medicine, 0501 psychology and cognitive sciences, Young adult, Psychology, 030217 neurology & neurosurgery, Psychopathology, Cohort study
Abstract

Adolescent subcortical structural brain development might underlie psychopathological symptoms, which often emerge in adolescence. At the same time, sex differences exist in psychopathology, which might be mirrored in underlying sex differences in structural development. However, previous studies showed inconsistencies in subcortical trajectories and potential sex differences. Therefore, we aimed to investigate the subcortical structural trajectories and their sex differences across adolescence using for the first time a single cohort design, the same quality control procedure, software and a general additive mixed modeling approach. We investigated two large European sites from ages 14 to 24 with 503 participants and 1408 total scans from France and Germany as part of the IMAGEN project including four waves of data acquisition. We found significantly larger volumes in males versus females in both sites and across all seven subcortical regions. Sex differences in age-related trajectories were observed across all regions in both sites. Our findings provide further evidence of sex differences in longitudinal adolescent brain development of subcortical regions and thus might eventually support the relationship of underlying brain development and different adolescent psychopathology in boys and girls.

Published
2021
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7. Association of Cannabis Use During Adolescence With Neurodevelopment

Author

Anthony C. Juliano, Alan C. Evans, Tomáš Paus, Frauke Nees, Deepak Cyril D'Souza, Tobias Banaschewski, Matthew D. Albaugh, Dimitri Papadopoulos Orfanos, Alexandra Potter, Seun Jeon, Max M. Owens, Amanda Sidwell, Bernd Ittermann, Nicholas R. Fontaine, Penny A. Gowland, Sylvane Desrivières, Jonatan Ottino-Gonzalez, Henrik Walter, Lindsay B. Lewis, Gunter Schumann, Arun L.W. Bokde, Hugh Garavan, Philip A. Spechler, Bader Chaarani, Claude Lepage, Juliane H. Fröhner, Luise Poustka, Herta Flor, Marie-Laure Paillère Martinot, Antoine Grigis, Jean-Luc Martinot, Erin Burke Quinlan, Pierre Rioux, Robert Whelan, Rajiv Radhakrishnan, Sabina Millenet, Michael N. Smolka, Andreas Heinz, and Patricia J. Conrod

Subjects
medicine.medical_specialty, medicine.medical_treatment, Audiology, Disease cluster, 03 medical and health sciences, 0302 clinical medicine, Neuroimaging, medicine, Online First, Association (psychology), Original Investigation, medicine.diagnostic_test, biology, business.industry, Research, Magnetic resonance imaging, Cannabis use, biology.organism_classification, 030227 psychiatry, Featured, Psychiatry and Mental health, Cannabinoid, Cannabis, business, 030217 neurology & neurosurgery, Comments, Cohort study
Abstract

Key Points Question To what extent is cannabis use associated with magnetic resonance imaging–measured cerebral cortical thickness development during adolescence? Findings In this cohort study, linear mixed-effects model analysis using 1598 magnetic resonance images from 799 participants revealed that cannabis use was associated with accelerated age-related cortical thinning from 14 to 19 years of age in predominantly prefrontal regions. The spatial pattern of cannabis-related cortical thinning was significantly associated with a positron emission tomography–assessed map of cannabinoid 1 receptor availability. Meaning Results suggest that cannabis use during middle to late adolescence may be associated with altered cerebral cortical development, particularly in regions rich in cannabinoid 1 receptors., Importance Animal studies have shown that the adolescent brain is sensitive to disruptions in endocannabinoid signaling, resulting in altered neurodevelopment and lasting behavioral effects. However, few studies have investigated ties between cannabis use and adolescent brain development in humans. Objective To examine the degree to which magnetic resonance (MR) imaging–assessed cerebral cortical thickness development is associated with cannabis use in a longitudinal sample of adolescents. Design, Setting, and Participants Data were obtained from the community-based IMAGEN cohort study, conducted across 8 European sites. Baseline data used in the present study were acquired from March 1, 2008, to December 31, 2011, and follow-up data were acquired from January 1, 2013, to December 31, 2016. A total of 799 IMAGEN participants were identified who reported being cannabis naive at study baseline and had behavioral and neuroimaging data available at baseline and 5-year follow-up. Statistical analysis was performed from October 1, 2019, to August 31, 2020. Main Outcomes and Measures Cannabis use was assessed at baseline and 5-year follow-up with the European School Survey Project on Alcohol and Other Drugs. Anatomical MR images were acquired with a 3-dimensional T1-weighted magnetization prepared gradient echo sequence. Quality-controlled native MR images were processed through the CIVET pipeline, version 2.1.0. Results The study evaluated 1598 MR images from 799 participants (450 female participants [56.3%]; mean [SD] age, 14.4 [0.4] years at baseline and 19.0 [0.7] years at follow-up). At 5-year follow-up, cannabis use (from 0 to >40 uses) was negatively associated with thickness in left prefrontal (peak: t785 = –4.87, cluster size = 1558 vertices; P = 1.10 × 10−6, random field theory cluster corrected) and right prefrontal (peak: t785 = –4.27, cluster size = 1551 vertices; P = 2.81 × 10−5, random field theory cluster corrected) cortices. There were no significant associations between lifetime cannabis use at 5-year follow-up and baseline cortical thickness, suggesting that the observed neuroanatomical differences did not precede initiation of cannabis use. Longitudinal analysis revealed that age-related cortical thinning was qualified by cannabis use in a dose-dependent fashion such that greater use, from baseline to follow-up, was associated with increased thinning in left prefrontal (peak: t815.27 = –4.24, cluster size = 3643 vertices; P = 2.28 × 10−8, random field theory cluster corrected) and right prefrontal (peak: t813.30 = –4.71, cluster size = 2675 vertices; P = 3.72 × 10−8, random field theory cluster corrected) cortices. The spatial pattern of cannabis-related thinning was associated with age-related thinning in this sample (r = 0.540; P, This cohort study examines the degree to which magnetic resonance imaging–assessed cerebral cortical thickness development is associated with cannabis use in a longitudinal sample of adolescents.

Published
2021

8. The bidirectional causal effects of brain morphology across the life course and risk of Alzheimers disease: A cross-cohort comparison and Mendelian randomization meta-analysis

Author

Elizabeth Coulthard, Robert Whelan, T. Sharp, Tomáš Paus, Laura D Howe, MN Smolka, J. Winterer, Henning Tiemeier, Herta Flor, Antoine Grigis, Esther Walton, Gunter Schumann, Tonya White, Alfie Wearn, Luise Poustka, Charlotte A.M. Cecil, Yoav Ben-Shlomo, B. Xu, L. Robinson, Sylvane Desrivières, Frauke Nees, J.L. Martinot, Henrik Walter, Arun L.W. Bokde, P Gowland, Roxanna Korologou-Linden, M.-L. Paillere Martinot, Emma L Anderson, Rüdiger Brühl, Erin Burke Quinlan, Andreas Heinz, Juliane H. Fröhner, E. Artiges, Tobias Banaschewski, D. Papadopoulos Orfanos, Gibran Hemani, Neil M Davies, and M. Sabina

Subjects
0303 health sciences, business.industry, Neurodegeneration, Brain morphometry, Disease, medicine.disease, 03 medical and health sciences, 0302 clinical medicine, Atrophy, Meta-analysis, Mendelian randomization, medicine, Young adult, business, Neuroscience, 030217 neurology & neurosurgery, 030304 developmental biology, Cognitive reserve
Abstract

Neuropathological changes associated with Alzheimers disease (AD) can occur decades before clinical symptoms. We investigated whether neurodevelopment and/or neurodegeneration affects the risk of AD, through reducing structural brain reserve and/or accelerating brain atrophy, respectively. We used bidirectional two-sample Mendelian randomization to estimate the effects of genetic liability to AD on global and regional cortical thickness, total intracranial volume, volume of subcortical structures and cerebral white matter in 36,842 participants aged eight to 81 years across five independent cohorts, and the effects of global and regional cortical thickness and subcortical volumes on AD risk in 94,337 participants. Our findings show that AD risk alleles have an age-dependent effect on a range of cortical and subcortical brain measures that starts in mid-life, in non-clinical populations. Evidence for such effects across childhood and young adulthood is weak. We also found little evidence to suggest brain morphology alters AD risk. Thus, genetic liability to AD is likely to alter mechanisms and/or rates of neurodegeneration, rather than reduce structural brain reserve.

Published
2021
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9. Orbitofrontal control of conduct problems? Evidence from healthy adolescents processing negative facial affect

Author

Henrik Walter, Frauke Nees, Sabina Millenet, Dimitri Papadopoulos Orfanos, Penny A. Gowland, Andreas Heinz, Eric Artiges, Juliane H. Fröhner, Bernd Ittermann, Boris William Böttinger, Erin Burke Quinlan, Luise Poustka, Daniel Brandeis, Tomáš Paus, Robert Whelan, Gareth J. Barker, Tobias Banaschewski, Jean-Luc Martinot, Michael N. Smolka, Sarah Baumeister, Hugh Garavan, Herta Flor, Antoine Grigis, Sylvane Desrivières, Arun L.W. Bokde, Gunter Schumann, Marie-Laure Paillère Martinot, Christian Büchel, Universität Heidelberg, Ecole des Neurosciences de Paris Île de France (ENP), and Ecole des Neurosciences de Paris

Subjects
Conduct Disorder, Male, medicine.medical_specialty, Adolescent, Prefrontal Cortex, Subclinical, Audiology, Adolescence, Conduct problems, Affective processing, Orbitofrontal cortex, FMRI, 03 medical and health sciences, Functional brain, 0302 clinical medicine, Linear regression, Developmental and Educational Psychology, Medicine, Humans, 0501 psychology and cognitive sciences, In patient, Subclinical infection, Problem Behavior, [SDV.MHEP.PED]Life Sciences [q-bio]/Human health and pathology/Pediatrics, Facial affect, [SDV.NEU.PC]Life Sciences [q-bio]/Neurons and Cognition [q-bio.NC]/Psychology and behavior, business.industry, 05 social sciences, Brain, General Medicine, Magnetic Resonance Imaging, Facial Expression, Psychiatry and Mental health, Multicenter study, [SDV.MHEP.PSM]Life Sciences [q-bio]/Human health and pathology/Psychiatrics and mental health, Pediatrics, Perinatology and Child Health, Female, Analysis of variance, business, 030217 neurology & neurosurgery, 050104 developmental & child psychology
Abstract

Conduct problems (CP) in patients with disruptive behavior disorders have been linked to impaired prefrontal processing of negative facial affect compared to controls. However, it is unknown whether associations with prefrontal activity during affective face processing hold along the CP dimension in a healthy population sample, and how subcortical processing is affected. We measured functional brain responses during negative affective face processing in 1444 healthy adolescents [M = 14.39 years (SD = 0.40), 51.5% female] from the European IMAGEN multicenter study. To determine the effects of CP, we applied a two-step approach: (a) testing matched subgroups of low versus high CP, extending into the clinical range [N = 182 per group, M = 14.44 years, (SD = 0.41), 47.3% female] using analysis of variance, and (b) considering (non)linear effects along the CP dimension in the full sample and in the high CP group using multiple regression. We observed no significant cortical or subcortical effect of CP group on brain responses to negative facial affect. In the full sample, regression analyses revealed a significant linear increase of left orbitofrontal cortex (OFC) activity with increasing CP up to the clinical range. In the high CP group, a significant inverted u-shaped effect indicated that left OFC responses decreased again in individuals with high CP. Left OFC activity during negative affective processing which is increasing with CP and decreasing in the highest CP range may reflect on the importance of frontal control mechanisms that counteract the consequences of severe CP by facilitating higher social engagement and better evaluation of social content in adolescents., European Child & Adolescent Psychiatry, 31 (8), ISSN:1435-165X, ISSN:1018-8827

Published
2021
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10. Linked patterns of biological and environmental covariation with brain structure in adolescence: a population-based longitudinal study

Author

Hugh Garavan, Yvonne Grimmer, Sylvane Desrivières, Gaelle E. Doucet, Arun L.W. Bokde, Dominik A. Moser, Jani Penttilä, Betteke van Noort, Sabina Millenet, Andreas Heinz, Abraham Reichenberg, Alex Ing, Penny A. Gowland, Robert Whelan, Dimitri Papadopoulos Orfanos, Michael N. Smolka, Gunter Schumann, Erin Burke Quinlan, Corinna Insensee, Herta Flor, Gareth J. Barker, Antoine Grigis, Juliane H. Fröhner, Jean-Luc Martinot, Andreas Becker, Eric Artiges, Marie-Laure Paillère Martinot, Tobias Banaschewski, Sophia Frangou, Amirhossein Modabbernia, Tomáš Paus, Frauke Nees, Argyris Stringaris, Luise Poustka, Bernd Ittermann, Henrik Walter, HYKS erva, and Päijät-Häme Welfare Consortium

Subjects
0301 basic medicine, Adult, CORTEX, Longitudinal study, SEX-DIFFERENCES, Adolescent, Population, INTELLIGENCE, SURFACE-AREA, MATURATION, 3124 Neurology and psychiatry, Article, 03 medical and health sciences, Cellular and Molecular Neuroscience, Young Adult, 0302 clinical medicine, Neuroimaging, Medicine, Psychology, Humans, MATERNAL SMOKING, Longitudinal Studies, Big Five personality traits, education, Molecular Biology, ASSOCIATIONS, education.field_of_study, business.industry, 3112 Neurosciences, Brain, Cognition, Anthropometry, Magnetic Resonance Imaging, Psychiatry and Mental health, 030104 developmental biology, Cross-Sectional Studies, Canonical Correlation Analysis, Cohort, 1182 Biochemistry, cell and molecular biology, PERSONALITY-TRAITS, TRAJECTORIES, business, 150 Psychology, CORTICAL THICKNESS, Psychosocial, 030217 neurology & neurosurgery, Demography, Neuroscience
Abstract

Adolescence is a period of major brain reorganization shaped by biologically timed and by environmental factors. We sought to discover linked patterns of covariation between brain structural development and a wide array of these factors by leveraging data from the IMAGEN study, a longitudinal population-based cohort of adolescents. Brain structural measures and a comprehensive array of non-imaging features (relating to demographic, anthropometric, and psychosocial characteristics) were available on 1476 IMAGEN participants aged 14 years and from a subsample reassessed at age 19 years (n = 714). We applied sparse canonical correlation analyses (sCCA) to the cross-sectional and longitudinal data to extract modes with maximum covariation between neuroimaging and non-imaging measures. Separate sCCAs for cortical thickness, cortical surface area and subcortical volumes confirmed that each imaging phenotype was correlated with non-imaging features (sCCA r range: 0.30–0.65, all PFDR ρ| = 0.31−0.61). Age, physical growth and sex had the highest association with adolescent brain structure (|ρ| = 0.24−0.62); at baseline, further significant positive associations were noted for cognitive measures while negative associations were observed at both time points for prenatal parental smoking, life events, and negative affect and substance use in youth (|ρ| = 0.10−0.23). Sex, physical growth and age are the dominant influences on adolescent brain development. We highlight the persistent negative influences of prenatal parental smoking and youth substance use as they are modifiable and of relevance for public health initiatives.

Published
2021
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11. Association of Genetic and Phenotypic Assessments With Onset of Disordered Eating Behaviors and Comorbid Mental Health Problems Among Adolescents

Author

Dimitri Papadopoulos Orfanos, Andreas Becker, Iain C. Campbell, Hugh Garavan, Zuo Zhang, Jani Penttilä, Betteke van Noort, Erin Burke Quinlan, Madeleine Irish, Marina Bobou, Nicole Tay, Gunter Schumann, Andreas Heinz, Sarah Hohmann, Corinna Insensee, Tianye Jia, Antoine Grigis, Ulrike Schmidt, Michael N. Smolka, Bernd Ittermann, Lauren Robinson, Juliane H. Fröhner, Henrik Walter, Frauke Nees, Jean-Luc Martinot, Tomáš Paus, Sylvane Desrivières, Luise Poustka, Argyris Stringaris, Tobias Banaschewski, Robert Whelan, Arun L.W. Bokde, Marie-Laure Paillère Martinot, Anna Roach, Yvonne Grimmer, and Edward D. Barker

Subjects
Male, Multifactorial Inheritance, Adolescent, Comorbidity, Anxiety, Feeding and Eating Disorders, 03 medical and health sciences, 0302 clinical medicine, Adolescent Psychiatry, Risk Factors, medicine, Genetics, Humans, 030212 general & internal medicine, Longitudinal Studies, Disordered eating, Original Investigation, Psychiatry, 2. Zero hunger, Psychiatric Status Rating Scales, Binge eating, business.industry, Depression, Research, Mental Disorders, Genomics, General Medicine, medicine.disease, Neuroticism, 3. Good health, 030227 psychiatry, Substance abuse, Europe, Online Only, Eating disorders, Mental Health, Phenotype, Adolescent Behavior, Female, medicine.symptom, business, Stress, Psychological, Demography, Dieting
Abstract

Key Points Question Do associations exist between disordered eating behaviors and other mental health disorders in adolescence, and if so, to what extent are those associations genetically predisposed? Findings Longitudinal assessments in this cohort study of a population-based sample of 1623 adolescents indicated that body mass index (BMI), neuroticism, impulse control, and addiction-related behaviors at 14 years of age were differentially associated with future disordered eating behaviors and symptoms of depression and generalized anxiety. Genetic analyses suggested etiologic overlaps between BMI, neuroticism, and attention-deficit/hyperactivity disorder with dieting, binge eating, and purging, respectively. Meaning Genetic and phenotypic assessments of BMI, impulse control problems, and personality may inform early and differential diagnoses of eating disorders., Importance Eating disorders are serious mental disorders with increasing prevalence. Without early identification and treatment, eating disorders may run a long-term course. Objective To characterize any associations among disordered eating behaviors (DEBs) and other mental health disorders and to identify early associations with the development of symptoms over time. Design, Setting, and Participants This multicenter, population-based, longitudinal cohort study used data from baseline (collected in 2010), follow-up 1 (collected in 2012), and follow-up 2 (collected in 2015) of the IMAGEN Study, which included adolescents recruited from 8 European sites. The present study assessed data from 1623 healthy adolescents, aged 14 years at baseline, recruited from high schools. Data analyses were performed from January 2018 to September 2019. Main Outcomes and Measures Body mass index (BMI), mental health symptoms, substance use behaviors, and personality variables were investigated as time-varying associations of DEBs (dieting, binge eating, and purging) or change in BMI over time. Polygenic risk scores were calculated to investigate genetic contributions associated with BMI, attention-deficit/hyperactivity disorder (ADHD) and neuroticism to DEBs. Results In this cohort study of 1623 adolescents (829 girls [51.1%]) recruited at a mean (SD) age of 14.5 (0.4) years and followed up at ages 16 and 19 years, 278 adolescents (17.1%) reported binge eating, 334 adolescents (20.6%) reported purging, and 356 adolescents (21.9%) reported dieting at 14, 16, or 19 years. Among the precursors of DEBs, high BMI was associated with future dieting (OR, 3.44; 95% CI, 2.09-5.65). High levels of neuroticism (OR, 1.04; 95% CI, 1.01-1.06), conduct problems (OR, 1.41; 95% CI, 1.17-1.69), and deliberate self-harm (OR, 2.18; 95% CI, 1.37-3.45) were associated with future binge eating. Low agreeableness (OR, 0.95; 95% CI, 0.92-0.97), deliberate self-harm (OR, 2.59; 95% CI, 1.69-3.95), conduct problems (OR, 1.42; 95% CI, 1.20-1.68), alcohol misuse (OR, 1.31; 95% CI, 1.10-1.54), and drug abuse (OR, 2.91; 95% CI, 1.78-4.74) were associated with future purging. Polygenetic risk scores for BMI were associated with dieting (at 14 years: OR, 1.27; lower bound 95% CI, 1.08; at 16 years: OR, 1.38; lower bound 95% CI, 1.17); ADHD, with purging (at 16 years: OR, 1.25; lower bound 95% CI, 1.08; at 19 years, OR, 1.23; lower bound 95% CI, 1.06); and neuroticism, with binge eating (at 14 years: OR, 1.32; lower bound 95% CI, 1.11; at 16 years: OR, 1.24; lower bound 95% CI, 1.06), highlighting distinct etiologic overlaps between these traits. The DEBs predated other mental health problems, with dieting at 14 years associated with future symptoms of depression (OR, 2.53; 95% CI, 1.56-4.10), generalized anxiety (OR, 2.27; 95% CI, 1.14-4.51), deliberate self-harm (OR, 2.10; 95% CI, 1.51-4.24), emotional problems (OR, 1.24; 95% CI, 1.08-1.43), and smoking (OR, 2.16; 95% CI, 1.36-3.48). Purging at 14 years was also associated with future depression (OR, 2.87; 95% CI, 1.69-5.01) and anxiety (OR, 2.48; 95% CI, 1.49-4.12) symptoms. Conclusions and Relevance The findings of this study delineate temporal associations and shared etiologies among DEBs and other mental health disorders and emphasize the potential of genetic and phenotypical assessments of obesity, behavioral disorders, and neuroticism to improve early and differential diagnosis of eating disorders., This cohort study across numerous European sites assesses whether associations and shared etiologies exist between disordered eating behaviors (dieting, purging, and binge eating) and other mental health disorders in early adolescence.

Published
2020

12. The Interaction of Child Abuse and rs1360780 of the FKBP5 Gene is Associated with Amygdala Resting-State Functional Connectivity in Young Adults

Author

Luise Poustka, Hugh Garavan, Gunter Schumann, Nicole Y. L. Oei, Gareth J. Barker, Frauke Nees, Ilya M. Veer, Tristram A. Lett, Dimitri Papadopoulos Orfanos, Herta Flor, Antoine Grigis, Eric Artiges, Henrik Walter, Sylvane Desrivières, Rüdiger Brühl, Christiane Wesarg, Arun L.W. Bokde, Andreas Heinz, Robert Whelan, Laura S. Daedelow, Jean-Luc Martinot, Michael N. Smolka, Tobias Banaschewski, Sarah Hohmann, Juliane H. Fröhner, and Erin Burke Quinlan

Subjects
Child abuse, 0303 health sciences, education.field_of_study, Resting state fMRI, Population, Amygdala, 03 medical and health sciences, 0302 clinical medicine, medicine.anatomical_structure, Genotype, medicine, Young adult, Psychology, education, Insula, 030217 neurology & neurosurgery, 030304 developmental biology, Psychopathology, Clinical psychology
Abstract

Extensive research has demonstrated that rs1360780, a common single nucleotide polymorphism within the FKBP5 gene, interacts with early-life stress in predicting psychopathology. Previous results suggest that carriers of the TT genotype of rs1360780 who were exposed to child abuse show differences in structure and functional activation of emotion-processing brain areas belonging to the salience network. Extending these findings on intermediate phenotypes of psychopathology, we examined if the interaction between rs1360780 and child abuse predicts resting-state functional connectivity (rsFC) between the amygdala and other areas of the salience network. We analyzed data of young European adults from the general population (N = 774; mean age = 18.76 years) who took part in the IMAGEN study. In the absence of main effects of genotype and abuse, a significant interaction effect was observed for rsFC between the right centromedial amygdala and right posterior insula (p < .025, FWE-corrected), which was driven by stronger rsFC in TT allele carriers with a history of abuse. Our results suggest that the TT genotype of rs1360780 may render individuals with a history of abuse more vulnerable to functional changes in communication between brain areas processing emotions and bodily sensations, which could underlie or increase risk for psychopathology.

Published
2020
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13. Reward Processing in Novelty Seekers: A Transdiagnostic Psychiatric Imaging Biomarker

Author

Shile Qi, Gunter Schumann, Juan Bustillo, Jessica A. Turner, Rongtao Jiang, Dongmei Zhi, Zening Fu, Andrew R. Mayer, Victor M. Vergara, Rogers F. Silva, Armin Iraji, Jiayu Chen, Eswar Damaraju, Xiaohong Ma, Xiao Yang, Michael Stevens, Daniel H. Mathalon, Judith M. Ford, James Voyvodic, Bryon A. Mueller, Aysenil Belger, Steven G. Potkin, Adrian Preda, Chuanjun Zhuo, Yong Xu, Congying Chu, Tobias Banaschewski, Gareth J. Barker, Arun L.W. Bokde, Erin Burke Quinlan, Sylvane Desrivières, Herta Flor, Antoine Grigis, Hugh Garavan, Penny Gowland, Andreas Heinz, Jean-Luc Martinot, Marie-Laure Paillère Martinot, Eric Artiges, Frauke Nees, Dimitri Papadopoulos Orfanos, Tomáš Paus, Luise Poustka, Sarah Hohmann, Juliane H. Fröhner, Michael N. Smolka, Henrik Walter, Robert Whelan, Vince D. Calhoun, and Jing Sui

Subjects
MDD, 0301 basic medicine, Substance use, Medical and Health Sciences, Substance Misuse, Alcohol Use and Health, 0302 clinical medicine, 2.1 Biological and endogenous factors, Aetiology, Pediatric, Psychiatry, Depression, Novelty, Major depressive disorders, Biological Sciences, Serious Mental Illness, Magnetic Resonance Imaging, Reward processing, Alcoholism, Mental Health, Schizophrenia, Biomarker (medicine), Major depressive disorder, Adult, medicine.medical_specialty, Psychosis, Adolescent, Article, 03 medical and health sciences, Young Adult, Neuroimaging, Reward, Clinical Research, Behavioral and Social Science, medicine, ADHD, Attention deficit hyperactivity disorder, Humans, IMAGEN Consortium, Biological Psychiatry, Depressive Disorder, Depressive Disorder, Major, business.industry, Prevention, Psychology and Cognitive Sciences, Neurosciences, Novelty seeking, Major, medicine.disease, Brain Disorders, Attention-deficit/hyperactivity disorder, Good Health and Well Being, 030104 developmental biology, Attention Deficit Disorder with Hyperactivity, business, 030217 neurology & neurosurgery, Biomarkers
Abstract

Background Dysfunctional reward processing is implicated in multiple mental disorders. Novelty seeking (NS) assesses preference for seeking novel experiences, which is linked to sensitivity to reward environmental cues. Methods A subset of 14-year-old adolescents (IMAGEN) with the top 20% ranked high-NS scores was used to identify high-NS–associated multimodal components by supervised fusion. These features were then used to longitudinally predict five different risk scales for the same and unseen subjects (an independent dataset of subjects at 19 years of age that was not used in predictive modeling training at 14 years of age) (within IMAGEN, n ≈ 1100) and even for the corresponding symptom scores of five types of patient cohorts (non-IMAGEN), including drinking (n = 313), smoking (n = 104), attention-deficit/hyperactivity disorder (n = 320), major depressive disorder (n = 81), and schizophrenia (n = 147), as well as to classify different patient groups with diagnostic labels. Results Multimodal biomarkers, including the prefrontal cortex, striatum, amygdala, and hippocampus, associated with high NS in 14-year-old adolescents were identified. The prediction models built on these features are able to longitudinally predict five different risk scales, including alcohol drinking, smoking, hyperactivity, depression, and psychosis for the same and unseen 19-year-old adolescents and even predict the corresponding symptom scores of five types of patient cohorts. Furthermore, the identified reward-related multimodal features can classify among attention-deficit/hyperactivity disorder, major depressive disorder, and schizophrenia with an accuracy of 87.2%. Conclusions Adolescents with higher NS scores can be used to reveal brain alterations in the reward-related system, implicating potential higher risk for subsequent development of multiple disorders. The identified high-NS–associated multimodal reward-related signatures may serve as a transdiagnostic neuroimaging biomarker to predict disease risks or severity.

Published
2020

14. Prospective associations between physical activity levels and white matter integrity in older adults: results from the MAPT study

Author

Audrey Gabelle, Mathieu Maltais, Philipe de Souto Barreto, Katherine Boisvert-Vigneault, Antoine Grigis, Marie Chupin, Jean-François Mangin, Ali Bouyahia, Yves Rolland, Bruno Vellas, Lisa Perus, Julien Delrieux, Service d'exploration de la fonction respiratoire et de médecine du sport, CHU Toulouse [Toulouse], Centre Hospitalier Universitaire de Sherbrooke, Unité Baobab (BAOBAB), Service NEUROSPIN (NEUROSPIN), 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-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, Neuropsychiatrie : recherche épidémiologique et clinique (PSNREC), Université Montpellier 1 (UM1)-Université de Montpellier (UM)-Institut National de la Santé et de la Recherche Médicale (INSERM), CATI Multicenter Neuroimaging Platform (CATI), Institut du Cerveau et de la Moëlle Epinière = Brain and Spine Institute (ICM), Institut National de la Santé et de la Recherche Médicale (INSERM)-CHU Pitié-Salpêtrière [AP-HP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-CHU Pitié-Salpêtrière [AP-HP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU), Centre Hospitalier Régional Universitaire [Montpellier] (CHRU Montpellier), Laboratoire de Gérontechnologie [Hôpital La Grave-CHU de Toulouse], Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-CHU Toulouse [Toulouse]-Institut National de la Santé et de la Recherche Médicale (INSERM)-Gérontopôle, Epidémiologie et analyses en santé publique : risques, maladies chroniques et handicaps (LEASP), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut National de la Santé et de la Recherche Médicale (INSERM), Centre Hospitalier Universitaire de Toulouse (CHU Toulouse), Building large instruments for neuroimaging: from population imaging to ultra-high magnetic fields (BAOBAB), 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)-Centre National de la Recherche Scientifique (CNRS), Université Montpellier 1 (UM1)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Montpellier (UM), Institut du Cerveau = Paris Brain Institute (ICM), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Institut National de la Santé et de la Recherche Médicale (INSERM)-CHU Pitié-Salpêtrière [AP-HP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Sorbonne Université (SU)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-CHU Pitié-Salpêtrière [AP-HP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), Pôle Gériatrie [CHU Toulouse], Université de Toulouse (UT)-Université de Toulouse (UT)-Institut National de la Santé et de la Recherche Médicale (INSERM), and ANR-16-IDEX-0006,MUSE,MUSE(2016)

Subjects
Male, medicine.medical_specialty, [SDV]Life Sciences [q-bio], Physical activity, Uncinate fasciculus, Audiology, General Biochemistry, Genetics and Molecular Biology, White matter, 03 medical and health sciences, 0302 clinical medicine, Neuroimaging, Fractional anisotropy, Medicine, Humans, 030212 general & internal medicine, Prospective Studies, Exercise, ComputingMilieux_MISCELLANEOUS, Aged, 030219 obstetrics & reproductive medicine, medicine.diagnostic_test, business.industry, Obstetrics and Gynecology, Magnetic resonance imaging, Cardiorespiratory fitness, Magnetic Resonance Imaging, White Matter, medicine.anatomical_structure, Cross-Sectional Studies, Diffusion Tensor Imaging, Anisotropy, Female, Sedentary Behavior, business, Diffusion MRI
Abstract

Background Higher levels of physical activity (PA) are known to be associated with better white matter integrity measured by diffusion tensor imaging (DTI) in older adults in cross-sectional studies. However, no studies have investigated the association between PA levels and the evolution of DTI parameters (fractional anisotropy and mean diffusivity). Objectives To examine the cross-sectional associations between PA levels and DTI parameters, then to investigate the association between baseline PA levels and the evolution of DTI parameters in older adults. Methods Data on magnetic resonance imaging with DTI method from the Multidomain Alzheimer’s Preventive Trial (MAPT) study were used; 228 participants had data on DTI measured at three time-points over five years. Fractional anisotropy and mean diffusivity were acquired for six different brain regions. Results No significant associations were found in the cross-sectional analyses. Only one association was found: compared with active individuals, a faster worsening in the mean diffusivity of the uncinate fasciculus region was found in inactive individuals (-5.0 × 10-6 (-9.5 × 10-5, 4.9 × 10-6)). Conclusions In this study, we found that the condition of the uncinate fasciculus region may be susceptible to changes in PA levels in older adults. Longitudinal studies that assess fitness and PA using objective measurements (e.g. cardiorespiratory fitness and accelerometry) could shed some new light on this topic.

Published
2020
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15. Neural network involving medial orbitofrontal cortex and dorsal periaqueductal gray regulation in human alcohol abuse

Author

Dimitri Papadopoulos Orfanos, Michael N. Smolka, Juliane H. Fröhner, Robert Whelan, Chao Xie, Gareth J. Barker, Andreas Heinz, Tianye Jia, Frauke Nees, Erin Burke Quinlan, Penny A. Gowland, Tobias Banaschewski, Bernd Ittermann, Gunter Schumann, Henrik Walter, Marie-Laure Paillère Martinot, Herta Flor, Antoine Grigis, Trevor W. Robbins, Christian Büchel, Hugh Garavan, Luise Poustka, Sylvane Desrivières, Arun L.W. Bokde, Jianfeng Feng, Jean-Luc Martinot, Gestionnaire, Hal Sorbonne Université, Fudan University [Shanghai], King‘s College London, Heidelberg University, Trinity College Dublin, Universitaetsklinikum Hamburg-Eppendorf = University Medical Center Hamburg-Eppendorf [Hamburg] (UKE), University of Mannheim, 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), University of Vermont [Burlington], University of Nottingham, UK (UON), Humboldt University Of Berlin, Physikalisch-Technische Bundesanstalt [Berlin] (PTB), CB - Centre Borelli - UMR 9010 (CB), Service de Santé des Armées-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Ecole Normale Supérieure Paris-Saclay (ENS Paris Saclay)-Université Paris Cité (UPCité), Service de Psychiatrie de l'Enfant et de l'Adolescent [CHU Pitié-Salpêtrière] (SPEA), CHU Pitié-Salpêtrière [AP-HP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU), Universität Heidelberg [Heidelberg], University Medical Center of Schleswig–Holstein = Universitätsklinikum Schleswig-Holstein (UKSH), Kiel University, University Medical Center Göttingen (UMG), Technische Universität Dresden = Dresden University of Technology (TU Dresden), University of Potsdam = Universität Potsdam, University of Cambridge [UK] (CAM), University of Warwick [Coventry], Zhejiang Normal University, Humboldt-Universität zu Berlin, Service de Santé des Armées-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Ecole Normale Supérieure Paris-Saclay (ENS Paris Saclay)-Université de Paris (UP), University of Potsdam, Universität Mannheim, Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU), and Universität Heidelberg [Heidelberg] = Heidelberg University

Subjects
Adolescent, [SDV]Life Sciences [q-bio], Prefrontal Cortex, Biology, Nucleus accumbens, Impulsivity, Periaqueductal gray, 03 medical and health sciences, 0302 clinical medicine, Biological neural network, medicine, Humans, Periaqueductal Gray, Research Articles, Cerebral Cortex, Multidisciplinary, medicine.diagnostic_test, Central nucleus of the amygdala, Alcohol dependence, SciAdv r-articles, Magnetic Resonance Imaging, 030227 psychiatry, [SDV] Life Sciences [q-bio], Alcoholism, Orbitofrontal cortex, Neural Networks, Computer, medicine.symptom, Functional magnetic resonance imaging, Neuroscience, 030217 neurology & neurosurgery, Research Article
Abstract

Neuroimaging data from 1890 adolescents implicated an orbitofronto-amygdalo-periaqueductal gray network in early alcohol abuse., Prompted by recent evidence of neural circuitry in rodent models, functional magnetic resonance imaging and functional connectivity analyses were conducted for a large adolescent population at two ages, together with alcohol abuse measures, to characterize a neural network that may underlie the onset of alcoholism. A network centered on the medial orbitofrontal cortex (mOFC), as well as including the dorsal periaqueductal gray (dPAG), central nucleus of the amygdala, and nucleus accumbens, was identified, consistent with the rodent models, with evidence of both inhibitory and excitatory coregulation by the mOFC over the dPAG. Furthermore, significant relationships were detected between raised baseline excitatory coregulation in this network and impulsivity measures, supporting a role for negative urgency in alcohol dependence.

Published
2020
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16. Cognitive and brain development is independently influenced by socioeconomic status and polygenic scores for educational attainment

Author

Dimitri Papadopoulos Orfanos, Juliane H. Fröhner, Jani Penttilä, Betteke van Noort, Michael N. Smolka, Sabina Millenet, Torkel Klingberg, Andreas Heinz, Gunter Schumann, Bruno Sauce, Luise Poustka, Eric Artiges, Corinna Insensee, Sarah Hohmann, Yvonne Grimmer, Bader Chaarani, Penny A. Gowland, Tobias Banaschewski, Nicholas Judd, Bernd Ittermann, Robert Whelan, Frauke Nees, John Wiedenhoeft, Henrik Walter, Andreas Becker, Herta Flor, Antoine Grigis, Tomáš Paus, Hugh Garavan, Erin Burke Quinlan, Marie-Laure Paillère Martinot, Alexander Schliep, Jeshua Tromp, Sylvane Desrivières, Arun L.W. Bokde, and Jean-Luc Martinot

Subjects
Adult, Male, Longitudinal study, Multifactorial Inheritance, Adolescent, Intraparietal sulcus, Developmental psychology, 03 medical and health sciences, Young Adult, 0302 clinical medicine, Cognition, Cognitive development, Humans, Longitudinal Studies, Socioeconomic status, 030304 developmental biology, 0303 health sciences, Academic Success, Working memory, Brain, Spatial cognition, Biological Sciences, Magnetic Resonance Imaging, Educational attainment, Memory, Short-Term, Social Class, Educational Status, Female, 030217 neurology & neurosurgery
Abstract

Genetic factors and socioeconomic (SES) inequalities play a large role in educational attainment, and both have been associated with variations in brain structure and cognition. However, genetics and SES are correlated, and no prior study has assessed their neural associations independently. Here we used polygenic score for educational attainment (EduYears-PGS) as well as SES, in a longitudinal study of 551 adolescents, to tease apart genetic and environmental associations with brain development and cognition. Subjects received a structural MRI scan at ages 14 and 19. At both time-points, they performed three working memory (WM) tasks. SES and EduYears-PGS were correlated (r = 0.27) and had both common and independent associations with brain structure and cognition. Specifically, lower SES was related to less total cortical surface area and lower WM. EduYears-PGS was also related to total cortical surface area, but in addition had a regional association with surface area in the right parietal lobe, a region related to non-verbal cognitive functions, including mathematics, spatial cognition, and WM. SES, but not EduYears-PGS, was related to a change in total cortical surface area from age 14 to 19. This is the first study demonstrating a regional association of EduYears-PGS and the independent prediction of SES on cognitive function and brain development. It suggests that the SES inequalities, in particular parental education, are related to global aspects of cortical development, and exert a persistent influence on brain development during adolescence.Significance statementThe influence of socioeconomic (SES) inequalities on brain and cognitive development is a hotly debated topic. However, previous studies have not considered that genetic factors overlap with SES. Here we showed, for the first time, that SES and EduYears-PGS (a score from thousands of genetic markers for educational attainment) have independent associations with both cognition and global cortical surface area in adolescents. EduYears-PGS also had a localized association in the brain: the intraparietal sulcus, a region related to non-verbal intelligence. In contrast, SES had global, but not regional, associations, and these persisted throughout adolescence. This suggests that the influence of SES inequalities is widespread – a result that opposes the current paradigm and can help inform policies in education.

Published
2020

17. Reward Versus Nonreward Sensitivity of the Medial Versus Lateral Orbitofrontal Cortex Relates to the Severity of Depressive Symptoms

Author

Chao Xie, Tianye Jia, Edmund T. Rolls, Trevor W. Robbins, Barbara J. Sahakian, Jie Zhang, Zhaowen Liu, Wei Cheng, Qiang Luo, Chun-Yi Zac Lo, He Wang, Tobias Banaschewski, Gareth J. Barker, Arun L.W. Bokde, Christian Büchel, Erin Burke Quinlan, Sylvane Desrivières, Herta Flor, Antoine Grigis, Hugh Garavan, Penny Gowland, Andreas Heinz, Sarah Hohmann, Bernd Ittermann, Jean-Luc Martinot, Marie-Laure Paillère Martinot, Frauke Nees, Dimitri Papadopoulos Orfanos, Tomáš Paus, Luise Poustka, Juliane H. Fröhner, Michael N. Smolka, Henrik Walter, Robert Whelan, Gunter Schumann, Jianfeng Feng, Eric Artiges, Semiha Aydin, Alexis Barbot, Gareth Barker, Andreas Becker, Pauline Bezivin-Frere, Francesca Biondo, Arun Bokde, Congying Chu, Patricia Conrod, Laura Daedelow, Jeffrey Dalley, Sylvane Desrivieres, Eoin Dooley, Irina Filippi, Ariane Fillmer, Juliane Fröhner, Vincent Frouin, Yvonne Grimmer, Albrecht Ihlenfeld, Alex Ing, Corinna Isensee, Hervé Lemaitre, Emma Lethbridge, Sabina Millenet, Sarah Miller, Ruben Miranda, Marie-Laure Paillere, Dimitri Papadopoulos, Zdenka Pausova, Jani Pentilla, Jean-Baptiste Poline, Erin Burke, Michael Rapp, Trevor Robbins, Gabriel Robert, John Rogers, Barbara Ruggeri, Michael Smolka, Argyris Stringaris, Betteke van Noort, Roux Simon, Steve Williams, Yuning Zhang, and IMAGEN Consortium

Subjects
Adult, medicine.medical_specialty, Adolescent, Reward anticipation, RJ, Cognitive Neuroscience, Population, Prefrontal Cortex, Audiology, Adolescents, Monetary incentive delay task, 050105 experimental psychology, 03 medical and health sciences, Young Adult, 0302 clinical medicine, Reward, Reward sensitivity, Orbitofrontal cortex, Medicine, Humans, 0501 psychology and cognitive sciences, Radiology, Nuclear Medicine and imaging, education, Biological Psychiatry, Depression (differential diagnoses), Depressive symptoms, education.field_of_study, business.industry, Depression, musculoskeletal, neural, and ocular physiology, 05 social sciences, Ventral striatum, Nonreward sensitivity, QP, Magnetic Resonance Imaging, Frontal Lobe, medicine.anatomical_structure, nervous system, Cohort, Neurology (clinical), business, psychological phenomena and processes, 030217 neurology & neurosurgery, RC
Abstract

BACKGROUND: The orbitofrontal cortex (OFC) is implicated in depression. The hypothesis investigated was whether the OFC sensitivity to reward and nonreward is related to the severity of depressive symptoms.METHODS: Activations in the monetary incentive delay task were measured in the IMAGEN cohort at ages 14 years (n = 1877) and 19 years (n = 1140) with a longitudinal design. Clinically relevant subgroups were compared at ages 19 (high-severity group: n = 116; low-severity group: n = 206) and 14.RESULTS: The medial OFC exhibited graded activation increases to reward, and the lateral OFC had graded activation increases to nonreward. In this general population, the medial and lateral OFC activations were associated with concurrent depressive symptoms at both ages 14 and 19 years. In a stratified high-severity depressive symptom group versus control group comparison, the lateral OFC showed greater sensitivity for the magnitudes of activations related to nonreward in the high-severity group at age 19 (p = .027), and the medial OFC showed decreased sensitivity to the reward magnitudes in the high-severity group at both ages 14 (p = .002) and 19 (p = .002). In a longitudinal design, there was greater sensitivity to nonreward of the lateral OFC at age 14 for those who exhibited high depressive symptom severity later at age 19 (p = .003).CONCLUSIONS: Activations in the lateral OFC relate to sensitivity to not winning, were associated with high depressive symptom scores, and at age 14 predicted the depressive symptoms at ages 16 and 19. Activations in the medial OFC were related to sensitivity to winning, and reduced reward sensitivity was associated with concurrent high depressive symptom scores.

Published
2020
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18. The empirical replicability of task-based fMRI as a function of sample size

Author

Gareth J. Barker, Han Bossier, Gunter Schumann, Henrik Walter, Bernd Ittermann, Dimitri Papadopoulos Orfanos, Beatrijs Moerkerke, Erin Burke Quinlan, Luise Poustka, Eric Artiges, Juliane H Fröhner Dipl-Psych, Michael N. Smolka, Ruth Seurinck, Sanne Roels, Robert Whelan, Andreas Heinz, Penny A. Gowland, Herta Flor, Hugh Garavan, Antoine Grigis, Tobias Banaschewski, Frauke Nees, Sylvane Desrivières, Arun L.W. Bokde, and Jean-Luc Martinot

Subjects
Computer science, Cognitive Neuroscience, Stability (learning theory), Machine learning, computer.software_genre, Task-based fMRI, 050105 experimental psychology, lcsh:RC321-571, 03 medical and health sciences, 0302 clinical medicine, Empirical research, Voxel, Replicability, medicine, Humans, FAILURE, 0501 psychology and cognitive sciences, lcsh:Neurosciences. Biological psychiatry. Neuropsychiatry, PERMUTATION, METAANALYSIS, Reliability (statistics), Brain Mapping, Reproducibility, medicine.diagnostic_test, business.industry, 05 social sciences, Reproducibility of Results, NEUROIMAGING DATA, Replicate, Coherence (statistics), Reliability, Magnetic Resonance Imaging, POWER CALCULATION, Mathematics and Statistics, Neurology, Sample size determination, Sample Size, TESTS, MR-IMAGES, INFERENCE, TEST-RETEST RELIABILITY, Artificial intelligence, Functional magnetic resonance imaging, business, computer, Stability, Coherence, 030217 neurology & neurosurgery
Abstract

Replicating results (i.e. obtaining consistent results using a new independent dataset) is an essential part of good science. As replicability has consequences for theories derived from empirical studies, it is of utmost importance to better understand the underlying mechanisms influencing it. A popular tool for non-invasive neuroimaging studies is functional magnetic resonance imaging (fMRI). While the effect of underpowered studies is well documented, the empirical assessment of the interplay between sample size and replicability of results for task-based fMRI studies remains limited. In this work, we extend existing work on this assessment in two ways. Firstly, we use a large database of 1400 subjects performing four types of tasks from the IMAGEN project to subsample a series of independent samples of increasing size. Secondly, replicability is evaluated using a multi-dimensional framework consisting of 3 different measures: (un)conditional test-retest reliability, coherence and stability. We demonstrate not only a positive effect of sample size, but also a trade-off between spatial resolution and replicability. When replicability is assessed voxelwise or when observing small areas of activation, a larger sample size than typically used in fMRI is required to replicate results. On the other hand, when focussing on clusters of voxels, we observe a higher replicability. In addition, we observe variability in the size of clusters of activation between experimental paradigms or contrasts of parameter estimates within these.

Published
2020
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19. Age-dependent genetic variants associated with longitudinal changes in brain structure across the lifespan

Author

Philip R. Jansen, Erlend Bøen, Erin Burke Quinlan, Javier Vázquez-Bourgon, Celso Arango, Sonja M C de Zwarte, Andrea Parolin Jackowski, Mohammad Arfan Ikram, Dennis van der Meer, Clara Alloza, Matthew S. Panizzon, Ryan L. Muetzel, Vidar M. Steen, Lars T. Westlye, Joanna Bright, Walter Heindel, Marcella Rietschel, Wei Wen, Frauke Nees, Daniel Keeser, Sintia Iole Belangero, Philip Shaw, Tiago Reis Marques, Neda Jahanshad, Jiyang Jiang, Benedicto Crespo Facorro, Tilo Kircher, David Ames, Dan J. Stein, Ulrik Fredrik Malt, Axel Krug, Kang Sim, Gaia Bonfiglio, Nhat Trung Doan, Katrin Amunts, John B.J. Kwok, Pedro Mario Pan, Udo Dannlowski, Markus M. Nöthen, Elena Shumskaya, Simon R. Cox, Sarah J. Heany, Perminder S. Sachdev, Aad van der Lugt, Mark E. Bastin, Brenda W.J.H. Penninx, Catherine Morgan, Elizabeth E.L. Buimer, Henrik Walter, Dara M. Cannon, Hugo G. Schnack, Sarah Hohmann, Evangelos Vassos, Shun Takahashi, Gloria Roberts, Simone Ciufolini, Loes M. Olde Loohuis, Penny A. Gowland, Joost Janssen, Michael N. Smolka, Temmuz Karali, Robin M. Murray, Herve Lemaitre, Karen A. Mather, Dennis van 't Ent, Derek W. Morris, William S. Kremen, Peter Falkai, Berend Malchow, Tim Hahn, Dag Alnæs, Ronny Redlich, Ingrid Agartz, Fabian Streit, João P.O.F.T. Guimarães, Nils Opel, Bernhard T. Baune, Marie-Laure Paillère Martinot, Catharina A. Hartman, Alexander Teumer, Frederike Stein, André Zugman, Nikita Setiaman, Jalmar Teeuw, Isabella A. Breukelaar, Vicente Medel, Stephanie H. Witt, Christienne G. Damatac, Nicolas Crossley, Luise Poustka, Hieab H.H. Adams, Linda Ding, Jonathan Repple, Jacqueline Hoare, Eric Artiges, Manon H.J. Hillegers, Andreas Heinz, Susanne Meinert, Tianye Jia, Diana Tordesillas-Gutiérrez, Marieke Klein, Herta Flor, Joanna M. Wardlaw, Roel A. Ophoff, Rodrigo A. Bressan, Antoine Grigis, Marcos L. Santoro, Javier González-Peñas, Thomas Espeseth, Torbjørn Elvsåshagen, Kristel R. van Eijk, Hilleke E. Hulshoff Pol, Sophia I. Thomopoulos, Gustavo Sudre, Juliane H. Fröhner, Rhoshel K. Lenroot, Bernd Ittermann, René S. Kahn, Gareth J. Barker, Wiepke Cahn, Yuri Milaneschi, Margaret J. Wright, Janita Bralten, Gail Davies, Elisabet Blok, Janice M. Fullerton, Jouke-Jan Hottenga, Paola Dazzan, Andreas J. Forstner, Leila Nabulsi, Christopher D. Whelan, Katharina Wittfeld, Mathew A. Harris, Julian N. Trollor, Mayuresh S. Korgaonkar, Igor Nenadic, Nitin Gogtay, Laura K.M. Han, Robin Bülow, Moji Aghajani, Leonard H. van den Berg, Marta Di Forti, Bronwyn Overs, Paul M. Thompson, Rick M. Tankard, Sven Cichon, Jason L. Stein, Jaap Oosterlaan, Jan K. Buitelaar, Jean-Luc Martinot, René C.W. Mandl, Victor Ortiz-García de la Foz, Robert Whelan, Svenja Caspers, Rosa Ayesa-Arriola, Sylvane Desrivières, Covadonga M. Díaz-Caneja, Ole A. Andreassen, Gunter Schumann, Arun L.W. Bokde, Alyssa H. Zhu, Henk-Jan Westeneng, Emma Sprooten, Sergi Papiol, Giovanni Abrahão Salum, Neeltje E.M. van Haren, Simon E. Fisher, Dominik Grotegerd, Casper L. de Mol, Alzheimer’s Disease Neuroimaging Initiative, Dorret I. Boomsma, Gennady V. Roshchupkin, Pieter J. Hoekstra, Andreas Jansen, Peter R. Schofield, Tonya White, Maria J. Knol, Rachel M. Brouwer, Martijn G.J.C. Koevoets, Thomas W. Mühleisen, Katharina Dohm, Barbara Franke, Philip B. Mitchell, Colm McDonald, Anbupalam Thalamuthu, Henry Brodaty, Gary Donohoe, Stephanie Le Hellard, Shareefa Dalvie, Georg Homuth, Jan H. Veldink, Nicola J. Armstrong, Christiane Jockwitz, Sarah E. Medland, Katrina L. Grasby, Tobias Banaschewski, Hans J. Grabe, Hugh Garavan, Dirk J. Heslenfeld, Erik G. Jönsson, Carol E. Franz, and Janik Goltermann

Subjects
2. Zero hunger, Apolipoprotein E, 0303 health sciences, Brain morphometry, Human brain, Biology, medicine.disease, 3. Good health, 03 medical and health sciences, 0302 clinical medicine, medicine.anatomical_structure, Atrophy, Schizophrenia, Ageing, medicine, Cognitive skill, Neuroscience, 030217 neurology & neurosurgery, Depression (differential diagnoses), 030304 developmental biology
Abstract

SummaryHuman brain structure changes throughout our lives. Altered brain growth or rates of decline are implicated in a vast range of psychiatric, developmental, and neurodegenerative diseases. Here, we identified common genetic variants that affect rates of brain growth or atrophy, in the first genome-wide association meta-analysis of changes in brain morphology across the lifespan. Longitudinal MRI data from 15,640 individuals were used to compute rates of change for 15 brain structures. The most robustly identified genesGPR139, DACH1andAPOEare associated with metabolic processes. We demonstrate global genetic overlap with depression, schizophrenia, cognitive functioning, insomnia, height, body mass index and smoking. Gene-set findings implicate both early brain development and neurodegenerative processes in the rates of brain changes. Identifying variants involved in structural brain changes may help to determine biological pathways underlying optimal and dysfunctional brain development and ageing.

Published
2020
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20. Longitudinal associations between amygdala reactivity and cannabis use in a large sample of adolescents

Author

Dimitri Papadopoulos Orfanos, Philip A. Spechler, Stephen T. Higgins, Tomáš Paus, Juliane H. Fröhner, Robert Whelan, Penny A. Gowland, Michael N. Smolka, Herta Flor, Antoine Grigis, Bader Chaarani, Frauke Nees, Sylvane Desrivières, Matthew D. Albaugh, Bernd Ittermann, Marie-Laure Paillère Martinot, Andreas Heinz, Gunter Schumann, Arun L.W. Bokde, Hugh Garavan, Catherine Orr, Henrik Walter, Luise Poustka, Sarah Hohmann, Tobias Banaschewski, Nicholas R. Fontaine, Erin Burke Quinlan, and Eric Artiges

Subjects
Male, Cannabinoid receptor, Adolescent, Amygdala, Article, Correlation, 03 medical and health sciences, Young Adult, 0302 clinical medicine, Medicine, Humans, Longitudinal Studies, Reactivity (psychology), Pharmacology, biology, business.industry, Cannabis use, biology.organism_classification, Magnetic Resonance Imaging, 030227 psychiatry, Large sample, medicine.anatomical_structure, Adolescent Behavior, Female, Marijuana Use, Cannabis, business, Facial Recognition, 030217 neurology & neurosurgery, Neurotypical, Clinical psychology
Abstract

RATIONALE: The amygdala is a key brain structure to study in relation to cannabis use as reflected by its high-density of cannabinoid receptors and functional reactivity to processes relevant to drug use. Previously, we identified a correlation between cannabis use in early adolescence and amygdala hyper-reactivity to angry faces (Spechler et al. 2015). OBJECTIVES: Here, we leveraged the longitudinal aspect of the same dataset (the IMAGEN study) to determine (1) if amygdala hyper-reactivity predicts future cannabis use and (2) if amygdala reactivity is affected by prolonged cannabis exposure during adolescence. METHODS: First, linear regressions predicted the level of cannabis use by age 19 using amygdala reactivity to angry faces measured at age 14 prior to cannabis exposure in a sample of 1119 participants. Next, we evaluated the time course of amygdala functional development from age 14 to 19 for angry face processing and how it might be associated with protracted cannabis use throughout this developmental window. We compared the sample from Spechler et al. 2015, the majority of whom escalated their use over the 5-year interval, to a matched sample of non-users. RESULTS: Right amygdala reactivity to angry faces significantly predicted cannabis use 5 years later in a dose-response fashion. Cannabis-naïve adolescents demonstrated the lowest levels of amygdala reactivity. No such predictive relationship was identified for alcohol or cigarette use. Next, follow-up analyses indicated a significant group-by-time interaction for the right amygdala. CONCLUSIONS: (1) Right amygdala hyper-reactivity is predictive of future cannabis use, and (2) protracted cannabis exposure during adolescence may alter the rate of neurotypical functional development.

Published
2020

21. Accelerating the Evolution of Nonhuman Primate Neuroimaging

Author

Olivier Coulon, Michael P. Milham, Patrik Lindenfors, Karl-Heinz Nenning, Xiaojin Liu, Ravi S. Menon, Stephanie J. Forkel, Adam Messinger, Zheng Wang, Alexander Thiele, Luciano Simone, Benjamin Jung, Chika Sato, Jamie Nagy, Sean Froudist-Walsh, Kelvin Mok, Renée Hartig, Julien Sein, Alessandro Gozzi, Julien Vezoli, Tomoko Sakai, Lynn Uhrig, Martine Meunier, Christienne G. Damatac, Bonhwang Koo, Roberto Toro, Rogier B. Mars, Henrietta Howells, Lea Roumazeilles, Ming Zhan, Ann-Marie Mallon, Román Rossi-Pool, Elinor L. Sullivan, Yannick Becker, Doris Y. Tsao, Antoine Grigis, Lei Ai, Céline Amiez, Sara Wells, Reza Rajimehr, Aki Nikolaidis, Anna S. Mitchell, Simon M. Reader, Michele A. Basso, Béchir Jarraya, Amir Raz, Wim Vanduffel, Charles R.E. Wilson, Brian E. Russ, Christopher R. Madan, Orlin S. Todorov, Wasana Madushanka, Carole Guedj, Mark A. Pinsk, Clémentine Bodin, Hugo Merchant, Jennifer Nacef, Damien A. Fair, Anna W. Roe, Sze Chai Kwok, Stephen J. Sawiak, Essa Yacoub, Bastien Cagna, Kevin N. Laland, Wilbert Zarco, Charles E. Schroeder, Ting Xu, P. Christiaan Klink, Stanislas Dehaene, Takuya Hayashi, Matthew F. S. Rushworth, Amir Shmuel, Fadila Hadj-Bouziane, Katja Heuer, Ioana-Sabina Rautu, Andrew S. Fox, Austin Benn, Sabine Kastner, Thomas Brochier, Emmanuel Procyk, Marco Pagani, David C. Van Essen, Frank Q. Ye, Dirk Jan Ardesch, Régis Trapeau, Jakob Seidlitz, Marike Schiffer, Bassem Hiba, John H. Morrison, David A. Rudko, Paula L. Croxson, Patrick Friedrich, Augix Guohua Xu, Lazar Fleysher, Piotr Majka, Jonathan Smallwood, Aihua Chen, Timothy D. Griffiths, Fabien Balezeau, Stefan Everling, Michael C. Schmid, Robert Leech, Leslie G. Ungerleider, Mark G. Baxter, Afonso C. Silva, Clare Kelly, Zhi-ming Shen, Daniel S. Margulies, Mark J. Prescott, Pascal Belin, Erwin L. A. Blezer, Igor Kagan, Suliann Ben Hamed, David A. Leopold, Adrien Meguerditchian, Wendy Jarrett, Michel Thiebaut de Schotten, Nikoloz Sirmpilatze, Julia Sliwa, Henry Kennedy, Vikas Pareek, Yong-di Zhou, Michael Ortiz-Rios, Sherif Hamdy El-Gohary, Susann Boretius, Christopher I. Petkov, Pamela Garcia-Saldivar, Bella Williams, Jordy Tasserie, Hank P. Jedema, Jerome Sallet, Pieter R. Roelfsema, Winrich A. Freiwald, Eduardo A. Garza-Villarreal, Noam Harel, Caspar M. Schwiedrzik, Kevin Marche, Colline Poirier, Yang Gao, Henry C. Evrard, Ashkan Alvand, ANS - Cellular & Molecular Mechanisms, Laboratoire des Sciences de l'Information et des Systèmes (LSIS), Aix Marseille Université (AMU)-Université de Toulon (UTLN)-Arts et Métiers Paristech ENSAM Aix-en-Provence-Centre National de la Recherche Scientifique (CNRS), Institut cellule souche et cerveau (SBRI), Institut National de la Recherche Agronomique (INRA)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Institut National de la Santé et de la Recherche Médicale (INSERM), Collège de France - Chaire Psychologie cognitive expérimentale, Collège de France (CdF (institution)), Institut des sciences cognitives Marc Jeannerod - Centre de neuroscience cognitive - UMR5229 (ISC-MJ), Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Centre National de la Recherche Scientifique (CNRS), Consortium, PRIMatE Data Exchange Global Collaboration Workshop and, Nathan S. Kline Institute for Psychiatric Research (NKI), New York State Office of Mental Health, Newcastle University [Newcastle], Max Planck Institute for Human Cognitive and Brain Sciences [Leipzig] (IMPNSC), Max-Planck-Gesellschaft, Medical Oncology, Department of Internal Medicine, Università Cattolica del Sacro Cuore [Roma] (Unicatt), Voice Neurocognition Laboratory, University of Glasgow, Oregon Health and Science University [Portland] (OHSU), Manchester Royal Infirmary, University of Manchester [Manchester], Princeton Neuroscience Institute [Princeton], University of Pennsylvania [Philadelphia], National Institute of Mental Health (NIMH), Harvard Medical School [Boston] (HMS), Washington University in St Louis, Laboratoire de psychologie cognitive (LPC), Centre National de la Recherche Scientifique (CNRS)-Aix Marseille Université (AMU), Institut des sciences cognitives Marc Jeannerod - Centre de neuroscience cognitive - UMR5229 (CNC), Centre National de la Recherche Scientifique (CNRS)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon, Institut de Neurosciences de la Timone (INT), Aix Marseille Université (AMU)-Centre National de la Recherche Scientifique (CNRS), Institute of Psychiatry, Psychology & Neuroscience, King's College London, King‘s College London, New York University [New York] (NYU), NYU System (NYU), State Key Laboratory of Novel Software Technology, University of Nanjing, Center for Nanotechnology Innovation, @NEST (CNI), National Enterprise for nanoScience and nanoTechnology (NEST), Scuola Normale Superiore di Pisa (SNS)-Scuola Universitaria Superiore Sant'Anna [Pisa] (SSSUP)-Istituto Italiano di Tecnologia (IIT)-Consiglio Nazionale delle Ricerche [Pisa] (CNR PISA)-Scuola Normale Superiore di Pisa (SNS)-Scuola Universitaria Superiore Sant'Anna [Pisa] (SSSUP)-Istituto Italiano di Tecnologia (IIT)-Consiglio Nazionale delle Ricerche [Pisa] (CNR PISA), Unité Analyse et Traitement de l'Information (UNATI), Service NEUROSPIN (NEUROSPIN), 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-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, Neuroimagerie cognitive - Psychologie cognitive expérimentale (UNICOG-U992), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Paris Saclay (COmUE), Institut cellule souche et cerveau (U846 Inserm - UCBL1), Royal Netherlands Academy of Arts and Sciences (KNAW), East China Normal University [Shangaï] (ECNU), The Computational, Cognitive and Clinical Neuroimaging Lab, Imperial College London, Medical Research Council Harwell (Mammalian Genetics Unit and Mary Lyon Centre), Medical Research Counc, Station de primatologie (SP), Centre National de la Recherche Scientifique (CNRS), Institute of Language, Communication and the Brain (ILCB), The University of Western Ontario, Instituto de Neurobiología, Universidad Nacional Autónoma de México (UNAM), Institute of integrative biology (Liverpool), University of Liverpool, McGovern Institute for Brain Research [Cambridge], Massachusetts Institute of Technology (MIT), University of Cambridge [UK] (CAM), Rockefeller University [New York], McConnell Brain Imaging Centre (MNI), Montreal Neurological Institute and Hospital, McGill University = Université McGill [Montréal, Canada]-McGill University = Université McGill [Montréal, Canada], Laboratory for Neuro- and Psychofysiology, katho, Institut du Cerveau et de la Moëlle Epinière = Brain and Spine Institute (ICM), Institut National de la Santé et de la Recherche Médicale (INSERM)-CHU Pitié-Salpêtrière [AP-HP], Sorbonne Université-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), University of York [York, UK], Centre de Recherche de l'Institut du Cerveau et de la Moelle épinière (CRICM), Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Pierre et Marie Curie - Paris 6 (UPMC), Génétique Humaine et Fonctions Cognitives, Institut Pasteur [Paris]-Centre National de la Recherche Scientifique (CNRS), Tianjin University of Science and Technology (TUST), Child Mind Institute, Center for Magnetic Resonance Research [Minneapolis] (CMRR), University of Minnesota Medical School, University of Minnesota System-University of Minnesota System, Institut cellule souche et cerveau / Stem Cell and Brain Research Institute (U1208 Inserm - UCBL1 / SBRI), Icahn School of Medicine at Mount Sinai [New York] (MSSM), University Medical Center [Utrecht], Radboud university [Nijmegen], Chaire Psychologie cognitive expérimentale, Centre de recherche en neurosciences de Lyon (CRNL), Université de Lyon-Université de Lyon-Université Jean Monnet [Saint-Étienne] (UJM)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), University of St Andrews [Scotland], Stockholm University, Hôpital du Bocage, Centre Hospitalier Universitaire de Dijon - Hôpital François Mitterrand (CHU Dijon), Princeton University, Utrecht University [Utrecht], Netherlands Institute for Neuroscience, Wellcome Trust Centre for Integrative Neuroimaging (WIN - FMRIB), University of Oxford [Oxford], National Institute of Environmental Health Sciences [Durham] (NIEHS-NIH), National Institutes of Health [Bethesda] (NIH), Oregon National Primate Research Center (ONPRC), California Institute of Technology (CALTECH), Johns Hopkins University (JHU), The PRIMatE Data Exchange (PRIME-DE) Global Collaboration Workshop and Consortium, ANR-16-CONV-0002,ILCB,ILCB: Institute of Language Communication and the Brain(2016), Amsterdam Neuroscience - Complex Trait Genetics, Amsterdam Neuroscience - Cellular & Molecular Mechanisms, Complex Trait Genetics, Centre National de la Recherche Scientifique (CNRS)-Arts et Métiers Paristech ENSAM Aix-en-Provence-Université de Toulon (UTLN)-Aix Marseille Université (AMU), Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Institut National de la Recherche Agronomique (INRA), and Vanduffel, Wim

Subjects
Primates, 0301 basic medicine, [SDV.IB.IMA]Life Sciences [q-bio]/Bioengineering/Imaging, education, Neuroimaging, Article, [SPI]Engineering Sciences [physics], 03 medical and health sciences, 0302 clinical medicine, London, Psychology, Animals, Humans, Sociology, ComputingMilieux_MISCELLANEOUS, Cognitive science, Science & Technology, Human Connectome Project, [SDV.NEU.PC]Life Sciences [q-bio]/Neurons and Cognition [q-bio.NC]/Psychology and behavior, Action, intention, and motor control, Information Dissemination, General Neuroscience, Neurosciences, Brain, [SDV.NEU.SC]Life Sciences [q-bio]/Neurons and Cognition [q-bio.NC]/Cognitive Sciences, Congresses as Topic, Nonhuman primate, 030104 developmental biology, [SDV.NEU]Life Sciences [q-bio]/Neurons and Cognition [q-bio.NC], Neurosciences & Neurology, Life Sciences & Biomedicine, [SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing, 030217 neurology & neurosurgery
Abstract

Contains fulltext : 217200.pdf (Publisher’s version ) (Closed access) Nonhuman primate neuroimaging is on the cusp of a transformation, much in the same way its human counterpart was in 2010, when the Human Connectome Project was launched to accelerate progress. Inspired by an open data-sharing initiative, the global community recently met and, in this article, breaks through obstacles to define its ambitions. 4 p.

Published
2020
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22. Hierarchical associations of alcohol use disorder symptoms in late adolescence with markers during early adolescence

Author

Herta Flor, Dimitri Papadopoulos Orfanos, Michael N. Smolka, Jean-Luc Martinot, Antoine Grigis, Robert Whelan, Marie-Laure Paillère Martinot, Tomáš Paus, Nina Lisofsky, Bernd Ittermann, Gunter Schumann, Gareth J. Barker, Frauke Nees, Sylvane Desrivières, Simone Kühn, Arun L.W. Bokde, Christian Büchel, Erin Burke Quinlan, Andreas Heinz, Uli Bromberg, Penny A. Gowland, Henrik Walter, Tobias Banaschewski, Luise Poustka, Jürgen Gallinat, Juliane H. Fröhner, Rüdiger Brühl, and Hugh Garavan

Subjects
Male, Adolescent, Alcohol Drinking, media_common.quotation_subject, Psychological intervention, Medicine (miscellaneous), Human sexuality, Alcohol use disorder, Toxicology, Life Change Events, 03 medical and health sciences, Young Adult, 0302 clinical medicine, Cognition, Risk Factors, medicine, Personality, Humans, 030212 general & internal medicine, media_common, Alcohol Use Disorders Identification Test, medicine.disease, Europe, Psychiatry and Mental health, Clinical Psychology, Alcoholism, Adolescent Behavior, Residence, Temperament and Character Inventory, Female, Psychology, Alcohol consumption, 030217 neurology & neurosurgery, Algorithms, Clinical psychology
Abstract

High adolescent alcohol consumption is predictive for alcohol problems later in life. To tailor interventions, early identification of risk groups for adolescent alcohol consumption is important. The IMAGEN dataset was utilized to investigate predictors for problematic alcohol consumption at age 18-20 years as a function self and parental personality and drug-related measures as well as life-events and cognitive variables all assessed at age 14 years (N = 1404). For this purpose the binary partitioning algorithm ctree was used in an explorative analysis. The algorithm recursively selects significant input variables and splits the outcome variable based on these, yielding a conditional inference tree. Four significant split variables, namely Place of residence, the Disorganization subscale of the Temperament and Character Inventory, Sex, and the Sexuality subscale of the life-events questionnaire were found to distinguish between adolescents scoring high or low on the Alcohol Use Disorders Identification Test about five years later (all p 0.001). The analyis adds to the literature on predictors of adolescent drinking problems using a large European sample. The identified split variables could easily be collected in community samples. If their validity is proven in independent samples, they could facilitate intervention studies in the field of adolescent alcohol prevention.

Published
2020

23. Prospective cohort study of early biosignatures of response to lithium in bipolar-I-disorders: overview of the H2020-funded R-LiNK initiative

Author

Diego Hidalgo-Mazzei, Matthieu Resche-Rigon, Fiona E. Smith, Cristina Mora, Aitana García-Estela, Maj Vinberg, Erik Pålsson, Adele Ferro, Andrew M. Blamire, Andreas Reif, Monica Mazzelli, Margrethe Collier Høegh, Eduard Vieta, Fawzi Boumezbeur, Caroline Dubertret, Petter Jakobsen, Edouard Duchesnay, Jan Scott, Klara Coello, Antoine Grigis, Thorsten Müller, Nicolas Mazer, Allan H. Young, Ole A. Andreassen, Nils Eiel Steen, Ketil J. Oedegaard, Peter E. Thelwall, Rebecca Strawbridge, Yann Cointepas, Letizia Squarcina, Frank Bellivier, Fanny Senner, Sergi Papiol, Farah Klöhn-Saghatolislam, David A. Cousins, Michael Bauer, Francesc Colom, Jose Manuel Goikolea, Emmanuel Haffen, Marie Chupin, Thomas G. Schulze, Ute Lewitzka, Bruno Etain, Annamaria Cattaneo, Lars Vedel Kessing, Lars T. Westlye, Michèle Wessa, Trine Vik Lagerberg, Ashley Lutticke, Paolo Brambilla, Philipp Ritter, C. Varo, Leif Oltedal, Nadia Cattane, Janos Kalman, Roberto Rossi, Dimitri Papadopoulos Orfanos, Víctor Pérez-Sola, Mikael Landén, Estanislao Mur-Mila, Djamila Bennabi, Newcastle University [Newcastle], Université Paris Diderot - Paris 7 (UPD7), King‘s College London, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Universitat de Barcelona (UB), Centre de Recherche Épidémiologie et Statistique Sorbonne Paris Cité (CRESS (U1153 / UMR_A_1125 / UMR_S_1153)), Université Paris Diderot - Paris 7 (UPD7)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut National de la Recherche Agronomique (INRA)-Université Paris Descartes - Paris 5 (UPD5)-Université Sorbonne Paris Cité (USPC), Service de biostatistique et information médicale de l’hôpital Saint Louis (Equipe ECSTRA) (SBIM), Université Paris Diderot - Paris 7 (UPD7)-Institut National de la Santé et de la Recherche Médicale (INSERM)-CHU Saint Louis [APHP]-Institut national du cancer [Boulogne] (INCA), Optimisation Thérapeutique en Neuropsychopharmacologie (VariaPsy - U1144), Université Paris Diderot - Paris 7 (UPD7)-Université Paris Descartes - Paris 5 (UPD5)-Institut National de la Santé et de la Recherche Médicale (INSERM), Hopital Saint-Louis, Assistance Publique – Hôpitaux de Paris (AP-HP), Centre d'Investigation Clinique de Besançon (CICB), Centre Hospitalier Régional Universitaire [Besançon] (CHRU Besançon)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Etablissement Français du Sang Bourgogne Franche-Comté-Université de Franche-Comté (UFC), Université Bourgogne Franche-Comté [COMUE] (UBFC), Service NEUROSPIN (NEUROSPIN), 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, CATI Multicenter Neuroimaging Platform (CATI), Institut du Cerveau et de la Moëlle Epinière = Brain and Spine Institute (ICM), Institut National de la Santé et de la Recherche Médicale (INSERM)-CHU Pitié-Salpêtrière [APHP]-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), Hopital Louis Mourier - AP-HP [Colombes], Institut de psychiatrie et neurosciences (U894 / UMS 1266), Université Paris Descartes - Paris 5 (UPD5)-Institut National de la Santé et de la Recherche Médicale (INSERM), Laboratoire de Neuroimagerie Assistée par Ordinateur (LNAO), Commissariat à l'énergie atomique et aux énergies alternatives (CEA), Unité Analyse et Traitement de l'Information (UNATI), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris-Saclay-Direction de Recherche Fondamentale (CEA) (DRF (CEA)), Max-Planck-Institut, This project has received funding from the European Union Horizon 2020 research and innovation program ((EU. 3.1.1. Understanding health, wellbeing and disease: Grant No 754907), Institut National de la Recherche Agronomique (INRA)-Université Paris Diderot - Paris 7 (UPD7)-Université Paris Descartes - Paris 5 (UPD5)-Université Sorbonne Paris Cité (USPC)-Institut National de la Santé et de la Recherche Médicale (INSERM), Université Paris Diderot - Paris 7 (UPD7)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut national du cancer [Boulogne] (INCA)-Hopital Saint-Louis [AP-HP] (AP-HP), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP), Variabilité de réponse aux Psychotropes (VariaPsy - U1144), Hopital Saint-Louis [AP-HP] (AP-HP), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP), Centre d'Investigation Clinique de Besançon (Inserm CIC 1431), Centre Hospitalier Régional Universitaire de Besançon (CHRU Besançon)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Etablissement français du sang [Bourgogne-Franche-Comté] (EFS BFC)-Université de Franche-Comté (UFC), Université Bourgogne Franche-Comté [COMUE] (UBFC)-Université Bourgogne Franche-Comté [COMUE] (UBFC), 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), Institut du Cerveau = Paris Brain Institute (ICM), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Institut National de la Santé et de la Recherche Médicale (INSERM)-CHU Pitié-Salpêtrière [AP-HP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Sorbonne Université (SU)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), Hôpital Louis Mourier - AP-HP [Colombes], Centre de Psychiatrie et Neurosciences (U894), Université Paris Diderot - Paris 7 (UPD7)-Université Sorbonne Paris Cité (USPC)-Université Paris Descartes - Paris 5 (UPD5)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut National de la Recherche Agronomique (INRA), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Institut national du cancer [Boulogne] (INCA)-Université Paris Diderot - Paris 7 (UPD7)-Institut National de la Santé et de la Recherche Médicale (INSERM), Université Paris Diderot - Paris 7 (UPD7)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Paris Descartes - Paris 5 (UPD5), Université de Franche-Comté (UFC), Université Bourgogne Franche-Comté [COMUE] (UBFC)-Université Bourgogne Franche-Comté [COMUE] (UBFC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre Hospitalier Régional Universitaire de Besançon (CHRU Besançon)-Etablissement français du sang [Bourgogne-Franche-Comté] (EFS [Bourgogne-Franche-Comté]), Institut National de la Santé et de la Recherche Médicale (INSERM)-CHU Pitié-Salpêtrière [AP-HP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), Université Paris Diderot - Paris 7 (UPD7)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut national du cancer [Boulogne] (INCA)-CHU Saint Louis [APHP], and Université Paris Descartes - Paris 5 (UPD5)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Paris Diderot - Paris 7 (UPD7)

Subjects
medicine.medical_specialty, Lithium (medication), [SDV]Life Sciences [q-bio], Psychological intervention, Omics, Neuroimaging, Review, Lithium, Digital, lcsh:RC321-571, 03 medical and health sciences, 0302 clinical medicine, medicine, Prospective cohort study, Intensive care medicine, lcsh:Neurosciences. Biological psychiatry. Neuropsychiatry, Biological Psychiatry, Personalization, business.industry, lcsh:QP351-495, Response, Actigraphy, Precision, 3. Good health, 030227 psychiatry, Psychiatry and Mental health, lcsh:Neurophysiology and neuropsychology, Phenotype, Mood, Tolerability, Bipolar, Biomarker (medicine), business, 030217 neurology & neurosurgery, medicine.drug
Abstract

Background Lithium is recommended as a first line treatment for bipolar disorders. However, only 30% of patients show an optimal outcome and variability in lithium response and tolerability is poorly understood. It remains difficult for clinicians to reliably predict which patients will benefit without recourse to a lengthy treatment trial. Greater precision in the early identification of individuals who are likely to respond to lithium is a significant unmet clinical need. Structure The H2020-funded Response to Lithium Network (R-LiNK; http://www.r-link.eu.com/) will undertake a prospective cohort study of over 300 individuals with bipolar-I-disorder who have agreed to commence a trial of lithium treatment following a recommendation by their treating clinician. The study aims to examine the early prediction of lithium response, non-response and tolerability by combining systematic clinical syndrome subtyping with examination of multi-modal biomarkers (or biosignatures), including omics, neuroimaging, and actigraphy, etc. Individuals will be followed up for 24 months and an independent panel will assess and classify each participants’ response to lithium according to predefined criteria that consider evidence of relapse, recurrence, remission, changes in illness activity or treatment failure (e.g. stopping lithium; new prescriptions of other mood stabilizers) and exposure to lithium. Novel elements of this study include the recruitment of a large, multinational, clinically representative sample specifically for the purpose of studying candidate biomarkers and biosignatures; the application of lithium-7 magnetic resonance imaging to explore the distribution of lithium in the brain; development of a digital phenotype (using actigraphy and ecological momentary assessment) to monitor daily variability in symptoms; and economic modelling of the cost-effectiveness of introducing biomarker tests for the customisation of lithium treatment into clinical practice. Also, study participants with sub-optimal medication adherence will be offered brief interventions (which can be delivered via a clinician or smartphone app) to enhance treatment engagement and to minimize confounding of lithium non-response with non-adherence. Conclusions The paper outlines the rationale, design and methodology of the first study being undertaken by the newly established R-LiNK collaboration and describes how the project may help to refine the clinical response phenotype and could translate into the personalization of lithium treatment.

Published
2019
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24. Prospective Associations Between Diffusion Tensor Imaging Parameters and Frailty in Older Adults

Author

Mathieu, Maltais, Philipe, de Souto Barreto, Lisa, Perus, Jean-François, Mangin, Antoine, Grigis, Marie, Chupin, Ali, Bouyahia, Audrey, Gabelle, Julien, Delrieux, Yves, Rolland, Bruno, Vellas, Sylvie, Caspar-Bauguil, Service NEUROSPIN (NEUROSPIN), 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, Laboratoire de Neuroimagerie Assistée par Ordinateur (LNAO), Commissariat à l'énergie atomique et aux énergies alternatives (CEA), Service Hospitalier Frédéric Joliot (SHFJ), Center for Neuroscience and Behavioral Medicine, Children's National Medical Center, Unité Baobab (BAOBAB), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris-Saclay-Direction de Recherche Fondamentale (CEA) (DRF (CEA)), Centre de Recherche de l'Institut du Cerveau et de la Moelle épinière (CRICM), Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Equipe NEMESIS - Centre de Recherches de l'Institut du Cerveau et de la Moelle épinière (NEMESIS-CRICM), Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Institut de génétique humaine (IGH), Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS), Centre Hospitalier Régional Universitaire [Montpellier] (CHRU Montpellier), Epidémiologie et analyses en santé publique : risques, maladies chroniques et handicaps (LEASP), Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut National de la Santé et de la Recherche Médicale (INSERM), CHU Toulouse [Toulouse], 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), Building large instruments for neuroimaging: from population imaging to ultra-high magnetic fields (BAOBAB), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Centre National de la Recherche Scientifique (CNRS), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut National de la Santé et de la Recherche Médicale (INSERM), Centre Hospitalier Universitaire de Toulouse (CHU Toulouse), and ANR-16-IDEX-0006,MUSE,MUSE(2016)

Subjects
Male, medicine.medical_specialty, brain health, Internal capsule, External capsule, diffusion magnetic resonance imagingfrailty, [SDV]Life Sciences [q-bio], physical capacity, White matter, 03 medical and health sciences, 0302 clinical medicine, Internal medicine, Fractional anisotropy, Fasciculus, Medicine, Dementia, Humans, 030212 general & internal medicine, Prospective Studies, Aged, Aged, 80 and over, biology, Frailty, business.industry, Superior longitudinal fasciculus, medicine.disease, biology.organism_classification, White Matter, 3. Good health, medicine.anatomical_structure, Diffusion Magnetic Resonance Imaging, Cardiology, Disease Progression, Anisotropy, Female, Geriatrics and Gerontology, business, 030217 neurology & neurosurgery, Diffusion MRI
Abstract

International audience; BACKGROUND: Cross-sectional associations have been found between frail individuals and worse white matter (WM) integrity. However, the prospective association between WM integrity and frailty is still unclear. Our objectives were to measure associations between WM integrity using diffusion tensor imaging (DTI) and the 5-year worsening of frailty in community-dwelling older adults. DESIGN: Secondary analysis of the randomized controlled Multidomain Alzheimer Preventive Trial (MAPT). SETTING: Thirteen memory centers in France and Monaco between 2008 and 2011. PARTICIPANTS: Participants (mean age = 74.7 ± 3.9 years) with no dementia at baseline who had functional magnetic resonance imaging performed as part of the MAPT study (n = 227). MEASUREMENTS: Fractional anisotropy and mean diffusivity (MD), axial diffusivity (AxD), and radial diffusivity (RD) were acquired for 10 different brain regions. Frailty was assessed by the Fried frailty phenotype (score from 0 to 5, higher is worse) at up to seven time points for 5 years. Mixed effect ordinal logistic regression model was used to assess the prospective association between DTI parameters (independent variables) and frailty (dependent variable). All the analyses were adjusted for age, sex, baseline total intracranial volume, and the presence of one of the following cardiovascular risk factors (hypertension, diabetes, and/or hypercholesterolemia). RESULTS: A statistically significant association was found between the RD, AxD, and MD for different brain regions (anterior limb of internal capsule, external capsule, posterior corona radiata, posterior thalamic radiation, superior corona radiata, superior frontal occipital fasciculus, and superior longitudinal fasciculus) and worsening of frailty over 5 years after adjusting for multiple comparisons. CONCLUSIONS: This is the first study to show that WM integrity is associated with frailty in older adults. The mechanisms related to these results require further investigation. J Am Geriatr Soc 68:1050-1055, 2020.

Published
2019
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25. The higher the grey matter volume the larger the slope increase

Author

Gunter Schumann, Jürgen Gallinat, Henrik Walter, Tomáš Paus, Arun Bodke, Anna Mascharek, Juliane H. Fröhner, Christian Büchel, Bernd Ittermann, Luise Poustka, Michael N. Smolka, Sabina Millenet, Andreas Heinz, Jean-Luc Martinot, Frauke Nees, Herta Flor, Sylvane Desrivières, Antoine Grigis, Robert Whelan, Simone Kühn, Tobias Banaschewski, Ulman Lindenberger, Penny A. Gowland, Hugh Garavan, Dimitri Papadopoulos Orfanos, Uli Bromberg, Erin Burke Quinlan, and IMAGEN Consortium

Subjects
Male, Poison control, Alcohol, Underage Drinking, Occupational safety and health, chemistry.chemical_compound, 0302 clinical medicine, Cerebellum, Medicine, Biology (General), 10. No inequality, Brain Mapping, Alcohol Use Disorders Identification Test, General Neuroscience, Brain, Human factors and ergonomics, General Medicine, Magnetic Resonance Imaging, Alcoholism, Female, Research Article, Human, Clinical psychology, Adolescent, QH301-705.5, Science, General Biochemistry, Genetics and Molecular Biology, Structural equation modeling, 03 medical and health sciences, Neuroimaging, Injury prevention, Humans, adolescence, alcohol use, brain structure, human, neuroscience, structural equation modelling, latent growth curve modelling, General Immunology and Microbiology, business.industry, 030227 psychiatry, chemistry, Alcohols, Caudate Nucleus, business, 030217 neurology & neurosurgery, Neuroscience
Abstract

Adolescence is a common time for initiation of alcohol use and development of alcohol use disorders. The present study investigates neuroanatomical predictors for trajectories of future alcohol use based on a novel voxel-wise whole-brain structural equation modeling framework. In 1814 healthy adolescents of the IMAGEN sample, the Alcohol Use Disorder Identification Test (AUDIT) was acquired at three measurement occasions across five years. Based on a two-part latent growth curve model, we conducted whole-brain analyses on structural MRI data at age 14, predicting change in alcohol use score over time. Higher grey-matter volumes in the caudate nucleus and the left cerebellum at age 14 years were predictive of stronger increase in alcohol use score over 5 years. The study is the first to demonstrate the feasibility of running separate voxel-wise structural equation models thereby opening new avenues for data analysis in brain imaging., eLife digest Puberty is a time of transformation. Physical changes in the body occur alongside changes in personality and behaviour. Compared to children, adolescents tend to be risk-takers and novelty-seekers. They crave new sensations and experiences, as well as social interaction with their peers. It is around puberty that many people try alcohol for the first time. But it is not clear why people differ in their drinking habits, and why a small minority of young adults go on to become dependent on alcohol. Part of the answer may lie in changes in the brain. Differences in the size and structure of brain regions contribute to differences in behaviour between individuals. During adolescence, the brain undergoes extensive re-modelling. It forms new connections, while also pruning away connections that are unused. Could differences in brain structure at puberty lead to differences in alcohol consumption in early adulthood? Kühn et al. scanned the brains of about 1,800 healthy adolescents at the age of 14 and then again at 19 (within the context of the IMAGEN study). At three time points, the teenagers also filled in questionnaires about their use of alcohol. Two areas of the brain – the caudate nucleus and the left cerebellum – were larger at age 14 in teenagers who would increase their alcohol consumption by age 19. The larger the areas at age 14, the bigger the increase in alcohol consumption over time. Notably, there was no relationship between the size of either brain area at the age of 14 and how much alcohol the individuals drank at the same age. These results may help us to understand why some young adults develop harmful drinking habits, whereas most do not. The findings are part of a large and complex picture. Other factors, such as social influences, also shape alcohol consumption. However, the findings of Kühn et al. suggest that differences in brain structure may make some individuals more likely to increase how much alcohol they drink than others. Understanding these biological differences could help researchers to develop measures to prevent addiction in young adults.

Published
2019
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26. Author response: Predicting development of adolescent drinking behaviour from whole brain structure at 14 years of age

Author

Herta Flor, Antoine Grigis, Bernd Ittermann, Jürgen Gallinat, Dimitri Papadopoulos Orfanos, Michael N. Smolka, Frauke Nees, Anna Mascharek, Ulman Lindenberger, Henrik Walter, Sylvane Desrivières, Luise Poustka, Penny A. Gowland, Gunter Schumann, Erin Burke Quinlan, Simone Kühn, Juliane H. Fröhner, Sabina Millenet, Tomáš Paus, Andreas Heinz, Robert Whelan, Jean-Luc Martinot, Christian Büchel, Arun Bodke, Tobias Banaschewski, Hugh Garavan, and Uli Bromberg

Subjects
Drinking behaviour, 03 medical and health sciences, 0302 clinical medicine, 030508 substance abuse, 030212 general & internal medicine, 0305 other medical science, Psychology, Developmental psychology
Published
2019
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27. Increased and Decreased Superficial White Matter Structural Connectivity in Schizophrenia and Bipolar Disorder

Author

Pamela Guevara, Nicole Labra, Nora Hamdani, Jean-François Mangin, Antoine Grigis, Josselin Houenou, Marine Delavest, Frank Bellivier, Samuel Sarrazin, Ellen Ji, Miguel Guevara, Ryad Tamouza, Cyril Poupon, and Marion Leboyer

Subjects
Adult, Male, Bipolar Disorder, Precuneus, Gyrus Cinguli, White matter, 03 medical and health sciences, Young Adult, 0302 clinical medicine, Parietal Lobe, Fractional anisotropy, Neural Pathways, medicine, Humans, Default mode network, Language, Cerebral Cortex, business.industry, Precentral gyrus, Middle Aged, medicine.disease, Magnetic Resonance Imaging, White Matter, Broca Area, Temporal Lobe, 030227 psychiatry, Frontal Lobe, Psychiatry and Mental health, Affect, medicine.anatomical_structure, Diffusion Tensor Imaging, Memory, Short-Term, Schizophrenia, Case-Control Studies, Anisotropy, Female, business, Neuroscience, 030217 neurology & neurosurgery, Tractography, Diffusion MRI, Regular Articles
Abstract

Schizophrenia (SZ) and bipolar disorder (BD) are often conceptualized as “disconnection syndromes”, with substantial evidence of abnormalities in deep white matter tracts, forming the substrates of long-range connectivity, seen in both disorders. However, the study of superficial white matter (SWM) U-shaped short-range tracts remained challenging until recently, although findings from post-mortem studies suggest they are likely integral components of SZ and BD neuropathology. This diffusion weighted imaging (DWI) study aimed to investigate SWM microstructure in vivo in both SZ and BD for the first time. We performed whole brain tractography in 31 people with SZ, 32 people with BD and 54 controls using BrainVISA and Connectomist 2.0. Segmentation and labelling of SWM tracts were performed using a novel, comprehensive U-fiber atlas. Analysis of covariances yielded significant generalized fractional anisotropy (gFA) differences for 17 SWM bundles in frontal, parietal and temporal cortices. Post hoc analyses showed gFA reductions in both patient groups as compared with controls in bundles connecting regions involved in language processing, mood regulation, working memory and motor function (pars opercularis, insula, anterior cingulate, precentral gyrus). We also found increased gFA in SZ patients in areas overlapping the default mode network (inferior parietal, middle temporal, precuneus), supporting functional hyperconnectivity of this network evidenced in SZ. We thus illustrate that short U-fibers are vulnerable to the pathological processes in major psychiatric illnesses, encouraging improved understanding of their anatomy and function.

Published
2019

28. Pubertal maturation and sex effects on the default-mode network connectivity implicated in mood dysregulation

Author

Christian Büchel, Herve Lemaitre, Monique Ernst, Andreas Heinz, Christian Grillon, Uli Bromberg, Sylvane Desrivières, Anna Cattrell, Frauke Nees, Gunter Schumann, Hugh Garavan, Argyris Stringaris, Eric Artiges, Patricia J. Conrod, Arun L.W. Bokde, Penny A. Gowland, Tahmine Fadai, Henrik Walter, Tobias Banaschewski, Viola Kappel, Rüdiger Brühl, Brenda E. Benson, Jani Penttilä, Betteke van Noort, Robert Whelan, Jean-Luc Martinot, Herta Flor, Antoine Grigis, Tiffany R. Lago, Marie-Laure Paillère Martinot, Adam X. Gorka, Yvonne Grimmer, Ruben Miranda, Maren Struve, Michael N. Smolka, Juergen Gallinat, Luise Poustka, Dimitri Papadopoulos-Orfanos, Université de Montréal. Faculté de médecine. Département de psychiatrie et d'addictologie, HYKS erva, and Päijät-Häme Welfare Consortium

Subjects
Male, 0301 basic medicine, Nerve net, Brain mapping, 3124 Neurology and psychiatry, 0302 clinical medicine, Neural Pathways, Sexual maturity, Sexual Maturation, Default mode network, Brain Mapping, LIFETIME PREVALENCE, Brain, FUNCTIONAL CONNECTIVITY, DEPRESSION, Magnetic Resonance Imaging, ADOLESCENT BRAIN, Psychiatry and Mental health, medicine.anatomical_structure, Female, Psychology, WHITE-MATTER, Clinical psychology, BRAIN-DEVELOPMENT, Adolescent, DISORDERS, POSTERIOR CINGULATE CORTEX, Gyrus Cinguli, Article, lcsh:RC321-571, 03 medical and health sciences, Cellular and Molecular Neuroscience, AGE, Sex Factors, Functional neuroimaging, medicine, Humans, lcsh:Neurosciences. Biological psychiatry. Neuropsychiatry, Biological Psychiatry, RESTING-STATE NETWORKS, Depressive Disorder, Functional Neuroimaging, medicine.disease, Affect, 030104 developmental biology, Mood, Mood disorders, Posterior cingulate, Self Report, Nerve Net, 030217 neurology & neurosurgery
Abstract

This study examines the effects of puberty and sex on the intrinsic functional connectivity (iFC) of brain networks, with a focus on the default-mode network (DMN). Consistently implicated in depressive disorders, the DMN’s function may interact with puberty and sex in the development of these disorders, whose onsets peak in adolescence, and which show strong sex disproportionality (females > males). The main question concerns how the DMN evolves with puberty as a function of sex. These effects are expected to involve within- and between-network iFC, particularly, the salience and the central-executive networks, consistent with the Triple-Network Model. Resting-state scans of an adolescent community sample (n = 304, male/female: 157/147; mean/std age: 14.6/0.41 years), from the IMAGEN database, were analyzed using the AFNI software suite and a data reduction strategy for the effects of puberty and sex. Three midline regions (medial prefrontal, pregenual anterior cingulate, and posterior cingulate), within the DMN and consistently implicated in mood disorders, were selected as seeds. Within- and between-network clusters of the DMN iFC changed with pubertal maturation differently in boys and girls (puberty-X-sex). Specifically, pubertal maturation predicted weaker iFC in girls and stronger iFC in boys. Finally, iFC was stronger in boys than girls independently of puberty. Brain–behavior associations indicated that lower connectivity of the anterior cingulate seed predicted higher internalizing symptoms at 2-year follow-up. In conclusion, weaker iFC of the anterior DMN may signal disconnections among circuits supporting mood regulation, conferring risk for internalizing disorders.

Published
2019
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29. 'Plis de passage' Deserve a Role in Models of the Cortical Folding Process

Author

Antoine Grigis, Yann Le Guen, Clara Fischer, Vincent Frouin, Miguel Guevara, Nicole Labra, William D. Hopkins, Zhong Yi Sun, Denis Rivière, Jean Régis, Jean-François Mangin, Unité Baobab (BAOBAB), Service NEUROSPIN (NEUROSPIN), 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-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, Centre d'Acquisition et de Traitement des Images [Paris], Commissariat à l'énergie atomique et aux énergies alternatives (CEA), Building large instruments for neuroimaging: from population imaging to ultra-high magnetic fields (BAOBAB), Université Paris-Saclay-Direction de Recherche Fondamentale (CEA) (DRF (CEA)), and Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Centre National de la Recherche Scientifique (CNRS)

Subjects
Male, Cortical folding, Review, Biology, Models, Biological, 03 medical and health sciences, Pli de passage, 0302 clinical medicine, Sulcal pits, Connectome, Humans, Radiology, Nuclear Medicine and imaging, Process (anatomy), 030304 developmental biology, Cerebral Cortex, 0303 health sciences, Human Connectome Project, Radiological and Ultrasound Technology, Central sulcus, Folding (DSP implementation), Hand, Magnetic Resonance Imaging, Sensorimotor Areas, Sulcal roots, Neurology, [SDV.NEU]Life Sciences [q-bio]/Neurons and Cognition [q-bio.NC], Neurology (clinical), Occipital Lobe, Sensorimotor Cortex, Anatomy, Neuroscience, 030217 neurology & neurosurgery
Abstract

Cortical folding is a hallmark of brain topography whose variability across individuals remains a puzzle. In this paper, we call for an effort to improve our understanding of the pli de passage phenomenon, namely annectant gyri buried in the depth of the main sulci. We suggest that plis de passage could become an interesting benchmark for models of the cortical folding process. As an illustration, we speculate on the link between modern biological models of cortical folding and the development of the Pli de Passage Frontal Moyen (PPFM) in the middle of the central sulcus. For this purpose, we have detected nine interrupted central sulci in the Human Connectome Project dataset, which are used to explore the organization of the hand sensorimotor areas in this rare configuration of the PPFM.

Published
2019
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30. Amygdalar reactivity is associated with prefrontal cortical thickness in a large population-based sample of adolescents

Author

Juliane H. Fröhner, Bernd Ittermann, James J. Hudziak, Henrik Walter, Tomáš Paus, Jean-Luc Martinot, Alan C. Evans, Sabina Millenet, Vladimir S. Fonov, Gunter Schumann, Sylvane Desrivières, Frauke Nees, Andreas Heinz, Matthew D. Albaugh, Michael N. Smolka, Alexandra Potter, Luise Poustka, Arun L.W. Bokde, Penny A. Gowland, Philip A. Spechler, Catherine Orr, Christian Büchel, Herta Flor, Claude Lepage, Erin Burke Quinlan, Antoine Grigis, Hugh Garavan, Bader Chaarani, Robert Whelan, Scott Mackey, Tobias Banaschewski, Marie-Laure Paillère Martinot, Dimitri Papadopoulos Orfanos, Uli Bromberg, and Pierre Rioux

Subjects
Male, Middle temporal gyrus, Emotions, Social Sciences, Anger, Adolescents, Diagnostic Radiology, Families, 0302 clinical medicine, Functional Magnetic Resonance Imaging, Image Processing, Computer-Assisted, Medicine and Health Sciences, Psychology, Premovement neuronal activity, Prefrontal cortex, Children, Cerebral Cortex, Brain Mapping, education.field_of_study, Multidisciplinary, medicine.diagnostic_test, Radiology and Imaging, Amygdala, Functional magnetic resonance imaging, Magnetic resonance imaging, Neuroimaging, Face, 05 social sciences, Brain, Magnetic Resonance Imaging, Temporal Lobe, medicine.anatomical_structure, Medicine, Female, Anatomy, Research Article, Adolescent, Imaging Techniques, Science, Population, Prefrontal Cortex, Research and Analysis Methods, 050105 experimental psychology, 03 medical and health sciences, Diagnostic Medicine, Functional neuroimaging, medicine, Humans, 0501 psychology and cognitive sciences, education, Biology and Life Sciences, Age Groups, People and Places, Population Groupings, Head, Neuroscience, 030217 neurology & neurosurgery
Abstract

In structural neuroimaging studies, reduced cerebral cortical thickness in orbital and ventromedial prefrontal regions is frequently interpreted as reflecting an impaired ability to downregulate neuronal activity in the amygdalae. Unfortunately, little research has been conducted in order to test this conjecture. We examine the extent to which amygdalar reactivity is associated with cortical thickness in a population-based sample of adolescents. Data were obtained from the IMAGEN study, which includes 2,223 adolescents. While undergoing functional neuroimaging, participants passively viewed video clips of a face that started from a neutral expression and progressively turned angry, or, instead, turned to a second neutral expression. Left and right amygdala ROIs were used to extract mean BOLD signal change for the angry minus neutral face contrast for all subjects. T1-weighted images were processed through the CIVET pipeline (version 2.1.0). In variable-centered analyses, local cortical thickness was regressed against amygdalar reactivity using first and second-order linear models. In a follow-up person-centered analysis, we defined a "high reactive" group of participants based on mean amygdalar BOLD signal change for the angry minus neutral face contrast. Between-group differences in cortical thickness were examined ("high reactive" versus all other participants). A significant association was revealed between the continuous measure of amygdalar reactivity and bilateral ventromedial prefrontal cortical thickness in a second-order linear model (p < 0.05, corrected). The "high reactive" group, in comparison to all other participants, possessed reduced cortical thickness in bilateral orbital and ventromedial prefrontal cortices, bilateral anterior temporal cortices, left caudal middle temporal gyrus, and the left inferior and middle frontal gyri (p < 0.05, corrected). Results are consistent with non-human primate studies, and provide empirical support for an association between reduced prefrontal cortical thickness and amygdalar reactivity. Future research will likely benefit from investigating the degree to which psychopathology qualifies relations between prefrontal cortical structure and amygdalar reactivity. peerReviewed

Published
2019
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31. Heritability of surface area and cortical thickness: a comparison between the Human Connectome Project and the UK Biobank dataset

Author

Antoine Grigis, Slim Karkar, Vincent Frouin, Yann Le Guen, Cathy Philippe, Jean-François Mangin, Unité Analyse et Traitement de l'Information (UNATI), Service NEUROSPIN (NEUROSPIN), 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-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, European Project: 720270,H2020 Pilier Excellent Science,H2020-Adhoc-2014-20,HBP SGA1(2016), European Project: 785907,H2020,HBP SGA2(2018), Université Paris-Saclay-Direction de Recherche Fondamentale (CEA) (DRF (CEA)), and Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)

Subjects
Human Connectome Project, [SDV.GEN.GPO]Life Sciences [q-bio]/Genetics/Populations and Evolution [q-bio.PE], [SDV.IB.IMA]Life Sciences [q-bio]/Bioengineering/Imaging, 05 social sciences, surface area, Biology, Heritability, heritability, cortical thickness, Biobank, 050105 experimental psychology, 03 medical and health sciences, 0302 clinical medicine, medicine.anatomical_structure, [STAT.ML]Statistics [stat]/Machine Learning [stat.ML], Evolutionary biology, imaging-genetic, Cortex (anatomy), medicine, 0501 psychology and cognitive sciences, [INFO.INFO-BI]Computer Science [cs]/Bioinformatics [q-bio.QM], Genotyping, 030217 neurology & neurosurgery
Abstract

International audience; Heritability of the regional thickness/surface in human cortex is established. Yet the estimates vary substantially depending on cohorts or the information they are derived from: pedigree or genotyping. Here we present three heritability studies of the cortex phenotype in two cohorts showing: i) both pedigree and genotyping or ii) genotyping only. We obtained clearly correlated heritability values between studies with a shift appearing between cohorts. Spatial pattern of heritability remains highly consistent across cohorts

Published
2019

32. CATI: A Large Distributed Infrastructure for the Neuroimaging of Cohorts

Author

Urielle Thoprakarn, Jinpeng Li, Clara Fischer, Michel Bottlaender, Bruno Dubois, Lydie Edward, Antoine Grigis, Vincent Frouin, Catherine Champseix, Mélanie Pélégrini-Issac, Denis Rivière, Christine Delmaire, Chabha Azouani, Stéphane Lehéricy, Sullivan Marie, Vincent Bouteloup, Sylvain Poret, Carole Dufouil, Marie-Odile Habert, Grégory Operto, Jean-François Mangin, Marie Chupin, Ali Bouyahia, Leila Makkaoui, Yann Cointepas, Habib Benali, Regine Trebossen, Dimitri Papadopoulos Orfanos, Gaël Chételat, Bénédicte Batrancourt, Mathilde Bouin, Olivier Colliot, Cyril Poupon, Hugo Dary, Ludovic Fillon, Vincent Perlbarg, 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), Centre d'Acquisition et de Traitement des Images [Paris], Commissariat à l'énergie atomique et aux énergies alternatives (CEA), Laboratoire de Neuroimagerie Assistée par Ordinateur (LNAO), Institut du Cerveau et de la Moëlle Epinière = Brain and Spine Institute (ICM), Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-CHU Pitié-Salpêtrière [AP-HP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), Algorithms, models and methods for images and signals of the human brain (ARAMIS), Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut du Cerveau et de la Moëlle Epinière = Brain and Spine Institute (ICM), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-CHU Pitié-Salpêtrière [AP-HP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Inria de Paris, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria), Information Analysis and Management project of France Life Imaging, CHU Pitié-Salpêtrière [AP-HP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU), Laboratoire d'Imagerie Biomédicale [Paris] (LIB), Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Services de neuroradiologie [Lille], Hôpital Roger Salengro [Lille]-Centre Hospitalier Régional Universitaire [Lille] (CHRU Lille), Institut de neurosciences translationnelles de Paris (NeurATRIS - IHU-A-ICM), Institut du Cerveau = Paris Brain Institute (ICM), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Institut National de la Santé et de la Recherche Médicale (INSERM)-CHU Pitié-Salpêtrière [AP-HP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Sorbonne Université (SU)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Institut National de la Santé et de la Recherche Médicale (INSERM)-CHU Pitié-Salpêtrière [AP-HP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Sorbonne Université (SU)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), Institut d'Imagerie BioMédicale (I2BM), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris-Saclay, Service Hospitalier Frédéric Joliot (SHFJ), Epidémiologie et Biostatistique [Bordeaux], Université Bordeaux Segalen - Bordeaux 2-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM), Epidemiologie-Biostatistique [Bordeaux], Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Bordeaux Ségalen [Bordeaux 2], Institut de Santé Publique, d'Epidémiologie et de Développement (ISPED), Université Bordeaux Segalen - Bordeaux 2, Neuropsychologie cognitive et neuroanatomie fonctionnelles de la mémoire humaine, Université de Caen Normandie (UNICAEN), Normandie Université (NU)-Normandie Université (NU)-École Pratique des Hautes Études (EPHE), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Institut National de la Santé et de la Recherche Médicale (INSERM), Institut de la Mémoire et de la Maladie d'Alzheimer [CHU Pitié-Salpétriêre] (IM2A), Université Pierre et Marie Curie - Paris 6 (UPMC)-CHU Pitié-Salpêtrière [AP-HP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU), Center for NeuroImaging Research-Human MRI Neuroimaging core facility for clinical research [ICM Paris] (CENIR), 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, Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-CHU Pitié-Salpêtrière [AP-HP], Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP), Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-CHU Pitié-Salpêtrière [AP-HP], Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Inria de Paris, Service de médecine nucléaire [CHU Pitié-Salpétrière], Laboratoire d'Imagerie Biomédicale (LIB), Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Pierre et Marie Curie - Paris 6 (UPMC), Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Université Pierre et Marie Curie - Paris 6 (UPMC), Service de Neuroradiologie [CHU Pitié-Salpêtrière], Unité de recherche Neuroépidémiologie [CHU Pitié-Salpêtrière], Institut National de la Santé et de la Recherche Médicale (INSERM)-CHU Pitié-Salpêtrière [AP-HP], Normandie Université (NU)-Normandie Université (NU)-École pratique des hautes études (EPHE), Institut de la Mémoire et de la Maladie d'Alzheimer [Paris] (IM2A), Université Pierre et Marie Curie - Paris 6 (UPMC), Centre de Neuro-Imagerie de Recherche (CENIR), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-CHU Pitié-Salpêtrière [AP-HP], Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU), Operto, Grégory, Service de Médecine nucléaire [CHU Pitié-Salpétrière], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-CHU Pitié-Salpêtrière [AP-HP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Inria de Paris, and Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Sorbonne Université (SU)

Subjects
0301 basic medicine, Service (systems architecture), Large-scale studies, Knowledge management, [SDV.IB.IMA]Life Sciences [q-bio]/Bioengineering/Imaging, Information Dissemination, Neuroimaging, Neuroimaging biomarkers, Plan (drawing), Computer security, computer.software_genre, Multicenter protocols, Workflow, 03 medical and health sciences, 0302 clinical medicine, Service infrastructure, Humans, Multicenter Studies as Topic, Data mining, business.industry, General Neuroscience, Computational Biology, 3. Good health, Data sharing, [SDV.IB.IMA] Life Sciences [q-bio]/Bioengineering/Imaging, 030104 developmental biology, Business, computer, 030217 neurology & neurosurgery, Software, Information Systems
Abstract

The CATI Consortium; International audience; This paper provides an overview of CATI, a platform dedicated to multicenter neuroimaging. Initiated by the French Alzheimer’s plan (2008–2012), CATI is a research project called on to provide service to other projects like an industrial partner. Its core mission is to support the neuroimaging of large populations, providing concrete solutions to the increasing complexity involved in such projects by bringing together a service infrastructure, the know-how of its expert academic teams and a large-scale, harmonized network of imaging facilities. CATI aims to make data sharing across studies easier and promotes sharing as much as possible. In the last 4 years, CATI has assisted the clinical community by taking charge of 35 projects so far and has emerged as a recognized actor at the national and international levels.

Published
2016
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33. Brain structure and habitat: Do the brains of our children tell us where they have been brought up?

Author

Penny A. Gowland, Jürgen Gallinat, Tomáš Paus, Herta Flor, Bernd Ittermann, Antoine Grigis, Luise Poustka, Sabina Millenet, Andreas Heinz, Christian Büchel, Jean-Luc Martinot, Andreas Meyer-Lindenberg, Henrik Walter, Sylvane Desrivières, Tobias Banaschewski, Simone Kühn, Arun L.W. Bokde, Robert Whelan, Frauke Nees, Michael N. Smolka, Hugh Garavan, Marie-Laure Paillère Martinot, Erin Burke Quinlan, Dimitri Papadopoulos Orfanos, Juliane H. Fröhner, and Gunter Schumann

Subjects
Male, Rural Population, Adolescent, Urban Population, Cognitive Neuroscience, Population, Significant group, City living, Neuroimaging, 050105 experimental psychology, lcsh:RC321-571, Developmental psychology, Environmental neuroscience, 03 medical and health sciences, 0302 clinical medicine, Urban planning, Humans, Urbanicity, Rural, 0501 psychology and cognitive sciences, Effects of sleep deprivation on cognitive performance, education, Association (psychology), lcsh:Neurosciences. Biological psychiatry. Neuropsychiatry, Ecosystem, education.field_of_study, 05 social sciences, Neurosciences, Brain, Voxel-based morphometry, Geography, Neurology, Habitat, Female, Rural area, 030217 neurology & neurosurgery
Abstract

Recently many lifestyle factors have been shown to be associated with brain structural alterations. At present we are facing increasing population shifts from rural to urban areas, which considerably change the living environments of human beings. To investigate the association between rural vs. urban upbringing and brain structure we selected 106 14-year old adolescents of whom half were exclusively raised in rural areas and the other half who exclusively lived in cities. Voxel-based morphometry revealed a group difference in left hippocampal formation (Rural > City), which was positively associated with cognitive performance in a spatial processing task. Moreover, significant group differences were observed in spatial processing (Rural > City). A mediation analysis revealed that hippocampal formation accounted for more than half of the association between upbringing and spatial processing. The results are compatible with studies reporting earlier and more intense opportunities for spatial exploration in children brought up in rural areas. The results are interesting in the light of urban planning where spaces enabling spatial exploration for children may deserve more attention.

Published
2020
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34. Pypreclin: An automatic pipeline for macaque functional MRI preprocessing

Author

Jordy Tasserie, Béchir Jarraya, Morgan Dupont, Lynn Uhrig, Antoine Grigis, Alexis Amadon, Commissariat à l'énergie atomique et aux énergies alternatives (CEA), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ), Institut National de la Santé et de la Recherche Médicale, Inserm Fondation pour la Recherche Médicale, FRM: ECO20160736100 Fondation de France Fondation Bettencourt Schueller Fondation du Collège de France, This work was supported by the Fondation pour la Recherche M?dicale (FRM grant number ECO20160736100 to JT), Fondation de France, Human Brain Project (Corticity project), Institut National de la Sant? et de la Recherche M?dicale, Commissariat ? l'Energie Atomique, Coll?ge de France, Fondation Bettencourt Schueller., and This work was supported by the Fondation pour la Recherche Médicale (FRM grant number ECO20160736100 to JT), Fondation de France , Human Brain Project (Corticity project), Institut National de la Santé et de la Recherche Médicale , Commissariat à l’Energie Atomique , Collège de France, Fondation Bettencourt Schueller .

Subjects
Male, Computer science, Automatic, Movement, Cognitive Neuroscience, Neuroimaging, Macaque, 050105 experimental psychology, lcsh:RC321-571, 03 medical and health sciences, 0302 clinical medicine, biology.animal, Image Processing, Computer-Assisted, Animals, Humans, Preprocessor, 0501 psychology and cognitive sciences, Preprocessing, lcsh:Neurosciences. Biological psychiatry. Neuropsychiatry, Cerebral Cortex, Brain Mapping, biology, business.industry, [SCCO.NEUR]Cognitive science/Neuroscience, fMRI, 05 social sciences, Brain, Pattern recognition, Non-human primate, Magnetic Resonance Imaging, Motion artifact, Neurology, Macaca, Female, Artificial intelligence, Data pre-processing, business, Algorithms, 030217 neurology & neurosurgery, Movement artifact
Abstract

International audience; Non-human primate functional MRI (fMRI) is a growing field in neuroscience. However, there is no standardized method for monkey fMRI data analysis, specifically for data preprocessing. The preprocessing of monkey fMRI data is challenged by several technical and experimental specificities of the monkey research such as artifacts related to body movements or to intracranial leads. Here we propose to address these challenges by developing a new versatile pipeline for macaque fMRI preprocessing. We developed a Python module, Pypreclin, to process raw images using state of the art algorithms embedded in a fully automatic pipeline. To evaluate its robustness, we applied Pypreclin to fMRI data acquired at 3T in both awake and anesthetized macaques, with or without iron oxide contrast agent, using single loop or multichannel phased-array coils, combined or not with intracranial implanted electrodes. We performed both resting-state and auditory evoked fMRI and compared the results of Pypreclin to a previously employed preprocessing pipeline. Pypreclin successfully achieved the registration of the fMRI data to the macaque brain template in all the experimental conditions. Moreover, Pypreclin enables more accurate locations of auditory evoked activations in relation to the gray matter at corrected level in the awake fMRI condition. Finally, using the Primate neuroimaging Data-Exchange open access platform, we could further validate Pypreclin for monkey fMRI images that were acquired at ultra-high fields, from other institutions and using different protocols. Pypreclin is a validated preprocessing tool that adapts to diverse experimental and technical situations of monkey fMRI. Pypreclin code is available on open source data sharing platform.

Published
2020
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35. Quantifying performance of machine learning methods for neuroimaging data

Author

Lee Jollans, Antoine Grigis, Henrik Walter, Tobias Banaschewski, Gunter Schumann, Michael N. Smolka, Robert Whelan, Rory Boyle, Eric Artiges, Jean-Luc Martinot, Hugh Garavan, Sylvane Desrivières, and Tomáš Paus

Subjects
Elastic net regularization, Computer science, Cognitive Neuroscience, Bootstrap aggregating, Feature selection, Neuroimaging, Machine learning, computer.software_genre, 050105 experimental psychology, Machine Learning, 03 medical and health sciences, 0302 clinical medicine, Kriging, Linear regression, Humans, 0501 psychology and cognitive sciences, Multiple kernel learning, business.industry, 05 social sciences, Brain, Reproducibility of Results, Models, Theoretical, Random forest, Neurology, Sample size determination, Multicollinearity, Artificial intelligence, business, computer, 030217 neurology & neurosurgery
Abstract

Machine learning is increasingly being applied to neuroimaging data. However, most machine learning algorithms have not been designed to accommodate neuroimaging data, which typically has many more data points than subjects, in addition to multicollinearity and low signal-to-noise. Consequently, the relative efficacy of different machine learning regression algorithms for different types of neuroimaging data are not known. Here, we sought to quantify the performance of a variety of machine learning algorithms for use with neuroimaging data with various sample sizes, feature set sizes, and predictor effect sizes. The contribution of additional machine learning techniques - embedded feature selection and bootstrap aggregation (bagging) - to model performance was also quantified. Five machine learning regression methods - Gaussian Process Regression, Multiple Kernel Learning, Kernel Ridge Regression, the Elastic Net and Random Forest, were examined with both real and simulated MRI data, and in comparison to standard multiple regression. The different machine learning regression algorithms produced varying results, which depended on sample size, feature set size, and predictor effect size. When the effect size was large, the Elastic Net, Kernel Ridge Regression and Gaussian Process Regression performed well at most sample sizes and feature set sizes. However, when the effect size was small, only the Elastic Net made accurate predictions, but this was limited to analyses with sample sizes greater than 400. Random Forest also produced a moderate performance for small effect sizes, but could do so across all sample sizes. Machine learning techniques also improved prediction accuracy for multiple regression. These data provide empirical evidence for the differential performance of various machines on neuroimaging data, which are dependent on number of sample size, features and effect size.

Published
2018

36. Analysis vs Synthesis-based Regularization for combined Compressed Sensing and Parallel MRI Reconstruction at 7 Tesla

Author

Antoine Grigis, Hamza Cherkaoui, Alexandre Vignaud, Philippe Ciuciu, Jean-Luc Starck, F. Poupon, L. El Gueddari, C. Lazarus, S. Farrens, Centre d'Etude de Saclay, Commissariat à l'énergie atomique et aux énergies alternatives (CEA), Modelling brain structure, function and variability based on high-field MRI data (PARIETAL), Inria Saclay - Ile de France, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-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)-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), Commissariat à l'énergie atomique et aux énergies alternatives ( CEA ), Modelling brain structure, function and variability based on high-field MRI data ( PARIETAL ), 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-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-Inria Saclay - Ile de France, Institut National de Recherche en Informatique et en Automatique ( Inria ) -Institut National de Recherche en Informatique et en Automatique ( Inria ), Service NEUROSPIN (NEUROSPIN), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Inria Saclay - Ile de France, and Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)

Subjects
Physics, [ INFO.INFO-TS ] Computer Science [cs]/Signal and Image Processing, [ INFO.INFO-IM ] Computer Science [cs]/Medical Imaging, Image quality, [SDV.IB.IMA]Life Sciences [q-bio]/Bioengineering/Imaging, Wavelet transform, 02 engineering and technology, Iterative reconstruction, Regularization (mathematics), 030218 nuclear medicine & medical imaging, 03 medical and health sciences, Orthogonal wavelet, 0302 clinical medicine, Wavelet, Compressed sensing, [INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing, Prior probability, 0202 electrical engineering, electronic engineering, information engineering, [INFO.INFO-IM]Computer Science [cs]/Medical Imaging, 020201 artificial intelligence & image processing, Algorithm, [ SDV.IB.IMA ] Life Sciences [q-bio]/Bioengineering/Imaging
Abstract

Compressed Sensing (CS) has allowed a significant reduction of acquisition times in MRI, especially in the high spatial resolution (e.g., 400 $\mu{\mathrm{m}}$ ) context. Nonlinear CS reconstruction usually relies on analysis (e.g., Total Variation) or synthesis (e.g., wavelet) based priors and $\ell_{1}$ regularization to promote sparsity in the transform domain. Here, we compare the performance of several orthogonal wavelet transforms with those of tight frames for MR image reconstruction in the CS setting combined with parallel imaging (multiple receiver coil). We show that overcomplete dictionaries such as the fast curvelet transform provide improved image quality as compared to orthogonal transforms. For doing so, we rely on an analysis-based formulation where the underlying $\ell_{1}$ regularized criterion is minimized using a primal dual splitting method (e.g., Condat-V $\tilde{u}$ algorithm). Validation is performed on ex-vivo baboon brain $T^{*}_{2}$ MRI data collected at 7 Tesla and restrospectively under-sampled using non-Cartesian schemes (radial and Sparkling). We show that multiscale analysis priors based on tight frames instead of orthogonal transforms achieve better image quality (pSNR, SSIM) in particular at low signal-to-noise ratio.

Published
2018

37. The chaotic morphology of the left superior temporal sulcus is genetically constrained

Author

Guillaume Auzias, Antoine Grigis, Olivier Coulon, Ghislaine Dehaene-Lambertz, Yann Le Guen, Denis Rivière, Jean-François Mangin, Vincent Frouin, François Leroy, Unité Analyse et Traitement de l'Information (UNATI), 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)-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), Neuroimagerie cognitive - Psychologie cognitive expérimentale (UNICOG-U992), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Paris-Saclay, Institut de Neurosciences de la Timone (INT), Aix Marseille Université (AMU)-Centre National de la Recherche Scientifique (CNRS), ANR-16-CONV-0002,ILCB,ILCB: Institute of Language Communication and the Brain(2016), ANR-11-IDEX-0001,Amidex,INITIATIVE D'EXCELLENCE AIX MARSEILLE UNIVERSITE(2011), 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, Neuroimagerie cognitive (UNICOG-U992), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris-Saclay-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Paris-Sud - Paris 11 (UP11), Centre National de la Recherche Scientifique (CNRS)-Aix Marseille Université (AMU), ANR-16-CONV-0002,ILCB,Institute of Language Communication and the Brain(2017), ANR-11-IDEX-0001-02/11-LABX-0036,BLRI,Brain and Language Research Institute(2011), and Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris Saclay (COmUE)-Institut National de la Santé et de la Recherche Médicale (INSERM)

Subjects
Adult, Male, Imaging genetics, [SDV.IB.IMA]Life Sciences [q-bio]/Bioengineering/Imaging, Cognitive Neuroscience, Biology, 050105 experimental psychology, Lateralization of brain function, White People, 03 medical and health sciences, Young Adult, 0302 clinical medicine, Quantitative Trait, Heritable, Cortex (anatomy), medicine, Connectome, Humans, 0501 psychology and cognitive sciences, ComputingMilieux_MISCELLANEOUS, Human Connectome Project, Fissure, [SCCO.NEUR]Cognitive science/Neuroscience, 05 social sciences, Superior temporal sulcus, Human brain, Hispanic or Latino, Sulcus, White Matter, Temporal Lobe, Pedigree, medicine.anatomical_structure, Neurology, Female, Cartography, 030217 neurology & neurosurgery
Abstract

The asymmetry of the superior temporal sulcus (STS) has been identified as a species-specific feature of the human brain. The so-called superior temporal asymmetrical pit (STAP) area is observed from the last trimester of gestation onwards and is far less pronounced in the chimpanzee brain. This asymmetry is associated with more frequent sulcal interruptions, named plis de passage (PPs), leading to the irregular morphology of the left sulcus. In this paper, we aimed to characterize the variability, asymmetry, and heritability of these interruptions in the STS in comparison with the other main sulci. We developed an automated method to extract PPs across the cortex based on a highly reproducible grid of sulcal pits across individuals, which we applied to a subset of Human Connectome Project (HCP) subjects (N = 820). We report that only a few PPs across the cortex are genetically constrained, namely in the collateral, postcentral and superior temporal sulci and the calcarine fissure. Moreover, some PPs occur more often in one hemisphere than the other, namely in the precentral, postcentral, intraparietal sulci, as well as in both inferior and superior temporal sulci. Most importantly, we found that only the interruptions within the STAP region are both asymmetric and genetically constrained. Because this morphological pattern is located in an area of the left hemisphere related to speech, our results suggest structural constraints on the architecture of the linguistic network.

Published
2018
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38. T145. ALTERATIONS IN SUPERFICIAL WHITE MATTER IN THE FRONTAL CORTEX IN SCHIZOPHRENIA: A DWI STUDY USING A NOVEL ATLAS

Author

Sarrazin Samuel, Josselin Houenou, Antoine Grigis, Ellen Ji, Cyril Poupon, Miguel Guevara, Marion Leboyer, and Pamela Guevara

Subjects
Postmortem studies, Poster Session I, business.industry, 05 social sciences, Anatomy, Neuropathology, 050105 experimental psychology, White matter, 03 medical and health sciences, Psychiatry and Mental health, Abstracts, 0302 clinical medicine, medicine.anatomical_structure, Fractional anisotropy, Medicine, 0501 psychology and cognitive sciences, Orbitofrontal cortex, business, Insula, 030217 neurology & neurosurgery, Tractography, Diffusion MRI
Abstract

Background Alterations in brain connectivity are strongly implicated in the pathophysiology of schizophrenia (SZ). Very recently, evidence is mounting to suggest that changes in superficial white matter (SWM) U-shaped short range fibers are integral components of disease neuropathology, a theory that is supported by findings from postmortem studies and less often in vivo in patients with SZ. This diffusion weighted imaging (DWI) study aimed to investigate SWM microstructure in the frontal cortex in people with SZ. Methods Whole brain tractography was performed in 31 people with SZ and 54 healthy controls using BrainVISA and Connectomist 2.0 software. Segmentation and labelling of superficial white matter tracts were performed using a novel atlas characterizing 100 bundles. Principal Components Analysis (PCA) using a varimax orthogonal rotation was performed on mean generalised fractional anisotropy (gFA) of bundles located in the frontal cortex. Composites scores were computed for each subject, reflecting a linear combination of mean gFA values. Results PCA revealed three components explaining 19.7 %, 5.8 %, and 5.4 % of the total variance. The mean score of the second component was significantly lower in the people with SZ compared with controls (p = 0.01) and included 13 bundles connecting regions in the pars orbitalis, insula, pars triangularis, pars opercularis, orbitofrontal cortex, anterior cingulate, superior frontal cortex and middle frontal cortex. Discussion Our results support findings of reduced white matter integrity in the frontal cortex in people with SZ. Moreover, PCA may be helpful in identifying specific networks as the deficits do not appear to be widespread. Identifying patterns of superficial white matter dysconnectivity may be helpful in understanding the prominent symptoms and cognitive deficits and observed in SZ.

Published
2018

39. eQTL of KCNK2 regionally influences the brain sulcal widening: evidence from 15,597 UK Biobank participants with neuroimaging data

Author

Yann Le Guen, Herve Lemaitre, Antoine Grigis, Ghislaine Dehaene-Lambertz, Clara Fischer, Cathy Philippe, Vincent Frouin, Denis Rivière, and Jean-François Mangin

Subjects
Male, GM thickness, Histology, Imaging genetics, Central nervous system, Quantitative Trait Loci, CSF, Neuroimaging, Locus (genetics), Genome-wide association study, Biology, Grey matter, Sulci widening, 050105 experimental psychology, White matter, 03 medical and health sciences, Potassium Channels, Tandem Pore Domain, 0302 clinical medicine, Brain ageing, medicine, GWAS, Humans, 0501 psychology and cognitive sciences, Gray Matter, Cognitive decline, 030304 developmental biology, Aged, Biological Specimen Banks, 0303 health sciences, General Neuroscience, 05 social sciences, Brain, Organ Size, Heritability, Middle Aged, Magnetic Resonance Imaging, medicine.anatomical_structure, Expression quantitative trait loci, Original Article, Female, Anatomy, Neuroscience, 030217 neurology & neurosurgery
Abstract

The grey and white matter volumes are known to reduce with age. This cortical shrinkage is visible on magnetic resonance images and is conveniently identified by the increased volume of cerebrospinal fluid in the sulci between two gyri. Here, we replicated this finding using the UK Biobank dataset and studied the genetic influence on these cortical features of aging. We divided all individuals genetically confirmed of British ancestry into two sub-cohorts (12,162 and 3435 subjects for discovery and replication samples, respectively). We found that the heritability of the sulcal opening ranges from 15 to 45% (SE = 4.8%). We identified 4 new loci that contribute to this opening, including one that also affects the sulci grey matter thickness. We identified the most significant variant (rs864736) on this locus as being an expression quantitative trait locus (eQTL) for the KCNK2 gene. This gene regulates the immune-cell into the central nervous system (CNS) and controls the CNS inflammation, which is implicated in cortical atrophy and cognitive decline. These results expand our knowledge of the genetic contribution to cortical shrinking and promote further investigation into these variants and genes in pathological context such as Alzheimer’s disease in which brain shrinkage is a key biomarker. Electronic supplementary material The online version of this article (10.1007/s00429-018-1808-9) contains supplementary material, which is available to authorized users.

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40. Development of Disordered Eating Behaviors and Comorbid Depressive Symptoms in Adolescence: Neural and Psychopathological Predictors

Author

Edward D. Barker, Andreas Becker, Lauren Robinson, Frauke Nees, Henrik Walter, Gunter Schumann, Argyris Stringaris, Tomáš Paus, Ulrike Schmidt, Erin Burke Quinlan, Michael N. Smolka, Luise Poustka, Marie-Laure Paillère Martinot, Jani Penttilä, Yvonne Grimmer, Tianye Jia, Betteke van Noort, Bernd Ittermann, Gareth J. Barker, Juliane H. Fröhner, Robert Whelan, Andreas Heinz, Penny A. Gowland, Herta Flor, Antoine Grigis, Dimitri Papadopoulos Orfanos, Congying Chu, Nicole Tay, Tobias Banaschewski, Hugh Garavan, Corinna Isensee, Zuo Zhang, Jean-Luc Martinot, Sylvane Desrivières, Arun L.W. Bokde, and Sarah Hohmann

Subjects
0301 basic medicine, Adolescent, Gray matter volume, Comorbidity, Asymptomatic, Conduct disorder, Feeding and Eating Disorders, 03 medical and health sciences, 0302 clinical medicine, Dorsolateral Prefrontal Cortex, medicine, Attention deficit hyperactivity disorder, Humans, Disordered eating, Gray Matter, Biological Psychiatry, business.industry, Depression, medicine.disease, Mental health, 3. Good health, Eating disorders, 030104 developmental biology, Attention-deficit/hyperactivity disorder, Attention Deficit Disorder with Hyperactivity, Etiology, medicine.symptom, business, 030217 neurology & neurosurgery, Biomarkers, Clinical psychology, Psychopathology
Abstract

Background: Eating disorders are common in adolescence and are devastating and strongly comorbid with other psychiatric disorders. Yet little is known about their etiology, knowing which would aid in developing effective preventive measures. Methods: Longitudinal assessments of disordered eating behaviors (DEBs)—binge-eating, purging, and dieting—and comorbid psychopathology were measured in 1386 adolescents from the IMAGEN study. Development of DEBs and associated mental health problems was investigated by comparing participants who reported symptoms at ages 16 or 19 years, but not at age 14 years, with asymptomatic control participants. Voxel-based morphometry and psychopathological differences at age 14 were investigated to identify risk factors for the development of DEBs and associated mental health problems. Results: DEBs and depressive symptoms developed together. Emotional and behavioral problems, including symptoms of attention-deficit/hyperactivity disorder and conduct disorder, predated their development. Alterations in frontostriatal brain areas also predated the development of DEBs and depressive symptoms. Specifically, development of binge-eating was predicted by higher gray matter volumes in the right putamen/globus pallidus at age 14. Conversely, development of purging and depressive symptoms was predicted by lower volumes in the medial orbitofrontal, dorsomedial, and dorsolateral prefrontal cortices. Lower gray matter volumes in the orbitofrontal and anterior cingulate cortices mediated the relationship between attention-deficit/hyperactivity disorder and conduct disorder symptoms and future purging and depressive symptoms. Conclusions: These findings suggest that alterations in frontal brain circuits are part of the shared etiology among eating disorders, attention-deficit/hyperactivity disorder, conduct disorder, and depression and highlight the importance of a transdiagnostic approach to treating these conditions.

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