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Magielse N, Heuer K, Toro R, Schutter DJLG, Valk SL. A Comparative Perspective on the Cerebello-Cerebral System and Its Link to Cognition. Cerebellum 2023; 22:1293-1307. [PMID: 36417091 PMCID: PMC10657313 DOI: 10.1007/s12311-022-01495-0] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Accepted: 11/11/2022] [Indexed: 11/24/2022]
Abstract
The longstanding idea that the cerebral cortex is the main neural correlate of human cognition can be elaborated by comparative analyses along the vertebrate phylogenetic tree that support the view that the cerebello-cerebral system is suited to support non-motor functions more generally. In humans, diverse accounts have illustrated cerebellar involvement in cognitive functions. Although the neocortex, and its transmodal association cortices such as the prefrontal cortex, have become disproportionately large over primate evolution specifically, human neocortical volume does not appear to be exceptional relative to the variability within primates. Rather, several lines of evidence indicate that the exceptional volumetric increase of the lateral cerebellum in conjunction with its connectivity with the cerebral cortical system may be linked to non-motor functions and mental operation in primates. This idea is supported by diverging cerebello-cerebral adaptations that potentially coevolve with cognitive abilities across other vertebrates such as dolphins, parrots, and elephants. Modular adaptations upon the vertebrate cerebello-cerebral system may thus help better understand the neuroevolutionary trajectory of the primate brain and its relation to cognition in humans. Lateral cerebellar lobules crura I-II and their reciprocal connections to the cerebral cortical association areas appear to have substantially expanded in great apes, and humans. This, along with the notable increase in the ventral portions of the dentate nucleus and a shift to increased relative prefrontal-cerebellar connectivity, suggests that modular cerebellar adaptations support cognitive functions in humans. In sum, we show how comparative neuroscience provides new avenues to broaden our understanding of cerebellar and cerebello-cerebral functions in the context of cognition.
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Affiliation(s)
- Neville Magielse
- Institute of Neuroscience and Medicine (INM-7: Brain and Behaviour), Research Center Jülich, Jülich, Germany
- Otto Hahn Cognitive Neurogenetics Group, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
- Institute of Systems Neuroscience, Heinrich Heine University, Düsseldorf, Germany
| | - Katja Heuer
- Institute Pasteur, Unité de Neuroanatomie Appliquée et Théorique, Université Paris Cité, Paris, France
- Department of Neuropsychology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Roberto Toro
- Institute Pasteur, Unité de Neuroanatomie Appliquée et Théorique, Université Paris Cité, Paris, France
| | - Dennis J L G Schutter
- Experimental Psychology, Helmholtz Institute, Utrecht University, Utrecht, The Netherlands
| | - Sofie L Valk
- Institute of Neuroscience and Medicine (INM-7: Brain and Behaviour), Research Center Jülich, Jülich, Germany.
- Otto Hahn Cognitive Neurogenetics Group, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany.
- Institute of Systems Neuroscience, Heinrich Heine University, Düsseldorf, Germany.
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Lefebvre A, Traut N, Pedoux A, Maruani A, Beggiato A, Elmaleh M, Germanaud D, Amestoy A, Ly-Le Moal M, Chatham C, Murtagh L, Bouvard M, Alisson M, Leboyer M, Bourgeron T, Toro R, Dumas G, Moreau C, Delorme R. Exploring the multidimensional nature of repetitive and restricted behaviors and interests (RRBI) in autism: neuroanatomical correlates and clinical implications. Mol Autism 2023; 14:45. [PMID: 38012709 PMCID: PMC10680239 DOI: 10.1186/s13229-023-00576-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/10/2023] [Accepted: 11/06/2023] [Indexed: 11/29/2023] Open
Abstract
BACKGROUND Repetitive and restricted behaviors and interests (RRBI) are core symptoms of autism with a complex entity and are commonly categorized into 'motor-driven' and 'cognitively driven'. RRBI symptomatology depends on the individual's clinical environment limiting the understanding of RRBI physiology, particularly their associated neuroanatomical structures. The complex RRBI heterogeneity needs to explore the whole RRBI spectrum by integrating the clinical context [autistic individuals, their relatives and typical developing (TD) individuals]. We hypothesized that different RRBI dimensions would emerge by exploring the whole spectrum of RRBI and that these dimensions are associated with neuroanatomical signatures-involving cortical and subcortical areas. METHOD A sample of 792 individuals composed of 267 autistic subjects, their 370 first-degree relatives and 155 TD individuals was enrolled in the study. We assessed the whole patterns of RRBI in each individual by using the Repetitive Behavior Scale-Revised and the Yale-Brown Obsessive Compulsive Scale. We estimated brain volumes using MRI scanner for a subsample of the subjects (n = 152, 42 ASD, 89 relatives and 13 TD). We first investigated the dimensionality of RRBI by performing a principal component analysis on all items of these scales and included all the sampling population. We then explored the relationship between RRBI-derived factors with brain volumes using linear regression models. RESULTS We identified 3 main factors (with 30.3% of the RRBI cumulative variance): Factor 1 (FA1, 12.7%) reflected mainly the 'motor-driven' RRBI symptoms; Factor 2 and 3 (respectively, 8.8% and 7.9%) gathered mainly Y-BOCS related items and represented the 'cognitively driven' RRBI symptoms. These three factors were significantly associated with the right/left putamen volumes but with opposite effects: FA1 was negatively associated with an increased volume of the right/left putamen conversely to FA2 and FA3 (all uncorrected p < 0.05). FA1 was negatively associated with the left amygdala (uncorrected p < 0.05), and FA2 was positively associated with the left parietal structure (uncorrected p = 0.001). CONCLUSION Our results suggested 3 coherent RRBI dimensions involving the putamen commonly and other structures according to the RRBI dimension. The exploration of the putamen's integrative role in RSBI needs to be strengthened in further studies.
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Affiliation(s)
- Aline Lefebvre
- Fondation Vallée, GHT Paris Sud, Hospital of Child and Adolescent Psychiatry, Gentilly, France.
- UMR 3571 CNRS, Human Genetics and Cognitive Functions, Institut Pasteur, Paris, France.
- UNIACT Neurospin - INSERM UMR 1129, CEA, Saclay, France.
- Department of Adult Psychiatry, Henri Mondor and Albert Chenevier Hospital, Créteil, France.
- Faculty of Medicine, Université Paris-Saclay, Le Kremlin-Bicêtre, France.
| | - Nicolas Traut
- Unité de Neuroanatomie Appliquée et Théorique, Institut Pasteur, Paris, France
| | - Amandine Pedoux
- Department of Child and Adolescent Psychiatry, Robert Debré Hospital, APHP, Paris, France
| | - Anna Maruani
- UMR 3571 CNRS, Human Genetics and Cognitive Functions, Institut Pasteur, Paris, France
- Department of Child and Adolescent Psychiatry, Robert Debré Hospital, APHP, Paris, France
| | - Anita Beggiato
- UMR 3571 CNRS, Human Genetics and Cognitive Functions, Institut Pasteur, Paris, France
- Department of Child and Adolescent Psychiatry, Robert Debré Hospital, APHP, Paris, France
| | - Monique Elmaleh
- Department of Pediatric Radiology, Robert-Debré Hospital, APHP, Paris, France
| | - David Germanaud
- UNIACT Neurospin - INSERM UMR 1129, CEA, Saclay, France
- Department of Clinical Genetics, Robert Debré Hospital, APHP, Paris, France
- Center for Research and Interdisciplinarity (CRI), Université Paris Cité, Paris, France
| | - Anouck Amestoy
- Autism Expert Center, Charles Perrens Hospital, Bordeaux, France
- Fondation FondaMental, French National Science Foundation, Créteil, France
| | | | - Christopher Chatham
- Roche Pharma Research and Early Development, Neuroscience and Rare Diseases, Roche Innovation Center Basel, F. Hoffmann-La Roche Ltd., Basel, Switzerland
| | - Lorraine Murtagh
- Roche Pharma Research and Early Development, Neuroscience and Rare Diseases, Roche Innovation Center Basel, F. Hoffmann-La Roche Ltd., Basel, Switzerland
| | - Manuel Bouvard
- Autism Expert Center, Charles Perrens Hospital, Bordeaux, France
- Fondation FondaMental, French National Science Foundation, Créteil, France
| | - Marianne Alisson
- Department of Pediatric Radiology, Robert-Debré Hospital, APHP, Paris, France
| | - Marion Leboyer
- Fondation FondaMental, French National Science Foundation, Créteil, France
- Institut National de la Santé et de la Recherche Médicale (INSERM), U955, Institut Mondor de Recherche Biomédicale, Psychiatrie Translationnelle, Créteil, France
| | - Thomas Bourgeron
- UMR 3571 CNRS, Human Genetics and Cognitive Functions, Institut Pasteur, Paris, France
- Université Paris Cité, Paris, France
| | - Roberto Toro
- Unité de Neuroanatomie Appliquée et Théorique, Institut Pasteur, Paris, France
| | - Guillaume Dumas
- Department of Psychiatry, Université de Montreal, CHU Ste Justine Hospital, Montreal, QC, Canada
| | - Clara Moreau
- UMR 3571 CNRS, Human Genetics and Cognitive Functions, Institut Pasteur, Paris, France
- Imaging Genetics Center, Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of USC, Los Angeles, CA, USA
| | - Richard Delorme
- Fondation Vallée, GHT Paris Sud, Hospital of Child and Adolescent Psychiatry, Gentilly, France
- UMR 3571 CNRS, Human Genetics and Cognitive Functions, Institut Pasteur, Paris, France
- Fondation FondaMental, French National Science Foundation, Créteil, France
- Université Paris Cité, Paris, France
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Magielse N, Toro R, Steigauf V, Abbaspour M, Eickhoff SB, Heuer K, Valk SL. Phylogenetic comparative analysis of the cerebello-cerebral system in 34 species highlights primate-general expansion of cerebellar crura I-II. Commun Biol 2023; 6:1188. [PMID: 37993596 PMCID: PMC10665558 DOI: 10.1038/s42003-023-05553-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2023] [Accepted: 11/07/2023] [Indexed: 11/24/2023] Open
Abstract
The reciprocal connections between the cerebellum and the cerebrum have been suggested to simultaneously play a role in brain size increase and to support a broad array of brain functions in primates. The cerebello-cerebral system has undergone marked functionally relevant reorganization. In particular, the lateral cerebellar lobules crura I-II (the ansiform) have been suggested to be expanded in hominoids. Here, we manually segmented 63 cerebella (34 primate species; 9 infraorders) and 30 ansiforms (13 species; 8 infraorders) to understand how their volumes have evolved over the primate lineage. Together, our analyses support proportional cerebellar-cerebral scaling, whereas ansiforms have expanded faster than the cerebellum and cerebrum. We did not find different scaling between strepsirrhines and haplorhines, nor between apes and non-apes. In sum, our study shows primate-general structural reorganization of the ansiform, relative to the cerebello-cerebral system, which is relevant for specialized brain functions in an evolutionary context.
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Grants
- RT and KH are supported by the French Agence Nationale de la Recherche, projects NeuroWebLab (ANR-19-DATA-0025) and DMOBE (ANR-21-CE45-0016). KH received funding from the European Union’s Horizon 2020 research and innovation program under the Marie Skłodowska-Curie grant agreement No101033485 (Individual Fellowship). Last, this work was funded in part by Helmholtz Association’s Initiative and Networking Fund under the Helmholtz International Lab grant agreement InterLabs-0015, and the Canada First Research Excellence Fund (CFREF Competition 2, 2015–2016), awarded to the Healthy Brains, Healthy Lives initiative at McGill University, through the Helmholtz International BigBrain Analytics and Learning Laboratory (HIBALL), including NM, SBE, and SLV.
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Affiliation(s)
- Neville Magielse
- Institute of Neuroscience and Medicine, Brain and Behaviour (INM-7), Research Center Jülich, Wilhelm-Johnen-Straße, 52428, Jülich, Germany.
- Otto Hahn Cognitive Neurogenetics Group, Max Planck Institute for Human Cognitive and Brain Sciences, Stephanstraße 1A, 04103, Leipzig, Germany.
- Institute of Systems Neuroscience, Medical Faculty, Heinrich Heine University Düsseldorf, Moorenstraße 5, 40225, Düsseldorf, Germany.
| | - Roberto Toro
- Institut Pasteur, Unité de Neuroanatomie Appliquée et Théorique, Université Paris Cité, 25 rue du Dr. Roux, 75724, Paris, France
| | - Vanessa Steigauf
- Department of Biology, Northern Michigan University, 1401 Presque Isle Ave, MI, 49855, Marquette, USA
| | - Mahta Abbaspour
- Berlin School of Mind and Brain, Humboldt-Universität zu Berlin, Luisenstraße 56, Haus 1, 10117, Berlin, Germany
- Department of Neurology, Charité - Universitätsmedizin Berlin, Bonhoefferweg 3, 10117, Berlin, Germany
| | - Simon B Eickhoff
- Institute of Neuroscience and Medicine, Brain and Behaviour (INM-7), Research Center Jülich, Wilhelm-Johnen-Straße, 52428, Jülich, Germany
- Institute of Systems Neuroscience, Medical Faculty, Heinrich Heine University Düsseldorf, Moorenstraße 5, 40225, Düsseldorf, Germany
| | - Katja Heuer
- Institut Pasteur, Unité de Neuroanatomie Appliquée et Théorique, Université Paris Cité, 25 rue du Dr. Roux, 75724, Paris, France
- Department of Neuropsychology, Max Planck Institute for Human Cognitive and Brain Sciences, Stephanstraße 1A, 04103, Leipzig, Germany
| | - Sofie L Valk
- Institute of Neuroscience and Medicine, Brain and Behaviour (INM-7), Research Center Jülich, Wilhelm-Johnen-Straße, 52428, Jülich, Germany.
- Otto Hahn Cognitive Neurogenetics Group, Max Planck Institute for Human Cognitive and Brain Sciences, Stephanstraße 1A, 04103, Leipzig, Germany.
- Institute of Systems Neuroscience, Medical Faculty, Heinrich Heine University Düsseldorf, Moorenstraße 5, 40225, Düsseldorf, Germany.
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Rasero J, Jimenez-Marin A, Diez I, Toro R, Hasan MT, Cortes JM. The Neurogenetics of Functional Connectivity Alterations in Autism: Insights From Subtyping in 657 Individuals. Biol Psychiatry 2023; 94:804-813. [PMID: 37088169 DOI: 10.1016/j.biopsych.2023.04.014] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/08/2022] [Revised: 03/24/2023] [Accepted: 04/14/2023] [Indexed: 04/25/2023]
Abstract
BACKGROUND There is little consensus and controversial evidence on anatomical alterations in the brains of people with autism spectrum disorder (ASD), due in part to the large heterogeneity present in ASD, which in turn is a major drawback for developing therapies. One strategy to characterize this heterogeneity in ASD is to cluster large-scale functional brain connectivity profiles. METHODS A subtyping approach based on consensus clustering of functional brain connectivity patterns was applied to a population of 657 autistic individuals with quality-assured neuroimaging data. We then used high-resolution gene transcriptomic data to characterize the molecular mechanism behind each subtype by performing enrichment analysis of the set of genes showing a high spatial similarity with the profiles of functional connectivity alterations between each subtype and a group of typically developing control participants. RESULTS Two major stable subtypes were found: subtype 1 exhibited hypoconnectivity (less average connectivity than typically developing control participants) and subtype 2, hyperconnectivity. The 2 subtypes did not differ in structural imaging metrics in any of the analyzed regions (68 cortical and 14 subcortical) or in any of the behavioral scores (including IQ, Autism Diagnostic Interview, and Autism Diagnostic Observation Schedule). Finally, only subtype 2, comprising about 43% of ASD participants, led to significant enrichments after multiple testing corrections. Notably, the dominant enrichment corresponded to excitation/inhibition imbalance, a leading well-known primary mechanism in the pathophysiology of ASD. CONCLUSIONS Our results support a link between excitation/inhibition imbalance and functional connectivity alterations, but only in one ASD subtype, overall characterized by brain hyperconnectivity and major alterations in somatomotor and default mode networks.
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Affiliation(s)
- Javier Rasero
- Cognitive Axon Laboratory, Department of Psychology, Carnegie Mellon University, Pittsburgh, Pennsylvania.
| | - Antonio Jimenez-Marin
- Computational Neuroimaging Laboratory, Biocruces-Bizkaia Health Research Institute, Barakaldo, Spain; Biomedical Research Doctorate Program, University of the Basque Country, Leioa, Spain
| | - Ibai Diez
- Department of Radiology, Division of Nuclear Medicine and Molecular Imaging, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts; Gordon Center for Medical Imaging, Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts; Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts
| | - Roberto Toro
- Institut Pasteur, Université de Paris, Département de neuroscience, Paris, France
| | - Mazahir T Hasan
- Laboratory of Brain Circuits Therapeutics, Achucarro Basque Center for Neuroscience, Leioa, Spain; Ikerbasque, The Basque Foundation for Science, Bilbao, Spain
| | - Jesus M Cortes
- Computational Neuroimaging Laboratory, Biocruces-Bizkaia Health Research Institute, Barakaldo, Spain; Ikerbasque, The Basque Foundation for Science, Bilbao, Spain; Department of Cell Biology and Histology, University of the Basque Country, Leioa, Spain
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Heuer K, Traut N, de Sousa AA, Valk SL, Clavel J, Toro R. Diversity and evolution of cerebellar folding in mammals. eLife 2023; 12:e85907. [PMID: 37737580 PMCID: PMC10617990 DOI: 10.7554/elife.85907] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/02/2023] [Accepted: 09/22/2023] [Indexed: 09/23/2023] Open
Abstract
The process of brain folding is thought to play an important role in the development and organisation of the cerebrum and the cerebellum. The study of cerebellar folding is challenging due to the small size and abundance of its folia. In consequence, little is known about its anatomical diversity and evolution. We constituted an open collection of histological data from 56 mammalian species and manually segmented the cerebrum and the cerebellum. We developed methods to measure the geometry of cerebellar folia and to estimate the thickness of the molecular layer. We used phylogenetic comparative methods to study the diversity and evolution of cerebellar folding and its relationship with the anatomy of the cerebrum. Our results show that the evolution of cerebellar and cerebral anatomy follows a stabilising selection process. We observed two groups of phenotypes changing concertedly through evolution: a group of 'diverse' phenotypes - varying over several orders of magnitude together with body size, and a group of 'stable' phenotypes varying over less than 1 order of magnitude across species. Our analyses confirmed the strong correlation between cerebral and cerebellar volumes across species, and showed in addition that large cerebella are disproportionately more folded than smaller ones. Compared with the extreme variations in cerebellar surface area, folial anatomy and molecular layer thickness varied only slightly, showing a much smaller increase in the larger cerebella. We discuss how these findings could provide new insights into the diversity and evolution of cerebellar folding, the mechanisms of cerebellar and cerebral folding, and their potential influence on the organisation of the brain across species.
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Affiliation(s)
- Katja Heuer
- Institut Pasteur, Université Paris Cité, Unité de Neuroanatomie Appliquée et ThéoriqueParisFrance
| | - Nicolas Traut
- Institut Pasteur, Université Paris Cité, Unité de Neuroanatomie Appliquée et ThéoriqueParisFrance
| | | | - Sofie Louise Valk
- Otto Hahn Group Cognitive Neurogenetics, Max Planck Institute for Human Cognitive and Brain SciencesLeipzigGermany
- Institute of Neuroscience and Medicine, Brain & Behaviour (INM-7), Research Centre Jülich, FZ JülichJülichGermany
- Institute of Systems Neuroscience, Medical Faculty, Heinrich Heine University DüsseldorfDüsseldorfGermany
| | - Julien Clavel
- Université Lyon, Université Claude Bernard Lyon 1, CNRS, ENTPE, UMR 5023 LEHNAVilleurbanneFrance
| | - Roberto Toro
- Institut Pasteur, Université Paris Cité, Unité de Neuroanatomie Appliquée et ThéoriqueParisFrance
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6
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Messé A, Hollensteiner KJ, Delettre C, Dell-Brown LA, Pieper F, Nentwig LJ, Galindo-Leon EE, Larrat B, Mériaux S, Mangin JF, Reillo I, de Juan Romero C, Borrell V, Engler G, Toro R, Engel AK, Hilgetag CC. Structural basis of envelope and phase intrinsic coupling modes in the cerebral cortex. Neuroimage 2023; 276:120212. [PMID: 37269959 PMCID: PMC10300241 DOI: 10.1016/j.neuroimage.2023.120212] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/09/2022] [Revised: 05/09/2023] [Accepted: 05/30/2023] [Indexed: 06/05/2023] Open
Abstract
Intrinsic coupling modes (ICMs) can be observed in ongoing brain activity at multiple spatial and temporal scales. Two families of ICMs can be distinguished: phase and envelope ICMs. The principles that shape these ICMs remain partly elusive, in particular their relation to the underlying brain structure. Here we explored structure-function relationships in the ferret brain between ICMs quantified from ongoing brain activity recorded with chronically implanted micro-ECoG arrays and structural connectivity (SC) obtained from high-resolution diffusion MRI tractography. Large-scale computational models were used to explore the ability to predict both types of ICMs. Importantly, all investigations were conducted with ICM measures that are sensitive or insensitive to volume conduction effects. The results show that both types of ICMs are significantly related to SC, except for phase ICMs when using measures removing zero-lag coupling. The correlation between SC and ICMs increases with increasing frequency which is accompanied by reduced delays. Computational models produced results that were highly dependent on the specific parameter settings. The most consistent predictions were derived from measures solely based on SC. Overall, the results demonstrate that patterns of cortical functional coupling as reflected in both phase and envelope ICMs are both related, albeit to different degrees, to the underlying structural connectivity in the cerebral cortex.
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Affiliation(s)
- Arnaud Messé
- Institute of Computational Neuroscience, Hamburg Center of Neuroscience, University Medical Center Hamburg-Eppendorf, Hamburg University, Martinistraße 52, Hamburg 20246, Germany.
| | - Karl J Hollensteiner
- Department of Neurophysiology and Pathophysiology, Hamburg Center of Neuroscience, University Medical Center Hamburg-Eppendorf, Hamburg University, Martinistraße 52, Hamburg 20246, Germany
| | - Céline Delettre
- Institute of Computational Neuroscience, Hamburg Center of Neuroscience, University Medical Center Hamburg-Eppendorf, Hamburg University, Martinistraße 52, Hamburg 20246, Germany; Unité de Neuroanatomie Appliquée et Théorique, Unité de Génétique Humaine et Fonctions Cognitives, Institut Pasteur, Université Paris Cité, 25-28 rue du Dr Roux, Paris 75015, France
| | - Leigh-Anne Dell-Brown
- Institute of Computational Neuroscience, Hamburg Center of Neuroscience, University Medical Center Hamburg-Eppendorf, Hamburg University, Martinistraße 52, Hamburg 20246, Germany
| | - Florian Pieper
- Department of Neurophysiology and Pathophysiology, Hamburg Center of Neuroscience, University Medical Center Hamburg-Eppendorf, Hamburg University, Martinistraße 52, Hamburg 20246, Germany
| | - Lena J Nentwig
- Institute of Computational Neuroscience, Hamburg Center of Neuroscience, University Medical Center Hamburg-Eppendorf, Hamburg University, Martinistraße 52, Hamburg 20246, Germany
| | - Edgar E Galindo-Leon
- Department of Neurophysiology and Pathophysiology, Hamburg Center of Neuroscience, University Medical Center Hamburg-Eppendorf, Hamburg University, Martinistraße 52, Hamburg 20246, Germany
| | - Benoît Larrat
- NeuroSpin, CEA, Paris-Saclay University, Centre d'études de Saclay, Bâtiment 145, Gif-sur-Yvette 91191, France
| | - Sébastien Mériaux
- NeuroSpin, CEA, Paris-Saclay University, Centre d'études de Saclay, Bâtiment 145, Gif-sur-Yvette 91191, France
| | - Jean-François Mangin
- NeuroSpin, CEA, Paris-Saclay University, Centre d'études de Saclay, Bâtiment 145, Gif-sur-Yvette 91191, France
| | - Isabel Reillo
- Developmental Neurobiology Unit, Instituto de Neurociencias, Consejo Superior de Investigaciones Científicas - Universidad Miguel Hernández, Sant Joan d'Alacant, Av. Santiago Ramón y Cajal s/n, Sant Joan d'Alacant 03550, Spain
| | - Camino de Juan Romero
- Developmental Neurobiology Unit, Instituto de Neurociencias, Consejo Superior de Investigaciones Científicas - Universidad Miguel Hernández, Sant Joan d'Alacant, Av. Santiago Ramón y Cajal s/n, Sant Joan d'Alacant 03550, Spain
| | - Víctor Borrell
- Developmental Neurobiology Unit, Instituto de Neurociencias, Consejo Superior de Investigaciones Científicas - Universidad Miguel Hernández, Sant Joan d'Alacant, Av. Santiago Ramón y Cajal s/n, Sant Joan d'Alacant 03550, Spain
| | - Gerhard Engler
- Department of Neurophysiology and Pathophysiology, Hamburg Center of Neuroscience, University Medical Center Hamburg-Eppendorf, Hamburg University, Martinistraße 52, Hamburg 20246, Germany
| | - Roberto Toro
- Unité de Neuroanatomie Appliquée et Théorique, Unité de Génétique Humaine et Fonctions Cognitives, Institut Pasteur, Université Paris Cité, 25-28 rue du Dr Roux, Paris 75015, France; Center for Research and Interdisciplinarity, Paris Descartes University, 24, rue du Faubourg Saint Jacques, Paris 75014, France
| | - Andreas K Engel
- Department of Neurophysiology and Pathophysiology, Hamburg Center of Neuroscience, University Medical Center Hamburg-Eppendorf, Hamburg University, Martinistraße 52, Hamburg 20246, Germany
| | - Claus C Hilgetag
- Institute of Computational Neuroscience, Hamburg Center of Neuroscience, University Medical Center Hamburg-Eppendorf, Hamburg University, Martinistraße 52, Hamburg 20246, Germany; Department of Health Sciences, Boston University, 635 Commonwealth Avenue, Boston, Massachusetts 02215, USA
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7
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Rolland T, Cliquet F, Anney RJL, Moreau C, Traut N, Mathieu A, Huguet G, Duan J, Warrier V, Portalier S, Dry L, Leblond CS, Douard E, Amsellem F, Malesys S, Maruani A, Toro R, Børglum AD, Grove J, Baron-Cohen S, Packer A, Chung WK, Jacquemont S, Delorme R, Bourgeron T. Phenotypic effects of genetic variants associated with autism. Nat Med 2023; 29:1671-1680. [PMID: 37365347 PMCID: PMC10353945 DOI: 10.1038/s41591-023-02408-2] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/12/2021] [Accepted: 05/19/2023] [Indexed: 06/28/2023]
Abstract
While over 100 genes have been associated with autism, little is known about the prevalence of variants affecting them in individuals without a diagnosis of autism. Nor do we fully appreciate the phenotypic diversity beyond the formal autism diagnosis. Based on data from more than 13,000 individuals with autism and 210,000 undiagnosed individuals, we estimated the odds ratios for autism associated to rare loss-of-function (LoF) variants in 185 genes associated with autism, alongside 2,492 genes displaying intolerance to LoF variants. In contrast to autism-centric approaches, we investigated the correlates of these variants in individuals without a diagnosis of autism. We show that these variants are associated with a small but significant decrease in fluid intelligence, qualification level and income and an increase in metrics related to material deprivation. These effects were larger for autism-associated genes than in other LoF-intolerant genes. Using brain imaging data from 21,040 individuals from the UK Biobank, we could not detect significant differences in the overall brain anatomy between LoF carriers and non-carriers. Our results highlight the importance of studying the effect of the genetic variants beyond categorical diagnosis and the need for more research to understand the association between these variants and sociodemographic factors, to best support individuals carrying these variants.
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Affiliation(s)
- Thomas Rolland
- Human Genetics and Cognitive Functions, Institut Pasteur, UMR3571 CNRS, IUF, Université Paris Cité, Paris, France.
| | - Freddy Cliquet
- Human Genetics and Cognitive Functions, Institut Pasteur, UMR3571 CNRS, IUF, Université Paris Cité, Paris, France
| | - Richard J L Anney
- Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, Cardiff University, Cardiff, UK
| | - Clara Moreau
- Human Genetics and Cognitive Functions, Institut Pasteur, UMR3571 CNRS, IUF, Université Paris Cité, Paris, France
| | - Nicolas Traut
- Human Genetics and Cognitive Functions, Institut Pasteur, UMR3571 CNRS, IUF, Université Paris Cité, Paris, France
- Center for Research and Interdisciplinarity (CRI), Université Paris Descartes, Paris, France
| | - Alexandre Mathieu
- Human Genetics and Cognitive Functions, Institut Pasteur, UMR3571 CNRS, IUF, Université Paris Cité, Paris, France
| | - Guillaume Huguet
- Centre de Recherche du Centre Hospitalier Universitaire Sainte-Justine, Montréal, Québec, Canada
| | - Jinjie Duan
- The Lundbeck Foundation Initiative for Integrative Psychiatric Research, iPSYCH, Aarhus, Denmark
- Department of Biomedicine and the iSEQ Centre, Aarhus University, Aarhus, Denmark
- Center for Genomics and Personalized Medicine, Aarhus, Denmark
| | - Varun Warrier
- Autism Research Centre, Department of Psychiatry, University of Cambridge, Cambridge, UK
| | - Swan Portalier
- Human Genetics and Cognitive Functions, Institut Pasteur, UMR3571 CNRS, IUF, Université Paris Cité, Paris, France
| | - Louise Dry
- Human Genetics and Cognitive Functions, Institut Pasteur, UMR3571 CNRS, IUF, Université Paris Cité, Paris, France
| | - Claire S Leblond
- Human Genetics and Cognitive Functions, Institut Pasteur, UMR3571 CNRS, IUF, Université Paris Cité, Paris, France
| | - Elise Douard
- Centre de Recherche du Centre Hospitalier Universitaire Sainte-Justine, Montréal, Québec, Canada
- Département de Pédiatrie, Université de Montréal, Montréal, Québec, Canada
| | - Frédérique Amsellem
- Human Genetics and Cognitive Functions, Institut Pasteur, UMR3571 CNRS, IUF, Université Paris Cité, Paris, France
- Department of Child and Adolescent Psychiatry, Robert Debré Hospital, APHP, Paris, France
| | - Simon Malesys
- Human Genetics and Cognitive Functions, Institut Pasteur, UMR3571 CNRS, IUF, Université Paris Cité, Paris, France
| | - Anna Maruani
- Human Genetics and Cognitive Functions, Institut Pasteur, UMR3571 CNRS, IUF, Université Paris Cité, Paris, France
- Department of Child and Adolescent Psychiatry, Robert Debré Hospital, APHP, Paris, France
| | - Roberto Toro
- Human Genetics and Cognitive Functions, Institut Pasteur, UMR3571 CNRS, IUF, Université Paris Cité, Paris, France
- Center for Research and Interdisciplinarity (CRI), Université Paris Descartes, Paris, France
| | - Anders D Børglum
- The Lundbeck Foundation Initiative for Integrative Psychiatric Research, iPSYCH, Aarhus, Denmark
- Department of Biomedicine and the iSEQ Centre, Aarhus University, Aarhus, Denmark
- Center for Genomics and Personalized Medicine, Aarhus, Denmark
| | - Jakob Grove
- The Lundbeck Foundation Initiative for Integrative Psychiatric Research, iPSYCH, Aarhus, Denmark
- Department of Biomedicine and the iSEQ Centre, Aarhus University, Aarhus, Denmark
- Center for Genomics and Personalized Medicine, Aarhus, Denmark
- Bioinformatics Research Centre, Aarhus University, Aarhus, Denmark
| | - Simon Baron-Cohen
- Autism Research Centre, Department of Psychiatry, University of Cambridge, Cambridge, UK
| | | | - Wendy K Chung
- Simons Foundation, New York, NY, USA
- Department of Pediatrics, Columbia University Medical Center, New York, NY, USA
| | - Sébastien Jacquemont
- Centre de Recherche du Centre Hospitalier Universitaire Sainte-Justine, Montréal, Québec, Canada
- Département de Pédiatrie, Université de Montréal, Montréal, Québec, Canada
| | - Richard Delorme
- Human Genetics and Cognitive Functions, Institut Pasteur, UMR3571 CNRS, IUF, Université Paris Cité, Paris, France
- Department of Child and Adolescent Psychiatry, Robert Debré Hospital, APHP, Paris, France
| | - Thomas Bourgeron
- Human Genetics and Cognitive Functions, Institut Pasteur, UMR3571 CNRS, IUF, Université Paris Cité, Paris, France.
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8
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de Sousa AA, Beaudet A, Calvey T, Bardo A, Benoit J, Charvet CJ, Dehay C, Gómez-Robles A, Gunz P, Heuer K, van den Heuvel MP, Hurst S, Lauters P, Reed D, Salagnon M, Sherwood CC, Ströckens F, Tawane M, Todorov OS, Toro R, Wei Y. From fossils to mind. Commun Biol 2023; 6:636. [PMID: 37311857 DOI: 10.1038/s42003-023-04803-4] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/17/2022] [Accepted: 04/04/2023] [Indexed: 06/15/2023] Open
Abstract
Fossil endocasts record features of brains from the past: size, shape, vasculature, and gyrification. These data, alongside experimental and comparative evidence, are needed to resolve questions about brain energetics, cognitive specializations, and developmental plasticity. Through the application of interdisciplinary techniques to the fossil record, paleoneurology has been leading major innovations. Neuroimaging is shedding light on fossil brain organization and behaviors. Inferences about the development and physiology of the brains of extinct species can be experimentally investigated through brain organoids and transgenic models based on ancient DNA. Phylogenetic comparative methods integrate data across species and associate genotypes to phenotypes, and brains to behaviors. Meanwhile, fossil and archeological discoveries continuously contribute new knowledge. Through cooperation, the scientific community can accelerate knowledge acquisition. Sharing digitized museum collections improves the availability of rare fossils and artifacts. Comparative neuroanatomical data are available through online databases, along with tools for their measurement and analysis. In the context of these advances, the paleoneurological record provides ample opportunity for future research. Biomedical and ecological sciences can benefit from paleoneurology's approach to understanding the mind as well as its novel research pipelines that establish connections between neuroanatomy, genes and behavior.
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Affiliation(s)
| | - Amélie Beaudet
- Laboratoire de Paléontologie, Évolution, Paléoécosystèmes et Paléoprimatologie (PALEVOPRIM), UMR 7262 CNRS & Université de Poitiers, Poitiers, France.
- University of Cambridge, Cambridge, UK.
| | - Tanya Calvey
- Division of Clinical Anatomy and Biological Anthropology, University of Cape Town, Cape Town, South Africa.
| | - Ameline Bardo
- UMR 7194, CNRS-MNHN, Département Homme et Environnement, Musée de l'Homme, Paris, France
- Skeletal Biology Research Centre, School of Anthropology and Conservation, University of Kent, Canterbury, UK
| | - Julien Benoit
- Evolutionary Studies Institute, University of the Witwatersrand, Johannesburg, South Africa
| | - Christine J Charvet
- Department of Anatomy, Physiology and Pharmacology, College of Veterinary Medicine, Auburn University, Auburn, AL, USA
| | - Colette Dehay
- University of Lyon, Université Claude Bernard Lyon 1, Inserm, Stem Cell and Brain Research Institute U1208, F-69500, Bron, France
| | | | - Philipp Gunz
- Department of Human Origins, Max Planck Institute for Evolutionary Anthropology, Deutscher Platz 6, D-04103, Leipzig, Germany
| | - Katja Heuer
- Institut Pasteur, Université Paris Cité, Unité de Neuroanatomie Appliquée et Théorique, F-75015, Paris, France
| | | | - Shawn Hurst
- University of Indianapolis, Indianapolis, IN, USA
| | - Pascaline Lauters
- Institut royal des Sciences naturelles, Direction Opérationnelle Terre et Histoire de la Vie, Brussels, Belgium
| | - Denné Reed
- Department of Anthropology, University of Texas at Austin, Austin, TX, USA
| | - Mathilde Salagnon
- CNRS, CEA, IMN, GIN, UMR 5293, Université Bordeaux, Bordeaux, France
- PACEA UMR 5199, CNRS, Université Bordeaux, Pessac, France
| | - Chet C Sherwood
- Department of Anthropology, The George Washington University, Washington, DC, USA
| | - Felix Ströckens
- C. & O. Vogt Institute for Brain Research, University Hospital Düsseldorf, Heinrich-Heine University Düsseldorf, Düsseldorf, Germany
| | - Mirriam Tawane
- Ditsong National Museum of Natural History, Pretoria, South Africa
| | - Orlin S Todorov
- School of Natural Sciences, Macquarie University, Sydney, NSW, Australia
| | - Roberto Toro
- Institut Pasteur, Université Paris Cité, Unité de Neuroanatomie Appliquée et Théorique, F-75015, Paris, France
| | - Yongbin Wei
- Beijing University of Posts and Telecommunications, Beijing, China
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9
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Schwartz E, Nenning KH, Heuer K, Jeffery N, Bertrand OC, Toro R, Kasprian G, Prayer D, Langs G. Evolution of cortical geometry and its link to function, behaviour and ecology. Nat Commun 2023; 14:2252. [PMID: 37080952 PMCID: PMC10119184 DOI: 10.1038/s41467-023-37574-x] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/14/2022] [Accepted: 03/22/2023] [Indexed: 04/22/2023] Open
Abstract
Studies in comparative neuroanatomy and of the fossil record demonstrate the influence of socio-ecological niches on the morphology of the cerebral cortex, but have led to oftentimes conflicting theories about its evolution. Here, we study the relationship between the shape of the cerebral cortex and the topography of its function. We establish a joint geometric representation of the cerebral cortices of ninety species of extant Euarchontoglires, including commonly used experimental model organisms. We show that variability in surface geometry relates to species' ecology and behaviour, independent of overall brain size. Notably, ancestral shape reconstruction of the cortical surface and its change during evolution enables us to trace the evolutionary history of localised cortical expansions, modal segregation of brain function, and their association to behaviour and cognition. We find that individual cortical regions follow different sequences of area increase during evolutionary adaptations to dynamic socio-ecological niches. Anatomical correlates of this sequence of events are still observable in extant species, and relate to their current behaviour and ecology. We decompose the deep evolutionary history of the shape of the human cortical surface into spatially and temporally conscribed components with highly interpretable functional associations, highlighting the importance of considering the evolutionary history of cortical regions when studying their anatomy and function.
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Affiliation(s)
- Ernst Schwartz
- Department of Biomedical Imaging and Image-guided Therapy, Computational Imaging Research Lab, Medical University of Vienna, Vienna, Austria
| | - Karl-Heinz Nenning
- Department of Biomedical Imaging and Image-guided Therapy, Computational Imaging Research Lab, Medical University of Vienna, Vienna, Austria
- Center for Biomedical Imaging and Neuromodulation, Nathan Kline Institute, Orangeburg, NY, USA
| | - Katja Heuer
- Institut Pasteur, Université Paris Cité, Unité de Neuroanatomie Appliquée et Théorique, F-75015, Paris, France
| | - Nathan Jeffery
- Institute of Life Course & Medical Sciences, University of Liverpool, Liverpool, England
| | - Ornella C Bertrand
- Institut Català de Paleontologia Miquel Crusafont, Universitat Autònoma de Barcelona Edifici ICTA-ICP, c/ Columnes s/n, Campus de la UAB, 08193 Cerdanyola del Vallès., Barcelona, Spain
- School of GeoSciences, University of Edinburgh, Grant Institute, Edinburgh, Scotland, EH9 3FE, United Kingdom
| | - Roberto Toro
- Institut Pasteur, Université Paris Cité, Unité de Neuroanatomie Appliquée et Théorique, F-75015, Paris, France
| | - Gregor Kasprian
- Department of Biomedical Imaging and Image-guided Therapy, Computational Imaging Research Lab, Medical University of Vienna, Vienna, Austria
| | - Daniela Prayer
- Department of Biomedical Imaging and Image-guided Therapy, Computational Imaging Research Lab, Medical University of Vienna, Vienna, Austria
| | - Georg Langs
- Department of Biomedical Imaging and Image-guided Therapy, Computational Imaging Research Lab, Medical University of Vienna, Vienna, Austria.
- Computer Science and Artificial Intelligence Lab, Massachusetts Institute of Technology, Cambridge, MA, USA.
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Bast N, Mason L, Ecker C, Baumeister S, Banaschewski T, Jones EJH, Murphy DGM, Buitelaar JK, Loth E, Pandina G, Freitag CM, Auyeung B, Banaschewski T, Baron-Cohen S, Bast N, Baumeister S, Beckmann CF, Bölte S, Bourgeron T, Bours C, Brammer M, Brandeis D, Brogna C, de Bruijn Y, Buitelaar JK, Chakrabarti B, Charman T, Cornelissen I, Crawley D, Dell’Acqua F, Dumas G, Durston S, Ecker C, Faulkner J, Frouin V, Garcés P, Goyard D, Ham L, Hayward H, Hipp J, Holt R, Johnson M, Jones EJH, Kundu P, Lai MC, D’ardhuy XL, Lombardo MV, Loth E, Lythgoe DJ, Mandl R, Marquand A, Mason L, Mennes M, Meyer-Lindenberg A, Moessnang C, Murphy DGM, Oakley B, O’Dwyer L, Oldehinkel M, Oranje B, Pandina G, Persico AM, Ruggeri B, Ruigrok A, Sabet J, Sacco R, Cáceres ASJ, Simonoff E, Spooren W, Tillmann J, Toro R, Tost H, Waldman J, Williams SCR, Wooldridge C, Zwiers MP, Freitag CM. Sensory salience processing moderates attenuated gazes on faces in autism spectrum disorder: a case-control study. Mol Autism 2023; 14:5. [PMID: 36759875 PMCID: PMC9912590 DOI: 10.1186/s13229-023-00537-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/11/2022] [Accepted: 01/20/2023] [Indexed: 02/11/2023] Open
Abstract
BACKGROUND Attenuated social attention is a key marker of autism spectrum disorder (ASD). Recent neuroimaging findings also emphasize an altered processing of sensory salience in ASD. The locus coeruleus-norepinephrine system (LC-NE) has been established as a modulator of this sensory salience processing (SSP). We tested the hypothesis that altered LC-NE functioning contributes to different SSP and results in diverging social attention in ASD. METHODS We analyzed the baseline eye-tracking data of the EU-AIMS Longitudinal European Autism Project (LEAP) for subgroups of autistic participants (n = 166, age = 6-30 years, IQ = 61-138, gender [female/male] = 41/125) or neurotypical development (TD; n = 166, age = 6-30 years, IQ = 63-138, gender [female/male] = 49/117) that were matched for demographic variables and data quality. Participants watched brief movie scenes (k = 85) depicting humans in social situations (human) or without humans (non-human). SSP was estimated by gazes on physical and motion salience and a corresponding pupillary response that indexes phasic activity of the LC-NE. Social attention is estimated by gazes on faces via manual areas of interest definition. SSP is compared between groups and related to social attention by linear mixed models that consider temporal dynamics within scenes. Models are controlled for comorbid psychopathology, gaze behavior, and luminance. RESULTS We found no group differences in gazes on salience, whereas pupillary responses were associated with altered gazes on physical and motion salience. In ASD compared to TD, we observed pupillary responses that were higher for non-human scenes and lower for human scenes. In ASD, we observed lower gazes on faces across the duration of the scenes. Crucially, this different social attention was influenced by gazes on physical salience and moderated by pupillary responses. LIMITATIONS The naturalistic study design precluded experimental manipulations and stimulus control, while effect sizes were small to moderate. Covariate effects of age and IQ indicate that the findings differ between age and developmental subgroups. CONCLUSIONS Pupillary responses as a proxy of LC-NE phasic activity during visual attention are suggested to modulate sensory salience processing and contribute to attenuated social attention in ASD.
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Affiliation(s)
- Nico Bast
- Department of Child and Adolescent Psychiatry, Psychosomatics and Psychotherapy, Autism Research and Intervention Center of Excellence, University Hospital Frankfurt, Goethe-University, Deutschordenstraße 50, 60528, Frankfurt Am Main, Germany.
| | - Luke Mason
- grid.4464.20000 0001 2161 2573Centre for Brain and Cognitive Development, Birkbeck College, University of London, Malet Street, London, UK
| | - Christine Ecker
- grid.7839.50000 0004 1936 9721Department of Child and Adolescent Psychiatry, Psychosomatics and Psychotherapy, Autism Research and Intervention Center of Excellence, University Hospital Frankfurt, Goethe-University, Deutschordenstraße 50, 60528 Frankfurt Am Main, Germany
| | - Sarah Baumeister
- grid.7700.00000 0001 2190 4373Department of Child and Adolescent Psychiatry, Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, Mannheim, Germany
| | - Tobias Banaschewski
- grid.7700.00000 0001 2190 4373Department of Child and Adolescent Psychiatry, Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, Mannheim, Germany
| | - Emily J. H. Jones
- grid.4464.20000 0001 2161 2573Centre for Brain and Cognitive Development, Birkbeck College, University of London, Malet Street, London, UK
| | - Declan G. M. Murphy
- grid.13097.3c0000 0001 2322 6764Institute of Psychiatry, Psychology and Neuroscience, King’s College, London, London, UK
| | - Jan K. Buitelaar
- grid.10417.330000 0004 0444 9382Department of Cognitive Neuroscience, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Eva Loth
- grid.13097.3c0000 0001 2322 6764Institute of Psychiatry, Psychology and Neuroscience, King’s College, London, London, UK
| | - Gahan Pandina
- grid.497530.c0000 0004 0389 4927Janssen Research & Development, 1125 Trenton Harbourton Road, Titusville, NJ 08560 USA
| | | | - Christine M. Freitag
- grid.7839.50000 0004 1936 9721Department of Child and Adolescent Psychiatry, Psychosomatics and Psychotherapy, Autism Research and Intervention Center of Excellence, University Hospital Frankfurt, Goethe-University, Deutschordenstraße 50, 60528 Frankfurt Am Main, Germany
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Looden T, Floris DL, Llera A, Chauvin RJ, Charman T, Banaschewski T, Murphy D, Marquand AF, Buitelaar JK, Beckmann CF, Ambrosino S, Auyeung B, Banaschewski T, Baron-Cohen S, Baumeister S, Beckmann CF, Bölte S, Bourgeron T, Bours C, Brammer M, Brandeis D, Brogna C, de Bruijn Y, Buitelaar JK, Chakrabarti B, Charman T, Cornelissen I, Crawley D, Acqua FD, Dumas G, Durston S, Ecker C, Faulkner J, Frouin V, Garcés P, Goyard D, Ham L, Hayward H, Hipp J, Holt R, Johnson MH, Jones EJH, Kundu P, Lai MC, D’ardhuy XL, Lombardo MV, Loth E, Lythgoe DJ, Mandl R, Marquand A, Mason L, Mennes M, Meyer-Lindenberg A, Moessnang C, Mueller N, Murphy DGM, Oakley B, O’Dwyer L, Oldehinkel M, Oranje B, Pandina G, Persico AM, Rausch A, Ruggeri B, Ruigrok A, Sabet J, Sacco R, Cáceres ASJ, Simonoff E, Spooren W, Tillmann J, Toro R, Tost H, Waldman J, Williams SCR, Wooldridge C, Ilioska I, Mei T, Zwiers MP. Patterns of connectome variability in autism across five functional activation tasks: findings from the LEAP project. Mol Autism 2022; 13:53. [PMID: 36575450 PMCID: PMC9793684 DOI: 10.1186/s13229-022-00529-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2022] [Accepted: 12/04/2022] [Indexed: 12/28/2022] Open
Abstract
BACKGROUND Autism spectrum disorder (autism) is a complex neurodevelopmental condition with pronounced behavioral, cognitive, and neural heterogeneities across individuals. Here, our goal was to characterize heterogeneity in autism by identifying patterns of neural diversity as reflected in BOLD fMRI in the way individuals with autism engage with a varied array of cognitive tasks. METHODS All analyses were based on the EU-AIMS/AIMS-2-TRIALS multisite Longitudinal European Autism Project (LEAP) with participants with autism (n = 282) and typically developing (TD) controls (n = 221) between 6 and 30 years of age. We employed a novel task potency approach which combines the unique aspects of both resting state fMRI and task-fMRI to quantify task-induced variations in the functional connectome. Normative modelling was used to map atypicality of features on an individual basis with respect to their distribution in neurotypical control participants. We applied robust out-of-sample canonical correlation analysis (CCA) to relate connectome data to behavioral data. RESULTS Deviation from the normative ranges of global functional connectivity was greater for individuals with autism compared to TD in each fMRI task paradigm (all tasks p < 0.001). The similarity across individuals of the deviation pattern was significantly increased in autistic relative to TD individuals (p < 0.002). The CCA identified significant and robust brain-behavior covariation between functional connectivity atypicality and autism-related behavioral features. CONCLUSIONS Individuals with autism engage with tasks in a globally atypical way, but the particular spatial pattern of this atypicality is nevertheless similar across tasks. Atypicalities in the tasks originate mostly from prefrontal cortex and default mode network regions, but also speech and auditory networks. We show how sophisticated modeling methods such as task potency and normative modeling can be used toward unravelling complex heterogeneous conditions like autism.
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Affiliation(s)
- Tristan Looden
- Department of Cognitive Neuroscience, Donders Institute for Brain, Cognition and Behaviour, Radboud University Nijmegen Medical Centre, Kapittelweg 29, 6525 EN, Nijmegen, The Netherlands.
| | - Dorothea L Floris
- Department of Cognitive Neuroscience, Donders Institute for Brain, Cognition and Behaviour, Radboud University Nijmegen Medical Centre, Kapittelweg 29, 6525 EN, Nijmegen, The Netherlands.,Methods of Plasticity Research, Department of Psychology, University of Zurich, Zurich, Switzerland
| | - Alberto Llera
- Department of Cognitive Neuroscience, Donders Institute for Brain, Cognition and Behaviour, Radboud University Nijmegen Medical Centre, Kapittelweg 29, 6525 EN, Nijmegen, The Netherlands.,Karakter Child and Adolescent Psychiatry University Centre, Nijmegen, The Netherlands
| | - Roselyne J Chauvin
- Department of Neurology, Washington University School of Medicine, St. Louis, USA
| | - Tony Charman
- Department of Psychology, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Tobias Banaschewski
- Department of Child and Adolescent Psychiatry, Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, Mannheim, Germany
| | - Declan Murphy
- Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Andre F Marquand
- Department of Cognitive Neuroscience, Donders Institute for Brain, Cognition and Behaviour, Radboud University Nijmegen Medical Centre, Kapittelweg 29, 6525 EN, Nijmegen, The Netherlands
| | - Jan K Buitelaar
- Department of Cognitive Neuroscience, Donders Institute for Brain, Cognition and Behaviour, Radboud University Nijmegen Medical Centre, Kapittelweg 29, 6525 EN, Nijmegen, The Netherlands.,Karakter Child and Adolescent Psychiatry University Centre, Nijmegen, The Netherlands
| | - Christian F Beckmann
- Department of Cognitive Neuroscience, Donders Institute for Brain, Cognition and Behaviour, Radboud University Nijmegen Medical Centre, Kapittelweg 29, 6525 EN, Nijmegen, The Netherlands.,Centre for Functional MRI of the Brain (FMRIB), Nuffield Department of Clinical Neurosciences, Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, UK
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12
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Traut N, Heuer K, Lemaître G, Beggiato A, Germanaud D, Elmaleh M, Bethegnies A, Bonnasse-Gahot L, Cai W, Chambon S, Cliquet F, Ghriss A, Guigui N, de Pierrefeu A, Wang M, Zantedeschi V, Boucaud A, van den Bossche J, Kegl B, Delorme R, Bourgeron T, Toro R, Varoquaux G. Insights from an autism imaging biomarker challenge: Promises and threats to biomarker discovery. Neuroimage 2022; 255:119171. [PMID: 35413445 DOI: 10.1016/j.neuroimage.2022.119171] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/26/2021] [Revised: 02/16/2022] [Accepted: 03/30/2022] [Indexed: 12/23/2022] Open
Abstract
MRI has been extensively used to identify anatomical and functional differences in Autism Spectrum Disorder (ASD). Yet, many of these findings have proven difficult to replicate because studies rely on small cohorts and are built on many complex, undisclosed, analytic choices. We conducted an international challenge to predict ASD diagnosis from MRI data, where we provided preprocessed anatomical and functional MRI data from > 2,000 individuals. Evaluation of the predictions was rigorously blinded. 146 challengers submitted prediction algorithms, which were evaluated at the end of the challenge using unseen data and an additional acquisition site. On the best algorithms, we studied the importance of MRI modalities, brain regions, and sample size. We found evidence that MRI could predict ASD diagnosis: the 10 best algorithms reliably predicted diagnosis with AUC∼0.80 - far superior to what can be currently obtained using genotyping data in cohorts 20-times larger. We observed that functional MRI was more important for prediction than anatomical MRI, and that increasing sample size steadily increased prediction accuracy, providing an efficient strategy to improve biomarkers. We also observed that despite a strong incentive to generalise to unseen data, model development on a given dataset faces the risk of overfitting: performing well in cross-validation on the data at hand, but not generalising. Finally, we were able to predict ASD diagnosis on an external sample added after the end of the challenge (EU-AIMS), although with a lower prediction accuracy (AUC=0.72). This indicates that despite being based on a large multisite cohort, our challenge still produced biomarkers fragile in the face of dataset shifts.
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Affiliation(s)
- Nicolas Traut
- Institut Pasteur, Université de Paris, Département de neuroscience, F-75015 Paris, France; Center for Research and Interdisciplinarity (CRI), Université Paris Descartes, Paris, France
| | - Katja Heuer
- Institut Pasteur, Université de Paris, Département de neuroscience, F-75015 Paris, France; Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany; Center for Research and Interdisciplinarity (CRI), Université Paris Descartes, Paris, France
| | - Guillaume Lemaître
- Parietal, Inria, Saclay, France; Paris-Saclay Center for Data Science, Université Paris Saclay, Saclay, France
| | - Anita Beggiato
- Institut Pasteur, Université de Paris, Département de neuroscience, F-75015 Paris, France; Child and Adolescent Psychiatry Department, Robert Debré, APHP, Paris, France
| | | | | | | | | | - Weidong Cai
- Stanford University School of Medicine, Palo Alto, US
| | | | - Freddy Cliquet
- Institut Pasteur, Université de Paris, Département de neuroscience, F-75015 Paris, France
| | | | | | | | - Meng Wang
- Brainnetome Center and National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Valentina Zantedeschi
- Univ Lyon, UJM-Saint-Etienne, CNRS, Institut d'Optique Graduate School, Laboratoire Hubert Curien UMR 5516, F-42023, Saint-Etienne, France
| | - Alexandre Boucaud
- Parietal, Inria, Saclay, France; Paris-Saclay Center for Data Science, Université Paris Saclay, Saclay, France
| | - Joris van den Bossche
- Parietal, Inria, Saclay, France; Paris-Saclay Center for Data Science, Université Paris Saclay, Saclay, France
| | | | - Richard Delorme
- Institut Pasteur, Université de Paris, Département de neuroscience, F-75015 Paris, France; Child and Adolescent Psychiatry Department, Robert Debré, APHP, Paris, France
| | - Thomas Bourgeron
- Institut Pasteur, Université de Paris, Département de neuroscience, F-75015 Paris, France
| | - Roberto Toro
- Institut Pasteur, Université de Paris, Département de neuroscience, F-75015 Paris, France
| | - Gaël Varoquaux
- Parietal, Inria, Saclay, France; Soda, Inria, Saclay, France.
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Bethlehem RAI, Seidlitz J, White SR, Vogel JW, Anderson KM, Adamson C, Adler S, Alexopoulos GS, Anagnostou E, Areces-Gonzalez A, Astle DE, Auyeung B, Ayub M, Bae J, Ball G, Baron-Cohen S, Beare R, Bedford SA, Benegal V, Beyer F, Blangero J, Blesa Cábez M, Boardman JP, Borzage M, Bosch-Bayard JF, Bourke N, Calhoun VD, Chakravarty MM, Chen C, Chertavian C, Chetelat G, Chong YS, Cole JH, Corvin A, Costantino M, Courchesne E, Crivello F, Cropley VL, Crosbie J, Crossley N, Delarue M, Delorme R, Desrivieres S, Devenyi GA, Di Biase MA, Dolan R, Donald KA, Donohoe G, Dunlop K, Edwards AD, Elison JT, Ellis CT, Elman JA, Eyler L, Fair DA, Feczko E, Fletcher PC, Fonagy P, Franz CE, Galan-Garcia L, Gholipour A, Giedd J, Gilmore JH, Glahn DC, Goodyer IM, Grant PE, Groenewold NA, Gunning FM, Gur RE, Gur RC, Hammill CF, Hansson O, Hedden T, Heinz A, Henson RN, Heuer K, Hoare J, Holla B, Holmes AJ, Holt R, Huang H, Im K, Ipser J, Jack CR, Jackowski AP, Jia T, Johnson KA, Jones PB, Jones DT, Kahn RS, Karlsson H, Karlsson L, Kawashima R, Kelley EA, Kern S, Kim KW, Kitzbichler MG, Kremen WS, Lalonde F, Landeau B, Lee S, Lerch J, Lewis JD, Li J, Liao W, Liston C, Lombardo MV, Lv J, Lynch C, Mallard TT, Marcelis M, Markello RD, Mathias SR, Mazoyer B, McGuire P, Meaney MJ, Mechelli A, Medic N, Misic B, Morgan SE, Mothersill D, Nigg J, Ong MQW, Ortinau C, Ossenkoppele R, Ouyang M, Palaniyappan L, Paly L, Pan PM, Pantelis C, Park MM, Paus T, Pausova Z, Paz-Linares D, Pichet Binette A, Pierce K, Qian X, Qiu J, Qiu A, Raznahan A, Rittman T, Rodrigue A, Rollins CK, Romero-Garcia R, Ronan L, Rosenberg MD, Rowitch DH, Salum GA, Satterthwaite TD, Schaare HL, Schachar RJ, Schultz AP, Schumann G, Schöll M, Sharp D, Shinohara RT, Skoog I, Smyser CD, Sperling RA, Stein DJ, Stolicyn A, Suckling J, Sullivan G, Taki Y, Thyreau B, Toro R, Traut N, Tsvetanov KA, Turk-Browne NB, Tuulari JJ, Tzourio C, Vachon-Presseau É, Valdes-Sosa MJ, Valdes-Sosa PA, Valk SL, van Amelsvoort T, Vandekar SN, Vasung L, Victoria LW, Villeneuve S, Villringer A, Vértes PE, Wagstyl K, Wang YS, Warfield SK, Warrier V, Westman E, Westwater ML, Whalley HC, Witte AV, Yang N, Yeo B, Yun H, Zalesky A, Zar HJ, Zettergren A, Zhou JH, Ziauddeen H, Zugman A, Zuo XN, Bullmore ET, Alexander-Bloch AF. Brain charts for the human lifespan. Nature 2022; 604:525-533. [PMID: 35388223 PMCID: PMC9021021 DOI: 10.1038/s41586-022-04554-y] [Citation(s) in RCA: 372] [Impact Index Per Article: 186.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2021] [Accepted: 02/16/2022] [Indexed: 02/02/2023]
Abstract
Over the past few decades, neuroimaging has become a ubiquitous tool in basic research and clinical studies of the human brain. However, no reference standards currently exist to quantify individual differences in neuroimaging metrics over time, in contrast to growth charts for anthropometric traits such as height and weight1. Here we assemble an interactive open resource to benchmark brain morphology derived from any current or future sample of MRI data ( http://www.brainchart.io/ ). With the goal of basing these reference charts on the largest and most inclusive dataset available, acknowledging limitations due to known biases of MRI studies relative to the diversity of the global population, we aggregated 123,984 MRI scans, across more than 100 primary studies, from 101,457 human participants between 115 days post-conception to 100 years of age. MRI metrics were quantified by centile scores, relative to non-linear trajectories2 of brain structural changes, and rates of change, over the lifespan. Brain charts identified previously unreported neurodevelopmental milestones3, showed high stability of individuals across longitudinal assessments, and demonstrated robustness to technical and methodological differences between primary studies. Centile scores showed increased heritability compared with non-centiled MRI phenotypes, and provided a standardized measure of atypical brain structure that revealed patterns of neuroanatomical variation across neurological and psychiatric disorders. In summary, brain charts are an essential step towards robust quantification of individual variation benchmarked to normative trajectories in multiple, commonly used neuroimaging phenotypes.
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Affiliation(s)
- R A I Bethlehem
- Autism Research Centre, Department of Psychiatry, University of Cambridge, Cambridge, UK.
- Brain Mapping Unit, Department of Psychiatry, University of Cambridge, Cambridge, UK.
| | - J Seidlitz
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA, USA.
- Department of Child and Adolescent Psychiatry and Behavioral Science, The Children's Hospital of Philadelphia, Philadelphia, PA, USA.
- Lifespan Brain Institute, The Children's Hospital of Philadelphia and Penn Medicine, Philadelphia, PA, USA.
| | - S R White
- Department of Psychiatry, University of Cambridge, Cambridge, UK
- MRC Biostatistics Unit, University of Cambridge, Cambridge, UK
| | - J W Vogel
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA, USA
- Lifespan Informatics & Neuroimaging Center, University of Pennsylvania, Philadelphia, PA, USA
| | - K M Anderson
- Department of Psychology, Yale University, New Haven, CT, USA
| | - C Adamson
- Developmental Imaging, Murdoch Children's Research Institute, Melbourne, Victoria, Australia
- Department of Medicine, Monash University, Melbourne, Victoria, Australia
| | - S Adler
- UCL Great Ormond Street Institute for Child Health, London, UK
| | - G S Alexopoulos
- Weill Cornell Institute of Geriatric Psychiatry, Department of Psychiatry, Weill Cornell Medicine, New York, USA
| | - E Anagnostou
- Department of Pediatrics University of Toronto, Toronto, Canada
- Holland Bloorview Kids Rehabilitation Hospital, Toronto, Canada
| | - A Areces-Gonzalez
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for NeuroInformation, University of Electronic Science and Technology of China, Chengdu, China
- University of Pinar del Río "Hermanos Saiz Montes de Oca", Pinar del Río, Cuba
| | - D E Astle
- MRC Cognition and Brain Sciences Unit, University of Cambridge, Cambridge, UK
| | - B Auyeung
- Autism Research Centre, Department of Psychiatry, University of Cambridge, Cambridge, UK
- Department of Psychology, School of Philosophy, Psychology and Language Sciences, University of Edinburgh, Edinburgh, UK
| | - M Ayub
- Queen's University, Department of Psychiatry, Centre for Neuroscience Studies, Kingston, Ontario, Canada
- University College London, Mental Health Neuroscience Research Department, Division of Psychiatry, London, UK
| | - J Bae
- Department of Neuropsychiatry, Seoul National University Bundang Hospital, Seongnam, Korea
| | - G Ball
- Developmental Imaging, Murdoch Children's Research Institute, Melbourne, Victoria, Australia
- Department of Paediatrics, University of Melbourne, Melbourne, Victoria, Australia
| | - S Baron-Cohen
- Autism Research Centre, Department of Psychiatry, University of Cambridge, Cambridge, UK
- Cambridge Lifetime Asperger Syndrome Service (CLASS), Cambridgeshire and Peterborough NHS Foundation Trust, Cambridge, UK
| | - R Beare
- Developmental Imaging, Murdoch Children's Research Institute, Melbourne, Victoria, Australia
- Department of Medicine, Monash University, Melbourne, Victoria, Australia
| | - S A Bedford
- Autism Research Centre, Department of Psychiatry, University of Cambridge, Cambridge, UK
| | - V Benegal
- Centre for Addiction Medicine, National Institute of Mental Health and Neurosciences (NIMHANS), Bengaluru, India
| | - F Beyer
- Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - J Blangero
- Department of Human Genetics, South Texas Diabetes and Obesity Institute, University of Texas Rio Grande Valley, Edinburg, TX, USA
| | - M Blesa Cábez
- MRC Centre for Reproductive Health, University of Edinburgh, Edinburgh, UK
| | - J P Boardman
- MRC Centre for Reproductive Health, University of Edinburgh, Edinburgh, UK
| | - M Borzage
- Fetal and Neonatal Institute, Division of Neonatology, Children's Hospital Los Angeles, Department of Pediatrics, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - J F Bosch-Bayard
- McGill Centre for Integrative Neuroscience, Ludmer Centre for Neuroinformatics and Mental Health, Montreal Neurological Institute, Montreal, Quebec, Canada
- McGill University, Montreal, Quebec, Canada
| | - N Bourke
- Department of Brain Sciences, Imperial College London, London, UK
- Care Research and Technology Centre, Dementia Research Institute, London, UK
| | - V D Calhoun
- Tri-institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of Technology, and Emory University, Atlanta, GA, USA
| | - M M Chakravarty
- McGill University, Montreal, Quebec, Canada
- Computational Brain Anatomy (CoBrA) Laboratory, Cerebral Imaging Centre, Douglas Mental Health University Institute, Montreal, Quebec, Canada
| | - C Chen
- Penn Statistics in Imaging and Visualization Center, Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - C Chertavian
- Lifespan Brain Institute, The Children's Hospital of Philadelphia and Penn Medicine, Philadelphia, PA, USA
| | - G Chetelat
- Normandie Univ, UNICAEN, INSERM, U1237, PhIND "Physiopathology and Imaging of Neurological Disorders", Institut Blood and Brain @ Caen-Normandie, Cyceron, Caen, France
| | - Y S Chong
- Singapore Institute for Clinical Sciences, Agency for Science, Technology and Research, Singapore, Singapore
- Department of Obstetrics and Gynaecology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - J H Cole
- Centre for Medical Image Computing (CMIC), University College London, London, UK
- Dementia Research Centre (DRC), University College London, London, UK
| | - A Corvin
- Department of Psychiatry, Trinity College, Dublin, Ireland
| | - M Costantino
- Cerebral Imaging Centre, Douglas Mental Health University Institute, Verdun, Quebec, Canada
- Undergraduate program in Neuroscience, McGill University, Montreal, Quebec, Canada
| | - E Courchesne
- Department of Neuroscience, University of California, San Diego, San Diego, CA, USA
- Autism Center of Excellence, University of California, San Diego, San Diego, CA, USA
| | - F Crivello
- Institute of Neurodegenerative Disorders, CNRS UMR5293, CEA, University of Bordeaux, Bordeaux, France
| | - V L Cropley
- Melbourne Neuropsychiatry Centre, University of Melbourne, Melbourne, Victoria, Australia
| | - J Crosbie
- The Hospital for Sick Children, Toronto, Ontario, Canada
| | - N Crossley
- Department of Psychiatry, School of Medicine, Pontificia Universidad Católica de Chile, Santiago, Chile
- Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
- Instituto Milenio Intelligent Healthcare Engineering, Santiago, Chile
| | - M Delarue
- Normandie Univ, UNICAEN, INSERM, U1237, PhIND "Physiopathology and Imaging of Neurological Disorders", Institut Blood and Brain @ Caen-Normandie, Cyceron, Caen, France
| | - R Delorme
- Child and Adolescent Psychiatry Department, Robert Debré University Hospital, AP-HP, Paris, France
- Human Genetics and Cognitive Functions, Institut Pasteur, Paris, France
| | - S Desrivieres
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - G A Devenyi
- Cerebral Imaging Centre, McGill Department of Psychiatry, Douglas Mental Health University Institute, Montreal, QC, Canada
- Department of Psychiatry, McGill University, Montreal, QC, Canada
| | - M A Di Biase
- Melbourne Neuropsychiatry Centre, University of Melbourne, Melbourne, Victoria, Australia
- Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - R Dolan
- Max Planck UCL Centre for Computational Psychiatry and Ageing Research, University College London, London, UK
- Wellcome Centre for Human Neuroimaging, London, UK
| | - K A Donald
- Division of Developmental Paediatrics, Department of Paediatrics and Child Health, Red Cross War Memorial Children's Hospital, Cape Town, South Africa
- Neuroscience Institute, University of Cape Town, Cape Town, South Africa
| | - G Donohoe
- Center for Neuroimaging, Cognition & Genomics (NICOG), School of Psychology, National University of Ireland Galway, Galway, Ireland
| | - K Dunlop
- Weil Family Brain and Mind Research Institute, Department of Psychiatry, Weill Cornell Medicine, New York, NY, USA
| | - A D Edwards
- Centre for the Developing Brain, King's College London, London, UK
- Evelina London Children's Hospital, London, UK
- MRC Centre for Neurodevelopmental Disorders, London, UK
| | - J T Elison
- Institute of Child Development, Department of Pediatrics, Masonic Institute for the Developing Brain, University of Minnesota, Minneapolis, MN, USA
| | - C T Ellis
- Department of Psychology, Yale University, New Haven, CT, USA
- Haskins Laboratories, New Haven, CT, USA
| | - J A Elman
- Department of Psychiatry, Center for Behavior Genetics of Aging, University of California, San Diego, La Jolla, CA, USA
| | - L Eyler
- Desert-Pacific Mental Illness Research Education and Clinical Center, VA San Diego Healthcare, San Diego, CA, USA
- Department of Psychiatry, University of California San Diego, Los Angeles, CA, USA
| | - D A Fair
- Institute of Child Development, Department of Pediatrics, Masonic Institute for the Developing Brain, University of Minnesota, Minneapolis, MN, USA
| | - E Feczko
- Institute of Child Development, Department of Pediatrics, Masonic Institute for the Developing Brain, University of Minnesota, Minneapolis, MN, USA
| | - P C Fletcher
- Department of Psychiatry, University of Cambridge, and Wellcome Trust MRC Institute of Metabolic Science, Cambridge Biomedical Campus, Cambridge, UK
- Cambridgeshire and Peterborough NHS Foundation Trust, Cambridge, UK
| | - P Fonagy
- Department of Clinical, Educational and Health Psychology, University College London, London, UK
- Anna Freud National Centre for Children and Families, London, UK
| | - C E Franz
- Department of Psychiatry, Center for Behavior Genetics of Aging, University of California, San Diego, La Jolla, CA, USA
| | | | - A Gholipour
- Computational Radiology Laboratory, Boston Children's Hospital, Boston, MA, USA
| | - J Giedd
- Department of Child and Adolescent Psychiatry, University of California, San Diego, San Diego, CA, USA
- Department of Psychiatry, University of California San Diego, San Diego, CA, USA
| | - J H Gilmore
- Department of Psychiatry, University of North Carolina, Chapel Hill, NC, USA
| | - D C Glahn
- Department of Psychiatry, Boston Children's Hospital and Harvard Medical School, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
| | - I M Goodyer
- Department of Psychiatry, University of Cambridge, Cambridge, UK
| | - P E Grant
- Division of Newborn Medicine and Neuroradiology, Fetal Neonatal Neuroimaging and Developmental Science Center, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
| | - N A Groenewold
- Neuroscience Institute, University of Cape Town, Cape Town, South Africa
- Department of Paediatrics and Child Health, Red Cross War Memorial Children's Hospital, SA-MRC Unit on Child & Adolescent Health, University of Cape Town, Cape Town, South Africa
| | - F M Gunning
- Weill Cornell Institute of Geriatric Psychiatry, Department of Psychiatry, Weill Cornell Medicine, New York, NY, USA
| | - R E Gur
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA, USA
- Lifespan Brain Institute, The Children's Hospital of Philadelphia and Penn Medicine, Philadelphia, PA, USA
| | - R C Gur
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA, USA
- Lifespan Brain Institute, The Children's Hospital of Philadelphia and Penn Medicine, Philadelphia, PA, USA
| | - C F Hammill
- The Hospital for Sick Children, Toronto, Ontario, Canada
- Mouse Imaging Centre, Toronto, Ontario, Canada
| | - O Hansson
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, Malmö, Sweden
- Memory Clinic, Skåne University Hospital, Malmö, Sweden
| | - T Hedden
- Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - A Heinz
- Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Department of Psychiatry and Psychotherapy, Charité Campus Mitte, Berlin, Germany
| | - R N Henson
- Department of Psychiatry, University of Cambridge, Cambridge, UK
- MRC Cognition and Brain Sciences Unit, University of Cambridge, Cambridge, UK
| | - K Heuer
- Department of Neuropsychology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
- Université de Paris, Paris, France
| | - J Hoare
- Department of Psychiatry, University of Cape Town, Cape Town, South Africa
| | - B Holla
- Department of Integrative Medicine, NIMHANS, Bengaluru, India
- Accelerator Program for Discovery in Brain disorders using Stem cells (ADBS), Department of Psychiatry, NIMHANS, Bengaluru, India
| | - A J Holmes
- Departments of Psychology and Psychiatry, Yale University, New Haven, CT, USA
| | - R Holt
- Autism Research Centre, Department of Psychiatry, University of Cambridge, Cambridge, UK
| | - H Huang
- Radiology Research, Children's Hospital of Philadelphia, Philadelphia, PA, USA
- The Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - K Im
- Department of Psychiatry, Boston Children's Hospital and Harvard Medical School, Boston, MA, USA
- Division of Newborn Medicine and Neuroradiology, Fetal Neonatal Neuroimaging and Developmental Science Center, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
| | - J Ipser
- Department of Psychiatry and Mental Health, Clinical Neuroscience Institute, University of Cape Town, Cape Town, South Africa
| | - C R Jack
- Department of Radiology, Mayo Clinic, Rochester, MN, USA
| | - A P Jackowski
- Department of Psychiatry, Universidade Federal de São Paulo, São Paulo, Brazil
- National Institute of Developmental Psychiatry, Beijing, China
| | - T Jia
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China
- Key Laboratory of Computational Neuroscience and BrainInspired Intelligence (Fudan University), Ministry of Education, Shanghai, China
- Centre for Population Neuroscience and Precision Medicine (PONS), Institute of Psychiatry, Psychology and Neuroscience, SGDP Centre, King's College London, London, UK
| | - K A Johnson
- Harvard Medical School, Boston, MA, USA
- Harvard Aging Brain Study, Department of Neurology, Massachusetts General Hospital, Boston, MA, USA
- Center for Alzheimer Research and Treatment, Department of Neurology, Brigham and Women's Hospital, Boston, MA, USA
- Department of Radiology, Massachusetts General Hospital, Boston, MA, USA
| | - P B Jones
- Department of Psychiatry, University of Cambridge, Cambridge, UK
- Cambridgeshire and Peterborough NHS Foundation Trust, Cambridge, UK
| | - D T Jones
- Department of Radiology, Mayo Clinic, Rochester, MN, USA
- Department of Neurology, Mayo Clinic, Rochester, MN, USA
| | - R S Kahn
- Department of Psychiatry, Icahn School of Medicine, Mount Sinai, NY, USA
| | - H Karlsson
- Department of Clinical Medicine, Department of Psychiatry and Turku Brain and Mind Center, FinnBrain Birth Cohort Study, University of Turku and Turku University Hospital, Turku, Finland
- Centre for Population Health Research, Turku University Hospital and University of Turku, Turku, Finland
| | - L Karlsson
- Department of Clinical Medicine, Department of Psychiatry and Turku Brain and Mind Center, FinnBrain Birth Cohort Study, University of Turku and Turku University Hospital, Turku, Finland
- Centre for Population Health Research, Turku University Hospital and University of Turku, Turku, Finland
| | - R Kawashima
- Institute of Development, Aging and Cancer, Tohoku University, Seiryocho, Aobaku, Sendai, Japan
| | - E A Kelley
- Queen's University, Departments of Psychology and Psychiatry, Centre for Neuroscience Studies, Kingston, Ontario, Canada
| | - S Kern
- Neuropsychiatric Epidemiology Unit, Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, the Sahlgrenska Academy, Centre for Ageing and Health (AGECAP) at the University of Gothenburg, Gothenburg, Sweden
- Region Västra Götaland, Sahlgrenska University Hospital, Psychiatry, Cognition and Old Age Psychiatry Clinic, Gothenburg, Sweden
| | - K W Kim
- Department of Brain and Cognitive Sciences, Seoul National University College of Natural Sciences, Seoul, South Korea
- Department of Neuropsychiatry, Seoul National University Bundang Hospital, Seongnam, South Korea
- Department of Psychiatry, Seoul National University College of Medicine, Seoul, South Korea
- Institute of Human Behavioral Medicine, SNU-MRC, Seoul, South Korea
| | - M G Kitzbichler
- Brain Mapping Unit, Department of Psychiatry, University of Cambridge, Cambridge, UK
- Department of Psychiatry, University of Cambridge, Cambridge, UK
| | - W S Kremen
- Department of Psychiatry, Center for Behavior Genetics of Aging, University of California, San Diego, La Jolla, CA, USA
| | - F Lalonde
- Section on Developmental Neurogenomics, Human Genetics Branch, National Institute of Mental Health, Bethesda, MD, USA
| | - B Landeau
- Normandie Univ, UNICAEN, INSERM, U1237, PhIND "Physiopathology and Imaging of Neurological Disorders", Institut Blood and Brain @ Caen-Normandie, Cyceron, Caen, France
| | - S Lee
- Department of Brain & Cognitive Sciences, Seoul National University College of Natural Sciences, Seoul, South Korea
| | - J Lerch
- Mouse Imaging Centre, Toronto, Ontario, Canada
- Department of Medical Biophysics, University of Toronto, Toronto, Ontario, Canada
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neuroscience, University of Oxford, Oxford, UK
| | - J D Lewis
- Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada
| | - J Li
- The Clinical Hospital of Chengdu Brain Science Institute, University of Electronic Science and Technology of China, Chengdu, China
| | - W Liao
- The Clinical Hospital of Chengdu Brain Science Institute, University of Electronic Science and Technology of China, Chengdu, China
| | - C Liston
- Department of Psychiatry and Brain and Mind Research Institute, Weill Cornell Medicine, New York, NY, USA
| | - M V Lombardo
- Autism Research Centre, Department of Psychiatry, University of Cambridge, Cambridge, UK
- Laboratory for Autism and Neurodevelopmental Disorders, Center for Neuroscience and Cognitive Systems @UniTn, Istituto Italiano di Tecnologia, Rovereto, Italy
| | - J Lv
- Melbourne Neuropsychiatry Centre, University of Melbourne, Melbourne, Victoria, Australia
- School of Biomedical Engineering and Brain and Mind Centre, The University of Sydney, Sydney, New South Wales, Australia
| | - C Lynch
- Weil Family Brain and Mind Research Institute, Department of Psychiatry, Weill Cornell Medicine, New York, NY, USA
| | - T T Mallard
- Department of Psychology, University of Texas, Austin, TX, USA
| | - M Marcelis
- Department of Psychiatry and Neuropsychology, School of Mental Health and Neuroscience, EURON, Maastricht University Medical Centre, Maastricht, The Netherlands
- Institute for Mental Health Care Eindhoven (GGzE), Eindhoven, The Netherlands
| | - R D Markello
- McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada
| | - S R Mathias
- Department of Psychiatry, Boston Children's Hospital and Harvard Medical School, Boston, MA, USA
| | - B Mazoyer
- Institute of Neurodegenerative Disorders, CNRS UMR5293, CEA, University of Bordeaux, Bordeaux, France
- Ludmer Centre for Neuroinformatics and Mental Health, Douglas Mental Health University Institute, Montreal, Quebec, Canada
| | - P McGuire
- Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - M J Meaney
- Ludmer Centre for Neuroinformatics and Mental Health, Douglas Mental Health University Institute, Montreal, Quebec, Canada
- Singapore Institute for Clinical Sciences, Singapore, Singapore
| | - A Mechelli
- Bordeaux University Hospital, Bordeaux, France
| | - N Medic
- Department of Psychiatry, University of Cambridge, Cambridge, UK
| | - B Misic
- McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada
| | - S E Morgan
- Department of Psychiatry, University of Cambridge, Cambridge, UK
- Department of Computer Science and Technology, University of Cambridge, Cambridge, UK
- The Alan Turing Institute, London, UK
| | - D Mothersill
- Department of Psychology, School of Business, National College of Ireland, Dublin, Ireland
- School of Psychology and Center for Neuroimaging and Cognitive Genomics, National University of Ireland Galway, Galway, Ireland
- Department of Psychiatry, Trinity College Dublin, Dublin, Ireland
| | - J Nigg
- Department of Psychiatry, School of Medicine, Oregon Health and Science University, Portland, OR, USA
| | - M Q W Ong
- Center for Sleep and Cognition, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - C Ortinau
- Department of Pediatrics, Washington University in St Louis, St Louis, MO, USA
| | - R Ossenkoppele
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
- Lund University, Clinical Memory Research Unit, Lund, Sweden
| | - M Ouyang
- Radiology Research, Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - L Palaniyappan
- Robarts Research Institute and The Brain and Mind Institute, University of Western Ontario, London, Ontario, Canada
| | - L Paly
- Normandie Univ, UNICAEN, INSERM, U1237, PhIND "Physiopathology and Imaging of Neurological Disorders", Institut Blood and Brain @ Caen-Normandie, Cyceron, Caen, France
| | - P M Pan
- Department of Psychiatry, Federal University of Sao Poalo (UNIFESP), Sao Poalo, Brazil
- National Institute of Developmental Psychiatry for Children and Adolescents (INPD), Sao Poalo, Brazil
| | - C Pantelis
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne and Melbourne Health, Carlton South, Victoria, Australia
- Melbourne School of Engineering, The University of Melbourne, Parkville, Victoria, Australia
- Florey Institute of Neuroscience and Mental Health, Parkville, Victoria, Australia
| | - M M Park
- Department of Psychiatry, Schulich School of Medicine and Dentistry, Western University, London, Ontario, Canada
| | - T Paus
- Department of Psychiatry, Faculty of Medicine and Centre Hospitalier Universitaire Sainte-Justine, University of Montreal, Montreal, Quebec, Canada
- Departments of Psychiatry and Psychology, University of Toronto, Toronto, Ontario, Canada
| | - Z Pausova
- The Hospital for Sick Children, Toronto, Ontario, Canada
- Departments of Physiology and Nutritional Sciences, University of Toronto, Toronto, Ontario, Canada
| | - D Paz-Linares
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for NeuroInformation, University of Electronic Science and Technology of China, Chengdu, China
- Cuban Neuroscience Center, Havana, Cuba
| | - A Pichet Binette
- Department of Psychiatry, Faculty of Medicine, McGill University, Montreal, Quebec, Canada
- Douglas Mental Health University Institute, Montreal, Quebec, Canada
| | - K Pierce
- Department of Neuroscience, University of California, San Diego, San Diego, CA, USA
| | - X Qian
- Center for Sleep and Cognition, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - J Qiu
- School of Psychology, Southwest University, Chongqing, China
| | - A Qiu
- Department of Biomedical Engineering, The N.1 Institute for Health, National University of Singapore, Singapore, Singapore
| | - A Raznahan
- Section on Developmental Neurogenomics, Human Genetics Branch, National Institute of Mental Health, Bethesda, MD, USA
| | - T Rittman
- Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK
| | - A Rodrigue
- Department of Psychiatry, Boston Children's Hospital and Harvard Medical School, Boston, MA, USA
| | - C K Rollins
- Department of Neurology, Harvard Medical School, Boston, MA, USA
- Department of Neurology, Boston Children's Hospital, Boston, MA, USA
| | - R Romero-Garcia
- Department of Psychiatry, University of Cambridge, Cambridge, UK
- Instituto de Biomedicina de Sevilla (IBiS) HUVR/CSIC/Universidad de Sevilla, Dpto. de Fisiología Médica y Biofísica, Seville, Spain
| | - L Ronan
- Department of Psychiatry, University of Cambridge, Cambridge, UK
| | - M D Rosenberg
- Department of Psychology and Neuroscience Institute, University of Chicago, Chicago, IL, USA
| | - D H Rowitch
- Department of Paediatrics and Wellcome-MRC Cambridge Stem Cell Institute, University of Cambridge, Cambridge, UK
| | - G A Salum
- Department of Psychiatry, Universidade Federal do Rio Grande do Sul (UFRGS), Hospital de Clinicas de Porto Alegre, Porto Alegre, Brazil
- National Institute of Developmental Psychiatry (INPD), São Paulo, Brazil
| | - T D Satterthwaite
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA, USA
- Lifespan Informatics & Neuroimaging Center, University of Pennsylvania, Philadelphia, PA, USA
| | - H L Schaare
- Otto Hahn Group Cognitive Neurogenetics, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
- Institute of Neuroscience and Medicine (INM-7: Brain and Behaviour), Research Centre Juelich, Juelich, Germany
| | - R J Schachar
- The Hospital for Sick Children, Toronto, Ontario, Canada
| | - A P Schultz
- Harvard Medical School, Boston, MA, USA
- Harvard Aging Brain Study, Department of Neurology, Massachusetts General Hospital, Boston, MA, USA
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, MA, USA
| | - G Schumann
- Centre for Population Neuroscience and Stratified Medicine (PONS), Institute for Science and Technology for Brain-inspired Intelligence, Fudan University, Shanghai, China
- PONS-Centre, Charite Mental Health, Dept of Psychiatry and Psychotherapy, Charite Campus Mitte, Berlin, Germany
| | - M Schöll
- Wallenberg Centre for Molecular and Translational Medicine, University of Gothenburg, Gothenburg, Sweden
- Department of Psychiatry and Neurochemistry, University of Gothenburg, Gothenburg, Sweden
- Dementia Research Centre, Queen's Square Institute of Neurology, University College London, London, UK
| | - D Sharp
- Department of Brain Sciences, Imperial College London, London, UK
- Care Research and Technology Centre, UK Dementia Research Institute, London, UK
| | - R T Shinohara
- Penn Statistics in Imaging and Visualization Center, Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Center for Biomedical Image Computing and Analytics, Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - I Skoog
- Neuropsychiatric Epidemiology Unit, Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, the Sahlgrenska Academy, Centre for Ageing and Health (AGECAP) at the University of Gothenburg, Gothenburg, Sweden
- Region Västra Götaland, Sahlgrenska University Hospital, Psychiatry, Cognition and Old Age Psychiatry Clinic, Gothenburg, Sweden
| | - C D Smyser
- Departments of Neurology, Pediatrics, and Radiology, Washington University School of Medicine, St Louis, MO, USA
| | - R A Sperling
- Harvard Medical School, Boston, MA, USA
- Harvard Aging Brain Study, Department of Neurology, Massachusetts General Hospital, Boston, MA, USA
- Center for Alzheimer Research and Treatment, Department of Neurology, Brigham and Women's Hospital, Boston, MA, USA
| | - D J Stein
- SA MRC Unit on Risk and Resilience in Mental Disorders, Dept of Psychiatry and Neuroscience Institute, University of Cape Town, Cape Town, South Africa
| | - A Stolicyn
- Division of Psychiatry, Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
| | - J Suckling
- Department of Psychiatry, University of Cambridge, Cambridge, UK
- Cambridgeshire and Peterborough NHS Foundation Trust, Cambridge, UK
| | - G Sullivan
- MRC Centre for Reproductive Health, University of Edinburgh, Edinburgh, UK
| | - Y Taki
- Institute of Development, Aging and Cancer, Tohoku University, Seiryocho, Aobaku, Sendai, Japan
| | - B Thyreau
- Institute of Development, Aging and Cancer, Tohoku University, Seiryocho, Aobaku, Sendai, Japan
| | - R Toro
- Université de Paris, Paris, France
- Department of Neuroscience, Institut Pasteur, Paris, France
| | - N Traut
- Department of Neuroscience, Institut Pasteur, Paris, France
- Center for Research and Interdisciplinarity (CRI), Université Paris Descartes, Paris, France
| | - K A Tsvetanov
- Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK
- Department of Psychology, University of Cambridge, Cambridge, UK
| | - N B Turk-Browne
- Department of Psychology, Yale University, New Haven, CT, USA
- Wu Tsai Institute, Yale University, New Haven, CT, USA
| | - J J Tuulari
- Department of Clinical Medicine, Department of Psychiatry and Turku Brain and Mind Center, FinnBrain Birth Cohort Study, University of Turku and Turku University Hospital, Turku, Finland
- Department of Clinical Medicine, University of Turku, Turku, Finland
- Turku Collegium for Science, Medicine and Technology, University of Turku, Turku, Finland
| | - C Tzourio
- Univ. Bordeaux, Inserm, Bordeaux Population Health Research Center, U1219, CHU Bordeaux, Bordeaux, France
| | - É Vachon-Presseau
- Faculty of Dental Medicine and Oral Health Sciences, McGill University, Montreal, Quebec, Canada
| | | | - P A Valdes-Sosa
- The Clinical Hospital of Chengdu Brain Science Institute, University of Electronic Science and Technology of China, Chengdu, China
- Alan Edwards Centre for Research on Pain (AECRP), McGill University, Montreal, Quebec, Canada
| | - S L Valk
- Institute for Neuroscience and Medicine 7, Forschungszentrum Jülich, Jülich, Germany
- Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - T van Amelsvoort
- Department of Psychiatry and Neurosychology, Maastricht University, Maastricht, The Netherlands
| | - S N Vandekar
- Department of Biostatistics, Vanderbilt University, Nashville, TN, USA
- Department of Biostatistics, Vanderbilt University Medical Center, Nashville, TN, USA
| | - L Vasung
- McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada
| | - L W Victoria
- Weill Cornell Institute of Geriatric Psychiatry, Department of Psychiatry, Weill Cornell Medicine, New York, NY, USA
| | - S Villeneuve
- McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada
- Department of Psychiatry, Faculty of Medicine, McGill University, Montreal, Quebec, Canada
- Douglas Mental Health University Institute, Montreal, Quebec, Canada
| | - A Villringer
- Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
- Clinic for Cognitive Neurology, University of Leipzig Medical Center, Leipzig, Germany
| | - P E Vértes
- Department of Psychiatry, University of Cambridge, Cambridge, UK
- The Alan Turing Institute, London, UK
| | - K Wagstyl
- Wellcome Centre for Human Neuroimaging, London, UK
| | - Y S Wang
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
- Developmental Population Neuroscience Research Center, IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
- National Basic Science Data Center, Beijing, China
- Research Center for Lifespan Development of Brain and Mind, Institute of Psychology, Chinese Academy of Sciences, Beijing, China
| | - S K Warfield
- Computational Radiology Laboratory, Boston Children's Hospital, Boston, MA, USA
| | - V Warrier
- Department of Psychiatry, University of Cambridge, Cambridge, UK
| | - E Westman
- Division of Clinical Geriatrics, Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden
| | - M L Westwater
- Department of Psychiatry, University of Cambridge, Cambridge, UK
| | - H C Whalley
- Division of Psychiatry, Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
| | - A V Witte
- Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
- Clinic for Cognitive Neurology, University of Leipzig Medical Center, Leipzig, Germany
- Faculty of Medicine, CRC 1052 'Obesity Mechanisms', University of Leipzig, Leipzig, Germany
| | - N Yang
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
- Developmental Population Neuroscience Research Center, IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
- National Basic Science Data Center, Beijing, China
- Research Center for Lifespan Development of Brain and Mind, Institute of Psychology, Chinese Academy of Sciences, Beijing, China
| | - B Yeo
- Department of Electrical and Computer Engineering, National University of Singapore, Singapore, Singapore
- Centre for Sleep and Cognition and Centre for Translational MR Research, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
- N.1 Institute for Health & Institute for Digital Medicine, National University of Singapore, Singapore, Singapore
- Integrative Sciences and Engineering Programme (ISEP), National University of Singapore, Singapore, Singapore
| | - H Yun
- Division of Newborn Medicine and Neuroradiology, Fetal Neonatal Neuroimaging and Developmental Science Center, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
| | - A Zalesky
- Melbourne Neuropsychiatry Centre, University of Melbourne, Melbourne, Victoria, Australia
- Department of Biomedical Engineering, University of Melbourne, Melbourne, Victoria, Australia
| | - H J Zar
- Department of Paediatrics and Child Health, Red Cross War Memorial Children's Hospital, SA-MRC Unit on Child & Adolescent Health, University of Cape Town, Cape Town, South Africa
| | - A Zettergren
- Neuropsychiatric Epidemiology Unit, Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, the Sahlgrenska Academy, Centre for Ageing and Health (AGECAP) at the University of Gothenburg, Gothenburg, Sweden
| | - J H Zhou
- Center for Sleep and Cognition, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
- Department of Electrical and Computer Engineering, National University of Singapore, Singapore, Singapore
- Center for Translational Magnetic Resonance Research, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - H Ziauddeen
- Department of Psychiatry, University of Cambridge, Cambridge, UK
- Cambridgeshire and Peterborough NHS Foundation Trust, Cambridge, UK
- Wellcome Trust-MRC Institute of Metabolic Science, University of Cambridge, Cambridge, UK
| | - A Zugman
- National Institute of Developmental Psychiatry for Children and Adolescents (INPD), Sao Poalo, Brazil
- National Institute of Mental Health (NIMH), National Institutes of Health (NIH), Bethesda, MD, USA
- Department of Psychiatry, Escola Paulista de Medicina, São Paulo, Brazil
| | - X N Zuo
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
- Developmental Population Neuroscience Research Center, IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
- National Basic Science Data Center, Beijing, China
- Research Center for Lifespan Development of Brain and Mind, Institute of Psychology, Chinese Academy of Sciences, Beijing, China
- Key Laboratory of Brain and Education, School of Education Science, Nanning Normal University, Nanning, China
| | - E T Bullmore
- Department of Psychiatry, University of Cambridge, Cambridge, UK
| | - A F Alexander-Bloch
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA, USA
- Department of Child and Adolescent Psychiatry and Behavioral Science, The Children's Hospital of Philadelphia, Philadelphia, PA, USA
- Lifespan Brain Institute, The Children's Hospital of Philadelphia and Penn Medicine, Philadelphia, PA, USA
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14
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Phelan K, Boccuto L, Powell CM, Boeckers TM, van Ravenswaaij-Arts C, Rogers RC, Sala C, Verpelli C, Thurm A, Bennett WE, Winrow CJ, Garrison SR, Toro R, Bourgeron T. Phelan-McDermid syndrome: a classification system after 30 years of experience. Orphanet J Rare Dis 2022; 17:27. [PMID: 35093143 PMCID: PMC8800328 DOI: 10.1186/s13023-022-02180-5] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/27/2021] [Accepted: 01/16/2022] [Indexed: 01/15/2023] Open
Abstract
Phelan-McDermid syndrome (PMS) was initially called the 22q13 deletion syndrome based on its etiology as a deletion of the distal long arm of chromosome 22. These included terminal and interstitial deletions, as well as other structural rearrangements. Later, pathogenetic variants and deletions of the SHANK3 gene were found to result in a phenotype consistent with PMS. The association between SHANK3 and PMS led investigators to consider disruption/deletion of SHANK3 to be a prerequisite for diagnosing PMS. This narrow definition of PMS based on the involvement of SHANK3 has the adverse effect of causing patients with interstitial deletions of chromosome 22 to “lose” their diagnosis. It also results in underreporting of individuals with interstitial deletions of 22q13 that preserve SHANK3. To reduce the confusion for families, clinicians, researchers, and pharma, a simple classification for PMS has been devised. PMS and will be further classified as PMS-SHANK3 related or PMS-SHANK3 unrelated. PMS can still be used as a general term, but this classification system is inclusive. It allows researchers, regulatory agencies, and other stakeholders to define SHANK3 alterations or interstitial deletions not affecting the SHANK3 coding region.
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15
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Milham M, Petkov C, Belin P, Ben Hamed S, Evrard H, Fair D, Fox A, Froudist-Walsh S, Hayashi T, Kastner S, Klink C, Majka P, Mars R, Messinger A, Poirier C, Schroeder C, Shmuel A, Silva AC, Vanduffel W, Van Essen DC, Wang Z, Roe AW, Wilke M, Xu T, Aarabi MH, Adolphs R, Ahuja A, Alvand A, Amiez C, Autio J, Azadi R, Baeg E, Bai R, Bao P, Basso M, Behel AK, Bennett Y, Bernhardt B, Biswal B, Boopathy S, Boretius S, Borra E, Boshra R, Buffalo E, Cao L, Cavanaugh J, Celine A, Chavez G, Chen LM, Chen X, Cheng L, Chouinard-Decorte F, Clavagnier S, Cléry J, Colcombe SJ, Conway B, Cordeau M, Coulon O, Cui Y, Dadarwal R, Dahnke R, Desrochers T, Deying L, Dougherty K, Doyle H, Drzewiecki CM, Duyck M, Arachchi WE, Elorette C, Essamlali A, Evans A, Fajardo A, Figueroa H, Franco A, Freches G, Frey S, Friedrich P, Fujimoto A, Fukunaga M, Gacoin M, Gallardo G, Gao L, Gao Y, Garside D, Garza-Villarreal EA, Gaudet-Trafit M, Gerbella M, Giavasis S, Glen D, Ribeiro Gomes AR, Torrecilla SG, Gozzi A, Gulli R, Haber S, Hadj-Bouziane F, Fujimoto SH, Hawrylycz M, He Q, He Y, Heuer K, Hiba B, Hoffstaedter F, Hong SJ, Hori Y, Hou Y, Howard A, de la Iglesia-Vaya M, Ikeda T, Jankovic-Rapan L, Jaramillo J, Jedema HP, Jin H, Jiang M, Jung B, Kagan I, Kahn I, Kiar G, Kikuchi Y, Kilavik B, Kimura N, Klatzmann U, Kwok SC, Lai HY, Lamberton F, Lehman J, Li P, Li X, Li X, Liang Z, Liston C, Little R, Liu C, Liu N, Liu X, Liu X, Lu H, Loh KK, Madan C, Magrou L, Margulies D, Mathilda F, Mejia S, Meng Y, Menon R, Meunier D, Mitchell A, Mitchell A, Murphy A, Mvula T, Ortiz-Rios M, Ortuzar Martinez DE, Pagani M, Palomero-Gallagher N, Pareek V, Perkins P, Ponce F, Postans M, Pouget P, Qian M, Ramirez J“B, Raven E, Restrepo I, Rima S, Rockland K, Rodriguez NY, Roger E, Hortelano ER, Rosa M, Rossi A, Rudebeck P, Russ B, Sakai T, Saleem KS, Sallet J, Sawiak S, Schaeffer D, Schwiedrzik CM, Seidlitz J, Sein J, Sharma J, Shen K, Sheng WA, Shi NS, Shim WM, Simone L, Sirmpilatze N, Sivan V, Song X, Tanenbaum A, Tasserie J, Taylor P, Tian X, Toro R, Trambaiolli L, Upright N, Vezoli J, Vickery S, Villalon J, Wang X, Wang Y, Weiss AR, Wilson C, Wong TY, Woo CW, Wu B, Xiao D, Xu AG, Xu D, Xufeng Z, Yacoub E, Ye N, Ying Z, Yokoyama C, Yu X, Yue S, Yuheng L, Yumeng X, Zaldivar D, Zhang S, Zhao Y, Zuo Z. Toward next-generation primate neuroscience: A collaboration-based strategic plan for integrative neuroimaging. Neuron 2022; 110:16-20. [PMID: 34731649 DOI: 10.1016/j.neuron.2021.10.015] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2021] [Revised: 09/30/2021] [Accepted: 10/11/2021] [Indexed: 12/22/2022]
Abstract
Open science initiatives are creating opportunities to increase research coordination and impact in nonhuman primate (NHP) imaging. The PRIMatE Data and Resource Exchange community recently developed a collaboration-based strategic plan to advance NHP imaging as an integrative approach for multiscale neuroscience.
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16
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Loth E, Ahmad J, Chatham C, López B, Carter B, Crawley D, Oakley B, Hayward H, Cooke J, San José Cáceres A, Bzdok D, Jones E, Charman T, Beckmann C, Bourgeron T, Toro R, Buitelaar J, Murphy D, Dumas G. The meaning of significant mean group differences for biomarker discovery. PLoS Comput Biol 2021; 17:e1009477. [PMID: 34793435 PMCID: PMC8601419 DOI: 10.1371/journal.pcbi.1009477] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/21/2023] Open
Abstract
Over the past decade, biomarker discovery has become a key goal in psychiatry to aid in the more reliable diagnosis and prognosis of heterogeneous psychiatric conditions and the development of tailored therapies. Nevertheless, the prevailing statistical approach is still the mean group comparison between "cases" and "controls," which tends to ignore within-group variability. In this educational article, we used empirical data simulations to investigate how effect size, sample size, and the shape of distributions impact the interpretation of mean group differences for biomarker discovery. We then applied these statistical criteria to evaluate biomarker discovery in one area of psychiatric research-autism research. Across the most influential areas of autism research, effect size estimates ranged from small (d = 0.21, anatomical structure) to medium (d = 0.36 electrophysiology, d = 0.5, eye-tracking) to large (d = 1.1 theory of mind). We show that in normal distributions, this translates to approximately 45% to 63% of cases performing within 1 standard deviation (SD) of the typical range, i.e., they do not have a deficit/atypicality in a statistical sense. For a measure to have diagnostic utility as defined by 80% sensitivity and 80% specificity, Cohen's d of 1.66 is required, with still 40% of cases falling within 1 SD. However, in both normal and nonnormal distributions, 1 (skewness) or 2 (platykurtic, bimodal) biologically plausible subgroups may exist despite small or even nonsignificant mean group differences. This conclusion drastically contrasts the way mean group differences are frequently reported. Over 95% of studies omitted the "on average" when summarising their findings in their abstracts ("autistic people have deficits in X"), which can be misleading as it implies that the group-level difference applies to all individuals in that group. We outline practical approaches and steps for researchers to explore mean group comparisons for the discovery of stratification biomarkers.
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Affiliation(s)
- Eva Loth
- Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, United Kingdom
- Sackler Institute for Translational Neuroscience, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, United Kingdom
| | - Jumana Ahmad
- Department of Psychology, Social Work and Counselling, Faculty of Education and Health, University of Greenwich, London, United Kingdom
| | - Chris Chatham
- Neuroscience & Rare Diseases, Pharma Research & Early Development, Roche Innovation Center New York, New York, United States of America
| | - Beatriz López
- Department of Psychology, Portsmouth University, Portsmouth, United Kingdom
| | - Ben Carter
- Department of Biostatistics, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, United Kingdom
| | - Daisy Crawley
- Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, United Kingdom
| | - Bethany Oakley
- Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, United Kingdom
| | - Hannah Hayward
- Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, United Kingdom
| | - Jennifer Cooke
- Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, United Kingdom
| | - Antonia San José Cáceres
- Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, United Kingdom
- Instituto de Investigación Sanitaria Gregorio Marañón, Departamento de Psiquiatría del Niño y del Adolescente, Hospital General Universitario Gregorio Marañón and Centro Investigación Biomédica en Red Salud Mental (CIBERSAM), Madrid, Spain
| | - Danilo Bzdok
- Department of Biomedical Engineering, McConnell Brain-Imaging Centre (BIC), Montreal Neurological Institute (MNI), Faculty of Medicine, McGill University, Montreal, Canada
- Canadian Institute for Advanced Research (CIFAR), Canada
- Mila–Quebec Artificial Intelligence Institute, Montreal, Canada
| | - Emily Jones
- Centre for Brain and Cognitive Development, Birkbeck, University of London, London, United Kingdom
| | - Tony Charman
- Department of Psychology, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, United Kingdom
| | - Christian Beckmann
- Department of Cognitive Neuroscience, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Centre, Nijmegen, the Netherlands
| | - Thomas Bourgeron
- Human Genetics and Cognitive Functions, Institut Pasteur, UMR3571 CNRS, Université de Paris, Paris, France
| | - Roberto Toro
- Human Genetics and Cognitive Functions, Institut Pasteur, UMR3571 CNRS, Université de Paris, Paris, France
| | - Jan Buitelaar
- Department of Cognitive Neuroscience, Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Centre, Nijmegen, the Netherlands
| | - Declan Murphy
- Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, United Kingdom
- Sackler Institute for Translational Neuroscience, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, United Kingdom
| | - Guillaume Dumas
- Mila–Quebec Artificial Intelligence Institute, Montreal, Canada
- Human Genetics and Cognitive Functions, Institut Pasteur, UMR3571 CNRS, Université de Paris, Paris, France
- Precision Psychiatry and Social Physiology laboratory, CHU Sainte-Justine Research Center, Department of Psychiatry, University of Montreal, Quebec, Canada
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17
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Williams CM, Peyre H, Toro R, Ramus F. Sex differences in the brain are not reduced to differences in body size. Neurosci Biobehav Rev 2021; 130:509-511. [PMID: 34520800 DOI: 10.1016/j.neubiorev.2021.09.015] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2021] [Revised: 09/02/2021] [Accepted: 09/06/2021] [Indexed: 11/18/2022]
Abstract
In their comprehensive review of sex differences in the brain, Eliot et al. (2021) conclude that (1) men and women significantly differ in global brain size, but this "mostly parallels the divergence of male/female body size during development" and that (2) "once we account for individual differences in brain size, there is almost no difference in the volume of specific cortical or subcortical structures between men and women". In sum, almost all brain differences would directly or indirectly follow from differences in body size. In a recent study that does not have the same limitations as most studies reviewed by Eliot et al., we find that sex differences in total brain volume are not accounted for by sex differences in height and weight, and that once global brain size is taken into account, there remain numerous regional sex differences in both directions (Williams et al., 2021).
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Affiliation(s)
- Camille Michèle Williams
- Laboratoire de Sciences Cognitives et Psycholinguistique, Département d'Études Cognitives, École Normale Supérieure, EHESS, CNRS, PSL University, 75005, Paris, France
| | - Hugo Peyre
- Laboratoire de Sciences Cognitives et Psycholinguistique, Département d'Études Cognitives, École Normale Supérieure, EHESS, CNRS, PSL University, 75005, Paris, France; INSERM UMR 1141, Paris Diderot University, Paris, France; Department of Child and Adolescent Psychiatry, Robert Debré Hospital, APHP, Paris, France
| | - Roberto Toro
- Human Genetics and Cognitive Functions, Institut Pasteur, UMR 3571 CNRS, France; Center for Research and Interdisciplinarity (CRI), INSERM U1284, France; Université de Paris, Paris, France
| | - Franck Ramus
- Laboratoire de Sciences Cognitives et Psycholinguistique, Département d'Études Cognitives, École Normale Supérieure, EHESS, CNRS, PSL University, 75005, Paris, France.
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18
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Levitis E, van Praag CDG, Gau R, Heunis S, DuPre E, Kiar G, Bottenhorn KL, Glatard T, Nikolaidis A, Whitaker KJ, Mancini M, Niso G, Afyouni S, Alonso-Ortiz E, Appelhoff S, Arnatkeviciute A, Atay SM, Auer T, Baracchini G, Bayer JMM, Beauvais MJS, Bijsterbosch JD, Bilgin IP, Bollmann S, Bollmann S, Botvinik-Nezer R, Bright MG, Calhoun VD, Chen X, Chopra S, Chuan-Peng H, Close TG, Cookson SL, Craddock RC, De La Vega A, De Leener B, Demeter DV, Di Maio P, Dickie EW, Eickhoff SB, Esteban O, Finc K, Frigo M, Ganesan S, Ganz M, Garner KG, Garza-Villarreal EA, Gonzalez-Escamilla G, Goswami R, Griffiths JD, Grootswagers T, Guay S, Guest O, Handwerker DA, Herholz P, Heuer K, Huijser DC, Iacovella V, Joseph MJE, Karakuzu A, Keator DB, Kobeleva X, Kumar M, Laird AR, Larson-Prior LJ, Lautarescu A, Lazari A, Legarreta JH, Li XY, Lv J, Mansour L S, Meunier D, Moraczewski D, Nandi T, Nastase SA, Nau M, Noble S, Norgaard M, Obungoloch J, Oostenveld R, Orchard ER, Pinho AL, Poldrack RA, Qiu A, Raamana PR, Rokem A, Rutherford S, Sharan M, Shaw TB, Syeda WT, Testerman MM, Toro R, Valk SL, Van Den Bossche S, Varoquaux G, Váša F, Veldsman M, Vohryzek J, Wagner AS, Walsh RJ, White T, Wong FT, Xie X, Yan CG, Yang YF, Yee Y, Zanitti GE, Van Gulick AE, Duff E, Maumet C. Centering inclusivity in the design of online conferences-An OHBM-Open Science perspective. Gigascience 2021; 10:6355274. [PMID: 34414422 DOI: 10.1093/gigascience/giab051] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/18/2023] Open
Abstract
As the global health crisis unfolded, many academic conferences moved online in 2020. This move has been hailed as a positive step towards inclusivity in its attenuation of economic, physical, and legal barriers and effectively enabled many individuals from groups that have traditionally been underrepresented to join and participate. A number of studies have outlined how moving online made it possible to gather a more global community and has increased opportunities for individuals with various constraints, e.g., caregiving responsibilities. Yet, the mere existence of online conferences is no guarantee that everyone can attend and participate meaningfully. In fact, many elements of an online conference are still significant barriers to truly diverse participation: the tools used can be inaccessible for some individuals; the scheduling choices can favour some geographical locations; the set-up of the conference can provide more visibility to well-established researchers and reduce opportunities for early-career researchers. While acknowledging the benefits of an online setting, especially for individuals who have traditionally been underrepresented or excluded, we recognize that fostering social justice requires inclusivity to actively be centered in every aspect of online conference design. Here, we draw from the literature and from our own experiences to identify practices that purposefully encourage a diverse community to attend, participate in, and lead online conferences. Reflecting on how to design more inclusive online events is especially important as multiple scientific organizations have announced that they will continue offering an online version of their event when in-person conferences can resume.
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Affiliation(s)
- Elizabeth Levitis
- Section on Developmental Neurogenomics, National Institute of Mental Health, Bethesda, MD 20892, USA.,Centre for Medical Image Computing, Department of Computer Science, University College London, London, WC1E 6BT, UK
| | - Cassandra D Gould van Praag
- Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, OX3 9DU, UK.,Department of Psychiatry, University of Oxford, Oxford, OX3 7JX, UK
| | - Rémi Gau
- Institute of Psychology, Université Catholique de Louvain, Louvain la Neuve 1348, Belgium
| | - Stephan Heunis
- Department of Electrical Engineering, Eindhoven University of Technology, Eindhoven, 5612 AP, The Netherlands
| | - Elizabeth DuPre
- NeuroDataScience - ORIGAMI laboratory, McGill University, Montreal, QC, H3A 2B4, Canada
| | - Gregory Kiar
- Department of Biomedical Engineering, McGill University, Montreal, QC, H3A 2B4, Canada.,Center for the Developing Brain, The Child Mind Institute, New York City, NY 10022, USA
| | | | - Tristan Glatard
- Department of Computer Science and Software Engineering, Concordia University, Montreal, QC, H3G 1M8, Canada
| | - Aki Nikolaidis
- Center for the Developing Brain, The Child Mind Institute, New York City, NY 10022, USA
| | | | - Matteo Mancini
- Department of Neuroscience, Brighton and Sussex Medical School, University of Sussex, Brighton, BN1 9RR, UK.,Cardiff University Brain Research Imaging Centre, Cardiff University, Cardiff, CF24 4HQ, UK.,NeuroPoly Lab, Polytechnique Montreal, Montreal, QC, H3T 1J4, Canada
| | - Guiomar Niso
- Departement of Psychological & Brain Sciences, Indiana University, Bloomington, IN 47405, USA.,ETSI Telecomunicación, Universidad Politécnica de Madrid and CIBER-BBN, 28040 Madrid, Spain
| | - Soroosh Afyouni
- Big Data Institute, University of Oxford, Oxford, OX3 7LF, UK.,Department of Psychology, University of Cambridge, CB2 3EB, Cambridge, UK
| | - Eva Alonso-Ortiz
- Department of Electrical Engineering, Polytechnique Montréal, Montréal, QC, H3T 1J4, Canada
| | - Stefan Appelhoff
- Center for Adaptive Rationality, Max Planck Institute for Human Development, Berlin 14195, Germany
| | - Aurina Arnatkeviciute
- The Turner Institute for Brain and Mental Health, School of Psychological Sciences, and Monash Biomedical Imaging, Monash University, Victoria, VIC, Clayton 3168, Australia
| | - Selim Melvin Atay
- Neuroscience and Neurotechnology, Middle East Technical University, Ankara 06800, Turkey
| | - Tibor Auer
- School of Psychology, University of Surrey, Guildford GU2 7XH, UK
| | - Giulia Baracchini
- Department of Neurology and Neurosurgery, McGill University, Montréal, QC, H3A 2B4, Canada.,Montréal Neurological Institute, Montréal, QC, H3A 2B4, Canada
| | - Johanna M M Bayer
- Centre for Youth Mental Health, University of Melbourne, Melbourne, VIC, 3010, Parkville, Melbourne, Australia.,Orygen Youth Health, Melbourne, VIC, 3052, Royal Park, Melbourne, Australia
| | | | - Janine D Bijsterbosch
- Department of Radiology, Washington University School of Medicine, Saint Louis, MO, 63110, USA
| | - Isil P Bilgin
- Department of Biomedical Engineering, Cybernetics, The School of Biological Sciences, The University of Reading, Reading, RG6 6AH, UK
| | - Saskia Bollmann
- Centre for Advanced Imaging, The University of Queensland, Brisbane, QLD 4072, Australia
| | - Steffen Bollmann
- School of Information Technology and Electrical Engineering, The University of Queensland, Brisbane, QLD 4072, Australia.,ARC Training Centre for Innovation in Biomedical Imaging Technology, The University of Queensland, Brisbane, QLD 4072, Australia
| | - Rotem Botvinik-Nezer
- Department of Psychological and Brain Sciences, Dartmouth College, Hanover, NH 03755, USA
| | - Molly G Bright
- Physical Therapy and Human Movement Sciences, Feinberg School of Medicine, Northwestern University, Chicago, IL 60611, USA.,Biomedical Engineering, McCormick School of Engineering and Applied Sciences, Northwestern University, Evanston, IL 60208, USA
| | - Vince D Calhoun
- Tri-institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State, Georgia Tech, Emory, Atlanta, GA 30303, USA
| | - Xiao Chen
- CAS Key Laboratory of Behavioral Science, Institute of Psychology, 100101, Beijing, China.,Magnetic Resonance Imaging Research Center, Institute of Psychology, Chinese Academy of Sciences, 100101, Beijing, China.,International Big-Data Center for Depression Research, Chinese Academy of Sciences, Beijing 100101, Beijing, China
| | - Sidhant Chopra
- The Turner Institute for Brain and Mental Health, School of Psychological Sciences, and Monash Biomedical Imaging, Monash University, Victoria, VIC, Clayton 3168, Australia
| | - Hu Chuan-Peng
- School of Psychology, Nanjing Normal University, Nanjing 210024, China
| | - Thomas G Close
- Department of Biomedical Engineering, The University of Sydney, Sydney, NSW 2006, Australia.,National Imaging Facility, The University of Sydney, Sydney, NSW 2006, Australia
| | - Savannah L Cookson
- Helen Wills Neuroscience Institute, University of California, Berkeley, Berkeley, CA 94720, USA
| | - R Cameron Craddock
- Department of Diagnostic Medicine, The University of Texas at Austin Dell Medical School, Austin, TX 78712, USA
| | - Alejandro De La Vega
- Department of Psychology, The University of Texas at Austin, Austin, TX 78712, USA
| | - Benjamin De Leener
- Department of Computer and Software Engineering, Polytechnique Montreal, Montreal, QC H3T 1J4, Canada.,Research Centre, Sainte-Justine University Hospital Center, Montreal, QC, H3T 1C5, Canada
| | - Damion V Demeter
- Department of Psychology, The University of Texas at Austin, Austin, TX 78712, USA
| | - Paola Di Maio
- Center for Systems, Knowledge Representation and Neuroscience, Edinburgh and Taipei, UK and Taiwan.,Institute for Globally Distributed Open Research and Education (IGDORE)
| | - Erin W Dickie
- Krembil Centre for Neuroinformatics, Centre for Addiction and Mental Health, Toronto, ON, M5T 1R8, Canada.,Department of Psychiatry, University of Toronto, Toronto, ON, M5T 1R8, Canada
| | - Simon B Eickhoff
- Institute of Systems Neuroscience, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf 40225, Germany.,Institute of Neuroscience and Medicine, Brain & Behaviour (INM-7), Research Centre Jülich, Jülich 52425, Germany
| | - Oscar Esteban
- Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne 1003, Switzerland
| | - Karolina Finc
- Centre for Modern Interdisciplinary Technologies, Nicolaus Copernicus University, Toruń 87-100, Poland
| | - Matteo Frigo
- Athena Project Team, Université Côte D'Azur, Inria, 06103 Nice, France
| | - Saampras Ganesan
- Melbourne Neuropsychiatry Centre, The University of Melbourne, Melbourne, VIC 3010, Australia.,Department of Biomedical Engineering, The University of Melbourne, Melbourne, VIC 3010, Australia
| | - Melanie Ganz
- Neurobiology Research Unit, Rigshospitalet, Copenhagen DK-2100, Denmark.,Department of Computer Science, University of Copenhagen, Copenhagen DK-2100, Denmark
| | - Kelly G Garner
- Queensland Brain Institute, University of Queensland, St. Lucia, QLD 4072, Australia.,School of Psychology, University of Birmingham, Birmingham, B15 2TT, UK.,School of Psychology, University of Queensland, St. Lucia, QLD 4072, Australia
| | - Eduardo A Garza-Villarreal
- Laboratorio Nacional de Imagenología por Resonancia Magnética, Instituto de Neurobiología, Universidad Nacional Autónoma de México campus Juriquilla, Querétaro, Qro 76230, Mexico
| | - Gabriel Gonzalez-Escamilla
- Department of Neurology, Focus Program Translational Neuroscience (FTN), Rhine Main Neuroscience Network (rmn2), University Medical Center of the Johannes Gutenberg University Mainz, Mainz 55131, Germany
| | - Rohit Goswami
- Faculty of Physical Sciences, University of Iceland, 102 Reykjavík, Iceland.,Department of Chemistry, Indian Institute of Technology Kanpur, Kanpur 208016, India
| | - John D Griffiths
- Department of Psychiatry, University of Toronto, Toronto, ON M5T 1R8, Canada.,Krembil Centre for Neuroinformatics, Centre for Addiction and Mental Health, Toronto, ON M6J 1H4, Canada
| | - Tijl Grootswagers
- The MARCS Institute for Brain, Behaviour & Development, Western Sydney University, Sydney 2751, NSW, Australia
| | - Samuel Guay
- Department of Psychology, Université de Montréal, Montreal, QC H3C 3J7, Canada
| | - Olivia Guest
- Donders Centre for Cognitive Neuroimaging, Radboud University, Nijmegen, 6525 EN, Netherlands
| | - Daniel A Handwerker
- Section on Functional Imaging Methods, Laboratory of Brain and Cognition, National Institute of Mental Health, Bethesda, MD 20892-9663, USA
| | - Peer Herholz
- NeuroDataScience - ORIGAMI laboratory, McGill University, Montreal, QC, H3A 2B4, Canada
| | - Katja Heuer
- Center for Research and Interdisciplinarity (CRI), INSERM U1284, Université de Paris, 75004 Paris, France.,Department of Neuropsychology, Max Planck Institute for Human Cognitive and Brain Sciences, 04103 Leipzig, Germany
| | - Dorien C Huijser
- Erasmus School of Social and Behavioral Sciences, Erasmus University Rotterdam, Rotterdam 3062, the Netherlands.,Developmental and Educational Psychology, Leiden University, Leiden 2333, the Netherlands
| | - Vittorio Iacovella
- Center for Mind/Brain Sciences - CIMeC, University of Trento, Rovereto 38068, Italy
| | - Michael J E Joseph
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, ON M5T 1R8, Canada
| | - Agah Karakuzu
- NeuroPoly Lab, Institute of Biomedical Engineering, Polytechnique Montréal, Montréal, QC, H3T 1N8, Canada.,Montréal Heart Institute, University of Montréal, Montréal, QC, H1T 1C8, Canada
| | - David B Keator
- Psychiatry and Human Behavior, University of California Irvine, Irvine, CA 92697, USA
| | - Xenia Kobeleva
- Department of Neurology, University Hospital Bonn, 53127 Bonn, Germany.,Clinical Research, German Center for Neurodegenerative Diseases, 53127 Bonn, Germany
| | - Manoj Kumar
- Princeton Neuroscience Institute, Princeton University, Princeton, NJ 08544, USA
| | - Angela R Laird
- Department of Physics, Florida International University, Miami, FL 33199, USA
| | - Linda J Larson-Prior
- Psychiatric Research Institute, University of Arkansas for Medical Sciences, Little Rock, AR 72205, USA.,Arkansas Children's Nutrition Center, Little Rock, AR, USA.,Department of Neurology, Pediatrics, Neuroscience & Developmental Sciences, Biomedical Informatics, University of Arkansas for Medical Sciences, Little Rock, AR 72205, USA
| | - Alexandra Lautarescu
- Department of Perinatal Imaging and Health, Centre for the Developing Brain, School of Biomedical Engineering and Imaging Sciences, King's College London, London SE5 8AF, UK.,Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London SE1 7EH, UK
| | - Alberto Lazari
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, OX3 9DU, UK
| | - Jon Haitz Legarreta
- Department of Computer Science, Université de Sherbrooke, Sherbrooke, QC J1K 2R1, Canada
| | - Xue-Ying Li
- Sino-Danish College, University of Chinese Academy of Sciences, Beijing101408, China.,CAS Key Laboratory of Behavioral Science, Institute of Psychology, Chinese Academy of Sciences, Beijing 100101, China.,Sino-Danish Center for Education and Research, Graduate University of Chinese Academy of Sciences, Beijing 101408, China.,CFIN and PET Center, Aarhus University, 8000 Aarhus, Denmark
| | - Jinglei Lv
- School of Biomedical Engineering & Brain and Mind Center, University of Sydney, Sydney, NSW 2006, Australia
| | - Sina Mansour L
- Melbourne Neuropsychiatry Centre, The University of Melbourne, Melbourne, VIC 3010, Australia.,Department of Biomedical Engineering, The University of Melbourne, Melbourne, VIC 3010, Australia
| | - David Meunier
- Aix Marseille Univ, CNRS, INT, Institut de Neurosciences de la Timone, 13005 Marseille, France
| | | | - Tulika Nandi
- Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford OX3 7LF, UK
| | - Samuel A Nastase
- Princeton Neuroscience Institute, Princeton University, Princeton, NJ 08544, USA
| | - Matthias Nau
- Section on Learning and Plasticity, Laboratory of Brain and Cognition, National Institute of Mental Health, Bethesda, MD 20892-9663, USA.,Max-Planck-Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Stephanie Noble
- Radiology & Biomedical Imaging, Yale University, New Haven, CT 06519, USA
| | - Martin Norgaard
- Center for Reproducible Neuroscience, Department of Psychology, Stanford University, Stanford, CA 94305Ci, USA.,Neurobiology Research Unit, Department of Neurology, Rigshospitalet, Copenhagen University Hospital, Copenhagen 2100, Denmark
| | - Johnes Obungoloch
- Department of Biomedical Sciences and Engineering, Mbarara University of Science and Technology, Mbarara City, Uganda
| | - Robert Oostenveld
- Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, 6500 GL, The Netherlands.,NatMEG, Karolinska Institutet, Stockholm 171 77, Sweden
| | - Edwina R Orchard
- The Turner Institute for Brain and Mental Health, School of Psychological Sciences, and Monash Biomedical Imaging, Monash University, Victoria, VIC, Clayton 3168, Australia
| | - Ana Luísa Pinho
- Université Paris-Saclay, Inria, CEA, 91120 Palaiseau, France
| | | | - Anqi Qiu
- Department of Biomedical Engineering, The N.1 Institute for Health, Smart Systems Institute, National University of Singapore, Singapore 117583, Singapore.,Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD 21218, USA
| | | | - Ariel Rokem
- Department of Psychology & eScience Institute, University of Washington, Seattle, WA 98195, USA
| | - Saige Rutherford
- Department of Cognitive Neuroscience, Radboud University Medical Center, Nijmegen 6525 EN, The Netherlands.,Department of Psychiatry, University of Michigan, Ann Arbor, MI 48109, USA
| | | | - Thomas B Shaw
- Centre for Advanced Imaging, The University of Queensland, Brisbane, QLD 4072, Australia
| | - Warda T Syeda
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne, VIC 3053, Australia
| | | | - Roberto Toro
- Center for Research and Interdisciplinarity (CRI), INSERM U1284, Université de Paris, 75004 Paris, France.,Neuroscience Department, Institut Pasteur, 75015 Paris, France
| | - Sofie L Valk
- Institute of Systems Neuroscience, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf 40225, Germany.,Institute of Neuroscience and Medicine, Brain & Behaviour (INM-7), Research Centre Jülich, Jülich 52425, Germany.,Otto Hahn Group Cognitive Neurogenetics, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig 04303, Germany
| | - Sofie Van Den Bossche
- Department of Data Analysis, Faculty of Psychology and Educational Sciences, Ghent University, Ghent 9000, Belgium
| | - Gaël Varoquaux
- Université Paris-Saclay, Inria, CEA, 91120 Palaiseau, France.,Montreal Neurological Institute, McGill, Montreal, QC, H3A 2B4, Canada
| | - František Váša
- Department of Neuroimaging, Institute of Psychiatry Psychology & Neuroscience, King's College London SE5 8AF, London, UK
| | - Michele Veldsman
- Department of Experimental Psychology, University of Oxford, Oxfordshire, OX2 6GG, Oxford, UK
| | - Jakub Vohryzek
- Department of Psychiatry, University of Oxford, Oxford, OX3 7JX, UK.,Center for Music in the Brain, Department of Clinical Medicine, Aarhus University, Aarhus 8000, Denmark
| | - Adina S Wagner
- Institute of Neuroscience and Medicine, Brain & Behaviour (INM-7), Research Centre Jülich, Jülich 52425, Germany
| | - Reubs J Walsh
- Department of Clinical, Neuro-, and Developmental Psychology, Vrije Universiteit Amsterdam, Amsterdam,1081BT, The Netherlands.,Center for Applied Transgender Studies , Chicago, USA
| | - Tonya White
- Department of Child and Adolescent Psychiatry, Erasmus University Medical Centre, Rotterdam, 3000CB, The Netherlands.,Department of Radiology and Nuclear Medicine, Erasmus University Medical Centre, Rotterdam 3000CB, The Netherlands
| | - Fu-Te Wong
- Institute of Linguistics, Academia Sinica, Taipei, Taiwan.,Institute of Medical Science, University of Toronto, Toronto, ON, M5S 1A8, Canada
| | - Xihe Xie
- Department of Neuroscience, Weill Cornell Graduate School, New York City, NY 10065, USA
| | - Chao-Gan Yan
- CAS Key Laboratory of Behavioral Science, Institute of Psychology, 100101, Beijing, China.,Department of Psychology, University of Chinese Academy of Sciences, 100101 Beijing, China.,International Big-Data Center for Depression Research, Chinese Academy of Sciences, 100101, Beijing, China
| | - Yu-Fang Yang
- Department of Psychology, University of Würzburg, Würzburg 97074, Germany
| | - Yohan Yee
- Department of Medical Biophysics, University of Toronto, Toronto, ON, M5G 1L7, Canada.,Mouse Imaging Centre, The Hospital for Sick Children, Toronto, ON, M5T 3H7, Canada
| | | | - Ana E Van Gulick
- Figshare, Cambridge, MA 02139, USA.,University Libraries, Carnegie Mellon University, Pittsburgh, PA, 15213, USA
| | - Eugene Duff
- Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, OX3 9DU, UK.,Department of Paediatrics, University of Oxford, Oxford, OX3 9DU, UK
| | - Camille Maumet
- Inria, Univ Rennes, CNRS, Inserm, IRISA UMR 6074, Empenn ERL U 1228, 35042 Rennes, France
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19
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Biton A, Traut N, Poline JB, Aribisala BS, Bastin ME, Bülow R, Cox SR, Deary IJ, Fukunaga M, Grabe HJ, Hagenaars S, Hashimoto R, Kikuchi M, Muñoz Maniega S, Nauck M, Royle NA, Teumer A, Valdés Hernández M, Völker U, Wardlaw JM, Wittfeld K, Yamamori H, Bourgeron T, Toro R. Polygenic Architecture of Human Neuroanatomical Diversity. Cereb Cortex 2021; 30:2307-2320. [PMID: 32109272 DOI: 10.1093/cercor/bhz241] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/16/2019] [Accepted: 09/17/2019] [Indexed: 01/15/2023] Open
Abstract
We analyzed the genomic architecture of neuroanatomical diversity using magnetic resonance imaging and single nucleotide polymorphism (SNP) data from >26 000 individuals from the UK Biobank project and 5 other projects that had previously participated in the ENIGMA (Enhancing NeuroImaging Genetics through Meta-Analysis) consortium. Our results confirm the polygenic architecture of neuroanatomical diversity, with SNPs capturing from 40% to 54% of regional brain volume variance. Chromosomal length correlated with the amount of phenotypic variance captured, r ~ 0.64 on average, suggesting that at a global scale causal variants are homogeneously distributed across the genome. At a local scale, SNPs within genes (~51%) captured ~1.5 times more genetic variance than the rest, and SNPs with low minor allele frequency (MAF) captured less variance than the rest: the 40% of SNPs with MAF <5% captured <one fourth of the genetic variance. We also observed extensive pleiotropy across regions, with an average genetic correlation of rG ~ 0.45. Genetic correlations were similar to phenotypic and environmental correlations; however, genetic correlations were often larger than phenotypic correlations for the left/right volumes of the same region. The heritability of differences in left/right volumes was generally not statistically significant, suggesting an important influence of environmental causes in the variability of brain asymmetry. Our code is available athttps://github.com/neuroanatomy/genomic-architecture.
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Affiliation(s)
- Anne Biton
- Human Genetics and Cognitive Functions Unit, Institut Pasteur, UMR 3571, CNRS, Université Paris Diderot, Paris 75015, France.,Hub de Bioinformatique et Biostatistique-Département Biologie Computationnelle, Institut Pasteur, USR 3756 CNRS, Paris 75015, France
| | - Nicolas Traut
- Human Genetics and Cognitive Functions Unit, Institut Pasteur, UMR 3571, CNRS, Université Paris Diderot, Paris 75015, France
| | - Jean-Baptiste Poline
- Department of Neurology and Neurosurgery, Montreal Neurological Institute, McGill University, Montreal, Quebec, H3A 2B4, Canada
| | - Benjamin S Aribisala
- Centre for Cognitive Ageing and Cognitive Epidemiology, Department of Psychology, University of Edinburgh, Edinburgh, EH8 9JZ, UK.,Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, EH16 4SB UK.,Department of Computer Science, Lagos State University, Lagos, 102101, Nigeria
| | - Mark E Bastin
- Centre for Cognitive Ageing and Cognitive Epidemiology, Department of Psychology, University of Edinburgh, Edinburgh, EH8 9JZ, UK.,Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, EH16 4SB UK.,Brain Research Imaging Centre, Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, EH16 4TJ, UK
| | - Robin Bülow
- The Institute of Diagnostic Radiology and Neuroradiology, University Medicine Greifswald, Greifswald, 17489, Germany
| | - Simon R Cox
- Centre for Cognitive Ageing and Cognitive Epidemiology, Department of Psychology, University of Edinburgh, Edinburgh, EH8 9JZ, UK.,Department of Psychology, University of Edinburgh, Edinburgh, EH8 9JZ, UK
| | - Ian J Deary
- Centre for Cognitive Ageing and Cognitive Epidemiology, Department of Psychology, University of Edinburgh, Edinburgh, EH8 9JZ, UK.,Department of Psychology, University of Edinburgh, Edinburgh, EH8 9JZ, UK
| | - Masaki Fukunaga
- Division of Cerebral Integration, National Institute for Physiological Sciences, Okazaki, 444-8585, Japan.,Department of Physiological Sciences, School of Life Sciences, The Graduate University for Advanced Studies (SOKENDAI), Hayama, 240-0193, Japan
| | - Hans J Grabe
- Department of Psychiatry and Psychotherapy, University Medicine Greifswald, Greifswald, 17485, Germany.,German Centre of Neurodegenerative Diseases (DZNE) Site Greifswald/Rostock, Greifswald, 17489, Germany
| | - Saskia Hagenaars
- Centre for Cognitive Ageing and Cognitive Epidemiology, Department of Psychology, University of Edinburgh, Edinburgh, EH8 9JZ, UK.,Department of Psychology, University of Edinburgh, Edinburgh, EH8 9JZ, UK.,The Social Genetic and Developmental Psychiatry Research Centre, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, SE5 8AF, UK
| | - Ryota Hashimoto
- Department of Pathology of Mental Diseases, National Institute of Mental Health, National Center of Neurology and Psychiatry, Tokyo, 187-0031, Japan
| | - Masataka Kikuchi
- Department of Genome Informatics, Graduate School of Medicine, Osaka University, Osaka, 565-0871, Japan
| | - Susana Muñoz Maniega
- Centre for Cognitive Ageing and Cognitive Epidemiology, Department of Psychology, University of Edinburgh, Edinburgh, EH8 9JZ, UK.,Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, EH16 4SB UK.,Brain Research Imaging Centre, Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, EH16 4TJ, UK
| | - Matthias Nauck
- Institute of Clinical Chemistry and Laboratory Medicine, University Medicine Greifswald, Greifswald, 17475, Germany.,DZHK (German Centre for Cardiovascular Research), Partner Site Greifswald, University Medicine, Greifswald, 17475, Germany
| | - Natalie A Royle
- Centre for Cognitive Ageing and Cognitive Epidemiology, Department of Psychology, University of Edinburgh, Edinburgh, EH8 9JZ, UK.,Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, EH16 4SB UK.,Brain Research Imaging Centre, Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, EH16 4TJ, UK
| | - Alexander Teumer
- Institute for Community Medicine, University Medicine Greifswald, Greifswald, 17475, Germany
| | - Maria Valdés Hernández
- Centre for Cognitive Ageing and Cognitive Epidemiology, Department of Psychology, University of Edinburgh, Edinburgh, EH8 9JZ, UK.,Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, EH16 4SB UK.,Brain Research Imaging Centre, Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, EH16 4TJ, UK
| | - Uwe Völker
- DZHK (German Centre for Cardiovascular Research), Partner Site Greifswald, University Medicine, Greifswald, 17475, Germany.,Department of Functional Genomics, Interfaculty Institute of Genetics and Functional Genomics, University Greifswald, Greifswald, 17475, Germany
| | - Joanna M Wardlaw
- Centre for Cognitive Ageing and Cognitive Epidemiology, Department of Psychology, University of Edinburgh, Edinburgh, EH8 9JZ, UK.,Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, EH16 4SB UK.,Brain Research Imaging Centre, Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, EH16 4TJ, UK
| | - Katharina Wittfeld
- Department of Psychiatry and Psychotherapy, University Medicine Greifswald, Greifswald, 17485, Germany.,German Centre of Neurodegenerative Diseases (DZNE) Site Greifswald/Rostock, Greifswald, 17489, Germany
| | - Hidenaga Yamamori
- Department of Psychiatry, Graduate School of Medicine, Osaka University, Osaka, 565-0871, Japan
| | | | - Thomas Bourgeron
- Human Genetics and Cognitive Functions Unit, Institut Pasteur, UMR 3571, CNRS, Université Paris Diderot, Paris 75015, France
| | - Roberto Toro
- Human Genetics and Cognitive Functions Unit, Institut Pasteur, UMR 3571, CNRS, Université Paris Diderot, Paris 75015, France.,Center for Research and Interdisciplinarity (CRI), Université Paris Descartes, Paris, 75004, France
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20
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Toro R, Pacheco G, Calderon M, Ramos M, Quezada-Feijoo M, Bermudez A, Montelongo M, Navarro AP, Rodriguez-Leal C, Belmonte T, Mangas A. A plasmatic microrna fingerprint for reduced ejection fraction in dilated cardiomyopathy. Atherosclerosis 2021. [DOI: 10.1016/j.atherosclerosis.2021.06.672] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/24/2022]
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21
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Toro R, Calderon M, Muñiz-Grijalvo O, Pacheco G, Belmonte T, Rodriguez-Leal C, Daroca T, Bermudez A, Montelongo M, Mangas A. Critical crosstalk between oxidative stress and re stress in ischemic dilated cardiomyopathy (IDCM). Atherosclerosis 2021. [DOI: 10.1016/j.atherosclerosis.2021.06.674] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 10/20/2022]
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22
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Gutiérrez-Barrios A, Mialdea-Salmerón D, Cañadas-Pruaño D, Garcia-Molinero D, Zayas-Rueda R, Calle-Pérez G, Vázquez-García R, Toro R, Gheorghe L. Electrocardiographic findings in true acute left main coronary total occlusion a subanalisys from ATOLMA registry. J Electrocardiol 2021; 68:48-52. [PMID: 34333405 DOI: 10.1016/j.jelectrocard.2021.07.017] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/25/2021] [Revised: 07/07/2021] [Accepted: 07/20/2021] [Indexed: 01/15/2023]
Abstract
INTRODUCTION Acute total occlusion of the left main coronary artery (ATOLMA) usually leads to a catastrophic presentation. Prediction of ATOLMA by electrocardiogram (ECG) may contribute to early detection and reperfusion. Limited data have been reported previously. This study aims to identify the admission 12‑leads ECG features that can predict the presence of ATOLMA and in-Hospital mortality in these patients. METHODS The admission ECGs findings in 24 patients from the previously reported ATOLMA multicenter registry were compared to the ECGs findings in 15 patients with an acute subtotal occlusion of the left main (ASOLMA) and to 15 patients with anterior ST-elevation myocardial infarction of the proximal left anterior descending (LADp-STEMI). RESULTS Some ECG features at presentation can predict an ATOLMA: QRS left axis deviation (-61.17 ± 9 degrees); ST-segment elevation in aVL (1.9 ± 0.65 mm); absence of ST-segment elevation in V1 (0.0 ± 0.6 mm); bifascicular block (58%); fragmented QRS (62.5%); prolongation of QTc interval (465 ± 19 ms) and of QRS interval (136 ± 12 mm). The multivariate analysis found that the independent predictors to distinguish ATOLMA from ASOLMA were aVL ST-segment deviation (OR 5.6(95% CI 1.5-21), p = 0.01) and absence of V1 ST-segment elevation (OR 27(95% CI 1.4-52), p = 0.01); and from LADp-STEMI was QRS width (OR 1.1(95% CI 1.02-1.2), p = 0.02). Fragmented QRS was the only independent predictor of in-hospital mortality in ATOLMA (OR 0.125(95% CI 0.01-0.81), p = 0.03). CONCLUSIONS aVL ST-segment elevation, the absence of V1 ST-segment elevation, left axis deviation, the presence of bifascicular block, and prolongation of QRS and QTc interval are predictors of ATOLMA. Fragmented QRS predicts in-hospital mortality in ATOLMA.
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Affiliation(s)
- A Gutiérrez-Barrios
- Cardiology Department, Hospital Puerta del Mar, Cádiz, Spain; Instituto de Investigación e Innovación en Ciencias Biomédicas de Cádiz, INiBICA, Spain.
| | | | - D Cañadas-Pruaño
- Cardiology Department, Hospital Puerta del Mar, Cádiz, Spain; Instituto de Investigación e Innovación en Ciencias Biomédicas de Cádiz, INiBICA, Spain
| | | | - R Zayas-Rueda
- Cardiology Department, Hospital Puerta del Mar, Cádiz, Spain; Instituto de Investigación e Innovación en Ciencias Biomédicas de Cádiz, INiBICA, Spain
| | - G Calle-Pérez
- Cardiology Department, Hospital Puerta del Mar, Cádiz, Spain; Instituto de Investigación e Innovación en Ciencias Biomédicas de Cádiz, INiBICA, Spain
| | - R Vázquez-García
- Cardiology Department, Hospital Puerta del Mar, Cádiz, Spain; Instituto de Investigación e Innovación en Ciencias Biomédicas de Cádiz, INiBICA, Spain
| | - R Toro
- Instituto de Investigación e Innovación en Ciencias Biomédicas de Cádiz, INiBICA, Spain
| | - L Gheorghe
- Cardiology Department, Hospital Puerta del Mar, Cádiz, Spain; Instituto de Investigación e Innovación en Ciencias Biomédicas de Cádiz, INiBICA, Spain
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23
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Williams CM, Peyre H, Toro R, Ramus F. Neuroanatomical norms in the UK Biobank: The impact of allometric scaling, sex, and age. Hum Brain Mapp 2021; 42:4623-4642. [PMID: 34268815 PMCID: PMC8410561 DOI: 10.1002/hbm.25572] [Citation(s) in RCA: 22] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2020] [Revised: 06/03/2021] [Accepted: 06/11/2021] [Indexed: 12/18/2022] Open
Abstract
Few neuroimaging studies are sufficiently large to adequately describe population‐wide variations. This study's primary aim was to generate neuroanatomical norms and individual markers that consider age, sex, and brain size, from 629 cerebral measures in the UK Biobank (N = 40,028). The secondary aim was to examine the effects and interactions of sex, age, and brain allometry—the nonlinear scaling relationship between a region and brain size (e.g., total brain volume)—across cerebral measures. Allometry was a common property of brain volumes, thicknesses, and surface areas (83%) and was largely stable across age and sex. Sex differences occurred in 67% of cerebral measures (median |β| = .13): 37% of regions were larger in males and 30% in females. Brain measures (49%) generally decreased with age, although aging effects varied across regions and sexes. While models with an allometric or linear covariate adjustment for brain size yielded similar significant effects, omitting brain allometry influenced reported sex differences in variance. Finally, we contribute to the reproducibility of research on sex differences in the brain by replicating previous studies examining cerebral sex differences. This large‐scale study advances our understanding of age, sex, and brain allometry's impact on brain structure and provides data for future UK Biobank studies to identify the cerebral regions that covary with specific phenotypes, independently of sex, age, and brain size.
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Affiliation(s)
- Camille Michèle Williams
- Laboratoire de Sciences Cognitives et Psycholinguistique, Département d'Études Cognitives, École Normale Supérieure, EHESS, CNRS, PSL University, Paris, France
| | - Hugo Peyre
- Laboratoire de Sciences Cognitives et Psycholinguistique, Département d'Études Cognitives, École Normale Supérieure, EHESS, CNRS, PSL University, Paris, France.,INSERM UMR 1141, Paris Diderot University, Paris, France.,Department of Child and Adolescent Psychiatry, Robert Debré Hospital, APHP, Paris, France
| | - Roberto Toro
- Human Genetics and Cognitive Functions, Institut Pasteur, UMR 3571 CNRS, Paris, France.,Center for Research and Interdisciplinarity (CRI), INSERM U1284, Paris, France.,Université de Paris, Paris, France
| | - Franck Ramus
- Laboratoire de Sciences Cognitives et Psycholinguistique, Département d'Études Cognitives, École Normale Supérieure, EHESS, CNRS, PSL University, Paris, France
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24
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Cauvet É, Van't Westeinde A, Toro R, Kuja-Halkola R, Neufeld J, Mevel K, Bölte S. The social brain in female autism: a structural imaging study of twins. Soc Cogn Affect Neurosci 2021; 15:423-436. [PMID: 32363404 PMCID: PMC7308659 DOI: 10.1093/scan/nsaa064] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/28/2019] [Revised: 03/26/2020] [Accepted: 04/27/2020] [Indexed: 12/30/2022] Open
Abstract
A female advantage in social cognition (SoC) might contribute to women's underrepresentation in autism spectrum disorder (ASD). The latter could be underpinned by sex differences in social brain structure. This study investigated the relationship between structural social brain networks and SoC in females and males in relation to ASD and autistic traits in twins. We used a co-twin design in 77 twin pairs (39 female) aged 12.5 to 31.0 years. Twin pairs were discordant or concordant for ASD or autistic traits, discordant or concordant for other neurodevelopmental disorders or concordant for neurotypical development. They underwent structural magnetic resonance imaging and were assessed for SoC using the naturalistic Movie for the Assessment of Social Cognition. Autistic traits predicted reduced SoC capacities predominantly in male twins, despite a comparable extent of autistic traits in each sex, although the association between SoC and autistic traits did not differ significantly between the sexes. Consistently, within-pair associations between SoC and social brain structure revealed that lower SoC ability was associated with increased cortical thickness of several brain regions, particularly in males. Our findings confirm the notion that sex differences in SoC in association with ASD are underpinned by sex differences in brain structure.
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Affiliation(s)
- Élodie Cauvet
- Department of Women's and Children's Health, Karolinska Institutet, Stockholm Health Care Services, Stockholm 11330, Sweden
| | - Annelies Van't Westeinde
- Department of Women's and Children's Health, Karolinska Institutet, Stockholm Health Care Services, Stockholm 11330, Sweden
| | - Roberto Toro
- Department of Neuroscience, Human Genetics and Cognitive Functions, Institut Pasteur, Paris 75015, France.,CNRS URA 2182 "Genes, synapses and cognition", Pasteur Institute, Paris 75015, France.,Human Genetics and Cognitive Functions, Université Paris Diderot, Sorbonne Paris Cité, Paris 75013, France
| | - Ralf Kuja-Halkola
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm 17177, Sweden
| | - Janina Neufeld
- Department of Women's and Children's Health, Karolinska Institutet, Stockholm Health Care Services, Stockholm 11330, Sweden
| | - Katell Mevel
- GIP Cyceron, Normandy University, Caen 14074, France
| | - Sven Bölte
- Department of Women's and Children's Health, Karolinska Institutet, Stockholm Health Care Services, Stockholm 11330, Sweden.,Child and Adolescent Psychiatry, Stockholm County Council, Stockholm 11330, Sweden.,School of Occupational Therapy, Social Work and Speech Pathology, Curtin University, Perth, Western Australia 6102, Australia
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25
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Gau R, Noble S, Heuer K, Bottenhorn KL, Bilgin IP, Yang YF, Huntenburg JM, Bayer JMM, Bethlehem RAI, Rhoads SA, Vogelbacher C, Borghesani V, Levitis E, Wang HT, Van Den Bossche S, Kobeleva X, Legarreta JH, Guay S, Atay SM, Varoquaux GP, Huijser DC, Sandström MS, Herholz P, Nastase SA, Badhwar A, Dumas G, Schwab S, Moia S, Dayan M, Bassil Y, Brooks PP, Mancini M, Shine JM, O'Connor D, Xie X, Poggiali D, Friedrich P, Heinsfeld AS, Riedl L, Toro R, Caballero-Gaudes C, Eklund A, Garner KG, Nolan CR, Demeter DV, Barrios FA, Merchant JS, McDevitt EA, Oostenveld R, Craddock RC, Rokem A, Doyle A, Ghosh SS, Nikolaidis A, Stanley OW, Uruñuela E. Brainhack: Developing a culture of open, inclusive, community-driven neuroscience. Neuron 2021; 109:1769-1775. [PMID: 33932337 DOI: 10.1016/j.neuron.2021.04.001] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2021] [Revised: 03/23/2021] [Accepted: 04/01/2021] [Indexed: 11/25/2022]
Abstract
Brainhack is an innovative meeting format that promotes scientific collaboration and education in an open, inclusive environment. This NeuroView describes the myriad benefits for participants and the research community and how Brainhacks complement conventional formats to augment scientific progress.
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Affiliation(s)
- Rémi Gau
- Institute of Psychology, Université Catholique de Louvain, Louvain la Neuve, Belgium.
| | - Stephanie Noble
- Radiology & Biomedical Imaging, Yale University, New Haven CT, USA
| | - Katja Heuer
- Center for Research and Interdisciplinarity, Université of Paris, Paris, France; Department of Neuropsychology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | | | - Isil P Bilgin
- Biomedical Engineering, Cybernetics, University of Reading, Reading, UK; Allied Health Professions Institute, University of the West of England, Bristol, UK
| | - Yu-Fang Yang
- Department of Psychology, University of Würzburg, Würzburg, Germany
| | | | - Johanna M M Bayer
- Centre for Youth Mental Health, University of Melbourne, Melbourne, Australia; Orygen Youth Health, Melbourne, Australia
| | - Richard A I Bethlehem
- Autism Research Centre, Department of Psychiatry, University of Cambridge, Cambridge, UK; Brain Mapping Unit, Department of Psychiatry, University of Cambridge, Cambridge, UK
| | - Shawn A Rhoads
- Department of Psychology, Georgetown University, Washington DC, USA
| | - Christoph Vogelbacher
- Laboratory for Multimodal Neuroimaging, Department of Psychiatry and Psychotherapy, University of Marburg, Marburg, Germany
| | - Valentina Borghesani
- Centre de Recherche de l'Institut Universitaire de Gériatrie de Montréal, Université de Montréal, Montréal, QC, Canada
| | - Elizabeth Levitis
- Section on Developmental Neurogenomics, National Institute of Mental Health, Bethesda, MD, USA; Centre for Medical Image Computing, Department of Computer Science, University College London, London, UK
| | - Hao-Ting Wang
- Sackler Centre for Consciousness Science, University of Sussex, Brighton, UK; Department of Neuroscience, Brighton and Sussex Medical School, University of Sussex, Brighton, UK; Sussex Neuroscience, University of Sussex, Brighton, UK
| | - Sofie Van Den Bossche
- Department of Data Analysis, Faculty of Psychology and Educational Sciences, Ghent University, Ghent, Belgium
| | - Xenia Kobeleva
- Department of Neurology, University of Bonn, Bonn, Germany; German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany
| | | | - Samuel Guay
- Université de Montréal, Montréal, QC, Canada
| | - Selim Melvin Atay
- Neuroscience and Neurotechnology, Middle East Technical University, Ankara, Turkey
| | - Gael P Varoquaux
- Parietal, INRIA, Saclay, France; Montréal Neurological Institute, McGill University, Montréal, QC, Canada
| | - Dorien C Huijser
- Erasmus School of Social and Behavioural Sciences, Erasmus University Rotterdam, Rotterdam, the Netherlands; Developmental and Educational Psychology, Leiden University, Leiden, the Netherlands
| | | | - Peer Herholz
- NeuroDataScience - ORIGAMI laboratory, Faculty of Medicine and Health Sciences McGill University Montréal, QC Canada
| | - Samuel A Nastase
- Princeton Neuroscience Institute, Princeton University, Princeton, NJ, USA
| | - AmanPreet Badhwar
- Centre de Recherche de l'Institut Universitaire de Gériatrie de Montréal, Université de Montréal, Montréal, QC, Canada; Multiomics Investigation of Neurodegenerative Diseases (MIND) Lab, Université de Montréal, Montréal, QC, Canada; Département de Pharmacologie et Physiologie, Université de Montréal, Montréal, QC, Canada
| | - Guillaume Dumas
- Department of Psychiatry, Université de Montréal, Montréal, QC, Canada; Mila, Université de Montréal, Montréal, QC, Canada
| | - Simon Schwab
- Department of Biostatistics & Center for Reproducible Science, University of Zurich, Zurich, Switzerland
| | - Stefano Moia
- Basque Center on Cognition, Brain and Language, San Sebastián-Donostia, Spain; University of the Basque Country (EHU UPV), San Sebastián-Donostia, Spain
| | - Michael Dayan
- Human Neuroscience Platform, Fondation Campus Biotech Geneva, Geneva, Switzerland
| | - Yasmine Bassil
- Graduate Division of Biological & Biomedical Sciences, Emory University, Atlanta, GA, USA
| | - Paula P Brooks
- Princeton Neuroscience Institute, Princeton University, Princeton, NJ, USA
| | - Matteo Mancini
- Department of Neuroscience, Brighton and Sussex Medical School, University of Sussex, Brighton, UK; Cardiff University Brain Research Imaging Centre, Cardiff University, Cardiff, UK; NeuroPoly Lab, Polytechnique Montréal, Montréal, QC, Canada
| | - James M Shine
- Faculty of Medicine and Health, The University of Sydney, Sydney, Australia
| | - David O'Connor
- Department of Biomedical Engineering, Yale University, New Haven, CT, USA
| | - Xihe Xie
- Department of Neuroscience, Weill Cornell Medicine, New York City, NY, USA
| | - Davide Poggiali
- Padova Neuroscience Center, University of Padova, Padova, Italy
| | - Patrick Friedrich
- Institute of Neuroscience and Medicine, Brain & Behaviour (INM-7), Research Centre Jülich, Jülich, Germany
| | - Anibal S Heinsfeld
- Computational Neuroimaging Lab, University of Texas at Austin, Austin, TX, USA; Department of Computer Science, University of Texas at Austin, Austin, TX, USA
| | - Lydia Riedl
- Department of Psychiatry and Psychotherapy, Philipps Universität, Marburg, Germany
| | - Roberto Toro
- Center for Research and Interdisciplinarity, Université of Paris, Paris, France; Neuroscience Department, Institut Pasteur, Paris, France
| | | | - Anders Eklund
- Department of Biomedical Engineering, Linköping University, Linköping, Sweden; Department of Computer and Information Science, Linköping University, Linköping, Sweden; Center for Medical Image Science and Visualization (CMIV), Linköping University, Linköping, Sweden
| | - Kelly G Garner
- Queensland Brain Institute, The University of Queensland, St Lucia, Australia; School of Psychology, University of Birmingham, Birmingham, UK; School of Psychology, The University of Queensland, St Lucia, Australia
| | | | - Damion V Demeter
- Psychology Department, The University of Texas at Austin, Austin, TX, USA
| | - Fernando A Barrios
- Instituto de Neurobiología, Universidad Nacional Autónoma de México, Querétaro, Mexico
| | - Junaid S Merchant
- Neuroscience and Cognitive Science Program, University of Maryland, College Park, MD, USA; Department of Psychology, University of Maryland, College Park, MD, USA
| | | | - Robert Oostenveld
- Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, the Netherlands; NatMEG, Karolinska Institutet, Stockholm, Sweden
| | - R Cameron Craddock
- Department of Diagnostic Medicine, The University of Texas at Austin Dell Medical School, Austin, TX, USA
| | - Ariel Rokem
- Psychology and eScience Institute, University of Washington, Seattle, WA, USA
| | - Andrew Doyle
- McGill Centre for Integrative Neuroscience, McGill University, Montréal, QC, Canada
| | - Satrajit S Ghosh
- McGovern Institute for Brain Research, MIT, Cambridge, MA, USA; Department of Otolaryngology - Head and Neck Surgery, Harvard Medical School, Boston, MA, USA
| | - Aki Nikolaidis
- Center for the Developing Brain, Child Mind Institute, New York City, NY, USA
| | - Olivia W Stanley
- Centre for Functional and Metabolic Mapping, University of Western Ontario, London, ON, Canada; Department of Medical Biophysics, University of Western Ontario, London, ON, Canada
| | - Eneko Uruñuela
- Basque Center on Cognition, Brain and Language, San Sebastián-Donostia, Spain; University of the Basque Country (EHU UPV), San Sebastián-Donostia, Spain
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26
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Friedrich P, Forkel SJ, Amiez C, Balsters JH, Coulon O, Fan L, Goulas A, Hadj-Bouziane F, Hecht EE, Heuer K, Jiang T, Latzman RD, Liu X, Loh KK, Patil KR, Lopez-Persem A, Procyk E, Sallet J, Toro R, Vickery S, Weis S, Wilson CRE, Xu T, Zerbi V, Eickoff SB, Margulies DS, Mars RB, Thiebaut de Schotten M. Imaging evolution of the primate brain: the next frontier? Neuroimage 2021; 228:117685. [PMID: 33359344 PMCID: PMC7116589 DOI: 10.1016/j.neuroimage.2020.117685] [Citation(s) in RCA: 31] [Impact Index Per Article: 10.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2020] [Revised: 12/14/2020] [Accepted: 12/16/2020] [Indexed: 11/22/2022] Open
Abstract
Evolution, as we currently understand it, strikes a delicate balance between animals' ancestral history and adaptations to their current niche. Similarities between species are generally considered inherited from a common ancestor whereas observed differences are considered as more recent evolution. Hence comparing species can provide insights into the evolutionary history. Comparative neuroimaging has recently emerged as a novel subdiscipline, which uses magnetic resonance imaging (MRI) to identify similarities and differences in brain structure and function across species. Whereas invasive histological and molecular techniques are superior in spatial resolution, they are laborious, post-mortem, and oftentimes limited to specific species. Neuroimaging, by comparison, has the advantages of being applicable across species and allows for fast, whole-brain, repeatable, and multi-modal measurements of the structure and function in living brains and post-mortem tissue. In this review, we summarise the current state of the art in comparative anatomy and function of the brain and gather together the main scientific questions to be explored in the future of the fascinating new field of brain evolution derived from comparative neuroimaging.
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Affiliation(s)
- Patrick Friedrich
- Brain Connectivity and Behaviour Laboratory, Sorbonne Universities, Paris, France; Groupe d'Imagerie Neurofonctionnelle, Institut des Maladies Neurodégénératives-UMR 5293, CNRS, CEA, University of Bordeaux, Bordeaux, France; Institute of Neuroscience and Medicine (Brain & Behaviour, INM-7), Research Center Jülich, Germany.
| | - Stephanie J Forkel
- Brain Connectivity and Behaviour Laboratory, Sorbonne Universities, Paris, France; Groupe d'Imagerie Neurofonctionnelle, Institut des Maladies Neurodégénératives-UMR 5293, CNRS, CEA, University of Bordeaux, Bordeaux, France; Centre for Neuroimaging Sciences, Department of Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom
| | - Céline Amiez
- Univ Lyon, Université Lyon 1, Inserm, Stem Cell and Brain Research Institute, U1208 Bron, France
| | - Joshua H Balsters
- Department of Psychology, Royal Holloway University of London, United Kingdom
| | - Olivier Coulon
- Institut de Neurosciences de la Timone, Aix Marseille Univ, CNRS, UMR 7289, Marseille, France; Institute for Language, Communication, and the Brain, Aix-Marseille University, Marseille, France
| | - Lingzhong Fan
- Brainnetome Center and National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China; CAS Center for Excellence in Brain Science and Intelligence Technology, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China
| | - Alexandros Goulas
- Institute of Computational Neuroscience, University Medical Center Hamburg-Eppendorf, Hamburg University, Hamburg, Germany
| | - Fadila Hadj-Bouziane
- Lyon Neuroscience Research Center, ImpAct Team, INSERM U1028, CNRS UMR5292, Université Lyon 1, Bron, France
| | - Erin E Hecht
- Department of Human Evolutionary Biology, Harvard University, Cambridge, MA, United States
| | - Katja Heuer
- Center for Research and Interdisciplinarity (CRI), Université de Paris, Inserm, Paris 75004, France; Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Tianzi Jiang
- Brainnetome Center and National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China; CAS Center for Excellence in Brain Science and Intelligence Technology, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China; The Queensland Brain Institute, University of Queensland, Brisbane QLD 4072, Australia
| | - Robert D Latzman
- Department of Psychology, Georgia State University, Atlanta, United States
| | - Xiaojin Liu
- Institute of Systems Neuroscience, Medical Faculty, Heinrich-Heine University Düsseldorf, Germany; Institute of Neuroscience and Medicine (Brain & Behaviour, INM-7), Research Center Jülich, Germany
| | - Kep Kee Loh
- Institut de Neurosciences de la Timone, Aix Marseille Univ, CNRS, UMR 7289, Marseille, France; Institute for Language, Communication, and the Brain, Aix-Marseille University, Marseille, France
| | - Kaustubh R Patil
- Institute of Systems Neuroscience, Medical Faculty, Heinrich-Heine University Düsseldorf, Germany; Institute of Neuroscience and Medicine (Brain & Behaviour, INM-7), Research Center Jülich, Germany
| | - Alizée Lopez-Persem
- Frontlab, Institut du Cerveau et de la Moelle épinière (ICM), UPMC UMRS 1127, Inserm U 1127, CNRS UMR 7225, Paris, France; Wellcome Centre for Integrative Neuroimaging, Department of Experimental Psychology, University of Oxford, Oxford, United Kingdom
| | - Emmanuel Procyk
- Univ Lyon, Université Lyon 1, Inserm, Stem Cell and Brain Research Institute, U1208 Bron, France
| | - Jerome Sallet
- Univ Lyon, Université Lyon 1, Inserm, Stem Cell and Brain Research Institute, U1208 Bron, France; Wellcome Centre for Integrative Neuroimaging, Department of Experimental Psychology, University of Oxford, Oxford, United Kingdom
| | - Roberto Toro
- Center for Research and Interdisciplinarity (CRI), Université de Paris, Inserm, Paris 75004, France; Neuroscience department, Institut Pasteur, UMR 3571, CNRS, Université de Paris, Paris 75015, France
| | - Sam Vickery
- Institute of Systems Neuroscience, Medical Faculty, Heinrich-Heine University Düsseldorf, Germany; Institute of Neuroscience and Medicine (Brain & Behaviour, INM-7), Research Center Jülich, Germany
| | - Susanne Weis
- Institute of Systems Neuroscience, Medical Faculty, Heinrich-Heine University Düsseldorf, Germany; Institute of Neuroscience and Medicine (Brain & Behaviour, INM-7), Research Center Jülich, Germany
| | - Charles R E Wilson
- Univ Lyon, Université Lyon 1, Inserm, Stem Cell and Brain Research Institute, U1208 Bron, France
| | - Ting Xu
- Child Mind Institute, New York, United States
| | - Valerio Zerbi
- Neural Control of Movement Lab, Department of Health Sciences and Technology, ETH Zurich, Zurich, Switzerland
| | - Simon B Eickoff
- Institute of Systems Neuroscience, Medical Faculty, Heinrich-Heine University Düsseldorf, Germany; Institute of Neuroscience and Medicine (Brain & Behaviour, INM-7), Research Center Jülich, Germany
| | - Daniel S Margulies
- Brain Connectivity and Behaviour Laboratory, Sorbonne Universities, Paris, France; Integrative Neuroscience and Cognition Center (UMR 8002), Centre National de la Recherche Scientifique (CNRS) and Université de Paris, 75006, Paris, France
| | - Rogier B Mars
- Wellcome Centre for Integrative Neuroimaging, Centre for Functional MRI of the Brain (FMRIB), Nuffield Department of Clinical Neurosciences, John Radcliffe Hospital, University of Oxford, Oxford, United Kingdom; Donders Institute for Brain, Cognition and Behaviour, Radboud University Nijmegen, Nijmegen, Netherlands
| | - Michel Thiebaut de Schotten
- Brain Connectivity and Behaviour Laboratory, Sorbonne Universities, Paris, France; Groupe d'Imagerie Neurofonctionnelle, Institut des Maladies Neurodégénératives-UMR 5293, CNRS, CEA, University of Bordeaux, Bordeaux, France.
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27
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Messinger A, Sirmpilatze N, Heuer K, Loh KK, Mars RB, Sein J, Xu T, Glen D, Jung B, Seidlitz J, Taylor P, Toro R, Garza-Villarreal EA, Sponheim C, Wang X, Benn RA, Cagna B, Dadarwal R, Evrard HC, Garcia-Saldivar P, Giavasis S, Hartig R, Lepage C, Liu C, Majka P, Merchant H, Milham MP, Rosa MGP, Tasserie J, Uhrig L, Margulies DS, Klink PC. A collaborative resource platform for non-human primate neuroimaging. Neuroimage 2020; 226:117519. [PMID: 33227425 PMCID: PMC9272762 DOI: 10.1016/j.neuroimage.2020.117519] [Citation(s) in RCA: 27] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2020] [Revised: 10/15/2020] [Accepted: 10/24/2020] [Indexed: 01/12/2023] Open
Abstract
Neuroimaging non-human primates (NHPs) is a growing, yet highly specialized field of neuroscience. Resources that were primarily developed for human neuroimaging often need to be significantly adapted for use with NHPs or other animals, which has led to an abundance of custom, in-house solutions. In recent years, the global NHP neuroimaging community has made significant efforts to transform the field towards more open and collaborative practices. Here we present the PRIMatE Resource Exchange (PRIME-RE), a new collaborative online platform for NHP neuroimaging. PRIME-RE is a dynamic community-driven hub for the exchange of practical knowledge, specialized analytical tools, and open data repositories, specifically related to NHP neuroimaging. PRIME-RE caters to both researchers and developers who are either new to the field, looking to stay abreast of the latest developments, or seeking to collaboratively advance the field.
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Affiliation(s)
- Adam Messinger
- Laboratory of Brain and Cognition, National Institute of Mental Health, Bethesda, USA
| | - Nikoloz Sirmpilatze
- German Primate Center - Leibniz Institute for Primate Research, Kellnerweg 4, 37077 Göttingen, Germany; Georg-August-University Göttingen, 37073 Göttingen, Germany
| | - Katja Heuer
- Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany; Center for Research and Interdisciplinarity (CRI), INSERM U1284, Université de Paris, Paris, France
| | - Kep Kee Loh
- Institut de Neurosciences de la Timone (INT), Aix-Marseille Université, CNRS, UMR 7289, 13005 Marseille, France; Institute for Language, Communication, and the Brain, Aix-Marseille University, Marseille, France
| | - Rogier B Mars
- Wellcome Centre for Integrative Neuroimaging, Nuffield Department of Clinical Neurosciences, John Radcliffe Hospital, University of Oxford, Oxford OX3 9DU, UK; Donders Institute for Brain, Cognition, and Behaviour, Radboud University Nijmegen, Montessorilaan 3, 6525 HR Nijmegen, The Netherlands
| | - Julien Sein
- Institut de Neurosciences de la Timone (INT), Aix-Marseille Université, CNRS, UMR 7289, 13005 Marseille, France
| | - Ting Xu
- Child Mind Institute, 101 E 56th St, New York, NY 10022, USA
| | - Daniel Glen
- Scientific and Statistical Computing Core, National Institute of Mental Health, Bethesda, USA
| | - Benjamin Jung
- Laboratory of Brain and Cognition, National Institute of Mental Health, Bethesda, USA; Department of Neuroscience, Brown University, Providence RI USA
| | - Jakob Seidlitz
- Department of Child and Adolescent Psychiatry and Behavioral Science, Children's Hospital of Philadelphia, Philadelphia PA USA; Department of Psychiatry, University of Pennsylvania, Philadelphia PA USA
| | - Paul Taylor
- Scientific and Statistical Computing Core, National Institute of Mental Health, Bethesda, USA
| | - Roberto Toro
- Center for Research and Interdisciplinarity (CRI), INSERM U1284, Université de Paris, Paris, France; Department of Neuroscience, Institut Pasteur, UMR 3571 CNRS, Université de Paris, Paris, France
| | - Eduardo A Garza-Villarreal
- Instituto de Neurobiologia, Universidad Nacional Autónoma de México campus Juriquilla, Queretaro, Mexico
| | - Caleb Sponheim
- Department of Organismal Biology and Anatomy, University of Chicago, Chicago IL USA
| | - Xindi Wang
- McGill Centre for Integrative Neuroscience, Montreal Neurological Institute (MNI), Quebec, Canada
| | - R Austin Benn
- Centro Nacional de Investigaciones Cardiovasculares Carlos III (CNIC), Madrid, Spain
| | - Bastien Cagna
- Institut de Neurosciences de la Timone (INT), Aix-Marseille Université, CNRS, UMR 7289, 13005 Marseille, France
| | - Rakshit Dadarwal
- German Primate Center - Leibniz Institute for Primate Research, Kellnerweg 4, 37077 Göttingen, Germany; Georg-August-University Göttingen, 37073 Göttingen, Germany
| | - Henry C Evrard
- Centre for Integrative Neurosciences, University of Tübingen, Tübingen, Germany; Max Planck Institute for Biological Cybernetics, Tübingen, Germany; Nathan S. Kline Institute for Psychiatric Research, Orangeburg, New York, USA; International Center for Primate Brain Research, Chinese Academy of Science, Shanghai, PRC
| | - Pamela Garcia-Saldivar
- Instituto de Neurobiologia, Universidad Nacional Autónoma de México campus Juriquilla, Queretaro, Mexico
| | - Steven Giavasis
- Child Mind Institute, 101 E 56th St, New York, NY 10022, USA
| | - Renée Hartig
- Centre for Integrative Neurosciences, University of Tübingen, Tübingen, Germany; Max Planck Institute for Biological Cybernetics, Tübingen, Germany; Focus Program Translational Neurosciences, University Medical Center, Mainz, Germany
| | - Claude Lepage
- McGill Centre for Integrative Neuroscience, Montreal Neurological Institute (MNI), Quebec, Canada
| | - Cirong Liu
- Department of Neurobiology, University of Pittsburgh Brain Institute, Pittsburgh PA, USA
| | - Piotr Majka
- Laboratory of Neuroinformatics, Nencki Institute of Experimental Biology of the Polish Academy of Sciences, 02-093 Warsaw, Poland; Australian Research Council, Centre of Excellence for Integrative Brain Function, Monash University Node, Clayton, VIC 3800, Australia; Biomedicine Discovery Institute and Department of Physiology, Monash University, Clayton, VIC 3800, Australia
| | - Hugo Merchant
- Instituto de Neurobiologia, Universidad Nacional Autónoma de México campus Juriquilla, Queretaro, Mexico
| | - Michael P Milham
- Child Mind Institute, 101 E 56th St, New York, NY 10022, USA; Nathan S. Kline Institute for Psychiatric Research, Orangeburg, New York, USA
| | - Marcello G P Rosa
- Australian Research Council, Centre of Excellence for Integrative Brain Function, Monash University Node, Clayton, VIC 3800, Australia; Biomedicine Discovery Institute and Department of Physiology, Monash University, Clayton, VIC 3800, Australia
| | - Jordy Tasserie
- Commissariat à l'Énergie Atomique et aux Énergies Alternatives, Direction de la Recherche Fondamentale, NeuroSpin Center, Gif-sur-Yvette, France; Cognitive Neuroimaging Unit, Institut National de la Santé et de la Recherche Médicale U992, Gif-sur-Yvette, France; Université Paris-Saclay, France
| | - Lynn Uhrig
- Commissariat à l'Énergie Atomique et aux Énergies Alternatives, Direction de la Recherche Fondamentale, NeuroSpin Center, Gif-sur-Yvette, France; Cognitive Neuroimaging Unit, Institut National de la Santé et de la Recherche Médicale U992, Gif-sur-Yvette, France
| | - Daniel S Margulies
- Integrative Neuroscience and Cognition Center, Centre National de la Recherche Scientifique (CNRS) UMR 8002, Paris, France
| | - P Christiaan Klink
- Department of Vision & Cognition, Netherlands Institute for Neuroscience, Amsterdam, The Netherlands.
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28
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Williams CM, Peyre H, Toro R, Beggiato A, Ramus F. Adjusting for allometric scaling in ABIDE I challenges subcortical volume differences in autism spectrum disorder. Hum Brain Mapp 2020; 41:4610-4629. [PMID: 32729664 PMCID: PMC7555078 DOI: 10.1002/hbm.25145] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/13/2020] [Revised: 06/29/2020] [Accepted: 07/07/2020] [Indexed: 12/17/2022] Open
Abstract
Inconsistencies across studies investigating subcortical correlates of autism spectrum disorder (ASD) may stem from small sample size, sample heterogeneity, and omitting or linearly adjusting for total brain volume (TBV). To properly adjust for TBV, brain allometry—the nonlinear scaling relationship between regional volumes and TBV—was considered when examining subcortical volumetric differences between typically developing (TD) and ASD individuals. Autism Brain Imaging Data Exchange I (ABIDE I; N = 654) data was analyzed with two methodological approaches: univariate linear mixed effects models and multivariate multiple group confirmatory factor analyses. Analyses were conducted on the entire sample and in subsamples based on age, sex, and full scale intelligence quotient (FSIQ). A similar ABIDE I study was replicated and the impact of different TBV adjustments on neuroanatomical group differences was investigated. No robust subcortical allometric or volumetric group differences were observed in the entire sample across methods. Exploratory analyses suggested that allometric scaling and volume group differences may exist in certain subgroups defined by age, sex, and/or FSIQ. The type of TBV adjustment influenced some reported volumetric and scaling group differences. This study supports the absence of robust volumetric differences between ASD and TD individuals in the investigated volumes when adjusting for brain allometry, expands the literature by finding no group difference in allometric scaling, and further suggests that differing TBV adjustments contribute to the variability of reported neuroanatomical differences in ASD.
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Affiliation(s)
- Camille Michèle Williams
- Laboratoire de Sciences Cognitives et Psycholinguistique, Département d'Etudes Cognitives, École Normale Supérieure, EHESS, CNRS, PSL University, Paris, France
| | - Hugo Peyre
- Laboratoire de Sciences Cognitives et Psycholinguistique, Département d'Etudes Cognitives, École Normale Supérieure, EHESS, CNRS, PSL University, Paris, France.,INSERM UMR 1141, Paris Diderot University, Paris, France.,Department of Child and Adolescent Psychiatry, Robert Debré Hospital, APHP, Paris, France
| | - Roberto Toro
- U1284, Center for Research and Interdisciplinarity (CRI), INSERM, Paris, France.,Unité Mixte de Recherche 3571, Human Genetics and Cognitive Functions, Centre National de la Recherche Scientifique, Institut Pasteur, Paris, France
| | - Anita Beggiato
- Department of Child and Adolescent Psychiatry, Robert Debré Hospital, APHP, Paris, France.,Unité Mixte de Recherche 3571, Human Genetics and Cognitive Functions, Centre National de la Recherche Scientifique, Institut Pasteur, Paris, France
| | - Franck Ramus
- Laboratoire de Sciences Cognitives et Psycholinguistique, Département d'Etudes Cognitives, École Normale Supérieure, EHESS, CNRS, PSL University, Paris, France
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29
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Cauvet É, Van't Westeinde A, Toro R, Kuja-Halkola R, Neufeld J, Mevel K, Bölte S. Sex Differences Along the Autism Continuum: A Twin Study of Brain Structure. Cereb Cortex 2020; 29:1342-1350. [PMID: 30566633 PMCID: PMC6373677 DOI: 10.1093/cercor/bhy303] [Citation(s) in RCA: 23] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2018] [Indexed: 12/27/2022] Open
Abstract
Females might possess protective mechanisms regarding autism spectrum disorder (ASD) and require a higher detrimental load, including structural brain alterations, before developing clinically relevant levels of autistic traits. This study examines sex differences in structural brain morphology in autism and autistic traits using a within-twin pair approach. Twin design inherently controls for shared confounders and enables the study of gene-independent neuroanatomical variation. N = 148 twins (62 females) from 49 monozygotic and 25 dizygotic same-sex pairs were included. Participants were distributed along the whole continuum of autism including twin pairs discordant and concordant for clinical ASD. Regional brain volume, surface area, and cortical thickness were computed. Within-twin pair increases in autistic traits were related to decreases in cortical volume and surface area of temporal and frontal regions specifically in female twin pairs, in particular regions involved in social communication, while only two regions were associated with autistic traits in males. The same pattern was detected in the monozygotic twin pairs only. Thus, non-shared environmental factors seem to impact female more than male cerebral architecture associated with autistic traits. Our results are in line with the hypothesis of a female protective effect in autism and highlights the need to study ASD in females separately from males.
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Affiliation(s)
- Élodie Cauvet
- Karolinska Institutet Center of Neurodevelopmental Disorders (KIND), Centre for Psychiatry Research, Department of Women's and Children's Health, Karolinska Institutet, and Stockholm Health Care Services, Stockholm County Council, CAP Research Centre, Sweden
| | - Annelies Van't Westeinde
- Karolinska Institutet Center of Neurodevelopmental Disorders (KIND), Centre for Psychiatry Research, Department of Women's and Children's Health, Karolinska Institutet, and Stockholm Health Care Services, Stockholm County Council, CAP Research Centre, Sweden
| | - Roberto Toro
- Human Genetics and Cognitive Functions, Institut Pasteur, Paris, France.,CNRS URA 2182 "Genes, synapses and cognition", Paris, France.,Université Paris Diderot, Sorbonne Paris Cité, Human Genetics and Cognitive Functions, Paris, France
| | - Ralf Kuja-Halkola
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Janina Neufeld
- Karolinska Institutet Center of Neurodevelopmental Disorders (KIND), Centre for Psychiatry Research, Department of Women's and Children's Health, Karolinska Institutet, and Stockholm Health Care Services, Stockholm County Council, CAP Research Centre, Sweden
| | - Katell Mevel
- Laboratory for the Psychology of Child Development and Education, CNRS Unit 8240, Paris-Descartes University and Caen University, Alliance for higher education and research Sorbonne Paris Cité (IDEX), Sorbonne, France
| | - Sven Bölte
- Karolinska Institutet Center of Neurodevelopmental Disorders (KIND), Centre for Psychiatry Research, Department of Women's and Children's Health, Karolinska Institutet, and Stockholm Health Care Services, Stockholm County Council, CAP Research Centre, Sweden.,Curtin Autism Research Group, School of Occupational Therapy, Social Work and Speech Pathology, Curtin University, Perth, Western Australia
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30
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Biton A, Traut N, Poline JB, Aribisala BS, Bastin ME, Bülow R, Cox SR, Deary IJ, Fukunaga M, Grabe HJ, Hagenaars S, Hashimoto R, Kikuchi M, Muñoz Maniega S, Nauck M, Royle NA, Teumer A, Valdés Hernández M, Völker U, Wardlaw JM, Wittfeld K, Yamamori H, Bourgeron T, Toro R. Corrigendum: Polygenic Architecture of Human Neuroanatomical Diversity. Cereb Cortex 2020; 30:3435-3436. [PMID: 32249901 DOI: 10.1093/cercor/bhaa093] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/16/2019] [Accepted: 09/17/2019] [Indexed: 11/13/2022] Open
Affiliation(s)
- Anne Biton
- Human Genetics and Cognitive Functions Unit, Institut Pasteur, UMR 3571, CNRS, Université Paris Diderot, Paris 75015, France.,Hub de Bioinformatique et Biostatistique-Département Biologie Computationnelle, Institut Pasteur, USR 3756 CNRS, Paris 75015, France
| | - Nicolas Traut
- Human Genetics and Cognitive Functions Unit, Institut Pasteur, UMR 3571, CNRS, Université Paris Diderot, Paris 75015, France
| | - Jean-Baptiste Poline
- Department of Neurology and Neurosurgery, Montreal Neurological Institute, McGill University, Montreal, Quebec, H3A 2B4, Canada
| | - Benjamin S Aribisala
- Centre for Cognitive Ageing and Cognitive Epidemiology, Department of Psychology, University of Edinburgh, Edinburgh, EH8 9JZ, UK.,Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, EH16 4SB UK.,Department of Computer Science, Lagos State University, Lagos, 102101, Nigeria
| | - Mark E Bastin
- Centre for Cognitive Ageing and Cognitive Epidemiology, Department of Psychology, University of Edinburgh, Edinburgh, EH8 9JZ, UK.,Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, EH16 4SB UK.,Brain Research Imaging Centre, Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, EH16 4TJ, UK
| | - Robin Bülow
- The Institute of Diagnostic Radiology and Neuroradiology, University Medicine Greifswald, Greifswald, 17489, Germany
| | - Simon R Cox
- Centre for Cognitive Ageing and Cognitive Epidemiology, Department of Psychology, University of Edinburgh, Edinburgh, EH8 9JZ, UK.,Department of Psychology, University of Edinburgh, Edinburgh, EH8 9JZ, UK
| | - Ian J Deary
- Centre for Cognitive Ageing and Cognitive Epidemiology, Department of Psychology, University of Edinburgh, Edinburgh, EH8 9JZ, UK.,Department of Psychology, University of Edinburgh, Edinburgh, EH8 9JZ, UK
| | - Masaki Fukunaga
- Division of Cerebral Integration, National Institute for Physiological Sciences, Okazaki, 444-8585, Japan.,Department of Physiological Sciences, School of Life Sciences, The Graduate University for Advanced Studies (SOKENDAI), Hayama, 240-0193, Japan
| | - Hans J Grabe
- Department of Psychiatry and Psychotherapy, University Medicine Greifswald, Greifswald, 17485, Germany.,German Centre of Neurodegenerative Diseases (DZNE) Site Greifswald/Rostock, Greifswald, 17489, Germany
| | - Saskia Hagenaars
- Centre for Cognitive Ageing and Cognitive Epidemiology, Department of Psychology, University of Edinburgh, Edinburgh, EH8 9JZ, UK.,Department of Psychology, University of Edinburgh, Edinburgh, EH8 9JZ, UK.,The Social Genetic and Developmental Psychiatry Research Centre, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, SE5 8AF, UK
| | - Ryota Hashimoto
- Department of Pathology of Mental Diseases, National Institute of Mental Health, National Center of Neurology and Psychiatry, Tokyo, 187-0031, Japan
| | - Masataka Kikuchi
- Department of Genome Informatics, Graduate School of Medicine, Osaka University, Osaka, 565-0871, Japan
| | - Susana Muñoz Maniega
- Centre for Cognitive Ageing and Cognitive Epidemiology, Department of Psychology, University of Edinburgh, Edinburgh, EH8 9JZ, UK.,Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, EH16 4SB UK.,Brain Research Imaging Centre, Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, EH16 4TJ, UK
| | - Matthias Nauck
- Institute of Clinical Chemistry and Laboratory Medicine, University Medicine Greifswald, Greifswald, 17475, Germany.,DZHK (German Centre for Cardiovascular Research), Partner Site Greifswald, University Medicine, Greifswald, 17475, Germany
| | - Natalie A Royle
- Centre for Cognitive Ageing and Cognitive Epidemiology, Department of Psychology, University of Edinburgh, Edinburgh, EH8 9JZ, UK.,Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, EH16 4SB UK.,Brain Research Imaging Centre, Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, EH16 4TJ, UK
| | - Alexander Teumer
- Institute for Community Medicine, University Medicine Greifswald, Greifswald, 17475, Germany
| | - Maria Valdés Hernández
- Centre for Cognitive Ageing and Cognitive Epidemiology, Department of Psychology, University of Edinburgh, Edinburgh, EH8 9JZ, UK.,Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, EH16 4SB UK.,Brain Research Imaging Centre, Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, EH16 4TJ, UK
| | - Uwe Völker
- DZHK (German Centre for Cardiovascular Research), Partner Site Greifswald, University Medicine, Greifswald, 17475, Germany.,Department of Functional Genomics, Interfaculty Institute of Genetics and Functional Genomics, University Greifswald, Greifswald, 17475, Germany
| | - Joanna M Wardlaw
- Centre for Cognitive Ageing and Cognitive Epidemiology, Department of Psychology, University of Edinburgh, Edinburgh, EH8 9JZ, UK.,Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, EH16 4SB UK.,Brain Research Imaging Centre, Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, EH16 4TJ, UK
| | - Katharina Wittfeld
- Department of Psychiatry and Psychotherapy, University Medicine Greifswald, Greifswald, 17485, Germany.,German Centre of Neurodegenerative Diseases (DZNE) Site Greifswald/Rostock, Greifswald, 17489, Germany
| | - Hidenaga Yamamori
- Department of Psychiatry, Graduate School of Medicine, Osaka University, Osaka, 565-0871, Japan
| | | | - Thomas Bourgeron
- Human Genetics and Cognitive Functions Unit, Institut Pasteur, UMR 3571, CNRS, Université Paris Diderot, Paris 75015, France
| | - Roberto Toro
- Human Genetics and Cognitive Functions Unit, Institut Pasteur, UMR 3571, CNRS, Université Paris Diderot, Paris 75015, France.,Center for Research and Interdisciplinarity (CRI), Université Paris Descartes, Paris, 75004, France
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31
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Milham M, Petkov CI, Margulies DS, Schroeder CE, Basso MA, Belin P, Fair DA, Fox A, Kastner S, Mars RB, Messinger A, Poirier C, Vanduffel W, Van Essen DC, Alvand A, Becker Y, Ben Hamed S, Benn A, Bodin C, Boretius S, Cagna B, Coulon O, El-Gohary SH, Evrard H, Forkel SJ, Friedrich P, Froudist-Walsh S, Garza-Villarreal EA, Gao Y, Gozzi A, Grigis A, Hartig R, Hayashi T, Heuer K, Howells H, Ardesch DJ, Jarraya B, Jarrett W, Jedema HP, Kagan I, Kelly C, Kennedy H, Klink PC, Kwok SC, Leech R, Liu X, Madan C, Madushanka W, Majka P, Mallon AM, Marche K, Meguerditchian A, Menon RS, Merchant H, Mitchell A, Nenning KH, Nikolaidis A, Ortiz-Rios M, Pagani M, Pareek V, Prescott M, Procyk E, Rajimehr R, Rautu IS, Raz A, Roe AW, Rossi-Pool R, Roumazeilles L, Sakai T, Sallet J, García-Saldivar P, Sato C, Sawiak S, Schiffer M, Schwiedrzik CM, Seidlitz J, Sein J, Shen ZM, Shmuel A, Silva AC, Simone L, Sirmpilatze N, Sliwa J, Smallwood J, Tasserie J, Thiebaut de Schotten M, Toro R, Trapeau R, Uhrig L, Vezoli J, Wang Z, Wells S, Williams B, Xu T, Xu AG, Yacoub E, Zhan M, Ai L, Amiez C, Balezeau F, Baxter MG, Blezer EL, Brochier T, Chen A, Croxson PL, Damatac CG, Dehaene S, Everling S, Fleysher L, Freiwald W, Griffiths TD, Guedj C, Hadj-Bouziane F, Harel N, Hiba B, Jung B, Koo B, Laland KN, Leopold DA, Lindenfors P, Meunier M, Mok K, Morrison JH, Nacef J, Nagy J, Pinsk M, Reader SM, Roelfsema PR, Rudko DA, Rushworth MF, Russ BE, Schmid MC, Sullivan EL, Thiele A, Todorov OS, Tsao D, Ungerleider L, Wilson CR, Ye FQ, Zarco W, Zhou YD. Accelerating the Evolution of Nonhuman Primate Neuroimaging. Neuron 2020; 105:600-603. [PMID: 32078795 PMCID: PMC7610430 DOI: 10.1016/j.neuron.2019.12.023] [Citation(s) in RCA: 66] [Impact Index Per Article: 16.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/21/2019] [Revised: 12/13/2019] [Accepted: 12/17/2019] [Indexed: 11/17/2022]
Abstract
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.
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32
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Peyre H, Mohanpuria N, Jednoróg K, Heim S, Grande M, van Ermingen-Marbach M, Altarelli I, Monzalvo K, Williams CM, Germanaud D, Toro R, Ramus F. Neuroanatomy of dyslexia: An allometric approach. Eur J Neurosci 2020; 52:3595-3609. [PMID: 31991019 DOI: 10.1111/ejn.14690] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2019] [Revised: 01/04/2020] [Accepted: 01/17/2020] [Indexed: 01/06/2023]
Abstract
Despite evidence for a difference in total brain volume between dyslexic and good readers, no previous neuroimaging study examined differences in allometric scaling (i.e. differences in the relationship between regional and total brain volumes) between dyslexic and good readers. The present study aims to fill this gap by testing differences in allometric scaling and regional brain volume differences in dyslexic and good readers. Object-based morphometry analysis was used to determine grey and white matter volumes of the four lobes, the cerebellum and limbic structures in 130 dyslexic and 106 good readers aged 8-14 years. Data were collected across three countries (France, Poland and Germany). Three methodological approaches were used as follows: principal component analysis (PCA), linear regression and multiple-group confirmatory factor analysis (MGCFA). Difference in total brain volume between good and dyslexic readers was Cohen's d = 0.39. We found no difference in allometric scaling, nor in regional brain volume between dyslexic and good readers. Results of our three methodological approaches (PCA, linear regression and MGCFA) were consistent. This study provides evidence for total brain volume differences between dyslexic and control children, but no evidence for differences in the volumes of the four lobes, the cerebellum or limbic structures, once allometry is taken into account. It also finds no evidence for a difference in allometric relationships between the groups. We highlight the methodological interest of the MGCFA approach to investigate such research issues.
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Affiliation(s)
- Hugo Peyre
- Laboratoire de Sciences Cognitives et Psycholinguistique (ENS, EHESS, CNRS), Ecole Normale Supérieure, PSL University, Paris, France.,Neurodiderot, INSERM UMR 1141, Paris Diderot University, Paris, France.,Department of Child and Adolescent Psychiatry, Robert Debré Hospital, APHP, Paris, France
| | - Neha Mohanpuria
- Laboratoire de Sciences Cognitives et Psycholinguistique (ENS, EHESS, CNRS), Ecole Normale Supérieure, PSL University, Paris, France
| | - Katarzyna Jednoróg
- Laboratory of Language Neurobiology, Nencki Institute of Experimental Biology, Polish Academy of Sciences (PAS), Warsaw, Poland
| | - Stefan Heim
- Department of Psychiatry, Psychotherapy and Psychosomatics, Medical Faculty, RWTH Aachen University, Aachen, Germany.,Institute of Neuroscience and Medicine (INM-1), Helmholtz-Gemeinschaft Deutscher Forschungszentren (HZ), Jülich, Germany
| | - Marion Grande
- Department of Neurology, Medical Faculty, RWTH Aachen University, Aachen, Germany
| | - Muna van Ermingen-Marbach
- Department of Psychiatry, Psychotherapy and Psychosomatics, Medical Faculty, RWTH Aachen University, Aachen, Germany.,Department of Neurology, Medical Faculty, RWTH Aachen University, Aachen, Germany
| | - Irene Altarelli
- Laboratory for the Psychology of Child Development and Education, CNRS UMR 8240, Université de Paris, Paris, France
| | - Karla Monzalvo
- INSERM, UMR992, CEA, NeuroSpin Center, University Paris Saclay, Gif-sur-Yvette, France
| | - Camille Michèle Williams
- Laboratoire de Sciences Cognitives et Psycholinguistique (ENS, EHESS, CNRS), Ecole Normale Supérieure, PSL University, Paris, France
| | - David Germanaud
- Neurodiderot, INSERM UMR 1141, Paris Diderot University, Paris, France.,INSERM, UMR992, CEA, NeuroSpin Center, University Paris Saclay, Gif-sur-Yvette, France.,Department of Pediatric Neurology and Metabolic Diseases, Robert Debré Hospital, APHP, Paris, France.,INSERM, CEA, UMR 1129, Sorbonne Paris Cité University (USPC), Paris, France
| | - Roberto Toro
- Human Genetics and Cognitive Functions, Institut Pasteur, Paris, France
| | - Franck Ramus
- Laboratoire de Sciences Cognitives et Psycholinguistique (ENS, EHESS, CNRS), Ecole Normale Supérieure, PSL University, Paris, France
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33
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Ramos Sanchez M, Quezada M, Garcia A, Ayala R, Herrera C, Gomez Pavon FJ, Jaramillo J, Toro R. P905 Value of global longitudinal strain (GLS) in the short term prognosis of geriatric patients with asymptomatic severe aortic stenosis. Eur Heart J Cardiovasc Imaging 2020. [DOI: 10.1093/ehjci/jez319.542] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Abstract
Abstract
Funding Acknowledgements
VII Convocatoria del Banco de Santander and Alfonso X el Sabio University.
Background
Detection of symptoms in geriatric population with aortic stenosis (AS) is challenging, especially when they associate other comorbidities or frailty. Left ventricular global longitudinal strain (GLS) occurs before left ventricular ejection fraction impairment and could be useful for risk stratification and management of these patients.
Purpose
We sought to analyze the usefulness of GLS for predicting major cardiovascular adverse events (MACEs) in geriatric patients with asymptomatic severe AS.
Material and Methods:
Prospective study on 54 patients older than 70 years old with severe asymptomatic AS. Patient evaluation included biochemistry tests, electrocardiogram and echocardiography. We use a GLS cut-off point of 18% to dichotomize patients. Outcomes were defined as the composite of MACEs – occurrence of death from any cause, hospitalization for heart failure, appearance of symptoms or change in treatment.
Results
The mean age was 83.2 ± 7.1, with 60.4% of women. 24.5% showed atrial fibrillation. At 6 months of follow-up, 33% of patients reached the endpoint: 5.6% CHF, 11.1% death, 3.7% symptoms without changes in management and 13% were referred to an invasive treatment. The event-free survival rate at 6 months for the global population was 83%. 41.5 % of the subjects had GLS < 18%. Kaplan Meier analysis showed that the probability of freedom from MACEs was not significant in patients with lower GLS (Log Rank p = 0.39). In the multivariate analysis only AVA was an inverse predictor of events (AVA) HR 0.05 (95% CI 0.007- 0.471, p < 0.05).
Conclusions
The value of GLS was not a predictor of short term events in geriatric patients. Only assessment of AVA was an independent marker of MACES and in this kind of subjects.
Charasteristics of the global population Global N = 53 (%) GLS ≥ 18 N = 31 (58.5%) GLS < 18 N = 22 (41.5%) (p) HBP 42 (79.2) 27 (87.1) 19 (82.6) 0.09 Atrial fibrillation 13 (24.5) 6 (19.4) 7 (31.8) 0.29 CVD 6 (11.3) 1 (3.2) 5 (22.7) 0.02 LVEF: Normal >50% 48 (92) 31 (100) 17 (77.2) 0.05 Peak velocity 3.72 ± 0.72 3.81 ± 0.71 3.60 ± 0.74 0.315 Mean gradient 34.01 ± 14.06 35.61 ± 13.54 32.09 ± 15.07 0.29 Integral ratio 0.25 ± 0.08 0.26 ± 0.09 0.25 ± 0.08 0.83 AVA 0.8 ± 0.26 0.78 ± 0.27 0.83 ± 0.26 0.651 Indexed AVA 0.48 ± 0.16 0.48 ± 0.17 0.48 ± 0.16 0.9 AVA Aortic valve area; CVD: cerebro vascular disease; HBP: High blood presure; LVEF: left ventricule ejection fraction.
Abstract P905 Figure. Kapplan-Meier event-free survival curves
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Affiliation(s)
- M Ramos Sanchez
- Hospital Central de la Cruz Roja. Alfonso X el sabio University., Madrid, Spain
| | - M Quezada
- Hospital Central de la Cruz Roja. Alfonso X el sabio University., Madrid, Spain
| | - A Garcia
- Alfonso X el sabio University, Madrid, Spain
| | - R Ayala
- Hospital Central de la Cruz Roja. Alfonso X el sabio University., Madrid, Spain
| | - C Herrera
- Hospital Central de la Cruz Roja, Madrid, Spain
| | - F J Gomez Pavon
- Hospital Central de la Cruz Roja. Alfonso X el sabio University., Madrid, Spain
| | - J Jaramillo
- Hospital Central de la Cruz Roja. Alfonso X el sabio University., Madrid, Spain
| | - R Toro
- University of Cadiz, Cadiz, Spain
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34
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Quezada M, Ayala R, Ramos M, Villa Benayas Z, Calderon-Dominguez M, Toro R. P225 Carcinoid heart disease: report of a case in a patients with trombocytopenia absent radius. Eur Heart J Cardiovasc Imaging 2020. [DOI: 10.1093/ehjci/jez319.091] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Abstract
Abstract
Background
The carcinoid syndrome is characterized by extensive and several clinical manifestations. The diarrhea, the cutaneous flushing are the most frequents symptoms while cardiac manifestations (carcinoid heart disease) (CHD) occurs in a mean of 40%. Nowadays, the number of cases of CHD is lower than 20%, as a consequence of the widespread use of somatostatin analogues. At present, there is a mean delay in diagnosis of CHD of 1.5 years from the time of carcinoid syndrome detection. Hence, CHD is associated with a poor prognosis for clinical management.
Case report
We present a case of 45-years-old active woman, with Thrombocytopenia absent radius (TAR). This is characterized by a bilateral absence of the radio with the presence of both thumbs and thrombocytopenia. Our patient was attended for dyspnea of medium efforts, history of diarrhea, cutaneous flushing with tachycardia and elevated urinary 5-hydroxyindoleacetic acid (5-HIAA) (89,6 mg/24 (2,0-9,0)). The Transthoracic echocardiography showed morphologic changes that affected the tricuspid valve: diminished curvature of the leaflets, altered dynamic motion of the leaflets during diastole, fused and shortened chordae retraction and reduced excursion of the valve. A moderate to severe tricuspid regurgitation and tricuspid stenosis with gradient media de 5 mmHg was observed. In addition, the right ventricle was dilated, a severe pulmonary hypertension, a right pleural effusion and a minor pericardial effusion circumference were detected. All these findings were consistent with CHD.
Conclusions
This report describes an unusual case of CHD in TAR patient. In fact, the interest of this case is the role played by the echocardiogram in the differential diagnosis for tricuspid valve diseases. Tricuspid stenosis is an infrequent condition and it is usually related with rheumatic disease associated with mitral valve disease. Although the carcinoid syndrome is infrequent, any changes in the anatomical structure of the tricuspid valve (thickening, fibrosis and rigidity associated with stenosis and tricuspid regurgitation) should alert us to the suspicion of CHD
Abstract P225 Figure.
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Affiliation(s)
- M Quezada
- University Hospital Central de LA Cruz Roja, School Of Medicine Alfonso X el Sabio University, Cardiology, Madrid, Spain
| | - R Ayala
- University Hospital Central de LA Cruz Roja, School Of Medicine Alfonso X el Sabio University, Cardiology, Madrid, Spain
| | - M Ramos
- University Hospital Central de LA Cruz Roja, School Of Medicine Alfonso X el Sabio University, Cardiology, Madrid, Spain
| | - Z Villa Benayas
- University Hospital Central de LA Cruz Roja, Cardiology, Madrid, Spain
| | - M Calderon-Dominguez
- Cádiz University and Instituto de Investigación e Innovación en Ciencias Biomédicas (INIBICA), Cardiology, Cádiz, Spain
| | - R Toro
- Cádiz University and Instituto de Investigación e Innovación en Ciencias Biomédicas (INIBICA), Cardiology, Cádiz, Spain
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Quezada M, Ramos M, Ayala R, Calderon- Dominguez M, Guerrero De La Riva P, Villa Benayas Z, Munoz Carrasco M, Toro R. P1439 Familial dilated cardiomyopathy: assessment of left ventricular systolic and diastolic function by echocardiogram in asymptomatic patients. Eur Heart J Cardiovasc Imaging 2020. [DOI: 10.1093/ehjci/jez319.868] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Abstract
Abstract
Funding Acknowledgements
Alfonso X El Sabio University
Introduction
Familial dilated cardiomyopathy (fDCM) represents 20% to 30% of idiopathic DCM (iDCM) ethiology. The assessment of cardiac function of these patients is awfully complex. Usually, myocardial fiber damages can not be detected in the early DCM stages. In this sense echocardiogram could be useful to detect incipient changes.
Purpose
The aim of this study was to characterize the systolic function of asymptomatic fDCM, compared within iDCM and control patients.
Material and methods
This study was carried out in 33 fDCM patients. A total of 4 fDCM families with LMNA gene mutation and 3 fDCM families with BLC2-associated athanogene 3 (BAG3) mutation were recruited. Moreover, a total of 30 iDCM and 66 healthy matched controls were enrolled in the study.
Results
58.14% were male. The average age was 45.3 ± 17 years. 72% showed sinus rhythm. Left bundle branch block (LBBB) was observed in 7.8% of patients. The LV ejection fraction (LVEF), sphericity index and mitral annular plane systolic excursion (MAPSE), were significantly improved in the fDCM patients compared to iDCM subjects. However, these parameters were aggravated compared with healthy controls. LVEF was enhanced in fDCM in contrast to iDCM (56% versus 35%; P < 0.001). Nevertheless, LVEF value was deteriorated in fDCM compared to healthy controls (56% versus 65%; P < 0.001). The values of septal and lateral annulus early diastolic velocity measured by DTI, were also diminished. All results are presented in Table 1.
Conclusions
Asymptomatic fDCM shown an intermediate value of LVEF between the iDCM and the control group. This ventricular remodeling process could be the consequence of a slight increase in the end-systolic diameter.
Patients Characteristics Patients Characteristics iDCM 30 patients fDCM 33 patients Control Group 66 Healthy P LVEF 32 (29.78-40) 56.0 (39.7-64.2) 65 (62-69.5) 0.001 EDD 62.5 (59.2-65.7) 53.7 (45.7-57.6) 45.50 (43-48.8) 0.001 ESD 53 (47-58.75) 36 (30.9-54.2) 27.9 (24-31) 0.001 MAPSE 11 (10-12.50) 14 (14-18) 19 (17-20) 0.001 Sphericity index 0.70 (0.66–0.79) 0.69 (0.66-0.79) 0.53 (0.48-58) 0.001 LA volume 61.5 (57-75.1) 32 (23-46.5) 17 (14.2-20) NS Septal annulus Early diastolic Velocity (cm/s) DTI 3.5 (3-4.2) 7.5 (1.6-8.8) 9 (7.9-11) 0.001 Lateral annulus Early diastolic Velocity (cm/s) DT 7.2 (5-8.9) 9.5 (1.8-11.8) 13 (10.37-15) 0.001 Table1. Echocardiografic findings in patients. LVEF: left ventricular ejection fraction; EDD: end-diastolic diameter; ESD: end systolic diameter; MAPSE:mitral annular plane systoluc excursion; LA: left atrium; TDI: Tissue Doppler imagin.
Abstract P1439 Figure. Familial dilated cardiomyopathy
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Affiliation(s)
- M Quezada
- University Hospital Central de LA Cruz Roja, School Of Medicine Alfonso X el Sabio University, Cardiology, Madrid, Spain
| | - M Ramos
- University Hospital Central de LA Cruz Roja, School Of Medicine Alfonso X el Sabio University, Cardiology, Madrid, Spain
| | - R Ayala
- University Hospital Central de LA Cruz Roja, School Of Medicine Alfonso X el Sabio University, Cardiology, Madrid, Spain
| | - M Calderon- Dominguez
- Cádiz University and Instituto de Investigación e Innovación en Ciencias Biomédicas (INIBICA), Cardiology, Cádiz, Spain
| | | | - Z Villa Benayas
- University Hospital Central de LA Cruz Roja, Cardiology, Madrid, Spain
| | - M Munoz Carrasco
- University Hospital Central de LA Cruz Roja, Cardiology, Madrid, Spain
| | - R Toro
- Cádiz University and Instituto de Investigación e Innovación en Ciencias Biomédicas (INIBICA), Cardiology, Cádiz, Spain
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Heuer K, Toro R. Role of mechanical morphogenesis in the development and evolution of the neocortex. Phys Life Rev 2019; 31:233-239. [DOI: 10.1016/j.plrev.2019.01.012] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/25/2018] [Revised: 12/20/2018] [Accepted: 01/15/2019] [Indexed: 01/05/2023]
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Warrier V, Toro R, Won H, Leblond CS, Cliquet F, Delorme R, De Witte W, Bralten J, Chakrabarti B, Børglum AD, Grove J, Poelmans G, Hinds DA, Bourgeron T, Baron-Cohen S. Social and non-social autism symptoms and trait domains are genetically dissociable. Commun Biol 2019; 2:328. [PMID: 31508503 PMCID: PMC6722082 DOI: 10.1038/s42003-019-0558-4] [Citation(s) in RCA: 42] [Impact Index Per Article: 8.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2018] [Accepted: 07/19/2019] [Indexed: 02/06/2023] Open
Abstract
The core diagnostic criteria for autism comprise two symptom domains - social and communication difficulties, and unusually repetitive and restricted behaviour, interests and activities. There is some evidence to suggest that these two domains are dissociable, though this hypothesis has not yet been tested using molecular genetics. We test this using a genome-wide association study (N = 51,564) of a non-social trait related to autism, systemising, defined as the drive to analyse and build systems. We demonstrate that systemising is heritable and genetically correlated with autism. In contrast, we do not identify significant genetic correlations between social autistic traits and systemising. Supporting this, polygenic scores for systemising are significantly and positively associated with restricted and repetitive behaviour but not with social difficulties in autistic individuals. These findings strongly suggest that the two core domains of autism are genetically dissociable, and point at how to fractionate the genetics of autism.
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Affiliation(s)
- Varun Warrier
- Autism Research Centre, Department of Psychiatry, University of Cambridge, Cambridgeshire, UK
| | - Roberto Toro
- Human Genetics and Cognitive Functions, Institut Pasteur, UMR3571 CNRS, Université de Paris, Paris, France
| | - Hyejung Won
- Department of Genetics and Neuroscience Center, University of North Carolina, Chapel Hill, NC 27599 USA
| | - Claire S. Leblond
- Human Genetics and Cognitive Functions, Institut Pasteur, UMR3571 CNRS, Université de Paris, Paris, France
| | - Freddy Cliquet
- Human Genetics and Cognitive Functions, Institut Pasteur, UMR3571 CNRS, Université de Paris, Paris, France
| | - Richard Delorme
- Human Genetics and Cognitive Functions, Institut Pasteur, UMR3571 CNRS, Université de Paris, Paris, France
- Child and Adolescent Psychiatry Department, Robert Debré Hospital, Paris, France
| | - Ward De Witte
- Department of Human Genetics, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Janita Bralten
- Department of Human Genetics, Radboud University Medical Center, Nijmegen, The Netherlands
- Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, The Netherlands
| | - Bhismadev Chakrabarti
- Autism Research Centre, Department of Psychiatry, University of Cambridge, Cambridgeshire, UK
- Centre for Autism, School of Psychology and Clinical Language Sciences, University of Reading, Reading, UK
| | - Anders D. Børglum
- The Lundbeck Foundation Initiative for Integrative Psychiatric Research, iPSYCH, Aarhus, Denmark
- Centre for Integrative Sequencing, iSEQ, Aarhus University, Aarhus, Denmark
- Department of Biomedicine - Human Genetics, Aarhus University, Aarhus, Denmark
| | - Jakob Grove
- The Lundbeck Foundation Initiative for Integrative Psychiatric Research, iPSYCH, Aarhus, Denmark
- Centre for Integrative Sequencing, iSEQ, Aarhus University, Aarhus, Denmark
- Department of Biomedicine - Human Genetics, Aarhus University, Aarhus, Denmark
- Bioinformatics Research Centre, Aarhus University, Aarhus, Denmark
| | - Geert Poelmans
- Department of Human Genetics, Radboud University Medical Center, Nijmegen, The Netherlands
| | | | - Thomas Bourgeron
- Human Genetics and Cognitive Functions, Institut Pasteur, UMR3571 CNRS, Université de Paris, Paris, France
| | - Simon Baron-Cohen
- Autism Research Centre, Department of Psychiatry, University of Cambridge, Cambridgeshire, UK
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Heuer K, Gulban OF, Bazin PL, Osoianu A, Valabregue R, Santin M, Herbin M, Toro R. Evolution of neocortical folding: A phylogenetic comparative analysis of MRI from 34 primate species. Cortex 2019; 118:275-291. [DOI: 10.1016/j.cortex.2019.04.011] [Citation(s) in RCA: 34] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/04/2018] [Revised: 04/08/2019] [Accepted: 04/09/2019] [Indexed: 01/14/2023]
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Delettre C, Messé A, Dell LA, Foubet O, Heuer K, Larrat B, Meriaux S, Mangin JF, Reillo I, de Juan Romero C, Borrell V, Toro R, Hilgetag CC. Comparison between diffusion MRI tractography and histological tract-tracing of cortico-cortical structural connectivity in the ferret brain. Netw Neurosci 2019; 3:1038-1050. [PMID: 31637337 PMCID: PMC6777980 DOI: 10.1162/netn_a_00098] [Citation(s) in RCA: 28] [Impact Index Per Article: 5.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/22/2019] [Accepted: 05/23/2019] [Indexed: 12/20/2022] Open
Abstract
The anatomical wiring of the brain is a central focus in network neuroscience. Diffusion MRI tractography offers the unique opportunity to investigate the brain fiber architecture in vivo and noninvasively. However, its reliability is still highly debated. Here, we explored the ability of diffusion MRI tractography to match invasive anatomical tract-tracing connectivity data of the ferret brain. We also investigated the influence of several state-of-the-art tractography algorithms on this match to ground truth connectivity data. Tract-tracing connectivity data were obtained from retrograde tracer injections into the occipital, parietal, and temporal cortices of adult ferrets. We found that the relative densities of projections identified from the anatomical experiments were highly correlated with the estimates from all the studied diffusion tractography algorithms (Spearman's rho ranging from 0.67 to 0.91), while only small, nonsignificant variations appeared across the tractography algorithms. These results are comparable to findings reported in mouse and monkey, increasing the confidence in diffusion MRI tractography results. Moreover, our results provide insights into the variations of sensitivity and specificity of the tractography algorithms, and hence into the influence of choosing one algorithm over another.
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Affiliation(s)
- Céline Delettre
- Unité de Génétique Humaine et Fonctions Cognitives, Institut Pasteur, UMR 3571, CNRS, Paris, France
- Institute of Computational Neuroscience, University Medical Center Eppendorf, Hamburg University, Hamburg, Germany
- Université Paris Diderot, Sorbonne Paris Cité, Paris, France
| | - Arnaud Messé
- Institute of Computational Neuroscience, University Medical Center Eppendorf, Hamburg University, Hamburg, Germany
| | - Leigh-Anne Dell
- Institute of Computational Neuroscience, University Medical Center Eppendorf, Hamburg University, Hamburg, Germany
| | - Ophélie Foubet
- Unité de Génétique Humaine et Fonctions Cognitives, Institut Pasteur, UMR 3571, CNRS, Paris, France
| | - Katja Heuer
- Unité de Génétique Humaine et Fonctions Cognitives, Institut Pasteur, UMR 3571, CNRS, Paris, France
- Department of Neuropsychology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Benoit Larrat
- NeuroSpin, CEA, Paris-Saclay University, Gif-sur-Yvette, France
| | | | | | - Isabel Reillo
- Developmental Neurobiology Unit, Instituto de Neurociencias, Consejo Superior de Investigaciones Científicas, Universidad Miguel Hernández, Sant Joan d’Alacant, Spain
| | - Camino de Juan Romero
- Developmental Neurobiology Unit, Instituto de Neurociencias, Consejo Superior de Investigaciones Científicas, Universidad Miguel Hernández, Sant Joan d’Alacant, Spain
| | - Victor Borrell
- Developmental Neurobiology Unit, Instituto de Neurociencias, Consejo Superior de Investigaciones Científicas, Universidad Miguel Hernández, Sant Joan d’Alacant, Spain
| | - Roberto Toro
- Unité de Génétique Humaine et Fonctions Cognitives, Institut Pasteur, UMR 3571, CNRS, Paris, France
- Center for Research and Interdisciplinarity (CRI), Université Paris Descartes, Paris, France
| | - Claus C. Hilgetag
- Institute of Computational Neuroscience, University Medical Center Eppendorf, Hamburg University, Hamburg, Germany
- Department of Health Sciences, Boston University, Boston, MA, USA
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De Gonzalo-Calvo D, Vilades D, Martínez-Camblor P, Vea A, Nasarre L, Toro R, Vega JS, Leta R, Puig-Grifol N, Benitez S, Sanchez-Quesada J, Carreras F, Llorente-Cortes V. Micrornas As Circulating Biomarkers Of Epicardial Fat Volume: A Multidetector Computed Tomography Study. Atherosclerosis 2019. [DOI: 10.1016/j.atherosclerosis.2019.06.204] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 10/26/2022]
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Ramos M, Quezada DM, Ayala R, Gómez-Pavón FJ, Jaramillo J, Toro R. Aortic stenosis prognosis in older patients: frailty is a strong marker of early congestive heart failure admissions. Eur Geriatr Med 2019; 10:483-491. [DOI: 10.1007/s41999-019-00165-5] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/23/2018] [Accepted: 01/09/2019] [Indexed: 01/09/2023]
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Maruani A, Dumas G, Beggiato A, Traut N, Peyre H, Cohen-Freoua A, Amsellem F, Elmaleh M, Germanaud D, Launay JM, Bourgeron T, Toro R, Delorme R. Morning Plasma Melatonin Differences in Autism: Beyond the Impact of Pineal Gland Volume. Front Psychiatry 2019; 10:11. [PMID: 30787884 PMCID: PMC6372551 DOI: 10.3389/fpsyt.2019.00011] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/04/2018] [Accepted: 01/09/2019] [Indexed: 12/14/2022] Open
Abstract
While low plasma melatonin, a neuro-hormone synthesized in the pineal gland, has been frequently associated with autism, our understanding of the mechanisms behind it have remained unclear. In this exploratory study, we hypothesized that low melatonin levels in ASD could be linked to a decrease of the pineal gland volume (PGV). PGV estimates with magnetic resonance imaging (MRI) with a voxel-based volumetric measurement method and early morning plasma melatonin levels were evaluated for 215 participants, including 78 individuals with ASD, 90 unaffected relatives, and 47 controls. We first found that both early morning melatonin level and PGV were lower in patients compared to controls. We secondly built a linear model and observed that plasma melatonin was correlated to the group of the participant, but also to the PGV. To further understand the relationship between PGV and melatonin, we generated a normative model of the PGV relationship with melatonin level based on control participant data. We found an effect of PGV on normalized melatonin levels in ASD. Melatonin deficit appeared however more related to the group of the subject. Thus, melatonin variations in ASD could be mainly driven by melatonin pathway dysregulation.
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Affiliation(s)
- Anna Maruani
- Child and Adolescent Psychiatry Department, Robert Debré Hospital, Paris, France.,Human Genetics and Cognitive Functions, Institut Pasteur, Paris, France
| | - Guillaume Dumas
- Human Genetics and Cognitive Functions, Institut Pasteur, Paris, France
| | - Anita Beggiato
- Child and Adolescent Psychiatry Department, Robert Debré Hospital, Paris, France.,Human Genetics and Cognitive Functions, Institut Pasteur, Paris, France
| | - Nicolas Traut
- Human Genetics and Cognitive Functions, Institut Pasteur, Paris, France
| | - Hugo Peyre
- Child and Adolescent Psychiatry Department, Robert Debré Hospital, Paris, France
| | - Alicia Cohen-Freoua
- Child and Adolescent Psychiatry Department, Robert Debré Hospital, Paris, France
| | - Frédérique Amsellem
- Child and Adolescent Psychiatry Department, Robert Debré Hospital, Paris, France.,Human Genetics and Cognitive Functions, Institut Pasteur, Paris, France
| | - Monique Elmaleh
- Pediatric Radiology Department, Robert Debré Hospital, Paris, France
| | - David Germanaud
- Department of Pediatric Neurology, Robert Debré Hospital, AP-HP, Paris, France.,Neuropaediatric Team, UNIACT, NeuroSpin, CEA-Saclay, Gif-sur-Yvette, France
| | - Jean-Marie Launay
- Biochemistry Department, INSERM U942, Lariboisière Hospital, Assistance Publique-Hopitaux de Paris EA 3621, Paris, France
| | - Thomas Bourgeron
- Human Genetics and Cognitive Functions, Institut Pasteur, Paris, France
| | - Roberto Toro
- Human Genetics and Cognitive Functions, Institut Pasteur, Paris, France
| | - Richard Delorme
- Child and Adolescent Psychiatry Department, Robert Debré Hospital, Paris, France.,Human Genetics and Cognitive Functions, Institut Pasteur, Paris, France
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Cury C, Glaunès JA, Toro R, Chupin M, Schumann G, Frouin V, Poline JB, Colliot O. Statistical Shape Analysis of Large Datasets Based on Diffeomorphic Iterative Centroids. Front Neurosci 2018; 12:803. [PMID: 30483045 PMCID: PMC6241313 DOI: 10.3389/fnins.2018.00803] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2018] [Accepted: 10/16/2018] [Indexed: 01/22/2023] Open
Abstract
In this paper, we propose an approach for template-based shape analysis of large datasets, using diffeomorphic centroids as atlas shapes. Diffeomorphic centroid methods fit in the Large Deformation Diffeomorphic Metric Mapping (LDDMM) framework and use kernel metrics on currents to quantify surface dissimilarities. The statistical analysis is based on a Kernel Principal Component Analysis (Kernel PCA) performed on the set of initial momentum vectors which parametrize the deformations. We tested the approach on different datasets of hippocampal shapes extracted from brain magnetic resonance imaging (MRI), compared three different centroid methods and a variational template estimation. The largest dataset is composed of 1,000 surfaces, and we are able to analyse this dataset in 26 h using a diffeomorphic centroid. Our experiments demonstrate that computing diffeomorphic centroids in place of standard variational templates leads to similar shape analysis results and saves around 70% of computation time. Furthermore, the approach is able to adequately capture the variability of hippocampal shapes with a reasonable number of dimensions, and to predict anatomical features of the hippocampus, only present in 17% of the population, in healthy subjects.
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Affiliation(s)
- Claire Cury
- Institut du Cerveau et de la Moelle épinire, ICM, Paris, France
- Inserm, U 1127, Paris, France
- CNRS,UMR 7225, Paris, France
- Sorbonne Université, Paris, France
- Inria, Aramis project-team, Paris, France
- Univ Rennes, Inria, CNRS, Inserm, IRISA UMR 6074, VISAGES ERL U 1228, Rennes, France
| | - Joan A. Glaunès
- MAP5, Université Paris Descartes, Sorbonne Paris Cité, Paris, France
| | - Roberto Toro
- Human Genetics and Cognitive Functions, Institut Pasteur, Paris, France
- CNRS URA 2182 “Genes, Synapses and Cognition”, Paris, France
| | - Marie Chupin
- Institut du Cerveau et de la Moelle épinire, ICM, Paris, France
- Inserm, U 1127, Paris, France
- CNRS,UMR 7225, Paris, France
- Sorbonne Université, Paris, France
- Inria, Aramis project-team, Paris, France
| | - Gunter Schumann
- MRC-Social Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, King's College London, London, United Kingdom
| | - Vincent Frouin
- Neurospin, Commissariat à l'Energie Atomique et aux Energies Alternatives, Paris, France
| | - Jean-Baptiste Poline
- Henry H. Wheeler Jr. Brain Imaging Center, University of California, Berkeley, California City, CA, United States
| | - Olivier Colliot
- Institut du Cerveau et de la Moelle épinire, ICM, Paris, France
- Inserm, U 1127, Paris, France
- CNRS,UMR 7225, Paris, France
- Sorbonne Université, Paris, France
- Inria, Aramis project-team, Paris, France
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Lefebvre A, Delorme R, Delanoë C, Amsellem F, Beggiato A, Germanaud D, Bourgeron T, Toro R, Dumas G. Alpha Waves as a Neuromarker of Autism Spectrum Disorder: The Challenge of Reproducibility and Heterogeneity. Front Neurosci 2018; 12:662. [PMID: 30327586 PMCID: PMC6174243 DOI: 10.3389/fnins.2018.00662] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/18/2018] [Accepted: 09/04/2018] [Indexed: 11/13/2022] Open
Abstract
Background: There is no consensus in the literature concerning the presence of abnormal alpha wave profiles in patients with autism spectrum disorder (ASD). This may be due to phenotypic heterogeneity among patients as well as the limited sample sizes utilized. Here we present our results of alpha wave profile analysis based on a sample larger than most of those in the field, performed using a robust processing pipeline. Methods: We compared the alpha waves profiles at rest in children with ASD to those of age-, sex-, and IQ-matched control individuals. We used linear regression and non-parametric normative models using age as covariate forparsing the clinical heterogeneity. We explored the correlation between EEG profiles and the patient's brain volumes, obtained from structural MRI. We automatized the detection of the alpha peak and visually quality controled our MRI measurements. We assessed the robustness of our results by running the EEG preprocessing with two different versions of Matlab as well as Python. Results: A simple linear regression between peak power or frequency of the alpha waves and the status or age of the participants did not allow to identify any statistically significant relationship. The non-parametric normative model (which took account the non-linear effect of age on the alpha profiles) suggested that participants with ASD displayed more variability than control participants for both frequency and amplitude of the alpha peak (p < 0.05). Independent of the status of the individual, we also observed weak associations (uncorrected p < 0.05) between the alpha frequency, and the volumes of several cortical and subcortical structures (in particular the striatum), but which did not survive correction for multiple testing and changed between analysis pelines. Discussions: Our study did not find evidence for abnormal alpha wave profiles in ASD. We propose, however, an analysis pipeline to perform standardized and automatized EEG analyses on large cohorts. These should help the community to address the challenge of clinical heterogeneity of ASD and to tackle the problems of reproducibility.
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Affiliation(s)
- Aline Lefebvre
- Department of Child and Adolescent Psychiatry, Assistance Publique-Hôpitaux de Paris, Robert Debré Hospital, Paris, France.,Human Genetics and Cognitive Functions Unit, Institut Pasteur, Paris, France.,CNRS UMR 3571 Genes, Synapses and Cognition, Institut Pasteur, Paris, France.,Sorbonne Paris Cité, Human Genetics and Cognitive Functions, University Paris Diderot, Paris, France
| | - Richard Delorme
- Department of Child and Adolescent Psychiatry, Assistance Publique-Hôpitaux de Paris, Robert Debré Hospital, Paris, France.,Human Genetics and Cognitive Functions Unit, Institut Pasteur, Paris, France.,CNRS UMR 3571 Genes, Synapses and Cognition, Institut Pasteur, Paris, France.,Sorbonne Paris Cité, Human Genetics and Cognitive Functions, University Paris Diderot, Paris, France
| | - Catherine Delanoë
- Neurophysiology Department, Assistance Publique-Hôpitaux de Paris, Robert Debré Hospital, Paris, France
| | - Frederique Amsellem
- Department of Child and Adolescent Psychiatry, Assistance Publique-Hôpitaux de Paris, Robert Debré Hospital, Paris, France.,Human Genetics and Cognitive Functions Unit, Institut Pasteur, Paris, France.,CNRS UMR 3571 Genes, Synapses and Cognition, Institut Pasteur, Paris, France.,Sorbonne Paris Cité, Human Genetics and Cognitive Functions, University Paris Diderot, Paris, France
| | - Anita Beggiato
- Department of Child and Adolescent Psychiatry, Assistance Publique-Hôpitaux de Paris, Robert Debré Hospital, Paris, France.,Human Genetics and Cognitive Functions Unit, Institut Pasteur, Paris, France.,CNRS UMR 3571 Genes, Synapses and Cognition, Institut Pasteur, Paris, France.,Sorbonne Paris Cité, Human Genetics and Cognitive Functions, University Paris Diderot, Paris, France
| | - David Germanaud
- Pediatric Neurology Department, Assistance Publique-Hôpitaux de Paris, Robert Debré Hospital, Paris, France
| | - Thomas Bourgeron
- Human Genetics and Cognitive Functions Unit, Institut Pasteur, Paris, France.,CNRS UMR 3571 Genes, Synapses and Cognition, Institut Pasteur, Paris, France.,Sorbonne Paris Cité, Human Genetics and Cognitive Functions, University Paris Diderot, Paris, France
| | - Roberto Toro
- Human Genetics and Cognitive Functions Unit, Institut Pasteur, Paris, France.,CNRS UMR 3571 Genes, Synapses and Cognition, Institut Pasteur, Paris, France.,Sorbonne Paris Cité, Human Genetics and Cognitive Functions, University Paris Diderot, Paris, France
| | - Guillaume Dumas
- Human Genetics and Cognitive Functions Unit, Institut Pasteur, Paris, France.,CNRS UMR 3571 Genes, Synapses and Cognition, Institut Pasteur, Paris, France.,Sorbonne Paris Cité, Human Genetics and Cognitive Functions, University Paris Diderot, Paris, France
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Dominguez Rodriguez F, Cuenca S, Bilinska Z, Toro R, Charron P, Barriales-Villa R, Asselbergs F, Akhtar M, Morris Hey T, Rangel-Sousa D, Limeres JM, Garcia-Pinilla JM, Ochoa JP, Elliott P, Garcia-Pavia P. P3169Clinical characteristics and natural history of dilated cardiomyopathy due to BAG3 mutations. Eur Heart J 2018. [DOI: 10.1093/eurheartj/ehy563.p3169] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Affiliation(s)
- F Dominguez Rodriguez
- University Hospital Puerta de Hierro Majadahonda, Inherited Cardiac Disease Unit, CNIC, CIBERCV, Madrid, Spain
| | - S Cuenca
- University Hospital Gregorio Maranon, Madrid, Spain
| | - Z Bilinska
- The Cardinal Stefan Wyszynski Institute of Cardiology, Warsaw, Poland
| | - R Toro
- University Hospital Puerta del Mar, Cadiz, Spain
| | - P Charron
- Hospital Pitie-Salpetriere, Paris, France
| | | | - F Asselbergs
- University Medical Center Utrecht, Utrecht, Netherlands
| | - M Akhtar
- St Bartholomew's Hospital, London, United Kingdom
| | | | | | - J M Limeres
- University Hospital Vall d'Hebron, Barcelona, Spain
| | - J M Garcia-Pinilla
- University Hospital Virgen de la Victoria, IBIMA, CIBERCV, Malaga, Spain
| | | | - P Elliott
- St Bartholomew's Hospital, London, United Kingdom
| | - P Garcia-Pavia
- University Hospital Puerta de Hierro Majadahonda, Inherited Cardiac Disease Unit, CNIC, CIBERCV, Madrid, Spain
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Lerma V, Macías M, Toro R, Moscoso A, Alonso Y, Hernández O, de Abajo FJ. Care in patients with epidermal necrolysis in burn units. A nursing perspective. Burns 2018; 44:1962-1972. [PMID: 30005991 DOI: 10.1016/j.burns.2018.06.010] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2018] [Revised: 05/03/2018] [Accepted: 06/15/2018] [Indexed: 10/28/2022]
Abstract
OBJECTIVE To describe how nursing care is delivered to patients with epidermal necrolysis in burn units/specialized units in Spain and a selection of countries. METHOD Descriptive cross-sectional study. Data were collected through a structured questionnaire which was sent to nurse managers in all burn units in Spain and a selection of countries. Descriptive statistics was used to summarize the results. RESULTS All BU/SUs in Spain (n=12) and seven BU/SUs from a selection of countries completed the questionnaire. A lack of specific nursing protocols on Epidermal Necrolysis was observed in most burn units in Spain. Skin cleansing techniques such as showering were only reported by participants from Spain. Use of antiseptics was less frequent in other countries. Conservative skin management was the most extended practice reported by all participants. The use of vaginal molds to prevent synechiae and coverage of the ocular surface with amniotic membrane to minimize sequelae were rarely reported. Pain assessment was not always documented in sedated patients and few participants reported the use of specific scales for this purpose. All nurses agreed in the need for consensus nursing care guidelines on the disease. CONCLUSIONS Nursing care in patients with epidermal necrolysis varied between burn units in Spain. Differences and similarities were observed when compared with burn units in other countries. Genital and ocular care were outdated in all BU/SUs. Pain assessment documentation was suboptimal. Evidence-based nursing care guidelines were generally demanded by all participants to help reduce mortality and morbidity of this rare and often devastating disease.
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Affiliation(s)
- V Lerma
- Clinical Pharmacology Unit, Príncipe de Asturias University Hospital, IRYCIS, Alcalá de Henares, Madrid, Spain.
| | - M Macías
- Quality Unit, Príncipe de Asturias University Hospital, Alcalá de Henares, Madrid, Spain
| | - R Toro
- Care Research Unit, Príncipe de Asturias University Hospital, Alcalá de Henares, Madrid, Spain
| | - A Moscoso
- Burn Unit, University Hospital of Getafe, Getafe, Madrid, Spain
| | - Y Alonso
- Burn Unit, University Hospital of Getafe, Getafe, Madrid, Spain
| | - O Hernández
- Burn Unit, La Paz University Hospital, Madrid, Spain
| | - F J de Abajo
- Clinical Pharmacology Unit, Príncipe de Asturias University Hospital, Department of Biomedical Sciences, University of Alcalá, IRYCIS, Alcalá de Henares, Madrid, Spain
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47
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Warrier V, Grasby KL, Uzefovsky F, Toro R, Smith P, Chakrabarti B, Khadake J, Mawbey-Adamson E, Litterman N, Hottenga JJ, Lubke G, Boomsma DI, Martin NG, Hatemi PK, Medland SE, Hinds DA, Bourgeron T, Baron-Cohen S. Genome-wide meta-analysis of cognitive empathy: heritability, and correlates with sex, neuropsychiatric conditions and cognition. Mol Psychiatry 2018; 23:1402-1409. [PMID: 28584286 PMCID: PMC5656177 DOI: 10.1038/mp.2017.122] [Citation(s) in RCA: 74] [Impact Index Per Article: 12.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/19/2016] [Revised: 04/08/2017] [Accepted: 04/12/2017] [Indexed: 12/19/2022]
Abstract
We conducted a genome-wide meta-analysis of cognitive empathy using the 'Reading the Mind in the Eyes' Test (Eyes Test) in 88,056 research volunteers of European Ancestry (44,574 females and 43,482 males) from 23andMe Inc., and an additional 1497 research volunteers of European Ancestry (891 females and 606 males) from the Brisbane Longitudinal Twin Study. We confirmed a female advantage on the Eyes Test (Cohen's d=0.21, P<2.2 × 10-16), and identified a locus in 3p26.1 that is associated with scores on the Eyes Test in females (rs7641347, Pmeta=1.58 × 10-8). Common single nucleotide polymorphisms explained 5.8% (95% CI: 4.5%-7.2%; P=1.00 × 10-17) of the total trait variance in both sexes, and we identified a twin heritability of 28% (95% CI: 13%-42%). Finally, we identified significant genetic correlation between the Eyes Test and anorexia nervosa, openness (NEO-Five Factor Inventory), and different measures of educational attainment and cognitive aptitude.
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Affiliation(s)
- Varun Warrier
- Autism Research Centre, Department of Psychiatry, University of Cambridge, Cambridgeshire, United Kingdom,Corresponding authors: Varun Warrier () and Simon Baron-Cohen (). Autism Research Centre, Douglas House, 18B Trumpington Road, Cambridge, CB2 8AH, United Kingdom. Telephone: 0044 (0) 1223 746057
| | | | - Florina Uzefovsky
- Autism Research Centre, Department of Psychiatry, University of Cambridge, Cambridgeshire, United Kingdom,Department of Psychology, Ben Gurion University of the Negev, Israel
| | - Roberto Toro
- CNRS UMR 3571: Genes, Synapses and Cognition, Institut Pasteur, Paris, France,Université Paris Diderot, Sorbonne Paris Cité, Human Genetics and Cognitive Functions, Paris, France,Institut Pasteur, 5-28 Rue du Dr Roux, 75015 Paris, France
| | - Paula Smith
- Autism Research Centre, Department of Psychiatry, University of Cambridge, Cambridgeshire, United Kingdom
| | - Bhismadev Chakrabarti
- Centre for Integrative Neuroscience and Neurodynamics, School of Psychology and Clinical Language Sciences, University of Reading, Reading, United Kingdom
| | - Jyoti Khadake
- NIHR Cambridge BioResource, Cambridge University and Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK
| | - Eleanor Mawbey-Adamson
- NIHR Cambridge BioResource, Cambridge University and Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK
| | - Nadia Litterman
- 23andMe Inc., 899 West Evelyn Ave, Mountain View, California 94041, USA
| | - Jouke-Jan Hottenga
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands,EMGO+ Institute for Health and Care Research, VU Medical Center, Amsterdam, the Netherlands.,Neuroscience Campus Amsterdam, Vrije Universiteit, Amsterdam, the Netherlands
| | - Gitta Lubke
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands,Department of Psychology, University of Notre Dame, United States
| | - Dorret I Boomsma
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
| | | | - Peter K Hatemi
- Political Science, Microbiology and Biochemistry, Pennsylvania State University
| | - Sarah E Medland
- QIMR Berghofer Medical Research Institute, Brisbane, Australia
| | - David A Hinds
- 23andMe Inc., 899 West Evelyn Ave, Mountain View, California 94041, USA
| | - Thomas Bourgeron
- CNRS UMR 3571: Genes, Synapses and Cognition, Institut Pasteur, Paris, France,Université Paris Diderot, Sorbonne Paris Cité, Human Genetics and Cognitive Functions, Paris, France,Institut Pasteur, 5-28 Rue du Dr Roux, 75015 Paris, France
| | - Simon Baron-Cohen
- Autism Research Centre, Department of Psychiatry, University of Cambridge, Cambridgeshire, United Kingdom,CLASS Clinic, Cambridgeshire and Peterborough NHS Foundation Trust (CPFT), Cambridgeshire, United Kingdom,Corresponding authors: Varun Warrier () and Simon Baron-Cohen (). Autism Research Centre, Douglas House, 18B Trumpington Road, Cambridge, CB2 8AH, United Kingdom. Telephone: 0044 (0) 1223 746057
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Huguet G, Schramm C, Douard E, Jiang L, Labbe A, Tihy F, Mathonnet G, Nizard S, Lemyre E, Mathieu A, Poline JB, Loth E, Toro R, Schumann G, Conrod P, Pausova Z, Greenwood C, Paus T, Bourgeron T, Jacquemont S. Measuring and Estimating the Effect Sizes of Copy Number Variants on General Intelligence in Community-Based Samples. JAMA Psychiatry 2018; 75:447-457. [PMID: 29562078 PMCID: PMC5875373 DOI: 10.1001/jamapsychiatry.2018.0039] [Citation(s) in RCA: 59] [Impact Index Per Article: 9.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
IMPORTANCE; Copy number variants (CNVs) classified as pathogenic are identified in 10% to 15% of patients referred for neurodevelopmental disorders. However, their effect sizes on cognitive traits measured as a continuum remain mostly unknown because most of them are too rare to be studied individually using association studies. OBJECTIVE To measure and estimate the effect sizes of recurrent and nonrecurrent CNVs on IQ. DESIGN, SETTING, AND PARTICIPANTS This study identified all CNVs that were 50 kilobases (kb) or larger in 2 general population cohorts (the IMAGEN project and the Saguenay Youth Study) with measures of IQ. Linear regressions, including functional annotations of genes included in CNVs, were used to identify features to explain their association with IQ. Validation was performed using intraclass correlation that compared IQ estimated by the model with empirical data. MAIN OUTCOMES AND MEASURES Performance IQ (PIQ), verbal IQ (VIQ), and frequency of de novo CNV events. RESULTS The study included 2090 European adolescents from the IMAGEN study and 1983 children and parents from the Saguenay Youth Study. Of these, genotyping was performed on 1804 individuals from IMAGEN and 977 adolescents, 445 mothers, and 448 fathers (484 families) from the Saguenay Youth Study. We observed 4928 autosomal CNVs larger than 50 kb across both cohorts. For rare deletions, size, number of genes, and exons affect IQ, and each deleted gene is associated with a mean (SE) decrease in PIQ of 0.67 (0.19) points (P = 6 × 10-4); this is not so for rare duplications and frequent CNVs. Among 10 functional annotations, haploinsufficiency scores best explain the association of any deletions with PIQ with a mean (SE) decrease of 2.74 (0.68) points per unit of the probability of being loss-of-function intolerant (P = 8 × 10-5). Results are consistent across cohorts and unaffected by sensitivity analyses removing pathogenic CNVs. There is a 0.75 concordance (95% CI, 0.39-0.91) between the effect size on IQ estimated by our model and IQ loss calculated in previous studies of 15 recurrent CNVs. There is a close association between effect size on IQ and the frequency at which deletions occur de novo (odds ratio, 0.86; 95% CI, 0.84-0.87; P = 2.7 × 10-88). There is a 0.76 concordance (95% CI, 0.41-0.91) between de novo frequency estimated by the model and calculated using data from the DECIPHER database. CONCLUSIONS AND RELEVANCE Models trained on nonpathogenic deletions in the general population reliably estimate the effect size of pathogenic deletions and suggest omnigenic associations of haploinsufficiency with IQ. This represents a new framework to study variants too rare to perform individual association studies and can help estimate the cognitive effect of undocumented deletions in the neurodevelopmental clinic.
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Affiliation(s)
- Guillaume Huguet
- Department of Pediatrics, Université de Montréal, Montreal, Quebec, Canada,Center Hospitalier Universitaire Sainte-Justine Research Center, Montreal, Quebec, Canada
| | - Catherine Schramm
- Department of Pediatrics, Université de Montréal, Montreal, Quebec, Canada,Center Hospitalier Universitaire Sainte-Justine Research Center, Montreal, Quebec, Canada,Lady Davis Institute for Medical Research, Jewish General Hospital, Montreal, Quebec, Canada
| | - Elise Douard
- Department of Pediatrics, Université de Montréal, Montreal, Quebec, Canada,Center Hospitalier Universitaire Sainte-Justine Research Center, Montreal, Quebec, Canada
| | - Lai Jiang
- Lady Davis Institute for Medical Research, Jewish General Hospital, Montreal, Quebec, Canada
| | - Aurélie Labbe
- Département de Sciences de la Décision, HEC Montreal, Montreal, Quebec, Canada
| | - Frédérique Tihy
- Department of Pediatrics, Université de Montréal, Montreal, Quebec, Canada,Center Hospitalier Universitaire Sainte-Justine Research Center, Montreal, Quebec, Canada
| | - Géraldine Mathonnet
- Department of Pediatrics, Université de Montréal, Montreal, Quebec, Canada,Center Hospitalier Universitaire Sainte-Justine Research Center, Montreal, Quebec, Canada
| | - Sonia Nizard
- Department of Pediatrics, Université de Montréal, Montreal, Quebec, Canada,Center Hospitalier Universitaire Sainte-Justine Research Center, Montreal, Quebec, Canada
| | - Emmanuelle Lemyre
- Department of Pediatrics, Université de Montréal, Montreal, Quebec, Canada,Center Hospitalier Universitaire Sainte-Justine Research Center, Montreal, Quebec, Canada
| | - Alexandre Mathieu
- Department of Neurosciences, Human Genetics and Cognitive Functions, Institut Pasteur, Paris, France,Centre National de la Recherche Scientifique Genes, Synapses and Cognition Laboratory, Institut Pasteur, Paris, France
| | | | - Eva Loth
- Institute of Psychiatry, Psychology, and Neuroscience, King’s College London, London, England
| | - Roberto Toro
- Department of Neurosciences, Human Genetics and Cognitive Functions, Institut Pasteur, Paris, France,Centre National de la Recherche Scientifique Genes, Synapses and Cognition Laboratory, Institut Pasteur, Paris, France
| | - Gunter Schumann
- Institute of Psychiatry, Psychology, and Neuroscience, King’s College London, London, England
| | - Patricia Conrod
- Department of Pediatrics, Université de Montréal, Montreal, Quebec, Canada,Center Hospitalier Universitaire Sainte-Justine Research Center, Montreal, Quebec, Canada,Institute of Psychiatry, Psychology, and Neuroscience, King’s College London, London, England
| | - Zdenka Pausova
- The Hospital for Sick Children, University of Toronto, Toronto, Ontario, Canada
| | - Celia Greenwood
- Lady Davis Institute for Medical Research, Jewish General Hospital, Montreal, Quebec, Canada,Departments of Human Genetics and Oncology, McGill University, Montreal, Quebec, Canada
| | - Tomas Paus
- Rotman Research Institute, Baycrest, Toronto, Ontario, Canada,Departments of Psychology and Psychiatry, University of Toronto, Toronto, Ontario, Canada,Child Mind Institute, New York, New York
| | - Thomas Bourgeron
- Department of Neurosciences, Human Genetics and Cognitive Functions, Institut Pasteur, Paris, France,Centre National de la Recherche Scientifique Genes, Synapses and Cognition Laboratory, Institut Pasteur, Paris, France,Human Genetics and Cognitive Functions, University Paris Diderot, Sorbonne Paris Cité, Paris, France
| | - Sébastien Jacquemont
- Department of Pediatrics, Université de Montréal, Montreal, Quebec, Canada,Center Hospitalier Universitaire Sainte-Justine Research Center, Montreal, Quebec, Canada
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Traut N, Beggiato A, Bourgeron T, Delorme R, Rondi-Reig L, Paradis AL, Toro R. Cerebellar Volume in Autism: Literature Meta-analysis and Analysis of the Autism Brain Imaging Data Exchange Cohort. Biol Psychiatry 2018; 83:579-588. [PMID: 29146048 DOI: 10.1016/j.biopsych.2017.09.029] [Citation(s) in RCA: 45] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/27/2017] [Revised: 09/13/2017] [Accepted: 09/27/2017] [Indexed: 11/24/2022]
Abstract
BACKGROUND The neuroanatomical bases of autism spectrum disorder remain largely unknown. Among the most widely discussed candidate endophenotypes, differences in cerebellar volume have been often reported as statistically significant. METHODS We aimed at objectifying this possible alteration by performing a systematic meta-analysis of the literature and an analysis of the ABIDE (Autism Brain Imaging Data Exchange) cohort. Our meta-analysis sought to determine a combined effect size of autism spectrum disorder diagnosis on different measures of the cerebellar anatomy as well as the effect of possible factors of variability across studies. We then analyzed the cerebellar volume of 328 patients and 353 control subjects from the ABIDE project. RESULTS The meta-analysis of the literature suggested a weak but significant association between autism spectrum disorder diagnosis and increased cerebellar volume (p = .049, uncorrected), but the analysis of ABIDE did not show any relationship. The studies meta-analyzed were generally underpowered; however, the number of statistically significant findings was larger than expected. CONCLUSIONS Although we could not provide a conclusive explanation for this excess of significant findings, our analyses would suggest publication bias as a possible reason. Finally, age, sex, and IQ were important sources of cerebellar volume variability, although independent of autism diagnosis.
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Affiliation(s)
- Nicolas Traut
- Unité de Génétique Humaine et Fonctions Cognitives, Département de Neuroscience, Institut Pasteur, Paris, France; Neuroscience Paris Seine, Institut de Biologie Paris Seine, Centre National de la Recherche Scientifique, Institut National de la Santé et de la Recherche Médicale, Université Pierre et Marie Curie, Sorbonne Universités, Paris, France; Genes, Synapses and Cognition, Unité Mixte de Recherche 3571, Centre National de la Recherche Scientifique, Institut Pasteur, Paris, France; Human Genetics and Cognitive Functions, University Paris Diderot, Sorbonne Paris Cité, Paris, France.
| | - Anita Beggiato
- Unité de Génétique Humaine et Fonctions Cognitives, Département de Neuroscience, Institut Pasteur, Paris, France; Département de Psychiatrie de l'Enfant et de l'Adolescent, Hôpital Robert Debré, L'Assistance Publique-Hôpitaux de Paris, Paris, France
| | - Thomas Bourgeron
- Unité de Génétique Humaine et Fonctions Cognitives, Département de Neuroscience, Institut Pasteur, Paris, France; Genes, Synapses and Cognition, Unité Mixte de Recherche 3571, Centre National de la Recherche Scientifique, Institut Pasteur, Paris, France; Human Genetics and Cognitive Functions, University Paris Diderot, Sorbonne Paris Cité, Paris, France; Foundation Fondamentale, Créteil, France
| | - Richard Delorme
- Unité de Génétique Humaine et Fonctions Cognitives, Département de Neuroscience, Institut Pasteur, Paris, France; Département de Psychiatrie de l'Enfant et de l'Adolescent, Hôpital Robert Debré, L'Assistance Publique-Hôpitaux de Paris, Paris, France
| | - Laure Rondi-Reig
- Neuroscience Paris Seine, Institut de Biologie Paris Seine, Centre National de la Recherche Scientifique, Institut National de la Santé et de la Recherche Médicale, Université Pierre et Marie Curie, Sorbonne Universités, Paris, France
| | - Anne-Lise Paradis
- Neuroscience Paris Seine, Institut de Biologie Paris Seine, Centre National de la Recherche Scientifique, Institut National de la Santé et de la Recherche Médicale, Université Pierre et Marie Curie, Sorbonne Universités, Paris, France
| | - Roberto Toro
- Unité de Génétique Humaine et Fonctions Cognitives, Département de Neuroscience, Institut Pasteur, Paris, France; Genes, Synapses and Cognition, Unité Mixte de Recherche 3571, Centre National de la Recherche Scientifique, Institut Pasteur, Paris, France; Human Genetics and Cognitive Functions, University Paris Diderot, Sorbonne Paris Cité, Paris, France.
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Toro R, Bakker R, Delzescaux T, Evans A, Tiesinga P. FIIND: Ferret Interactive Integrated Neurodevelopment Atlas. RIO 2018. [DOI: 10.3897/rio.4.e25312] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
Abstract
The first days after birth in ferrets provide a privileged view of the development of a complex mammalian brain. Unlike mice, ferrets develop a rich pattern of deep neocortical folds and cortico- cortical connections. Unlike humans and other primates, whose brains are well differentiated and folded at birth, ferrets are born with a very immature and completely smooth neocortex: folds, neocortical regionalisation and cortico-cortical connectivity develop in ferrets during the first postnatal days. After a period of fast neocortical expansion, during which brain volume increases by up to a factor of 4 in 2 weeks, the ferret brain reaches its adult volume at about 6 weeks of age. Ferrets could thus become a major animal model to investigate the neurobiological correlates of the phenomena observed in human neuroimaging. Many of these phenomena, such as the relationship between brain folding, cortico-cortical connectivity and neocortical regionalisation cannot be investigated in mice, but could be investigated in ferrets.
Our aim is to provide the research community with a detailed description of the development of a complex brain, necessary to better understand the nature of human neuroimaging data, create models of brain development, or analyse the relationship between multiple spatial scales. We have already started a project to constitute an open, collaborative atlas of ferret brain development, integrating multi-modal and multi-scale data. We have acquired data for 28 ferrets (4 animals per time point from P0 to adults), using high-resolution MRI and diffusion tensor imaging (DTI). We have developed an open-source pipeline to segment and produce – online – 3D reconstructions of brain MRI data.
We propose to process the brains of 16 of our specimens (from P0 to P16) using high-throughput 3D histology, staining for cytoarchitectonic landmarks, neuronal progenitors and neurogenesis. This would allow us to relate the MRI data that we have already acquired with multi-dimensional cell-scale information. Brains will be sectioned at 25 μm, stained, scanned at 0.25 μm of resolution, and processed for real-time multi-scale visualisation. We will extend our current web-platform to integrate an interactive multi-scale visualisation of the data. Using our combined expertise in computational neuroanatomy, multi-modal neuroimaging, neuroinformatics, and the development of inter-species atlases, we propose to build an open-source web platform to allow the collaborative, online, creation of atlases of the development of the ferret brain. The web platform will allow researchers to access and visualise interactively the MRI and histology data. It will also allow researchers to create collaborative, human curated, 3D segmentations of brain structures, as well as vectorial atlases. Our work will provide a first integrated atlas of ferret brain development, and the basis for an open platform for the creation of collaborative multi-modal, multi-scale, multi-species atlases.
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