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Kang K, Seidlitz J, Bethlehem RA, Xiong J, Jones MT, Mehta K, Keller AS, Tao R, Randolph A, Larsen B, Tervo-Clemmens B, Feczko E, Dominguez OM, Nelson S, Schildcrout J, Fair D, Satterthwaite TD, Alexander-Bloch A, Vandekar S. Study design features that improve effect sizes in cross-sectional and longitudinal brain-wide association studies. bioRxiv 2024:2023.05.29.542742. [PMID: 37398345 PMCID: PMC10312450 DOI: 10.1101/2023.05.29.542742] [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] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/04/2023]
Abstract
Brain-wide association studies (BWAS) are a fundamental tool in discovering brain-behavior associations. Several recent studies showed that thousands of study participants are required to improve the replicability of BWAS because actual effect sizes are much smaller than those reported in smaller studies. Here, we perform analyses and meta-analyses of a robust effect size index (RESI) using 63 longitudinal and cross-sectional magnetic resonance imaging studies from the Lifespan Brain Chart Consortium (77,695 total scans) to demonstrate that optimizing study design is critical for improving standardized effect sizes and replicability in BWAS. A meta-analysis of brain volume associations with age indicates that BWAS with larger covariate variance have larger effect size estimates and that the longitudinal studies we examined have systematically larger standardized effect sizes than cross-sectional studies. We propose a cross-sectional RESI to adjust for the systematic difference in effect sizes between cross-sectional and longitudinal studies that allows investigators to quantify the benefit of conducting their study longitudinally. Analyzing age effects on global and regional brain measures from the United Kingdom Biobank and the Alzheimer's Disease Neuroimaging Initiative, we show that modifying longitudinal study design through sampling schemes to increase between-subject variability and adding a single additional longitudinal measurement per subject can improve effect sizes. However, evaluating these longitudinal sampling schemes on cognitive, psychopathology, and demographic associations with structural and functional brain outcome measures in the Adolescent Brain and Cognitive Development dataset shows that commonly used longitudinal models can, counterintuitively, reduce effect sizes. We demonstrate that the benefit of conducting longitudinal studies depends on the strengths of the between- and within-subject associations of the brain and non-brain measures. Explicitly modeling between- and within-subject effects avoids conflating the effects and allows optimizing effect sizes for them separately. These findings underscore the importance of considering study design features to improve the replicability of BWAS.
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Affiliation(s)
- Kaidi Kang
- Department of Biostatistics, Vanderbilt University Medical Center
| | - Jakob Seidlitz
- Department of Child and Adolescent Psychiatry and Behavioral Sciences, The Children’s Hospital of Philadelphia
- Department of Psychiatry, University of Pennsylvania
- Lifespan Brain Institute of The Children’s Hospital of Philadelphia and Penn Medicine
| | | | - Jiangmei Xiong
- Department of Biostatistics, Vanderbilt University Medical Center
| | - Megan T. Jones
- Department of Biostatistics, Vanderbilt University Medical Center
| | - Kahini Mehta
- Department of Psychiatry, University of Pennsylvania
- Lifespan Brain Institute of The Children’s Hospital of Philadelphia and Penn Medicine
- Penn Lifespan Informatics and Neuroimaging Center (PennLINC), Perelman School of Medicine, University of Pennsylvania
| | - Arielle S. Keller
- Department of Psychiatry, University of Pennsylvania
- Lifespan Brain Institute of The Children’s Hospital of Philadelphia and Penn Medicine
- Penn Lifespan Informatics and Neuroimaging Center (PennLINC), Perelman School of Medicine, University of Pennsylvania
| | - Ran Tao
- Department of Biostatistics, Vanderbilt University Medical Center
| | - Anita Randolph
- Department of Pediatrics, University of Minnesota Medical School
| | - Bart Larsen
- Department of Pediatrics, University of Minnesota Medical School
| | - Brenden Tervo-Clemmens
- Department of Department of Psychiatry & Behavioral Sciences, University of Minnesota Medical School
| | - Eric Feczko
- Department of Pediatrics, University of Minnesota Medical School
| | | | - Steve Nelson
- Department of Pediatrics, University of Minnesota Medical School
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | - Damien Fair
- Department of Pediatrics, University of Minnesota Medical School
| | - Theodore D. Satterthwaite
- Department of Psychiatry, University of Pennsylvania
- Lifespan Brain Institute of The Children’s Hospital of Philadelphia and Penn Medicine
- Penn Lifespan Informatics and Neuroimaging Center (PennLINC), Perelman School of Medicine, University of Pennsylvania
| | - Aaron Alexander-Bloch
- Department of Child and Adolescent Psychiatry and Behavioral Sciences, The Children’s Hospital of Philadelphia
- Department of Psychiatry, University of Pennsylvania
- Lifespan Brain Institute of The Children’s Hospital of Philadelphia and Penn Medicine
| | - Simon Vandekar
- Department of Biostatistics, Vanderbilt University Medical Center
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Ball G, Oldham S, Kyriakopoulou V, Williams LZJ, Karolis V, Price A, Hutter J, Seal ML, Alexander-Bloch A, Hajnal JV, Edwards AD, Robinson EC, Seidlitz J. Molecular signatures of cortical expansion in the human fetal brain. bioRxiv 2024:2024.02.13.580198. [PMID: 38405710 PMCID: PMC10888819 DOI: 10.1101/2024.02.13.580198] [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] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/27/2024]
Abstract
The third trimester of human gestation is characterised by rapid increases in brain volume and cortical surface area. A growing catalogue of cells in the prenatal brain has revealed remarkable molecular diversity across cortical areas.1,2 Despite this, little is known about how this translates into the patterns of differential cortical expansion observed in humans during the latter stages of gestation. Here we present a new resource, μBrain, to facilitate knowledge translation between molecular and anatomical descriptions of the prenatal developing brain. Built using generative artificial intelligence, μBrain is a three-dimensional cellular-resolution digital atlas combining publicly-available serial sections of the postmortem human brain at 21 weeks gestation3 with bulk tissue microarray data, sampled across 29 cortical regions and 5 transient tissue zones.4 Using μBrain, we evaluate the molecular signatures of preferentially-expanded cortical regions during human gestation, quantified in utero using magnetic resonance imaging (MRI). We find that differences in the rates of expansion across cortical areas during gestation respect anatomical and evolutionary boundaries between cortical types5 and are founded upon extended periods of upper-layer cortical neuron migration that continue beyond mid-gestation. We identify a set of genes that are upregulated from mid-gestation and highly expressed in rapidly expanding neocortex, which are implicated in genetic disorders with cognitive sequelae. Our findings demonstrate a spatial coupling between areal differences in the timing of neurogenesis and rates of expansion across the neocortical sheet during the prenatal epoch. The μBrain atlas is available from: https://garedaba.github.io/micro-brain/ and provides a new tool to comprehensively map early brain development across domains, model systems and resolution scales.
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Affiliation(s)
- G Ball
- Developmental Imaging, Murdoch Children's Research Institute, Melbourne, Australia
- Department of Paediatrics, University of Melbourne, Melbourne, Australia
| | - S Oldham
- Developmental Imaging, Murdoch Children's Research Institute, Melbourne, Australia
| | - V Kyriakopoulou
- Centre for the Developing Brain, King's College London, London, UK
- School of Biomedical Engineering & Imaging Science, King's College London, London, UK
| | - L Z J Williams
- Centre for the Developing Brain, King's College London, London, UK
- School of Biomedical Engineering & Imaging Science, King's College London, London, UK
| | - V Karolis
- Centre for the Developing Brain, King's College London, London, UK
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - A Price
- Centre for the Developing Brain, King's College London, London, UK
- School of Biomedical Engineering & Imaging Science, King's College London, London, UK
| | - J Hutter
- Centre for the Developing Brain, King's College London, London, UK
- School of Biomedical Engineering & Imaging Science, King's College London, London, UK
| | - M L Seal
- Developmental Imaging, Murdoch Children's Research Institute, Melbourne, Australia
- Department of Paediatrics, University of Melbourne, Melbourne, Australia
| | - A Alexander-Bloch
- Department of Child and Adolescent Psychiatry and Behavioral Sciences, The Children's Hospital of Philadelphia, Philadelphia, PA
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA
- Lifespan Brain Institute, The Children's Hospital of Philadelphia and Penn Medicine, Philadelphia, PA
- Institute of Translational Medicine and Therapeutics, University of Pennsylvania, Philadelphia, PA
| | - J V Hajnal
- Centre for the Developing Brain, King's College London, London, UK
- School of Biomedical Engineering & Imaging Science, King's College London, London, UK
| | - A D Edwards
- Centre for the Developing Brain, King's College London, London, UK
- School of Biomedical Engineering & Imaging Science, King's College London, London, UK
| | - E C Robinson
- Centre for the Developing Brain, King's College London, London, UK
- School of Biomedical Engineering & Imaging Science, King's College London, London, UK
| | - J Seidlitz
- Department of Child and Adolescent Psychiatry and Behavioral Sciences, The Children's Hospital of Philadelphia, Philadelphia, PA
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA
- Lifespan Brain Institute, The Children's Hospital of Philadelphia and Penn Medicine, Philadelphia, PA
- Institute of Translational Medicine and Therapeutics, University of Pennsylvania, Philadelphia, PA
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3
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Wagstyl K, Adler S, Seidlitz J, Vandekar S, Mallard TT, Dear R, DeCasien AR, Satterthwaite TD, Liu S, Vértes PE, Shinohara RT, Alexander-Bloch A, Geschwind DH, Raznahan A. Transcriptional cartography integrates multiscale biology of the human cortex. eLife 2024; 12:RP86933. [PMID: 38324465 PMCID: PMC10945526 DOI: 10.7554/elife.86933] [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] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/09/2024] Open
Abstract
The cerebral cortex underlies many of our unique strengths and vulnerabilities, but efforts to understand human cortical organization are challenged by reliance on incompatible measurement methods at different spatial scales. Macroscale features such as cortical folding and functional activation are accessed through spatially dense neuroimaging maps, whereas microscale cellular and molecular features are typically measured with sparse postmortem sampling. Here, we integrate these distinct windows on brain organization by building upon existing postmortem data to impute, validate, and analyze a library of spatially dense neuroimaging-like maps of human cortical gene expression. These maps allow spatially unbiased discovery of cortical zones with extreme transcriptional profiles or unusually rapid transcriptional change which index distinct microstructure and predict neuroimaging measures of cortical folding and functional activation. Modules of spatially coexpressed genes define a family of canonical expression maps that integrate diverse spatial scales and temporal epochs of human brain organization - ranging from protein-protein interactions to large-scale systems for cognitive processing. These module maps also parse neuropsychiatric risk genes into subsets which tag distinct cyto-laminar features and differentially predict the location of altered cortical anatomy and gene expression in patients. Taken together, the methods, resources, and findings described here advance our understanding of human cortical organization and offer flexible bridges to connect scientific fields operating at different spatial scales of human brain research.
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Affiliation(s)
- Konrad Wagstyl
- Wellcome Centre for Human Neuroimaging, University College LondonLondonUnited Kingdom
| | - Sophie Adler
- UCL Great Ormond Street Institute for Child HealthHolbornUnited Kingdom
| | - Jakob Seidlitz
- Department of Psychiatry, University of PennsylvaniaPhiladelphiaUnited States
- Department of Child and Adolescent Psychiatry and Behavioral Science, The Children's Hospital of PhiladelphiaPhiladelphiaUnited States
| | - Simon Vandekar
- Department of Biostatistics, Vanderbilt UniversityNashvilleUnited States
| | - Travis T Mallard
- Psychiatric and Neurodevelopmental Genetics Unit, Center for Genomic Medicine, Massachusetts General HospitalBostonUnited States
- Department of Psychiatry, Harvard Medical SchoolBostonUnited States
| | - Richard Dear
- Department of Psychiatry, University of CambridgeCambridgeUnited Kingdom
| | - Alex R DeCasien
- Section on Developmental Neurogenomics, Human Genetics Branch, National Institute of Mental HealthBethesdaUnited States
| | - Theodore D Satterthwaite
- Department of Psychiatry, University of PennsylvaniaPhiladelphiaUnited States
- Lifespan Informatics and Neuroimaging Center, University of Pennsylvania School of MedicinePhiladelphiaUnited States
| | - Siyuan Liu
- Section on Developmental Neurogenomics, Human Genetics Branch, National Institute of Mental HealthBethesdaUnited States
| | - Petra E Vértes
- Department of Psychiatry, University of CambridgeCambridgeUnited Kingdom
| | - Russell T Shinohara
- Penn Statistics in Imaging and Visualization Center, Department of Biostatistics, Epidemiology and Informatics, Perelman School of Medicine, University of PennsylvaniaPhiladelphiaUnited States
| | - Aaron Alexander-Bloch
- Department of Psychiatry, University of PennsylvaniaPhiladelphiaUnited States
- Department of Child and Adolescent Psychiatry and Behavioral Science, The Children's Hospital of PhiladelphiaPhiladelphiaUnited States
| | - Daniel H Geschwind
- Center for Autism Research and Treatment, Semel Institute, Program in Neurogenetics, Department of Neurology and Department of Human Genetics, David Geffen School of Medicine, University of California, Los AngelesLos AngelesUnited States
| | - Armin Raznahan
- Section on Developmental Neurogenomics, Human Genetics Branch, National Institute of Mental HealthBethesdaUnited States
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4
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Zhao K, Chen P, Alexander-Bloch A, Wei Y, Dyrba M, Yang F, Kang X, Wang D, Fan D, Ye S, Tang Y, Yao H, Zhou B, Lu J, Yu C, Wang P, Liao Z, Chen Y, Huang L, Zhang X, Han Y, Li S, Liu Y. A neuroimaging biomarker for Individual Brain-Related Abnormalities In Neurodegeneration (IBRAIN): a cross-sectional study. EClinicalMedicine 2023; 65:102276. [PMID: 37954904 PMCID: PMC10632687 DOI: 10.1016/j.eclinm.2023.102276] [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] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/19/2023] [Revised: 09/27/2023] [Accepted: 09/29/2023] [Indexed: 11/14/2023] Open
Abstract
Background Alzheimer's disease (AD) is a prevalent neurodegenerative disorder that poses a worldwide public health challenge. A neuroimaging biomarker would significantly improve early diagnosis and intervention, ultimately enhancing the quality of life for affected individuals and reducing the burden on healthcare systems. Methods Cross-sectional and longitudinal data (10,099 participants with 13,380 scans) from 12 independent datasets were used in the present study (this study was performed between September 1, 2021 and February 15, 2023). The Individual Brain-Related Abnormalities In Neurodegeneration (IBRAIN) score was developed via integrated regional- and network-based measures under an ensemble machine learning model based on structural MRI data. We systematically assessed whether IBRAIN could be a neuroimaging biomarker for AD. Findings IBRAIN accurately differentiated individuals with AD from NCs (AUC = 0.92) and other neurodegenerative diseases, including Frontotemporal dementia (FTD), Parkinson's disease (PD), Vascular dementia (VaD) and Amyotrophic Lateral Sclerosis (ALS) (AUC = 0.92). IBRAIN was significantly correlated to clinical measures and gene expression, enriched in immune process and protein metabolism. The IBRAIN score exhibited a significant ability to reveal the distinct progression of prodromal AD (i.e., Mild cognitive impairment, MCI) (Hazard Ratio (HR) = 6.52 [95% CI: 4.42∼9.62], p < 1 × 10-16), which offers similar powerful performance with Cerebrospinal Fluid (CSF) Aβ (HR = 3.78 [95% CI: 2.63∼5.43], p = 2.13 × 10-14) and CSF Tau (HR = 3.77 [95% CI: 2.64∼5.39], p = 9.53 × 10-15) based on the COX and Log-rank test. Notably, the IBRAIN shows comparable sensitivity (beta = -0.70, p < 1 × 10-16) in capturing longitudinal changes in individuals with conversion to AD than CSF Aβ (beta = -0.26, p = 4.40 × 10-9) and CSF Tau (beta = 0.12, p = 1.02 × 10-5). Interpretation Our findings suggested that IBRAIN is a biologically relevant, specific, and sensitive neuroimaging biomarker that can serve as a clinical measure to uncover prodromal AD progression. It has strong potential for application in future clinical practice and treatment trials. Funding Science and Technology Innovation 2030 Major Projects, the National Natural Science Foundation of China, Beijing Natural Science Funds, the Fundamental Research Funds for the CentralUniversity, and the Startup Funds for Talents at Beijing Normal University.
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Affiliation(s)
- Kun Zhao
- School of Artificial Intelligence, Beijing University of Posts and Telecommunications, Beijing, China
| | - Pindong Chen
- School of Artificial Intelligence, University of Chinese Academy of Sciences & Brainnetome Centre, Chinese Academy of Sciences, Beijing, China
| | - Aaron Alexander-Bloch
- Department of Psychiatry, University of Pennsylvania, Philadelphia, USA
- Department of Child and Adolescent Psychiatry and Behavioral Science, Children's Hospital of Philadelphia, Philadelphia, USA
| | - Yongbin Wei
- School of Artificial Intelligence, Beijing University of Posts and Telecommunications, Beijing, China
| | - Martin Dyrba
- German Centre for Neurodegenerative Diseases (DZNE), Rostock, Germany
| | - Fan Yang
- CAS Key Laboratory of Molecular Imaging, Institute of Automation, Beijing, China
| | - Xiaopeng Kang
- School of Artificial Intelligence, University of Chinese Academy of Sciences & Brainnetome Centre, Chinese Academy of Sciences, Beijing, China
| | - Dawei Wang
- Department of Radiology, Qilu Hospital of Shandong University, Ji'nan, China
| | - Dongsheng Fan
- Department of Neurology, Peking University Third Hospital, Beijing, China
- Key Laboratory for Neuroscience, National Health Commission/Ministry of Education, Peking University, Beijing, China
- Beijing Key Laboratory of Biomarker and Translational Research in Neurodegenerative Diseases, Beijing, China
| | - Shan Ye
- Department of Neurology, Peking University Third Hospital, Beijing, China
- Key Laboratory for Neuroscience, National Health Commission/Ministry of Education, Peking University, Beijing, China
- Beijing Key Laboratory of Biomarker and Translational Research in Neurodegenerative Diseases, Beijing, China
| | - Yi Tang
- Department of Neurology, Xuanwu Hospital of Capital Medical University, Beijing, China
| | - Hongxiang Yao
- Department of Radiology, The Second Medical Centre, National Clinical Research Centre for Geriatric Diseases, Chinese PLA General Hospital, Beijing, China
| | - Bo Zhou
- Department of Neurology, The Second Medical Centre, National Clinical Research Centre for Geriatric Diseases, Chinese PLA General Hospital, Beijing, China
| | - Jie Lu
- Department of Radiology, Xuanwu Hospital of Capital Medical University, Beijing, China
| | - Chunshui Yu
- Department of Radiology, Tianjin Medical University General Hospital, Tianjin, China
| | - Pan Wang
- Department of Neurology, Tianjin Huanhu Hospital, Tianjin, China
| | - Zhengluan Liao
- Department of Psychiatry, People's Hospital of Hangzhou Medical College, Zhejiang Provincial People's Hospital, Hangzhou, China
| | - Yan Chen
- Department of Psychiatry, People's Hospital of Hangzhou Medical College, Zhejiang Provincial People's Hospital, Hangzhou, China
| | - Longjian Huang
- Affiliated Hospital of Youjiang Medical University for Nationalities, Baise, China
| | - Xi Zhang
- Department of Neurology, The Second Medical Centre, National Clinical Research Centre for Geriatric Diseases, Chinese PLA General Hospital, Beijing, China
| | - Ying Han
- Department of Neurology, Xuanwu Hospital of Capital Medical University, Beijing, China
- National Clinical Research Centre for Geriatric Disorders, Beijing, China
- Centre of Alzheimer's Disease, Beijing Institute for Brain Disorders, Beijing, China
| | - Shuyu Li
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
| | - Yong Liu
- School of Artificial Intelligence, Beijing University of Posts and Telecommunications, Beijing, China
- School of Artificial Intelligence, University of Chinese Academy of Sciences & Brainnetome Centre, Chinese Academy of Sciences, Beijing, China
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5
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Mollon J, Schultz LM, Huguet G, Knowles EEM, Mathias SR, Rodrigue A, Alexander-Bloch A, Saci Z, Jean-Louis M, Kumar K, Douard E, Almasy L, Jacquemont S, Glahn DC. Impact of Copy Number Variants and Polygenic Risk Scores on Psychopathology in the UK Biobank. Biol Psychiatry 2023; 94:591-600. [PMID: 36764568 PMCID: PMC10409883 DOI: 10.1016/j.biopsych.2023.01.028] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/06/2022] [Revised: 01/31/2023] [Accepted: 01/31/2023] [Indexed: 02/11/2023]
Abstract
BACKGROUND Our understanding of the impact of copy number variants (CNVs) on psychopathology and their joint influence with polygenic risk scores (PRSs) remains limited. METHODS The UK Biobank recruited 502,534 individuals ages 37 to 73 years living in the United Kingdom between 2006 and 2010. After quality control, genotype data from 459,855 individuals were available for CNV calling. A total of 61 commonly studied recurrent neuropsychiatric CNVs were selected for analyses and examined individually and in aggregate (any CNV, deletion, or duplication). CNV risk scores were used to quantify intolerance of CNVs to haploinsufficiency. Major depressive disorder and generalized anxiety disorder PRSs were generated for White British individuals (N = 408,870). Mood/anxiety factor scores were generated using item-level questionnaire data (N = 501,289). RESULTS CNV carriers showed higher mood/anxiety scores than noncarriers, with the largest effects seen for intolerant deletions. A total of 11 individual deletions and 8 duplications were associated with higher mood/anxiety. Carriers of the 9p24.3 (DMRT1) duplication showed lower mood/anxiety. Associations remained significant for most CNVs when excluding individuals with psychiatric diagnoses. Nominally significant CNV × PRS interactions provided preliminary evidence that associations between select individual CNVs, but not CNVs in aggregate, and mood/anxiety may be modulated by PRSs. CONCLUSIONS CNVs associated with risk for psychiatric disorders showed small to large effects on dimensional mood/anxiety scores in a general population cohort, even when excluding individuals with psychiatric diagnoses. CNV × PRS interactions showed that associations between select CNVs and mood/anxiety may be modulated by PRSs.
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Affiliation(s)
- Josephine Mollon
- Department of Psychiatry, Boston Children's Hospital, Harvard Medical School, Boston, Massachusetts.
| | - Laura M Schultz
- Department of Biomedical and Health Informatics, The Children's Hospital of Philadelphia, Philadelphia, Pennsylvania
| | - Guillaume Huguet
- Department of Pediatrics, Université de Montréal, Montreal, Quebec, Canada; Department of Pediatrics, Center Hospitalier Universitaire Sainte-Justine Research Center, Montreal, Quebec, Canada
| | - Emma E M Knowles
- Department of Psychiatry, Boston Children's Hospital, Harvard Medical School, Boston, Massachusetts
| | - Samuel R Mathias
- Department of Psychiatry, Boston Children's Hospital, Harvard Medical School, Boston, Massachusetts
| | - Amanda Rodrigue
- Department of Psychiatry, Boston Children's Hospital, Harvard Medical School, Boston, Massachusetts
| | - Aaron Alexander-Bloch
- Department of Child and Adolescent Psychiatry and Behavioral Science, The Children's Hospital of Philadelphia, Philadelphia, Pennsylvania; Lifespan Brain Institute, The Children's Hospital of Philadelphia and Penn Medicine, University of Pennsylvania, Philadelphia, Pennsylvania; Neurodevelopment and Psychosis Section, Department of Psychiatry, University of Pennsylvania, Philadelphia, Pennsylvania
| | - Zohra Saci
- Department of Pediatrics, Center Hospitalier Universitaire Sainte-Justine Research Center, Montreal, Quebec, Canada
| | - Martineau Jean-Louis
- Department of Pediatrics, Center Hospitalier Universitaire Sainte-Justine Research Center, Montreal, Quebec, Canada
| | - Kuldeep Kumar
- Department of Pediatrics, Center Hospitalier Universitaire Sainte-Justine Research Center, Montreal, Quebec, Canada
| | - Elise Douard
- Department of Pediatrics, Université de Montréal, Montreal, Quebec, Canada; Department of Pediatrics, Center Hospitalier Universitaire Sainte-Justine Research Center, Montreal, Quebec, Canada
| | - Laura Almasy
- Department of Biomedical and Health Informatics, The Children's Hospital of Philadelphia, Philadelphia, Pennsylvania; Department of Genetics, Perelman School of Medicine, Penn-CHOP Lifespan Brain Institute, University of Pennsylvania, Philadelphia, Pennsylvania
| | - Sebastien Jacquemont
- Department of Pediatrics, Université de Montréal, Montreal, Quebec, Canada; Department of Pediatrics, Center Hospitalier Universitaire Sainte-Justine Research Center, Montreal, Quebec, Canada
| | - David C Glahn
- Department of Psychiatry, Boston Children's Hospital, Harvard Medical School, Boston, Massachusetts; Olin Neuropsychiatry Research Center, Institute of Living, Hartford, Connecticut
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6
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Schabdach JM, Schmitt JE, Sotardi S, Vossough A, Andronikou S, Roberts TP, Huang H, Padmanabhan V, Ortiz-Rosa A, Gardner M, Covitz S, Bedford SA, Mandal AS, Chaiyachati BH, White SR, Bullmore E, Bethlehem RAI, Shinohara RT, Billot B, Iglesias JE, Ghosh S, Gur RE, Satterthwaite TD, Roalf D, Seidlitz J, Alexander-Bloch A. Brain Growth Charts for Quantitative Analysis of Pediatric Clinical Brain MRI Scans with Limited Imaging Pathology. Radiology 2023; 309:e230096. [PMID: 37906015 PMCID: PMC10623207 DOI: 10.1148/radiol.230096] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2023] [Revised: 08/21/2023] [Accepted: 09/12/2023] [Indexed: 11/02/2023]
Abstract
Background Clinically acquired brain MRI scans represent a valuable but underused resource for investigating neurodevelopment due to their technical heterogeneity and lack of appropriate controls. These barriers have curtailed retrospective studies of clinical brain MRI scans compared with more costly prospectively acquired research-quality brain MRI scans. Purpose To provide a benchmark for neuroanatomic variability in clinically acquired brain MRI scans with limited imaging pathology (SLIPs) and to evaluate if growth charts from curated clinical MRI scans differed from research-quality MRI scans or were influenced by clinical indication for the scan. Materials and Methods In this secondary analysis of preexisting data, clinical brain MRI SLIPs from an urban pediatric health care system (individuals aged ≤22 years) were scanned across nine 3.0-T MRI scanners. The curation process included manual review of signed radiology reports and automated and manual quality review of images without gross pathology. Global and regional volumetric imaging phenotypes were measured using two image segmentation pipelines, and clinical brain growth charts were quantitatively compared with charts derived from a large set of research controls in the same age range by means of Pearson correlation and age at peak volume. Results The curated clinical data set included 532 patients (277 male; median age, 10 years [IQR, 5-14 years]; age range, 28 days after birth to 22 years) scanned between 2005 and 2020. Clinical brain growth charts were highly correlated with growth charts derived from research data sets (22 studies, 8346 individuals [4947 male]; age range, 152 days after birth to 22 years) in terms of normative developmental trajectories predicted by the models (median r = 0.979). Conclusion The clinical indication of the scans did not significantly bias the output of clinical brain charts. Brain growth charts derived from clinical controls with limited imaging pathology were highly correlated with brain charts from research controls, suggesting the potential of curated clinical MRI scans to supplement research data sets. © RSNA, 2023 Supplemental material is available for this article. See also the editorial by Ertl-Wagner and Pai in this issue.
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Affiliation(s)
- Jenna M. Schabdach
- From the Lifespan Brain Institute (LiBI) of the Children’s
Hospital of Philadelphia (CHOP) and Penn Medicine, Philadelphia, Pa (J.M.S.,
A.O.R., M.G., A.S.M., B.H.C., R.E.G., T.D.S., J.S., A.A.B.); Department of Child
and Adolescent Psychiatry and Behavioral Science (J.M.S., J.S., A.A.B.),
Department of Radiology (S.S., A.V., S.A., T.P.R., H.H.), PolicyLab and Clinical
Futures, CHOP Research Institute (B.H.C.), and Department of Biomedical and
Health Informatics (J.E.S., S.S., V.P.), Children’s Hospital of
Philadelphia, Philadelphia, Pa; Department of Psychiatry (J.E.S., R.E.G.,
T.D.S., D.R., J.S., A.A.B.), Department of Radiology (J.E.S., S.S., A.V., S.A.,
T.P.R., H.H.), Lifespan Informatics and Neuroimaging Center (PennLINC),
Department of Psychiatry (S.C., T.D.S.), and Department of Pediatrics (B.H.C.),
Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pa;
Departments of Psychiatry (S.A.B., S.R.W., E.B., R.A.I.B.) and Psychology
(R.A.I.B.), University of Cambridge, Cambridge, United Kingdom; Center for
Biomedical Image Computation and Analytics (R.T.S.), Penn Statistics in Imaging
and Visualization Center, Department of Biostatistics, Epidemiology and
Informatics (R.T.S.), and Lifespan Brain Chart Consortium (S.R.W., E.B.,
R.A.I.B., R.T.S., T.D.S., J.S., A.A.B.), University of Pennsylvania,
Philadelphia, Pa; Centre for Medical Image Computing, Department of Medical
Physics and Biomedical Engineering, University College London, London, United
Kingdom (B.B., J.E.I.); Martinos Center for Biomedical Imaging and Department of
Radiology (J.E.I.) and Department of Otolaryngology–Head and Neck Surgery
(S.G.), Massachusetts General Hospital and Harvard Medical School, Boston, Mass;
and McGovern Institute for Brain Research (S.G.) and Computer Science &
Artificial Intelligence Laboratory (B.B., J.E.I.), Massachusetts Institute of
Technology, Cambridge, Mass
| | - J. Eric Schmitt
- From the Lifespan Brain Institute (LiBI) of the Children’s
Hospital of Philadelphia (CHOP) and Penn Medicine, Philadelphia, Pa (J.M.S.,
A.O.R., M.G., A.S.M., B.H.C., R.E.G., T.D.S., J.S., A.A.B.); Department of Child
and Adolescent Psychiatry and Behavioral Science (J.M.S., J.S., A.A.B.),
Department of Radiology (S.S., A.V., S.A., T.P.R., H.H.), PolicyLab and Clinical
Futures, CHOP Research Institute (B.H.C.), and Department of Biomedical and
Health Informatics (J.E.S., S.S., V.P.), Children’s Hospital of
Philadelphia, Philadelphia, Pa; Department of Psychiatry (J.E.S., R.E.G.,
T.D.S., D.R., J.S., A.A.B.), Department of Radiology (J.E.S., S.S., A.V., S.A.,
T.P.R., H.H.), Lifespan Informatics and Neuroimaging Center (PennLINC),
Department of Psychiatry (S.C., T.D.S.), and Department of Pediatrics (B.H.C.),
Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pa;
Departments of Psychiatry (S.A.B., S.R.W., E.B., R.A.I.B.) and Psychology
(R.A.I.B.), University of Cambridge, Cambridge, United Kingdom; Center for
Biomedical Image Computation and Analytics (R.T.S.), Penn Statistics in Imaging
and Visualization Center, Department of Biostatistics, Epidemiology and
Informatics (R.T.S.), and Lifespan Brain Chart Consortium (S.R.W., E.B.,
R.A.I.B., R.T.S., T.D.S., J.S., A.A.B.), University of Pennsylvania,
Philadelphia, Pa; Centre for Medical Image Computing, Department of Medical
Physics and Biomedical Engineering, University College London, London, United
Kingdom (B.B., J.E.I.); Martinos Center for Biomedical Imaging and Department of
Radiology (J.E.I.) and Department of Otolaryngology–Head and Neck Surgery
(S.G.), Massachusetts General Hospital and Harvard Medical School, Boston, Mass;
and McGovern Institute for Brain Research (S.G.) and Computer Science &
Artificial Intelligence Laboratory (B.B., J.E.I.), Massachusetts Institute of
Technology, Cambridge, Mass
| | - Susan Sotardi
- From the Lifespan Brain Institute (LiBI) of the Children’s
Hospital of Philadelphia (CHOP) and Penn Medicine, Philadelphia, Pa (J.M.S.,
A.O.R., M.G., A.S.M., B.H.C., R.E.G., T.D.S., J.S., A.A.B.); Department of Child
and Adolescent Psychiatry and Behavioral Science (J.M.S., J.S., A.A.B.),
Department of Radiology (S.S., A.V., S.A., T.P.R., H.H.), PolicyLab and Clinical
Futures, CHOP Research Institute (B.H.C.), and Department of Biomedical and
Health Informatics (J.E.S., S.S., V.P.), Children’s Hospital of
Philadelphia, Philadelphia, Pa; Department of Psychiatry (J.E.S., R.E.G.,
T.D.S., D.R., J.S., A.A.B.), Department of Radiology (J.E.S., S.S., A.V., S.A.,
T.P.R., H.H.), Lifespan Informatics and Neuroimaging Center (PennLINC),
Department of Psychiatry (S.C., T.D.S.), and Department of Pediatrics (B.H.C.),
Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pa;
Departments of Psychiatry (S.A.B., S.R.W., E.B., R.A.I.B.) and Psychology
(R.A.I.B.), University of Cambridge, Cambridge, United Kingdom; Center for
Biomedical Image Computation and Analytics (R.T.S.), Penn Statistics in Imaging
and Visualization Center, Department of Biostatistics, Epidemiology and
Informatics (R.T.S.), and Lifespan Brain Chart Consortium (S.R.W., E.B.,
R.A.I.B., R.T.S., T.D.S., J.S., A.A.B.), University of Pennsylvania,
Philadelphia, Pa; Centre for Medical Image Computing, Department of Medical
Physics and Biomedical Engineering, University College London, London, United
Kingdom (B.B., J.E.I.); Martinos Center for Biomedical Imaging and Department of
Radiology (J.E.I.) and Department of Otolaryngology–Head and Neck Surgery
(S.G.), Massachusetts General Hospital and Harvard Medical School, Boston, Mass;
and McGovern Institute for Brain Research (S.G.) and Computer Science &
Artificial Intelligence Laboratory (B.B., J.E.I.), Massachusetts Institute of
Technology, Cambridge, Mass
| | - Arastoo Vossough
- From the Lifespan Brain Institute (LiBI) of the Children’s
Hospital of Philadelphia (CHOP) and Penn Medicine, Philadelphia, Pa (J.M.S.,
A.O.R., M.G., A.S.M., B.H.C., R.E.G., T.D.S., J.S., A.A.B.); Department of Child
and Adolescent Psychiatry and Behavioral Science (J.M.S., J.S., A.A.B.),
Department of Radiology (S.S., A.V., S.A., T.P.R., H.H.), PolicyLab and Clinical
Futures, CHOP Research Institute (B.H.C.), and Department of Biomedical and
Health Informatics (J.E.S., S.S., V.P.), Children’s Hospital of
Philadelphia, Philadelphia, Pa; Department of Psychiatry (J.E.S., R.E.G.,
T.D.S., D.R., J.S., A.A.B.), Department of Radiology (J.E.S., S.S., A.V., S.A.,
T.P.R., H.H.), Lifespan Informatics and Neuroimaging Center (PennLINC),
Department of Psychiatry (S.C., T.D.S.), and Department of Pediatrics (B.H.C.),
Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pa;
Departments of Psychiatry (S.A.B., S.R.W., E.B., R.A.I.B.) and Psychology
(R.A.I.B.), University of Cambridge, Cambridge, United Kingdom; Center for
Biomedical Image Computation and Analytics (R.T.S.), Penn Statistics in Imaging
and Visualization Center, Department of Biostatistics, Epidemiology and
Informatics (R.T.S.), and Lifespan Brain Chart Consortium (S.R.W., E.B.,
R.A.I.B., R.T.S., T.D.S., J.S., A.A.B.), University of Pennsylvania,
Philadelphia, Pa; Centre for Medical Image Computing, Department of Medical
Physics and Biomedical Engineering, University College London, London, United
Kingdom (B.B., J.E.I.); Martinos Center for Biomedical Imaging and Department of
Radiology (J.E.I.) and Department of Otolaryngology–Head and Neck Surgery
(S.G.), Massachusetts General Hospital and Harvard Medical School, Boston, Mass;
and McGovern Institute for Brain Research (S.G.) and Computer Science &
Artificial Intelligence Laboratory (B.B., J.E.I.), Massachusetts Institute of
Technology, Cambridge, Mass
| | - Savvas Andronikou
- From the Lifespan Brain Institute (LiBI) of the Children’s
Hospital of Philadelphia (CHOP) and Penn Medicine, Philadelphia, Pa (J.M.S.,
A.O.R., M.G., A.S.M., B.H.C., R.E.G., T.D.S., J.S., A.A.B.); Department of Child
and Adolescent Psychiatry and Behavioral Science (J.M.S., J.S., A.A.B.),
Department of Radiology (S.S., A.V., S.A., T.P.R., H.H.), PolicyLab and Clinical
Futures, CHOP Research Institute (B.H.C.), and Department of Biomedical and
Health Informatics (J.E.S., S.S., V.P.), Children’s Hospital of
Philadelphia, Philadelphia, Pa; Department of Psychiatry (J.E.S., R.E.G.,
T.D.S., D.R., J.S., A.A.B.), Department of Radiology (J.E.S., S.S., A.V., S.A.,
T.P.R., H.H.), Lifespan Informatics and Neuroimaging Center (PennLINC),
Department of Psychiatry (S.C., T.D.S.), and Department of Pediatrics (B.H.C.),
Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pa;
Departments of Psychiatry (S.A.B., S.R.W., E.B., R.A.I.B.) and Psychology
(R.A.I.B.), University of Cambridge, Cambridge, United Kingdom; Center for
Biomedical Image Computation and Analytics (R.T.S.), Penn Statistics in Imaging
and Visualization Center, Department of Biostatistics, Epidemiology and
Informatics (R.T.S.), and Lifespan Brain Chart Consortium (S.R.W., E.B.,
R.A.I.B., R.T.S., T.D.S., J.S., A.A.B.), University of Pennsylvania,
Philadelphia, Pa; Centre for Medical Image Computing, Department of Medical
Physics and Biomedical Engineering, University College London, London, United
Kingdom (B.B., J.E.I.); Martinos Center for Biomedical Imaging and Department of
Radiology (J.E.I.) and Department of Otolaryngology–Head and Neck Surgery
(S.G.), Massachusetts General Hospital and Harvard Medical School, Boston, Mass;
and McGovern Institute for Brain Research (S.G.) and Computer Science &
Artificial Intelligence Laboratory (B.B., J.E.I.), Massachusetts Institute of
Technology, Cambridge, Mass
| | - Timothy P. Roberts
- From the Lifespan Brain Institute (LiBI) of the Children’s
Hospital of Philadelphia (CHOP) and Penn Medicine, Philadelphia, Pa (J.M.S.,
A.O.R., M.G., A.S.M., B.H.C., R.E.G., T.D.S., J.S., A.A.B.); Department of Child
and Adolescent Psychiatry and Behavioral Science (J.M.S., J.S., A.A.B.),
Department of Radiology (S.S., A.V., S.A., T.P.R., H.H.), PolicyLab and Clinical
Futures, CHOP Research Institute (B.H.C.), and Department of Biomedical and
Health Informatics (J.E.S., S.S., V.P.), Children’s Hospital of
Philadelphia, Philadelphia, Pa; Department of Psychiatry (J.E.S., R.E.G.,
T.D.S., D.R., J.S., A.A.B.), Department of Radiology (J.E.S., S.S., A.V., S.A.,
T.P.R., H.H.), Lifespan Informatics and Neuroimaging Center (PennLINC),
Department of Psychiatry (S.C., T.D.S.), and Department of Pediatrics (B.H.C.),
Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pa;
Departments of Psychiatry (S.A.B., S.R.W., E.B., R.A.I.B.) and Psychology
(R.A.I.B.), University of Cambridge, Cambridge, United Kingdom; Center for
Biomedical Image Computation and Analytics (R.T.S.), Penn Statistics in Imaging
and Visualization Center, Department of Biostatistics, Epidemiology and
Informatics (R.T.S.), and Lifespan Brain Chart Consortium (S.R.W., E.B.,
R.A.I.B., R.T.S., T.D.S., J.S., A.A.B.), University of Pennsylvania,
Philadelphia, Pa; Centre for Medical Image Computing, Department of Medical
Physics and Biomedical Engineering, University College London, London, United
Kingdom (B.B., J.E.I.); Martinos Center for Biomedical Imaging and Department of
Radiology (J.E.I.) and Department of Otolaryngology–Head and Neck Surgery
(S.G.), Massachusetts General Hospital and Harvard Medical School, Boston, Mass;
and McGovern Institute for Brain Research (S.G.) and Computer Science &
Artificial Intelligence Laboratory (B.B., J.E.I.), Massachusetts Institute of
Technology, Cambridge, Mass
| | - Hao Huang
- From the Lifespan Brain Institute (LiBI) of the Children’s
Hospital of Philadelphia (CHOP) and Penn Medicine, Philadelphia, Pa (J.M.S.,
A.O.R., M.G., A.S.M., B.H.C., R.E.G., T.D.S., J.S., A.A.B.); Department of Child
and Adolescent Psychiatry and Behavioral Science (J.M.S., J.S., A.A.B.),
Department of Radiology (S.S., A.V., S.A., T.P.R., H.H.), PolicyLab and Clinical
Futures, CHOP Research Institute (B.H.C.), and Department of Biomedical and
Health Informatics (J.E.S., S.S., V.P.), Children’s Hospital of
Philadelphia, Philadelphia, Pa; Department of Psychiatry (J.E.S., R.E.G.,
T.D.S., D.R., J.S., A.A.B.), Department of Radiology (J.E.S., S.S., A.V., S.A.,
T.P.R., H.H.), Lifespan Informatics and Neuroimaging Center (PennLINC),
Department of Psychiatry (S.C., T.D.S.), and Department of Pediatrics (B.H.C.),
Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pa;
Departments of Psychiatry (S.A.B., S.R.W., E.B., R.A.I.B.) and Psychology
(R.A.I.B.), University of Cambridge, Cambridge, United Kingdom; Center for
Biomedical Image Computation and Analytics (R.T.S.), Penn Statistics in Imaging
and Visualization Center, Department of Biostatistics, Epidemiology and
Informatics (R.T.S.), and Lifespan Brain Chart Consortium (S.R.W., E.B.,
R.A.I.B., R.T.S., T.D.S., J.S., A.A.B.), University of Pennsylvania,
Philadelphia, Pa; Centre for Medical Image Computing, Department of Medical
Physics and Biomedical Engineering, University College London, London, United
Kingdom (B.B., J.E.I.); Martinos Center for Biomedical Imaging and Department of
Radiology (J.E.I.) and Department of Otolaryngology–Head and Neck Surgery
(S.G.), Massachusetts General Hospital and Harvard Medical School, Boston, Mass;
and McGovern Institute for Brain Research (S.G.) and Computer Science &
Artificial Intelligence Laboratory (B.B., J.E.I.), Massachusetts Institute of
Technology, Cambridge, Mass
| | - Viveknarayanan Padmanabhan
- From the Lifespan Brain Institute (LiBI) of the Children’s
Hospital of Philadelphia (CHOP) and Penn Medicine, Philadelphia, Pa (J.M.S.,
A.O.R., M.G., A.S.M., B.H.C., R.E.G., T.D.S., J.S., A.A.B.); Department of Child
and Adolescent Psychiatry and Behavioral Science (J.M.S., J.S., A.A.B.),
Department of Radiology (S.S., A.V., S.A., T.P.R., H.H.), PolicyLab and Clinical
Futures, CHOP Research Institute (B.H.C.), and Department of Biomedical and
Health Informatics (J.E.S., S.S., V.P.), Children’s Hospital of
Philadelphia, Philadelphia, Pa; Department of Psychiatry (J.E.S., R.E.G.,
T.D.S., D.R., J.S., A.A.B.), Department of Radiology (J.E.S., S.S., A.V., S.A.,
T.P.R., H.H.), Lifespan Informatics and Neuroimaging Center (PennLINC),
Department of Psychiatry (S.C., T.D.S.), and Department of Pediatrics (B.H.C.),
Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pa;
Departments of Psychiatry (S.A.B., S.R.W., E.B., R.A.I.B.) and Psychology
(R.A.I.B.), University of Cambridge, Cambridge, United Kingdom; Center for
Biomedical Image Computation and Analytics (R.T.S.), Penn Statistics in Imaging
and Visualization Center, Department of Biostatistics, Epidemiology and
Informatics (R.T.S.), and Lifespan Brain Chart Consortium (S.R.W., E.B.,
R.A.I.B., R.T.S., T.D.S., J.S., A.A.B.), University of Pennsylvania,
Philadelphia, Pa; Centre for Medical Image Computing, Department of Medical
Physics and Biomedical Engineering, University College London, London, United
Kingdom (B.B., J.E.I.); Martinos Center for Biomedical Imaging and Department of
Radiology (J.E.I.) and Department of Otolaryngology–Head and Neck Surgery
(S.G.), Massachusetts General Hospital and Harvard Medical School, Boston, Mass;
and McGovern Institute for Brain Research (S.G.) and Computer Science &
Artificial Intelligence Laboratory (B.B., J.E.I.), Massachusetts Institute of
Technology, Cambridge, Mass
| | - Alfredo Ortiz-Rosa
- From the Lifespan Brain Institute (LiBI) of the Children’s
Hospital of Philadelphia (CHOP) and Penn Medicine, Philadelphia, Pa (J.M.S.,
A.O.R., M.G., A.S.M., B.H.C., R.E.G., T.D.S., J.S., A.A.B.); Department of Child
and Adolescent Psychiatry and Behavioral Science (J.M.S., J.S., A.A.B.),
Department of Radiology (S.S., A.V., S.A., T.P.R., H.H.), PolicyLab and Clinical
Futures, CHOP Research Institute (B.H.C.), and Department of Biomedical and
Health Informatics (J.E.S., S.S., V.P.), Children’s Hospital of
Philadelphia, Philadelphia, Pa; Department of Psychiatry (J.E.S., R.E.G.,
T.D.S., D.R., J.S., A.A.B.), Department of Radiology (J.E.S., S.S., A.V., S.A.,
T.P.R., H.H.), Lifespan Informatics and Neuroimaging Center (PennLINC),
Department of Psychiatry (S.C., T.D.S.), and Department of Pediatrics (B.H.C.),
Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pa;
Departments of Psychiatry (S.A.B., S.R.W., E.B., R.A.I.B.) and Psychology
(R.A.I.B.), University of Cambridge, Cambridge, United Kingdom; Center for
Biomedical Image Computation and Analytics (R.T.S.), Penn Statistics in Imaging
and Visualization Center, Department of Biostatistics, Epidemiology and
Informatics (R.T.S.), and Lifespan Brain Chart Consortium (S.R.W., E.B.,
R.A.I.B., R.T.S., T.D.S., J.S., A.A.B.), University of Pennsylvania,
Philadelphia, Pa; Centre for Medical Image Computing, Department of Medical
Physics and Biomedical Engineering, University College London, London, United
Kingdom (B.B., J.E.I.); Martinos Center for Biomedical Imaging and Department of
Radiology (J.E.I.) and Department of Otolaryngology–Head and Neck Surgery
(S.G.), Massachusetts General Hospital and Harvard Medical School, Boston, Mass;
and McGovern Institute for Brain Research (S.G.) and Computer Science &
Artificial Intelligence Laboratory (B.B., J.E.I.), Massachusetts Institute of
Technology, Cambridge, Mass
| | - Margaret Gardner
- From the Lifespan Brain Institute (LiBI) of the Children’s
Hospital of Philadelphia (CHOP) and Penn Medicine, Philadelphia, Pa (J.M.S.,
A.O.R., M.G., A.S.M., B.H.C., R.E.G., T.D.S., J.S., A.A.B.); Department of Child
and Adolescent Psychiatry and Behavioral Science (J.M.S., J.S., A.A.B.),
Department of Radiology (S.S., A.V., S.A., T.P.R., H.H.), PolicyLab and Clinical
Futures, CHOP Research Institute (B.H.C.), and Department of Biomedical and
Health Informatics (J.E.S., S.S., V.P.), Children’s Hospital of
Philadelphia, Philadelphia, Pa; Department of Psychiatry (J.E.S., R.E.G.,
T.D.S., D.R., J.S., A.A.B.), Department of Radiology (J.E.S., S.S., A.V., S.A.,
T.P.R., H.H.), Lifespan Informatics and Neuroimaging Center (PennLINC),
Department of Psychiatry (S.C., T.D.S.), and Department of Pediatrics (B.H.C.),
Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pa;
Departments of Psychiatry (S.A.B., S.R.W., E.B., R.A.I.B.) and Psychology
(R.A.I.B.), University of Cambridge, Cambridge, United Kingdom; Center for
Biomedical Image Computation and Analytics (R.T.S.), Penn Statistics in Imaging
and Visualization Center, Department of Biostatistics, Epidemiology and
Informatics (R.T.S.), and Lifespan Brain Chart Consortium (S.R.W., E.B.,
R.A.I.B., R.T.S., T.D.S., J.S., A.A.B.), University of Pennsylvania,
Philadelphia, Pa; Centre for Medical Image Computing, Department of Medical
Physics and Biomedical Engineering, University College London, London, United
Kingdom (B.B., J.E.I.); Martinos Center for Biomedical Imaging and Department of
Radiology (J.E.I.) and Department of Otolaryngology–Head and Neck Surgery
(S.G.), Massachusetts General Hospital and Harvard Medical School, Boston, Mass;
and McGovern Institute for Brain Research (S.G.) and Computer Science &
Artificial Intelligence Laboratory (B.B., J.E.I.), Massachusetts Institute of
Technology, Cambridge, Mass
| | - Sydney Covitz
- From the Lifespan Brain Institute (LiBI) of the Children’s
Hospital of Philadelphia (CHOP) and Penn Medicine, Philadelphia, Pa (J.M.S.,
A.O.R., M.G., A.S.M., B.H.C., R.E.G., T.D.S., J.S., A.A.B.); Department of Child
and Adolescent Psychiatry and Behavioral Science (J.M.S., J.S., A.A.B.),
Department of Radiology (S.S., A.V., S.A., T.P.R., H.H.), PolicyLab and Clinical
Futures, CHOP Research Institute (B.H.C.), and Department of Biomedical and
Health Informatics (J.E.S., S.S., V.P.), Children’s Hospital of
Philadelphia, Philadelphia, Pa; Department of Psychiatry (J.E.S., R.E.G.,
T.D.S., D.R., J.S., A.A.B.), Department of Radiology (J.E.S., S.S., A.V., S.A.,
T.P.R., H.H.), Lifespan Informatics and Neuroimaging Center (PennLINC),
Department of Psychiatry (S.C., T.D.S.), and Department of Pediatrics (B.H.C.),
Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pa;
Departments of Psychiatry (S.A.B., S.R.W., E.B., R.A.I.B.) and Psychology
(R.A.I.B.), University of Cambridge, Cambridge, United Kingdom; Center for
Biomedical Image Computation and Analytics (R.T.S.), Penn Statistics in Imaging
and Visualization Center, Department of Biostatistics, Epidemiology and
Informatics (R.T.S.), and Lifespan Brain Chart Consortium (S.R.W., E.B.,
R.A.I.B., R.T.S., T.D.S., J.S., A.A.B.), University of Pennsylvania,
Philadelphia, Pa; Centre for Medical Image Computing, Department of Medical
Physics and Biomedical Engineering, University College London, London, United
Kingdom (B.B., J.E.I.); Martinos Center for Biomedical Imaging and Department of
Radiology (J.E.I.) and Department of Otolaryngology–Head and Neck Surgery
(S.G.), Massachusetts General Hospital and Harvard Medical School, Boston, Mass;
and McGovern Institute for Brain Research (S.G.) and Computer Science &
Artificial Intelligence Laboratory (B.B., J.E.I.), Massachusetts Institute of
Technology, Cambridge, Mass
| | - Saashi A. Bedford
- From the Lifespan Brain Institute (LiBI) of the Children’s
Hospital of Philadelphia (CHOP) and Penn Medicine, Philadelphia, Pa (J.M.S.,
A.O.R., M.G., A.S.M., B.H.C., R.E.G., T.D.S., J.S., A.A.B.); Department of Child
and Adolescent Psychiatry and Behavioral Science (J.M.S., J.S., A.A.B.),
Department of Radiology (S.S., A.V., S.A., T.P.R., H.H.), PolicyLab and Clinical
Futures, CHOP Research Institute (B.H.C.), and Department of Biomedical and
Health Informatics (J.E.S., S.S., V.P.), Children’s Hospital of
Philadelphia, Philadelphia, Pa; Department of Psychiatry (J.E.S., R.E.G.,
T.D.S., D.R., J.S., A.A.B.), Department of Radiology (J.E.S., S.S., A.V., S.A.,
T.P.R., H.H.), Lifespan Informatics and Neuroimaging Center (PennLINC),
Department of Psychiatry (S.C., T.D.S.), and Department of Pediatrics (B.H.C.),
Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pa;
Departments of Psychiatry (S.A.B., S.R.W., E.B., R.A.I.B.) and Psychology
(R.A.I.B.), University of Cambridge, Cambridge, United Kingdom; Center for
Biomedical Image Computation and Analytics (R.T.S.), Penn Statistics in Imaging
and Visualization Center, Department of Biostatistics, Epidemiology and
Informatics (R.T.S.), and Lifespan Brain Chart Consortium (S.R.W., E.B.,
R.A.I.B., R.T.S., T.D.S., J.S., A.A.B.), University of Pennsylvania,
Philadelphia, Pa; Centre for Medical Image Computing, Department of Medical
Physics and Biomedical Engineering, University College London, London, United
Kingdom (B.B., J.E.I.); Martinos Center for Biomedical Imaging and Department of
Radiology (J.E.I.) and Department of Otolaryngology–Head and Neck Surgery
(S.G.), Massachusetts General Hospital and Harvard Medical School, Boston, Mass;
and McGovern Institute for Brain Research (S.G.) and Computer Science &
Artificial Intelligence Laboratory (B.B., J.E.I.), Massachusetts Institute of
Technology, Cambridge, Mass
| | - Ayan S. Mandal
- From the Lifespan Brain Institute (LiBI) of the Children’s
Hospital of Philadelphia (CHOP) and Penn Medicine, Philadelphia, Pa (J.M.S.,
A.O.R., M.G., A.S.M., B.H.C., R.E.G., T.D.S., J.S., A.A.B.); Department of Child
and Adolescent Psychiatry and Behavioral Science (J.M.S., J.S., A.A.B.),
Department of Radiology (S.S., A.V., S.A., T.P.R., H.H.), PolicyLab and Clinical
Futures, CHOP Research Institute (B.H.C.), and Department of Biomedical and
Health Informatics (J.E.S., S.S., V.P.), Children’s Hospital of
Philadelphia, Philadelphia, Pa; Department of Psychiatry (J.E.S., R.E.G.,
T.D.S., D.R., J.S., A.A.B.), Department of Radiology (J.E.S., S.S., A.V., S.A.,
T.P.R., H.H.), Lifespan Informatics and Neuroimaging Center (PennLINC),
Department of Psychiatry (S.C., T.D.S.), and Department of Pediatrics (B.H.C.),
Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pa;
Departments of Psychiatry (S.A.B., S.R.W., E.B., R.A.I.B.) and Psychology
(R.A.I.B.), University of Cambridge, Cambridge, United Kingdom; Center for
Biomedical Image Computation and Analytics (R.T.S.), Penn Statistics in Imaging
and Visualization Center, Department of Biostatistics, Epidemiology and
Informatics (R.T.S.), and Lifespan Brain Chart Consortium (S.R.W., E.B.,
R.A.I.B., R.T.S., T.D.S., J.S., A.A.B.), University of Pennsylvania,
Philadelphia, Pa; Centre for Medical Image Computing, Department of Medical
Physics and Biomedical Engineering, University College London, London, United
Kingdom (B.B., J.E.I.); Martinos Center for Biomedical Imaging and Department of
Radiology (J.E.I.) and Department of Otolaryngology–Head and Neck Surgery
(S.G.), Massachusetts General Hospital and Harvard Medical School, Boston, Mass;
and McGovern Institute for Brain Research (S.G.) and Computer Science &
Artificial Intelligence Laboratory (B.B., J.E.I.), Massachusetts Institute of
Technology, Cambridge, Mass
| | - Barbara H. Chaiyachati
- From the Lifespan Brain Institute (LiBI) of the Children’s
Hospital of Philadelphia (CHOP) and Penn Medicine, Philadelphia, Pa (J.M.S.,
A.O.R., M.G., A.S.M., B.H.C., R.E.G., T.D.S., J.S., A.A.B.); Department of Child
and Adolescent Psychiatry and Behavioral Science (J.M.S., J.S., A.A.B.),
Department of Radiology (S.S., A.V., S.A., T.P.R., H.H.), PolicyLab and Clinical
Futures, CHOP Research Institute (B.H.C.), and Department of Biomedical and
Health Informatics (J.E.S., S.S., V.P.), Children’s Hospital of
Philadelphia, Philadelphia, Pa; Department of Psychiatry (J.E.S., R.E.G.,
T.D.S., D.R., J.S., A.A.B.), Department of Radiology (J.E.S., S.S., A.V., S.A.,
T.P.R., H.H.), Lifespan Informatics and Neuroimaging Center (PennLINC),
Department of Psychiatry (S.C., T.D.S.), and Department of Pediatrics (B.H.C.),
Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pa;
Departments of Psychiatry (S.A.B., S.R.W., E.B., R.A.I.B.) and Psychology
(R.A.I.B.), University of Cambridge, Cambridge, United Kingdom; Center for
Biomedical Image Computation and Analytics (R.T.S.), Penn Statistics in Imaging
and Visualization Center, Department of Biostatistics, Epidemiology and
Informatics (R.T.S.), and Lifespan Brain Chart Consortium (S.R.W., E.B.,
R.A.I.B., R.T.S., T.D.S., J.S., A.A.B.), University of Pennsylvania,
Philadelphia, Pa; Centre for Medical Image Computing, Department of Medical
Physics and Biomedical Engineering, University College London, London, United
Kingdom (B.B., J.E.I.); Martinos Center for Biomedical Imaging and Department of
Radiology (J.E.I.) and Department of Otolaryngology–Head and Neck Surgery
(S.G.), Massachusetts General Hospital and Harvard Medical School, Boston, Mass;
and McGovern Institute for Brain Research (S.G.) and Computer Science &
Artificial Intelligence Laboratory (B.B., J.E.I.), Massachusetts Institute of
Technology, Cambridge, Mass
| | - Simon R. White
- From the Lifespan Brain Institute (LiBI) of the Children’s
Hospital of Philadelphia (CHOP) and Penn Medicine, Philadelphia, Pa (J.M.S.,
A.O.R., M.G., A.S.M., B.H.C., R.E.G., T.D.S., J.S., A.A.B.); Department of Child
and Adolescent Psychiatry and Behavioral Science (J.M.S., J.S., A.A.B.),
Department of Radiology (S.S., A.V., S.A., T.P.R., H.H.), PolicyLab and Clinical
Futures, CHOP Research Institute (B.H.C.), and Department of Biomedical and
Health Informatics (J.E.S., S.S., V.P.), Children’s Hospital of
Philadelphia, Philadelphia, Pa; Department of Psychiatry (J.E.S., R.E.G.,
T.D.S., D.R., J.S., A.A.B.), Department of Radiology (J.E.S., S.S., A.V., S.A.,
T.P.R., H.H.), Lifespan Informatics and Neuroimaging Center (PennLINC),
Department of Psychiatry (S.C., T.D.S.), and Department of Pediatrics (B.H.C.),
Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pa;
Departments of Psychiatry (S.A.B., S.R.W., E.B., R.A.I.B.) and Psychology
(R.A.I.B.), University of Cambridge, Cambridge, United Kingdom; Center for
Biomedical Image Computation and Analytics (R.T.S.), Penn Statistics in Imaging
and Visualization Center, Department of Biostatistics, Epidemiology and
Informatics (R.T.S.), and Lifespan Brain Chart Consortium (S.R.W., E.B.,
R.A.I.B., R.T.S., T.D.S., J.S., A.A.B.), University of Pennsylvania,
Philadelphia, Pa; Centre for Medical Image Computing, Department of Medical
Physics and Biomedical Engineering, University College London, London, United
Kingdom (B.B., J.E.I.); Martinos Center for Biomedical Imaging and Department of
Radiology (J.E.I.) and Department of Otolaryngology–Head and Neck Surgery
(S.G.), Massachusetts General Hospital and Harvard Medical School, Boston, Mass;
and McGovern Institute for Brain Research (S.G.) and Computer Science &
Artificial Intelligence Laboratory (B.B., J.E.I.), Massachusetts Institute of
Technology, Cambridge, Mass
| | - Edward Bullmore
- From the Lifespan Brain Institute (LiBI) of the Children’s
Hospital of Philadelphia (CHOP) and Penn Medicine, Philadelphia, Pa (J.M.S.,
A.O.R., M.G., A.S.M., B.H.C., R.E.G., T.D.S., J.S., A.A.B.); Department of Child
and Adolescent Psychiatry and Behavioral Science (J.M.S., J.S., A.A.B.),
Department of Radiology (S.S., A.V., S.A., T.P.R., H.H.), PolicyLab and Clinical
Futures, CHOP Research Institute (B.H.C.), and Department of Biomedical and
Health Informatics (J.E.S., S.S., V.P.), Children’s Hospital of
Philadelphia, Philadelphia, Pa; Department of Psychiatry (J.E.S., R.E.G.,
T.D.S., D.R., J.S., A.A.B.), Department of Radiology (J.E.S., S.S., A.V., S.A.,
T.P.R., H.H.), Lifespan Informatics and Neuroimaging Center (PennLINC),
Department of Psychiatry (S.C., T.D.S.), and Department of Pediatrics (B.H.C.),
Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pa;
Departments of Psychiatry (S.A.B., S.R.W., E.B., R.A.I.B.) and Psychology
(R.A.I.B.), University of Cambridge, Cambridge, United Kingdom; Center for
Biomedical Image Computation and Analytics (R.T.S.), Penn Statistics in Imaging
and Visualization Center, Department of Biostatistics, Epidemiology and
Informatics (R.T.S.), and Lifespan Brain Chart Consortium (S.R.W., E.B.,
R.A.I.B., R.T.S., T.D.S., J.S., A.A.B.), University of Pennsylvania,
Philadelphia, Pa; Centre for Medical Image Computing, Department of Medical
Physics and Biomedical Engineering, University College London, London, United
Kingdom (B.B., J.E.I.); Martinos Center for Biomedical Imaging and Department of
Radiology (J.E.I.) and Department of Otolaryngology–Head and Neck Surgery
(S.G.), Massachusetts General Hospital and Harvard Medical School, Boston, Mass;
and McGovern Institute for Brain Research (S.G.) and Computer Science &
Artificial Intelligence Laboratory (B.B., J.E.I.), Massachusetts Institute of
Technology, Cambridge, Mass
| | - Richard A. I. Bethlehem
- From the Lifespan Brain Institute (LiBI) of the Children’s
Hospital of Philadelphia (CHOP) and Penn Medicine, Philadelphia, Pa (J.M.S.,
A.O.R., M.G., A.S.M., B.H.C., R.E.G., T.D.S., J.S., A.A.B.); Department of Child
and Adolescent Psychiatry and Behavioral Science (J.M.S., J.S., A.A.B.),
Department of Radiology (S.S., A.V., S.A., T.P.R., H.H.), PolicyLab and Clinical
Futures, CHOP Research Institute (B.H.C.), and Department of Biomedical and
Health Informatics (J.E.S., S.S., V.P.), Children’s Hospital of
Philadelphia, Philadelphia, Pa; Department of Psychiatry (J.E.S., R.E.G.,
T.D.S., D.R., J.S., A.A.B.), Department of Radiology (J.E.S., S.S., A.V., S.A.,
T.P.R., H.H.), Lifespan Informatics and Neuroimaging Center (PennLINC),
Department of Psychiatry (S.C., T.D.S.), and Department of Pediatrics (B.H.C.),
Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pa;
Departments of Psychiatry (S.A.B., S.R.W., E.B., R.A.I.B.) and Psychology
(R.A.I.B.), University of Cambridge, Cambridge, United Kingdom; Center for
Biomedical Image Computation and Analytics (R.T.S.), Penn Statistics in Imaging
and Visualization Center, Department of Biostatistics, Epidemiology and
Informatics (R.T.S.), and Lifespan Brain Chart Consortium (S.R.W., E.B.,
R.A.I.B., R.T.S., T.D.S., J.S., A.A.B.), University of Pennsylvania,
Philadelphia, Pa; Centre for Medical Image Computing, Department of Medical
Physics and Biomedical Engineering, University College London, London, United
Kingdom (B.B., J.E.I.); Martinos Center for Biomedical Imaging and Department of
Radiology (J.E.I.) and Department of Otolaryngology–Head and Neck Surgery
(S.G.), Massachusetts General Hospital and Harvard Medical School, Boston, Mass;
and McGovern Institute for Brain Research (S.G.) and Computer Science &
Artificial Intelligence Laboratory (B.B., J.E.I.), Massachusetts Institute of
Technology, Cambridge, Mass
| | - Russell T. Shinohara
- From the Lifespan Brain Institute (LiBI) of the Children’s
Hospital of Philadelphia (CHOP) and Penn Medicine, Philadelphia, Pa (J.M.S.,
A.O.R., M.G., A.S.M., B.H.C., R.E.G., T.D.S., J.S., A.A.B.); Department of Child
and Adolescent Psychiatry and Behavioral Science (J.M.S., J.S., A.A.B.),
Department of Radiology (S.S., A.V., S.A., T.P.R., H.H.), PolicyLab and Clinical
Futures, CHOP Research Institute (B.H.C.), and Department of Biomedical and
Health Informatics (J.E.S., S.S., V.P.), Children’s Hospital of
Philadelphia, Philadelphia, Pa; Department of Psychiatry (J.E.S., R.E.G.,
T.D.S., D.R., J.S., A.A.B.), Department of Radiology (J.E.S., S.S., A.V., S.A.,
T.P.R., H.H.), Lifespan Informatics and Neuroimaging Center (PennLINC),
Department of Psychiatry (S.C., T.D.S.), and Department of Pediatrics (B.H.C.),
Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pa;
Departments of Psychiatry (S.A.B., S.R.W., E.B., R.A.I.B.) and Psychology
(R.A.I.B.), University of Cambridge, Cambridge, United Kingdom; Center for
Biomedical Image Computation and Analytics (R.T.S.), Penn Statistics in Imaging
and Visualization Center, Department of Biostatistics, Epidemiology and
Informatics (R.T.S.), and Lifespan Brain Chart Consortium (S.R.W., E.B.,
R.A.I.B., R.T.S., T.D.S., J.S., A.A.B.), University of Pennsylvania,
Philadelphia, Pa; Centre for Medical Image Computing, Department of Medical
Physics and Biomedical Engineering, University College London, London, United
Kingdom (B.B., J.E.I.); Martinos Center for Biomedical Imaging and Department of
Radiology (J.E.I.) and Department of Otolaryngology–Head and Neck Surgery
(S.G.), Massachusetts General Hospital and Harvard Medical School, Boston, Mass;
and McGovern Institute for Brain Research (S.G.) and Computer Science &
Artificial Intelligence Laboratory (B.B., J.E.I.), Massachusetts Institute of
Technology, Cambridge, Mass
| | - Benjamin Billot
- From the Lifespan Brain Institute (LiBI) of the Children’s
Hospital of Philadelphia (CHOP) and Penn Medicine, Philadelphia, Pa (J.M.S.,
A.O.R., M.G., A.S.M., B.H.C., R.E.G., T.D.S., J.S., A.A.B.); Department of Child
and Adolescent Psychiatry and Behavioral Science (J.M.S., J.S., A.A.B.),
Department of Radiology (S.S., A.V., S.A., T.P.R., H.H.), PolicyLab and Clinical
Futures, CHOP Research Institute (B.H.C.), and Department of Biomedical and
Health Informatics (J.E.S., S.S., V.P.), Children’s Hospital of
Philadelphia, Philadelphia, Pa; Department of Psychiatry (J.E.S., R.E.G.,
T.D.S., D.R., J.S., A.A.B.), Department of Radiology (J.E.S., S.S., A.V., S.A.,
T.P.R., H.H.), Lifespan Informatics and Neuroimaging Center (PennLINC),
Department of Psychiatry (S.C., T.D.S.), and Department of Pediatrics (B.H.C.),
Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pa;
Departments of Psychiatry (S.A.B., S.R.W., E.B., R.A.I.B.) and Psychology
(R.A.I.B.), University of Cambridge, Cambridge, United Kingdom; Center for
Biomedical Image Computation and Analytics (R.T.S.), Penn Statistics in Imaging
and Visualization Center, Department of Biostatistics, Epidemiology and
Informatics (R.T.S.), and Lifespan Brain Chart Consortium (S.R.W., E.B.,
R.A.I.B., R.T.S., T.D.S., J.S., A.A.B.), University of Pennsylvania,
Philadelphia, Pa; Centre for Medical Image Computing, Department of Medical
Physics and Biomedical Engineering, University College London, London, United
Kingdom (B.B., J.E.I.); Martinos Center for Biomedical Imaging and Department of
Radiology (J.E.I.) and Department of Otolaryngology–Head and Neck Surgery
(S.G.), Massachusetts General Hospital and Harvard Medical School, Boston, Mass;
and McGovern Institute for Brain Research (S.G.) and Computer Science &
Artificial Intelligence Laboratory (B.B., J.E.I.), Massachusetts Institute of
Technology, Cambridge, Mass
| | - J. Eugenio Iglesias
- From the Lifespan Brain Institute (LiBI) of the Children’s
Hospital of Philadelphia (CHOP) and Penn Medicine, Philadelphia, Pa (J.M.S.,
A.O.R., M.G., A.S.M., B.H.C., R.E.G., T.D.S., J.S., A.A.B.); Department of Child
and Adolescent Psychiatry and Behavioral Science (J.M.S., J.S., A.A.B.),
Department of Radiology (S.S., A.V., S.A., T.P.R., H.H.), PolicyLab and Clinical
Futures, CHOP Research Institute (B.H.C.), and Department of Biomedical and
Health Informatics (J.E.S., S.S., V.P.), Children’s Hospital of
Philadelphia, Philadelphia, Pa; Department of Psychiatry (J.E.S., R.E.G.,
T.D.S., D.R., J.S., A.A.B.), Department of Radiology (J.E.S., S.S., A.V., S.A.,
T.P.R., H.H.), Lifespan Informatics and Neuroimaging Center (PennLINC),
Department of Psychiatry (S.C., T.D.S.), and Department of Pediatrics (B.H.C.),
Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pa;
Departments of Psychiatry (S.A.B., S.R.W., E.B., R.A.I.B.) and Psychology
(R.A.I.B.), University of Cambridge, Cambridge, United Kingdom; Center for
Biomedical Image Computation and Analytics (R.T.S.), Penn Statistics in Imaging
and Visualization Center, Department of Biostatistics, Epidemiology and
Informatics (R.T.S.), and Lifespan Brain Chart Consortium (S.R.W., E.B.,
R.A.I.B., R.T.S., T.D.S., J.S., A.A.B.), University of Pennsylvania,
Philadelphia, Pa; Centre for Medical Image Computing, Department of Medical
Physics and Biomedical Engineering, University College London, London, United
Kingdom (B.B., J.E.I.); Martinos Center for Biomedical Imaging and Department of
Radiology (J.E.I.) and Department of Otolaryngology–Head and Neck Surgery
(S.G.), Massachusetts General Hospital and Harvard Medical School, Boston, Mass;
and McGovern Institute for Brain Research (S.G.) and Computer Science &
Artificial Intelligence Laboratory (B.B., J.E.I.), Massachusetts Institute of
Technology, Cambridge, Mass
| | - Satrajit Ghosh
- From the Lifespan Brain Institute (LiBI) of the Children’s
Hospital of Philadelphia (CHOP) and Penn Medicine, Philadelphia, Pa (J.M.S.,
A.O.R., M.G., A.S.M., B.H.C., R.E.G., T.D.S., J.S., A.A.B.); Department of Child
and Adolescent Psychiatry and Behavioral Science (J.M.S., J.S., A.A.B.),
Department of Radiology (S.S., A.V., S.A., T.P.R., H.H.), PolicyLab and Clinical
Futures, CHOP Research Institute (B.H.C.), and Department of Biomedical and
Health Informatics (J.E.S., S.S., V.P.), Children’s Hospital of
Philadelphia, Philadelphia, Pa; Department of Psychiatry (J.E.S., R.E.G.,
T.D.S., D.R., J.S., A.A.B.), Department of Radiology (J.E.S., S.S., A.V., S.A.,
T.P.R., H.H.), Lifespan Informatics and Neuroimaging Center (PennLINC),
Department of Psychiatry (S.C., T.D.S.), and Department of Pediatrics (B.H.C.),
Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pa;
Departments of Psychiatry (S.A.B., S.R.W., E.B., R.A.I.B.) and Psychology
(R.A.I.B.), University of Cambridge, Cambridge, United Kingdom; Center for
Biomedical Image Computation and Analytics (R.T.S.), Penn Statistics in Imaging
and Visualization Center, Department of Biostatistics, Epidemiology and
Informatics (R.T.S.), and Lifespan Brain Chart Consortium (S.R.W., E.B.,
R.A.I.B., R.T.S., T.D.S., J.S., A.A.B.), University of Pennsylvania,
Philadelphia, Pa; Centre for Medical Image Computing, Department of Medical
Physics and Biomedical Engineering, University College London, London, United
Kingdom (B.B., J.E.I.); Martinos Center for Biomedical Imaging and Department of
Radiology (J.E.I.) and Department of Otolaryngology–Head and Neck Surgery
(S.G.), Massachusetts General Hospital and Harvard Medical School, Boston, Mass;
and McGovern Institute for Brain Research (S.G.) and Computer Science &
Artificial Intelligence Laboratory (B.B., J.E.I.), Massachusetts Institute of
Technology, Cambridge, Mass
| | - Raquel E. Gur
- From the Lifespan Brain Institute (LiBI) of the Children’s
Hospital of Philadelphia (CHOP) and Penn Medicine, Philadelphia, Pa (J.M.S.,
A.O.R., M.G., A.S.M., B.H.C., R.E.G., T.D.S., J.S., A.A.B.); Department of Child
and Adolescent Psychiatry and Behavioral Science (J.M.S., J.S., A.A.B.),
Department of Radiology (S.S., A.V., S.A., T.P.R., H.H.), PolicyLab and Clinical
Futures, CHOP Research Institute (B.H.C.), and Department of Biomedical and
Health Informatics (J.E.S., S.S., V.P.), Children’s Hospital of
Philadelphia, Philadelphia, Pa; Department of Psychiatry (J.E.S., R.E.G.,
T.D.S., D.R., J.S., A.A.B.), Department of Radiology (J.E.S., S.S., A.V., S.A.,
T.P.R., H.H.), Lifespan Informatics and Neuroimaging Center (PennLINC),
Department of Psychiatry (S.C., T.D.S.), and Department of Pediatrics (B.H.C.),
Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pa;
Departments of Psychiatry (S.A.B., S.R.W., E.B., R.A.I.B.) and Psychology
(R.A.I.B.), University of Cambridge, Cambridge, United Kingdom; Center for
Biomedical Image Computation and Analytics (R.T.S.), Penn Statistics in Imaging
and Visualization Center, Department of Biostatistics, Epidemiology and
Informatics (R.T.S.), and Lifespan Brain Chart Consortium (S.R.W., E.B.,
R.A.I.B., R.T.S., T.D.S., J.S., A.A.B.), University of Pennsylvania,
Philadelphia, Pa; Centre for Medical Image Computing, Department of Medical
Physics and Biomedical Engineering, University College London, London, United
Kingdom (B.B., J.E.I.); Martinos Center for Biomedical Imaging and Department of
Radiology (J.E.I.) and Department of Otolaryngology–Head and Neck Surgery
(S.G.), Massachusetts General Hospital and Harvard Medical School, Boston, Mass;
and McGovern Institute for Brain Research (S.G.) and Computer Science &
Artificial Intelligence Laboratory (B.B., J.E.I.), Massachusetts Institute of
Technology, Cambridge, Mass
| | - Theodore D. Satterthwaite
- From the Lifespan Brain Institute (LiBI) of the Children’s
Hospital of Philadelphia (CHOP) and Penn Medicine, Philadelphia, Pa (J.M.S.,
A.O.R., M.G., A.S.M., B.H.C., R.E.G., T.D.S., J.S., A.A.B.); Department of Child
and Adolescent Psychiatry and Behavioral Science (J.M.S., J.S., A.A.B.),
Department of Radiology (S.S., A.V., S.A., T.P.R., H.H.), PolicyLab and Clinical
Futures, CHOP Research Institute (B.H.C.), and Department of Biomedical and
Health Informatics (J.E.S., S.S., V.P.), Children’s Hospital of
Philadelphia, Philadelphia, Pa; Department of Psychiatry (J.E.S., R.E.G.,
T.D.S., D.R., J.S., A.A.B.), Department of Radiology (J.E.S., S.S., A.V., S.A.,
T.P.R., H.H.), Lifespan Informatics and Neuroimaging Center (PennLINC),
Department of Psychiatry (S.C., T.D.S.), and Department of Pediatrics (B.H.C.),
Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pa;
Departments of Psychiatry (S.A.B., S.R.W., E.B., R.A.I.B.) and Psychology
(R.A.I.B.), University of Cambridge, Cambridge, United Kingdom; Center for
Biomedical Image Computation and Analytics (R.T.S.), Penn Statistics in Imaging
and Visualization Center, Department of Biostatistics, Epidemiology and
Informatics (R.T.S.), and Lifespan Brain Chart Consortium (S.R.W., E.B.,
R.A.I.B., R.T.S., T.D.S., J.S., A.A.B.), University of Pennsylvania,
Philadelphia, Pa; Centre for Medical Image Computing, Department of Medical
Physics and Biomedical Engineering, University College London, London, United
Kingdom (B.B., J.E.I.); Martinos Center for Biomedical Imaging and Department of
Radiology (J.E.I.) and Department of Otolaryngology–Head and Neck Surgery
(S.G.), Massachusetts General Hospital and Harvard Medical School, Boston, Mass;
and McGovern Institute for Brain Research (S.G.) and Computer Science &
Artificial Intelligence Laboratory (B.B., J.E.I.), Massachusetts Institute of
Technology, Cambridge, Mass
| | - David Roalf
- From the Lifespan Brain Institute (LiBI) of the Children’s
Hospital of Philadelphia (CHOP) and Penn Medicine, Philadelphia, Pa (J.M.S.,
A.O.R., M.G., A.S.M., B.H.C., R.E.G., T.D.S., J.S., A.A.B.); Department of Child
and Adolescent Psychiatry and Behavioral Science (J.M.S., J.S., A.A.B.),
Department of Radiology (S.S., A.V., S.A., T.P.R., H.H.), PolicyLab and Clinical
Futures, CHOP Research Institute (B.H.C.), and Department of Biomedical and
Health Informatics (J.E.S., S.S., V.P.), Children’s Hospital of
Philadelphia, Philadelphia, Pa; Department of Psychiatry (J.E.S., R.E.G.,
T.D.S., D.R., J.S., A.A.B.), Department of Radiology (J.E.S., S.S., A.V., S.A.,
T.P.R., H.H.), Lifespan Informatics and Neuroimaging Center (PennLINC),
Department of Psychiatry (S.C., T.D.S.), and Department of Pediatrics (B.H.C.),
Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pa;
Departments of Psychiatry (S.A.B., S.R.W., E.B., R.A.I.B.) and Psychology
(R.A.I.B.), University of Cambridge, Cambridge, United Kingdom; Center for
Biomedical Image Computation and Analytics (R.T.S.), Penn Statistics in Imaging
and Visualization Center, Department of Biostatistics, Epidemiology and
Informatics (R.T.S.), and Lifespan Brain Chart Consortium (S.R.W., E.B.,
R.A.I.B., R.T.S., T.D.S., J.S., A.A.B.), University of Pennsylvania,
Philadelphia, Pa; Centre for Medical Image Computing, Department of Medical
Physics and Biomedical Engineering, University College London, London, United
Kingdom (B.B., J.E.I.); Martinos Center for Biomedical Imaging and Department of
Radiology (J.E.I.) and Department of Otolaryngology–Head and Neck Surgery
(S.G.), Massachusetts General Hospital and Harvard Medical School, Boston, Mass;
and McGovern Institute for Brain Research (S.G.) and Computer Science &
Artificial Intelligence Laboratory (B.B., J.E.I.), Massachusetts Institute of
Technology, Cambridge, Mass
| | - Jakob Seidlitz
- From the Lifespan Brain Institute (LiBI) of the Children’s
Hospital of Philadelphia (CHOP) and Penn Medicine, Philadelphia, Pa (J.M.S.,
A.O.R., M.G., A.S.M., B.H.C., R.E.G., T.D.S., J.S., A.A.B.); Department of Child
and Adolescent Psychiatry and Behavioral Science (J.M.S., J.S., A.A.B.),
Department of Radiology (S.S., A.V., S.A., T.P.R., H.H.), PolicyLab and Clinical
Futures, CHOP Research Institute (B.H.C.), and Department of Biomedical and
Health Informatics (J.E.S., S.S., V.P.), Children’s Hospital of
Philadelphia, Philadelphia, Pa; Department of Psychiatry (J.E.S., R.E.G.,
T.D.S., D.R., J.S., A.A.B.), Department of Radiology (J.E.S., S.S., A.V., S.A.,
T.P.R., H.H.), Lifespan Informatics and Neuroimaging Center (PennLINC),
Department of Psychiatry (S.C., T.D.S.), and Department of Pediatrics (B.H.C.),
Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pa;
Departments of Psychiatry (S.A.B., S.R.W., E.B., R.A.I.B.) and Psychology
(R.A.I.B.), University of Cambridge, Cambridge, United Kingdom; Center for
Biomedical Image Computation and Analytics (R.T.S.), Penn Statistics in Imaging
and Visualization Center, Department of Biostatistics, Epidemiology and
Informatics (R.T.S.), and Lifespan Brain Chart Consortium (S.R.W., E.B.,
R.A.I.B., R.T.S., T.D.S., J.S., A.A.B.), University of Pennsylvania,
Philadelphia, Pa; Centre for Medical Image Computing, Department of Medical
Physics and Biomedical Engineering, University College London, London, United
Kingdom (B.B., J.E.I.); Martinos Center for Biomedical Imaging and Department of
Radiology (J.E.I.) and Department of Otolaryngology–Head and Neck Surgery
(S.G.), Massachusetts General Hospital and Harvard Medical School, Boston, Mass;
and McGovern Institute for Brain Research (S.G.) and Computer Science &
Artificial Intelligence Laboratory (B.B., J.E.I.), Massachusetts Institute of
Technology, Cambridge, Mass
| | - Aaron Alexander-Bloch
- From the Lifespan Brain Institute (LiBI) of the Children’s
Hospital of Philadelphia (CHOP) and Penn Medicine, Philadelphia, Pa (J.M.S.,
A.O.R., M.G., A.S.M., B.H.C., R.E.G., T.D.S., J.S., A.A.B.); Department of Child
and Adolescent Psychiatry and Behavioral Science (J.M.S., J.S., A.A.B.),
Department of Radiology (S.S., A.V., S.A., T.P.R., H.H.), PolicyLab and Clinical
Futures, CHOP Research Institute (B.H.C.), and Department of Biomedical and
Health Informatics (J.E.S., S.S., V.P.), Children’s Hospital of
Philadelphia, Philadelphia, Pa; Department of Psychiatry (J.E.S., R.E.G.,
T.D.S., D.R., J.S., A.A.B.), Department of Radiology (J.E.S., S.S., A.V., S.A.,
T.P.R., H.H.), Lifespan Informatics and Neuroimaging Center (PennLINC),
Department of Psychiatry (S.C., T.D.S.), and Department of Pediatrics (B.H.C.),
Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pa;
Departments of Psychiatry (S.A.B., S.R.W., E.B., R.A.I.B.) and Psychology
(R.A.I.B.), University of Cambridge, Cambridge, United Kingdom; Center for
Biomedical Image Computation and Analytics (R.T.S.), Penn Statistics in Imaging
and Visualization Center, Department of Biostatistics, Epidemiology and
Informatics (R.T.S.), and Lifespan Brain Chart Consortium (S.R.W., E.B.,
R.A.I.B., R.T.S., T.D.S., J.S., A.A.B.), University of Pennsylvania,
Philadelphia, Pa; Centre for Medical Image Computing, Department of Medical
Physics and Biomedical Engineering, University College London, London, United
Kingdom (B.B., J.E.I.); Martinos Center for Biomedical Imaging and Department of
Radiology (J.E.I.) and Department of Otolaryngology–Head and Neck Surgery
(S.G.), Massachusetts General Hospital and Harvard Medical School, Boston, Mass;
and McGovern Institute for Brain Research (S.G.) and Computer Science &
Artificial Intelligence Laboratory (B.B., J.E.I.), Massachusetts Institute of
Technology, Cambridge, Mass
| | - for the Lifespan Brain Chart Consortium
- From the Lifespan Brain Institute (LiBI) of the Children’s
Hospital of Philadelphia (CHOP) and Penn Medicine, Philadelphia, Pa (J.M.S.,
A.O.R., M.G., A.S.M., B.H.C., R.E.G., T.D.S., J.S., A.A.B.); Department of Child
and Adolescent Psychiatry and Behavioral Science (J.M.S., J.S., A.A.B.),
Department of Radiology (S.S., A.V., S.A., T.P.R., H.H.), PolicyLab and Clinical
Futures, CHOP Research Institute (B.H.C.), and Department of Biomedical and
Health Informatics (J.E.S., S.S., V.P.), Children’s Hospital of
Philadelphia, Philadelphia, Pa; Department of Psychiatry (J.E.S., R.E.G.,
T.D.S., D.R., J.S., A.A.B.), Department of Radiology (J.E.S., S.S., A.V., S.A.,
T.P.R., H.H.), Lifespan Informatics and Neuroimaging Center (PennLINC),
Department of Psychiatry (S.C., T.D.S.), and Department of Pediatrics (B.H.C.),
Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pa;
Departments of Psychiatry (S.A.B., S.R.W., E.B., R.A.I.B.) and Psychology
(R.A.I.B.), University of Cambridge, Cambridge, United Kingdom; Center for
Biomedical Image Computation and Analytics (R.T.S.), Penn Statistics in Imaging
and Visualization Center, Department of Biostatistics, Epidemiology and
Informatics (R.T.S.), and Lifespan Brain Chart Consortium (S.R.W., E.B.,
R.A.I.B., R.T.S., T.D.S., J.S., A.A.B.), University of Pennsylvania,
Philadelphia, Pa; Centre for Medical Image Computing, Department of Medical
Physics and Biomedical Engineering, University College London, London, United
Kingdom (B.B., J.E.I.); Martinos Center for Biomedical Imaging and Department of
Radiology (J.E.I.) and Department of Otolaryngology–Head and Neck Surgery
(S.G.), Massachusetts General Hospital and Harvard Medical School, Boston, Mass;
and McGovern Institute for Brain Research (S.G.) and Computer Science &
Artificial Intelligence Laboratory (B.B., J.E.I.), Massachusetts Institute of
Technology, Cambridge, Mass
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7
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Warrier V, Stauffer EM, Huang QQ, Wigdor EM, Slob EAW, Seidlitz J, Ronan L, Valk SL, Mallard TT, Grotzinger AD, Romero-Garcia R, Baron-Cohen S, Geschwind DH, Lancaster MA, Murray GK, Gandal MJ, Alexander-Bloch A, Won H, Martin HC, Bullmore ET, Bethlehem RAI. Genetic insights into human cortical organization and development through genome-wide analyses of 2,347 neuroimaging phenotypes. Nat Genet 2023; 55:1483-1493. [PMID: 37592024 PMCID: PMC10600728 DOI: 10.1038/s41588-023-01475-y] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2022] [Accepted: 07/13/2023] [Indexed: 08/19/2023]
Abstract
Our understanding of the genetics of the human cerebral cortex is limited both in terms of the diversity and the anatomical granularity of brain structural phenotypes. Here we conducted a genome-wide association meta-analysis of 13 structural and diffusion magnetic resonance imaging-derived cortical phenotypes, measured globally and at 180 bilaterally averaged regions in 36,663 individuals and identified 4,349 experiment-wide significant loci. These phenotypes include cortical thickness, surface area, gray matter volume, measures of folding, neurite density and water diffusion. We identified four genetic latent structures and causal relationships between surface area and some measures of cortical folding. These latent structures partly relate to different underlying gene expression trajectories during development and are enriched for different cell types. We also identified differential enrichment for neurodevelopmental and constrained genes and demonstrate that common genetic variants associated with cortical expansion are associated with cephalic disorders. Finally, we identified complex interphenotype and inter-regional genetic relationships among the 13 phenotypes, reflecting the developmental differences among them. Together, these analyses identify distinct genetic organizational principles of the cortex and their correlates with neurodevelopment.
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Affiliation(s)
- Varun Warrier
- Department of Psychiatry, University of Cambridge, Cambridge, UK.
- Department of Psychology, University of Cambridge, Cambridge, UK.
| | | | | | | | - Eric A W Slob
- Medical Research Council Biostatistics Unit, University of Cambridge, Cambridge, UK
- Department of Applied Economics, Erasmus School of Economics, Erasmus University Rotterdam, Rotterdam, the Netherlands
- Erasmus University Rotterdam Institute for Behavior and Biology, Erasmus University Rotterdam, Rotterdam, the Netherlands
| | - Jakob Seidlitz
- 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
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA, USA
| | - Lisa Ronan
- Department of Psychiatry, University of Cambridge, Cambridge, UK
| | - Sofie L Valk
- Institute of Neuroscience and Medicine, Brain & Behaviour (INM-7), Research Centre Jülich, FZ Jülich, Jülich, Germany
- Institute of Systems Neuroscience, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
- Otto Hahn Group Cognitive Neurogenetics, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Travis T Mallard
- Psychiatric and Neurodevelopmental Genetics Unit, Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
- Department of Psychiatry, Harvard Medical School, Boston, MA, USA
| | - Andrew D Grotzinger
- Department of Psychology and Neuroscience, University of Colorado at Boulder, Boulder, CO, USA
- Institute for Behavioral Genetics, University of Colorado at Boulder, Boulder, CO, USA
| | - Rafael Romero-Garcia
- Department of Psychiatry, University of Cambridge, Cambridge, UK
- Instituto de Biomedicina de Sevilla (IBiS) HUVR/CSIC/Universidad de Sevilla/CIBERSAM, ISCIII, Dpto. de Fisiología Médica y Biofísica, Seville, Spain
| | - Simon Baron-Cohen
- Department of Psychiatry, University of Cambridge, Cambridge, UK
- Department of Psychology, University of Cambridge, Cambridge, UK
| | - Daniel H Geschwind
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, CA, USA
- Program in Neurogenetics, Department of Neurology, University of California, Los Angeles, CA, USA
- Center for Autism Research and Treatment, Jane and TerrySemel Institute for Neuroscience and Human Behavior, University of California, Los Angeles, CA, USA
- Institute of Precision Health, University of California, Los Angeles, CA, USA
| | - Madeline A Lancaster
- MRC Laboratory of Molecular Biology, Cambridge Biomedical Campus, Francis Crick Avenue, Cambridge, UK
| | - Graham K Murray
- Department of Psychiatry, University of Cambridge, Cambridge, UK
- Cambridgeshire and Peterborough NHS Trust, Cambridge, UK
- Institute for Molecular Bioscience, University of Queensland, Brisbane, Queensland, Australia
| | - Michael J Gandal
- 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
| | - Aaron Alexander-Bloch
- 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
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA, USA
| | - Hyejung Won
- Department of Genetics and the Neuroscience Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | | | - Edward T Bullmore
- Department of Psychiatry, University of Cambridge, Cambridge, UK
- Cambridgeshire and Peterborough NHS Trust, Cambridge, UK
| | - Richard A I Bethlehem
- Department of Psychiatry, University of Cambridge, Cambridge, UK.
- Department of Psychology, University of Cambridge, Cambridge, UK.
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8
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Sebenius I, Seidlitz J, Warrier V, Bethlehem RAI, Alexander-Bloch A, Mallard TT, Garcia RR, Bullmore ET, Morgan SE. Robust estimation of cortical similarity networks from brain MRI. Nat Neurosci 2023; 26:1461-1471. [PMID: 37460809 PMCID: PMC10400419 DOI: 10.1038/s41593-023-01376-7] [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: 10/11/2022] [Accepted: 06/08/2023] [Indexed: 08/05/2023]
Abstract
Structural similarity is a growing focus for magnetic resonance imaging (MRI) of connectomes. Here we propose Morphometric INverse Divergence (MIND), a new method to estimate within-subject similarity between cortical areas based on the divergence between their multivariate distributions of multiple MRI features. Compared to the prior approach of morphometric similarity networks (MSNs) on n > 11,000 scans spanning three human datasets and one macaque dataset, MIND networks were more reliable, more consistent with cortical cytoarchitectonics and symmetry and more correlated with tract-tracing measures of axonal connectivity. MIND networks derived from human T1-weighted MRI were more sensitive to age-related changes than MSNs or networks derived by tractography of diffusion-weighted MRI. Gene co-expression between cortical areas was more strongly coupled to MIND networks than to MSNs or tractography. MIND network phenotypes were also more heritable, especially edges between structurally differentiated areas. MIND network analysis provides a biologically validated lens for cortical connectomics using readily available MRI data.
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Affiliation(s)
- Isaac Sebenius
- Department of Psychiatry, University of Cambridge, Cambridge, UK.
- Department of Computer Science and Technology, University of Cambridge, Cambridge, UK.
| | - Jakob Seidlitz
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA, USA
- Department of Child and Adolescent Psychiatry and Behavioral Science, Children's Hospital of Philadelphia, Philadelphia, PA, USA
- Lifespan Brain Institute, Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Varun Warrier
- Autism Research Centre, Department of Psychiatry, University of Cambridge, Cambridge, UK
| | - Richard A I Bethlehem
- Department of Psychiatry, University of Cambridge, Cambridge, UK
- Autism Research Centre, Department of Psychiatry, University of Cambridge, Cambridge, UK
| | - Aaron Alexander-Bloch
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA, USA
- Department of Child and Adolescent Psychiatry and Behavioral Science, Children's Hospital of Philadelphia, Philadelphia, PA, USA
- Lifespan Brain Institute, Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Travis T Mallard
- Department of Psychiatry, Harvard Medical School, Boston, MA, USA
- Psychiatric and Neurodevelopmental Genetics Unit, Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Rafael Romero Garcia
- Department of Psychiatry, University of Cambridge, Cambridge, UK
- Instituto de Biomedicina de Sevilla (IBiS) HUVR/CSIC/Universidad de Sevilla/CIBERSAM, ISCIII, Dpto. de Fisiología Médica y Biofísica, Barcelona, Spain
| | | | - Sarah E Morgan
- Department of Psychiatry, University of Cambridge, Cambridge, UK
- Department of Computer Science and Technology, University of Cambridge, Cambridge, UK
- Alan Turing Institute, London, UK
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9
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Hu F, Chen AA, Horng H, Bashyam V, Davatzikos C, Alexander-Bloch A, Li M, Shou H, Satterthwaite TD, Yu M, Shinohara RT. Image harmonization: A review of statistical and deep learning methods for removing batch effects and evaluation metrics for effective harmonization. Neuroimage 2023; 274:120125. [PMID: 37084926 PMCID: PMC10257347 DOI: 10.1016/j.neuroimage.2023.120125] [Citation(s) in RCA: 13] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2023] [Revised: 04/12/2023] [Accepted: 04/19/2023] [Indexed: 04/23/2023] Open
Abstract
Magnetic resonance imaging and computed tomography from multiple batches (e.g. sites, scanners, datasets, etc.) are increasingly used alongside complex downstream analyses to obtain new insights into the human brain. However, significant confounding due to batch-related technical variation, called batch effects, is present in this data; direct application of downstream analyses to the data may lead to biased results. Image harmonization methods seek to remove these batch effects and enable increased generalizability and reproducibility of downstream results. In this review, we describe and categorize current approaches in statistical and deep learning harmonization methods. We also describe current evaluation metrics used to assess harmonization methods and provide a standardized framework to evaluate newly-proposed methods for effective harmonization and preservation of biological information. Finally, we provide recommendations to end-users to advocate for more effective use of current methods and to methodologists to direct future efforts and accelerate development of the field.
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Affiliation(s)
- Fengling Hu
- Penn Statistics in Imaging and Visualization Endeavor (PennSIVE), Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine, University of Pennsylvania, 423 Guardian Dr, Philadelphia, PA 19104, United States.
| | - Andrew A Chen
- Penn Statistics in Imaging and Visualization Endeavor (PennSIVE), Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine, University of Pennsylvania, 423 Guardian Dr, Philadelphia, PA 19104, United States
| | - Hannah Horng
- Penn Statistics in Imaging and Visualization Endeavor (PennSIVE), Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine, University of Pennsylvania, 423 Guardian Dr, Philadelphia, PA 19104, United States
| | - Vishnu Bashyam
- Center for Biomedical Image Computing and Analytics (CBICA), Perelman School of Medicine, United States
| | - Christos Davatzikos
- Center for Biomedical Image Computing and Analytics (CBICA), Perelman School of Medicine, United States
| | - Aaron Alexander-Bloch
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, United States; Penn-CHOP Lifespan Brain Institute, United States; Department of Child and Adolescent Psychiatry and Behavioral Science, Children's Hospital of Philadelphia, United States
| | - Mingyao Li
- Statistical Center for Single-Cell and Spatial Genomics, Perelman School of Medicine, University of Pennsylvania, United States
| | - Haochang Shou
- Penn Statistics in Imaging and Visualization Endeavor (PennSIVE), Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine, University of Pennsylvania, 423 Guardian Dr, Philadelphia, PA 19104, United States; Center for Biomedical Image Computing and Analytics (CBICA), Perelman School of Medicine, United States
| | - Theodore D Satterthwaite
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, United States; Penn-CHOP Lifespan Brain Institute, United States; The Penn Lifespan Informatics and Neuroimaging Center, Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, United States
| | - Meichen Yu
- Indiana Alzheimer's Disease Research Center, Indiana University School of Medicine, United States
| | - Russell T Shinohara
- Penn Statistics in Imaging and Visualization Endeavor (PennSIVE), Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine, University of Pennsylvania, 423 Guardian Dr, Philadelphia, PA 19104, United States; Center for Biomedical Image Computing and Analytics (CBICA), Perelman School of Medicine, United States
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10
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Murtha K, Larsen B, Pines A, Parkes L, Moore TM, Adebimpe A, Bertolero M, Alexander-Bloch A, Calkins ME, Davila DG, Lindquist MA, Mackey AP, Roalf DR, Scott JC, Wolf DH, Gur RC, Gur RE, Barzilay R, Satterthwaite TD. Associations between neighborhood socioeconomic status, parental education, and executive system activation in youth. Cereb Cortex 2023; 33:1058-1073. [PMID: 35348659 PMCID: PMC9930626 DOI: 10.1093/cercor/bhac120] [Citation(s) in RCA: 9] [Impact Index Per Article: 9.0] [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: 08/12/2021] [Revised: 02/16/2022] [Accepted: 02/17/2022] [Indexed: 11/13/2022] Open
Abstract
Socioeconomic status (SES) can impact cognitive performance, including working memory (WM). As executive systems that support WM undergo functional neurodevelopment during adolescence, environmental stressors at both individual and community levels may influence cognitive outcomes. Here, we sought to examine how SES at the neighborhood and family level impacts task-related activation of the executive system during adolescence and determine whether this effect mediates the relationship between SES and WM performance. To address these questions, we studied 1,150 youths (age 8-23) that completed a fractal n-back WM task during functional magnetic resonance imaging at 3T as part of the Philadelphia Neurodevelopmental Cohort. We found that both higher neighborhood SES and parental education were associated with greater activation of the executive system to WM load, including the bilateral dorsolateral prefrontal cortex, posterior parietal cortex, and precuneus. The association of neighborhood SES remained significant when controlling for task performance, or related factors like exposure to traumatic events. Furthermore, high-dimensional multivariate mediation analysis identified distinct patterns of brain activity within the executive system that significantly mediated the relationship between measures of SES and task performance. These findings underscore the importance of multilevel environmental factors in shaping executive system function and WM in youth.
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Affiliation(s)
- Kristin Murtha
- Neurodevelopment and Psychosis Section, Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
- Lifespan Brain Institute, Children's Hospital of Philadelphia and Perleman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
- Lifespan Informatics and Neuroimaging Center, Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Bart Larsen
- Neurodevelopment and Psychosis Section, Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
- Lifespan Brain Institute, Children's Hospital of Philadelphia and Perleman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
- Lifespan Informatics and Neuroimaging Center, Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Adam Pines
- Neurodevelopment and Psychosis Section, Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
- Lifespan Brain Institute, Children's Hospital of Philadelphia and Perleman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
- Lifespan Informatics and Neuroimaging Center, Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Linden Parkes
- Neurodevelopment and Psychosis Section, Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
- Department of Bioengineering, School of Engineering & Applied Science, University of Philadelphia, Philadelphia, PA 19104, USA
| | - Tyler M Moore
- Neurodevelopment and Psychosis Section, Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
- Lifespan Brain Institute, Children's Hospital of Philadelphia and Perleman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Azeez Adebimpe
- Neurodevelopment and Psychosis Section, Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
- Lifespan Brain Institute, Children's Hospital of Philadelphia and Perleman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
- Lifespan Informatics and Neuroimaging Center, Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Maxwell Bertolero
- Neurodevelopment and Psychosis Section, Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
- Lifespan Brain Institute, Children's Hospital of Philadelphia and Perleman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
- Lifespan Informatics and Neuroimaging Center, Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Aaron Alexander-Bloch
- Neurodevelopment and Psychosis Section, Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
- Lifespan Brain Institute, Children's Hospital of Philadelphia and Perleman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Monica E Calkins
- Neurodevelopment and Psychosis Section, Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
- Lifespan Brain Institute, Children's Hospital of Philadelphia and Perleman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Diego G Davila
- Neurodevelopment and Psychosis Section, Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
- Lifespan Brain Institute, Children's Hospital of Philadelphia and Perleman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
- Lifespan Informatics and Neuroimaging Center, Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Martin A Lindquist
- Department of Biostatistics, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD 21205, USA
| | - Allyson P Mackey
- Department of Psychology, College of Arts and Sciences, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - David R Roalf
- Neurodevelopment and Psychosis Section, Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
- Lifespan Brain Institute, Children's Hospital of Philadelphia and Perleman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - James C Scott
- Neurodevelopment and Psychosis Section, Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
- Lifespan Brain Institute, Children's Hospital of Philadelphia and Perleman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Daniel H Wolf
- Neurodevelopment and Psychosis Section, Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
- Lifespan Brain Institute, Children's Hospital of Philadelphia and Perleman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Ruben C Gur
- Neurodevelopment and Psychosis Section, Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
- Lifespan Brain Institute, Children's Hospital of Philadelphia and Perleman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
- Department of Child and Adolescent Psychiatry and Behavioral Sciences, Children’s Hospital of Philadelphia, Philadelphia, PA 19104, USA
| | - Raquel E Gur
- Neurodevelopment and Psychosis Section, Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
- Lifespan Brain Institute, Children's Hospital of Philadelphia and Perleman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
- Department of Child and Adolescent Psychiatry and Behavioral Sciences, Children’s Hospital of Philadelphia, Philadelphia, PA 19104, USA
| | - Ran Barzilay
- Neurodevelopment and Psychosis Section, Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
- Lifespan Brain Institute, Children's Hospital of Philadelphia and Perleman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
- Department of Child and Adolescent Psychiatry and Behavioral Sciences, Children’s Hospital of Philadelphia, Philadelphia, PA 19104, USA
| | - Theodore D Satterthwaite
- Neurodevelopment and Psychosis Section, Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
- Lifespan Brain Institute, Children's Hospital of Philadelphia and Perleman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
- Lifespan Informatics and Neuroimaging Center, Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
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11
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Schmitt JE, DeBevits JJ, Roalf DR, Ruparel K, Gallagher RS, Gur RC, Alexander-Bloch A, Eom TY, Alam S, Steinberg J, Akers W, Khairy K, Crowley TB, Emanuel B, Zakharenko SS, McDonald-McGinn DM, Gur RE. A Comprehensive Analysis of Cerebellar Volumes in the 22q11.2 Deletion Syndrome. Biol Psychiatry Cogn Neurosci Neuroimaging 2023; 8:79-90. [PMID: 34848384 PMCID: PMC9162086 DOI: 10.1016/j.bpsc.2021.11.008] [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] [Subscribe] [Scholar Register] [Received: 05/13/2021] [Revised: 10/12/2021] [Accepted: 11/08/2021] [Indexed: 01/17/2023]
Abstract
BACKGROUND The presence of a 22q11.2 microdeletion (22q11.2 deletion syndrome [22q11DS]) ranks among the greatest known genetic risk factors for the development of psychotic disorders. There is emerging evidence that the cerebellum is important in the pathophysiology of psychosis. However, there is currently limited information on cerebellar neuroanatomy in 22q11DS specifically. METHODS High-resolution 3T magnetic resonance imaging was acquired in 79 individuals with 22q11DS and 70 typically developing control subjects (N = 149). Lobar and lobule-level cerebellar volumes were estimated using validated automated segmentation algorithms, and subsequently group differences were compared. Hierarchical clustering, principal component analysis, and graph theoretical models were used to explore intercerebellar relationships. Cerebrocerebellar structural connectivity with cortical thickness was examined via linear regression models. RESULTS Individuals with 22q11DS had, on average, 17.3% smaller total cerebellar volumes relative to typically developing subjects (p < .0001). The lobules of the superior posterior cerebellum (e.g., VII and VIII) were particularly affected in 22q11DS. However, all cerebellar lobules were significantly smaller, even after adjusting for total brain volumes (all cerebellar lobules p < .0002). The superior posterior lobule was disproportionately associated with cortical thickness in the frontal lobes and cingulate cortex, brain regions known be affected in 22q11DS. Exploratory analyses suggested that the superior posterior lobule, particularly Crus I, may be associated with psychotic symptoms in 22q11DS. CONCLUSIONS The cerebellum is a critical but understudied component of the 22q11DS neuroendophenotype.
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Affiliation(s)
- J Eric Schmitt
- Brain Behavior Laboratory, Neurodevelopment and Psychosis Section, Department of Psychiatry, Philadelphia, Pennsylvania; Division of Neuroradiology, Department of Radiology, Hospital of the University of Pennsylvania, Philadelphia, Pennsylvania.
| | - John J DeBevits
- Division of Neuroradiology, Department of Radiology, Hospital of the University of Pennsylvania, Philadelphia, Pennsylvania
| | - David R Roalf
- Brain Behavior Laboratory, Neurodevelopment and Psychosis Section, Department of Psychiatry, Philadelphia, Pennsylvania
| | - Kosha Ruparel
- Brain Behavior Laboratory, Neurodevelopment and Psychosis Section, Department of Psychiatry, Philadelphia, Pennsylvania
| | - R Sean Gallagher
- Brain Behavior Laboratory, Neurodevelopment and Psychosis Section, Department of Psychiatry, Philadelphia, Pennsylvania
| | - Ruben C Gur
- Brain Behavior Laboratory, Neurodevelopment and Psychosis Section, Department of Psychiatry, Philadelphia, Pennsylvania
| | - Aaron Alexander-Bloch
- Brain Behavior Laboratory, Neurodevelopment and Psychosis Section, Department of Psychiatry, Philadelphia, Pennsylvania
| | - Tae-Yeon Eom
- Department of Developmental Neurobiology, St. Jude Children's Research Hospital, Memphis, Tennessee
| | - Shahinur Alam
- Center for Bioimage Informatics, St. Jude Children's Research Hospital, Memphis, Tennessee
| | - Jeffrey Steinberg
- Center for Bioimage Informatics, St. Jude Children's Research Hospital, Memphis, Tennessee
| | - Walter Akers
- Center for Bioimage Informatics, St. Jude Children's Research Hospital, Memphis, Tennessee
| | - Khaled Khairy
- Center for In Vivo Imaging and Therapeutics, St. Jude Children's Research Hospital, Memphis, Tennessee
| | - T Blaine Crowley
- Division of Human Genetics, Children's Hospital of Philadelphia, Philadelphia, Pennsylvania
| | - Beverly Emanuel
- Department of Pediatrics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania; Division of Human Genetics, Children's Hospital of Philadelphia, Philadelphia, Pennsylvania
| | - Stanislav S Zakharenko
- Department of Developmental Neurobiology, St. Jude Children's Research Hospital, Memphis, Tennessee
| | - Donna M McDonald-McGinn
- Department of Pediatrics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania; Division of Human Genetics, Children's Hospital of Philadelphia, Philadelphia, Pennsylvania
| | - Raquel E Gur
- Brain Behavior Laboratory, Neurodevelopment and Psychosis Section, Department of Psychiatry, Philadelphia, Pennsylvania; Division of Neuroradiology, Department of Radiology, Hospital of the University of Pennsylvania, Philadelphia, Pennsylvania
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Brownstein CA, Douard E, Mollon J, Smith R, Hojlo MA, Das A, Goldman M, Garvey E, Cabral K, Li J, Bowen J, Rao AS, Genetti C, Carroll D, Knowles EEM, Deaso E, Agrawal PB, Beggs AH, D'Angelo E, Almasy L, Alexander-Bloch A, Saci Z, Moreau CA, Huguet G, Deo AJ, Jacquemont S, Glahn DC, Gonzalez-Heydrich J. Similar Rates of Deleterious Copy Number Variants in Early-Onset Psychosis and Autism Spectrum Disorder. Am J Psychiatry 2022; 179:853-861. [PMID: 36000218 PMCID: PMC9633349 DOI: 10.1176/appi.ajp.21111175] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/19/2023]
Abstract
OBJECTIVE Copy number variants (CNVs) are strongly associated with neurodevelopmental and psychotic disorders. Early-onset psychosis (EOP), where symptoms appear before 18 years of age, is thought to be more strongly influenced by genetic factors than adult-onset psychotic disorders. However, the prevalence and effect of CNVs in EOP is unclear. METHODS The authors documented the prevalence of recurrent CNVs and the functional impact of deletions and duplications genome-wide in 137 children and adolescents with EOP compared with 5,540 individuals with autism spectrum disorder (ASD) and 16,504 population control subjects. Specifically, the frequency of 47 recurrent CNVs previously associated with neurodevelopmental and neuropsychiatric illnesses in each cohort were compared. Next, CNV risk scores (CRSs), indices reflecting the dosage sensitivity for any gene across the genome that is encapsulated in a deletion or duplication separately, were compared between groups. RESULTS The prevalence of recurrent CNVs was significantly higher in the EOP group than in the ASD (odds ratio=2.30) and control (odds ratio=5.06) groups. However, the difference between the EOP and ASD groups was attenuated when EOP participants with co-occurring ASD were excluded. CRS was significantly higher in the EOP group compared with the control group for both deletions (odds ratio=1.30) and duplications (odds ratio=1.09). In contrast, the EOP and ASD groups did not differ significantly in terms of CRS. CONCLUSIONS Given the high frequency of recurrent CNVs in the EOP group and comparable CRSs in the EOP and ASD groups, the findings suggest that all children and adolescents with a psychotic diagnosis should undergo genetic screening, as is recommended in ASD.
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Affiliation(s)
- Catherine A Brownstein
- Early Psychosis Investigation Center (Brownstein, Mollon, Smith, Hojlo, Knowles, Deaso, D'Angelo, Deo, Glahn, Gonzalez-Heydrich), Division of Genetics and Genomics (Brownstein, Smith, Cabral, Li, Bowen, Rao, Genetti, Agrawal, Beggs, Glahn), Manton Center for Orphan Disease Research (Brownstein, Smith, Cabral, Li, Bowen, Genetti, Agrawal, Beggs, Glahn), Department of Psychiatry and Behavioral Sciences (Mollon, Hojlo, Das, Goldman, Garvey, Carroll, Knowles, Deaso, D'Angelo, Deo, Glahn, Gonzalez-Heydrich), Tommy Fuss Center for Neuropsychiatric Disease Research (Deo, Glahn, Gonzalez-Heydrich), and Division of Newborn Medicine (Agrawal), Boston Children's Hospital, Boston; Department of Pediatrics (Brownstein, Smith, Genetti, Agrawal, Beggs, Deo) and Department of Psychiatry (Mollon, Carroll, Knowles, D'Angelo, Deo, Glahn, Gonzalez-Heydrich), Harvard Medical School, Boston; Department of Pediatrics (Jacquemont) and Department of Neuroscience (Douard, Moreau), Université de Montréal, Montreal; Sainte-Justine Hospital Research Center, Montreal (Douard, Saci, Moreau, Huguet, Jacquemont); Department of Biomedical and Health Informatics (Almasy) and Department of Psychiatry (Alexander-Bloch), Children's Hospital of Philadelphia, Philadelphia; Department of Psychiatry, Rutgers-Robert Wood Johnson Medical School, Piscataway, N.J. (Deo); Rutgers University Behavioral Health Care, Piscataway, N.J. (Deo). Lifespan Brain Institute, Children's Hospital of Philadelphia, Philadelphia (Almasy); Department of Genetics, University of Pennsylvania, Philadelphia (Almasy); Department of Pharmacology, Feinberg School of Medicine, Northwestern University, Chicago (Smith)
| | - Elise Douard
- Early Psychosis Investigation Center (Brownstein, Mollon, Smith, Hojlo, Knowles, Deaso, D'Angelo, Deo, Glahn, Gonzalez-Heydrich), Division of Genetics and Genomics (Brownstein, Smith, Cabral, Li, Bowen, Rao, Genetti, Agrawal, Beggs, Glahn), Manton Center for Orphan Disease Research (Brownstein, Smith, Cabral, Li, Bowen, Genetti, Agrawal, Beggs, Glahn), Department of Psychiatry and Behavioral Sciences (Mollon, Hojlo, Das, Goldman, Garvey, Carroll, Knowles, Deaso, D'Angelo, Deo, Glahn, Gonzalez-Heydrich), Tommy Fuss Center for Neuropsychiatric Disease Research (Deo, Glahn, Gonzalez-Heydrich), and Division of Newborn Medicine (Agrawal), Boston Children's Hospital, Boston; Department of Pediatrics (Brownstein, Smith, Genetti, Agrawal, Beggs, Deo) and Department of Psychiatry (Mollon, Carroll, Knowles, D'Angelo, Deo, Glahn, Gonzalez-Heydrich), Harvard Medical School, Boston; Department of Pediatrics (Jacquemont) and Department of Neuroscience (Douard, Moreau), Université de Montréal, Montreal; Sainte-Justine Hospital Research Center, Montreal (Douard, Saci, Moreau, Huguet, Jacquemont); Department of Biomedical and Health Informatics (Almasy) and Department of Psychiatry (Alexander-Bloch), Children's Hospital of Philadelphia, Philadelphia; Department of Psychiatry, Rutgers-Robert Wood Johnson Medical School, Piscataway, N.J. (Deo); Rutgers University Behavioral Health Care, Piscataway, N.J. (Deo). Lifespan Brain Institute, Children's Hospital of Philadelphia, Philadelphia (Almasy); Department of Genetics, University of Pennsylvania, Philadelphia (Almasy); Department of Pharmacology, Feinberg School of Medicine, Northwestern University, Chicago (Smith)
| | - Josephine Mollon
- Early Psychosis Investigation Center (Brownstein, Mollon, Smith, Hojlo, Knowles, Deaso, D'Angelo, Deo, Glahn, Gonzalez-Heydrich), Division of Genetics and Genomics (Brownstein, Smith, Cabral, Li, Bowen, Rao, Genetti, Agrawal, Beggs, Glahn), Manton Center for Orphan Disease Research (Brownstein, Smith, Cabral, Li, Bowen, Genetti, Agrawal, Beggs, Glahn), Department of Psychiatry and Behavioral Sciences (Mollon, Hojlo, Das, Goldman, Garvey, Carroll, Knowles, Deaso, D'Angelo, Deo, Glahn, Gonzalez-Heydrich), Tommy Fuss Center for Neuropsychiatric Disease Research (Deo, Glahn, Gonzalez-Heydrich), and Division of Newborn Medicine (Agrawal), Boston Children's Hospital, Boston; Department of Pediatrics (Brownstein, Smith, Genetti, Agrawal, Beggs, Deo) and Department of Psychiatry (Mollon, Carroll, Knowles, D'Angelo, Deo, Glahn, Gonzalez-Heydrich), Harvard Medical School, Boston; Department of Pediatrics (Jacquemont) and Department of Neuroscience (Douard, Moreau), Université de Montréal, Montreal; Sainte-Justine Hospital Research Center, Montreal (Douard, Saci, Moreau, Huguet, Jacquemont); Department of Biomedical and Health Informatics (Almasy) and Department of Psychiatry (Alexander-Bloch), Children's Hospital of Philadelphia, Philadelphia; Department of Psychiatry, Rutgers-Robert Wood Johnson Medical School, Piscataway, N.J. (Deo); Rutgers University Behavioral Health Care, Piscataway, N.J. (Deo). Lifespan Brain Institute, Children's Hospital of Philadelphia, Philadelphia (Almasy); Department of Genetics, University of Pennsylvania, Philadelphia (Almasy); Department of Pharmacology, Feinberg School of Medicine, Northwestern University, Chicago (Smith)
| | - Richard Smith
- Early Psychosis Investigation Center (Brownstein, Mollon, Smith, Hojlo, Knowles, Deaso, D'Angelo, Deo, Glahn, Gonzalez-Heydrich), Division of Genetics and Genomics (Brownstein, Smith, Cabral, Li, Bowen, Rao, Genetti, Agrawal, Beggs, Glahn), Manton Center for Orphan Disease Research (Brownstein, Smith, Cabral, Li, Bowen, Genetti, Agrawal, Beggs, Glahn), Department of Psychiatry and Behavioral Sciences (Mollon, Hojlo, Das, Goldman, Garvey, Carroll, Knowles, Deaso, D'Angelo, Deo, Glahn, Gonzalez-Heydrich), Tommy Fuss Center for Neuropsychiatric Disease Research (Deo, Glahn, Gonzalez-Heydrich), and Division of Newborn Medicine (Agrawal), Boston Children's Hospital, Boston; Department of Pediatrics (Brownstein, Smith, Genetti, Agrawal, Beggs, Deo) and Department of Psychiatry (Mollon, Carroll, Knowles, D'Angelo, Deo, Glahn, Gonzalez-Heydrich), Harvard Medical School, Boston; Department of Pediatrics (Jacquemont) and Department of Neuroscience (Douard, Moreau), Université de Montréal, Montreal; Sainte-Justine Hospital Research Center, Montreal (Douard, Saci, Moreau, Huguet, Jacquemont); Department of Biomedical and Health Informatics (Almasy) and Department of Psychiatry (Alexander-Bloch), Children's Hospital of Philadelphia, Philadelphia; Department of Psychiatry, Rutgers-Robert Wood Johnson Medical School, Piscataway, N.J. (Deo); Rutgers University Behavioral Health Care, Piscataway, N.J. (Deo). Lifespan Brain Institute, Children's Hospital of Philadelphia, Philadelphia (Almasy); Department of Genetics, University of Pennsylvania, Philadelphia (Almasy); Department of Pharmacology, Feinberg School of Medicine, Northwestern University, Chicago (Smith)
| | - Margaret A Hojlo
- Early Psychosis Investigation Center (Brownstein, Mollon, Smith, Hojlo, Knowles, Deaso, D'Angelo, Deo, Glahn, Gonzalez-Heydrich), Division of Genetics and Genomics (Brownstein, Smith, Cabral, Li, Bowen, Rao, Genetti, Agrawal, Beggs, Glahn), Manton Center for Orphan Disease Research (Brownstein, Smith, Cabral, Li, Bowen, Genetti, Agrawal, Beggs, Glahn), Department of Psychiatry and Behavioral Sciences (Mollon, Hojlo, Das, Goldman, Garvey, Carroll, Knowles, Deaso, D'Angelo, Deo, Glahn, Gonzalez-Heydrich), Tommy Fuss Center for Neuropsychiatric Disease Research (Deo, Glahn, Gonzalez-Heydrich), and Division of Newborn Medicine (Agrawal), Boston Children's Hospital, Boston; Department of Pediatrics (Brownstein, Smith, Genetti, Agrawal, Beggs, Deo) and Department of Psychiatry (Mollon, Carroll, Knowles, D'Angelo, Deo, Glahn, Gonzalez-Heydrich), Harvard Medical School, Boston; Department of Pediatrics (Jacquemont) and Department of Neuroscience (Douard, Moreau), Université de Montréal, Montreal; Sainte-Justine Hospital Research Center, Montreal (Douard, Saci, Moreau, Huguet, Jacquemont); Department of Biomedical and Health Informatics (Almasy) and Department of Psychiatry (Alexander-Bloch), Children's Hospital of Philadelphia, Philadelphia; Department of Psychiatry, Rutgers-Robert Wood Johnson Medical School, Piscataway, N.J. (Deo); Rutgers University Behavioral Health Care, Piscataway, N.J. (Deo). Lifespan Brain Institute, Children's Hospital of Philadelphia, Philadelphia (Almasy); Department of Genetics, University of Pennsylvania, Philadelphia (Almasy); Department of Pharmacology, Feinberg School of Medicine, Northwestern University, Chicago (Smith)
| | - Ananth Das
- Early Psychosis Investigation Center (Brownstein, Mollon, Smith, Hojlo, Knowles, Deaso, D'Angelo, Deo, Glahn, Gonzalez-Heydrich), Division of Genetics and Genomics (Brownstein, Smith, Cabral, Li, Bowen, Rao, Genetti, Agrawal, Beggs, Glahn), Manton Center for Orphan Disease Research (Brownstein, Smith, Cabral, Li, Bowen, Genetti, Agrawal, Beggs, Glahn), Department of Psychiatry and Behavioral Sciences (Mollon, Hojlo, Das, Goldman, Garvey, Carroll, Knowles, Deaso, D'Angelo, Deo, Glahn, Gonzalez-Heydrich), Tommy Fuss Center for Neuropsychiatric Disease Research (Deo, Glahn, Gonzalez-Heydrich), and Division of Newborn Medicine (Agrawal), Boston Children's Hospital, Boston; Department of Pediatrics (Brownstein, Smith, Genetti, Agrawal, Beggs, Deo) and Department of Psychiatry (Mollon, Carroll, Knowles, D'Angelo, Deo, Glahn, Gonzalez-Heydrich), Harvard Medical School, Boston; Department of Pediatrics (Jacquemont) and Department of Neuroscience (Douard, Moreau), Université de Montréal, Montreal; Sainte-Justine Hospital Research Center, Montreal (Douard, Saci, Moreau, Huguet, Jacquemont); Department of Biomedical and Health Informatics (Almasy) and Department of Psychiatry (Alexander-Bloch), Children's Hospital of Philadelphia, Philadelphia; Department of Psychiatry, Rutgers-Robert Wood Johnson Medical School, Piscataway, N.J. (Deo); Rutgers University Behavioral Health Care, Piscataway, N.J. (Deo). Lifespan Brain Institute, Children's Hospital of Philadelphia, Philadelphia (Almasy); Department of Genetics, University of Pennsylvania, Philadelphia (Almasy); Department of Pharmacology, Feinberg School of Medicine, Northwestern University, Chicago (Smith)
| | - Maria Goldman
- Early Psychosis Investigation Center (Brownstein, Mollon, Smith, Hojlo, Knowles, Deaso, D'Angelo, Deo, Glahn, Gonzalez-Heydrich), Division of Genetics and Genomics (Brownstein, Smith, Cabral, Li, Bowen, Rao, Genetti, Agrawal, Beggs, Glahn), Manton Center for Orphan Disease Research (Brownstein, Smith, Cabral, Li, Bowen, Genetti, Agrawal, Beggs, Glahn), Department of Psychiatry and Behavioral Sciences (Mollon, Hojlo, Das, Goldman, Garvey, Carroll, Knowles, Deaso, D'Angelo, Deo, Glahn, Gonzalez-Heydrich), Tommy Fuss Center for Neuropsychiatric Disease Research (Deo, Glahn, Gonzalez-Heydrich), and Division of Newborn Medicine (Agrawal), Boston Children's Hospital, Boston; Department of Pediatrics (Brownstein, Smith, Genetti, Agrawal, Beggs, Deo) and Department of Psychiatry (Mollon, Carroll, Knowles, D'Angelo, Deo, Glahn, Gonzalez-Heydrich), Harvard Medical School, Boston; Department of Pediatrics (Jacquemont) and Department of Neuroscience (Douard, Moreau), Université de Montréal, Montreal; Sainte-Justine Hospital Research Center, Montreal (Douard, Saci, Moreau, Huguet, Jacquemont); Department of Biomedical and Health Informatics (Almasy) and Department of Psychiatry (Alexander-Bloch), Children's Hospital of Philadelphia, Philadelphia; Department of Psychiatry, Rutgers-Robert Wood Johnson Medical School, Piscataway, N.J. (Deo); Rutgers University Behavioral Health Care, Piscataway, N.J. (Deo). Lifespan Brain Institute, Children's Hospital of Philadelphia, Philadelphia (Almasy); Department of Genetics, University of Pennsylvania, Philadelphia (Almasy); Department of Pharmacology, Feinberg School of Medicine, Northwestern University, Chicago (Smith)
| | - Emily Garvey
- Early Psychosis Investigation Center (Brownstein, Mollon, Smith, Hojlo, Knowles, Deaso, D'Angelo, Deo, Glahn, Gonzalez-Heydrich), Division of Genetics and Genomics (Brownstein, Smith, Cabral, Li, Bowen, Rao, Genetti, Agrawal, Beggs, Glahn), Manton Center for Orphan Disease Research (Brownstein, Smith, Cabral, Li, Bowen, Genetti, Agrawal, Beggs, Glahn), Department of Psychiatry and Behavioral Sciences (Mollon, Hojlo, Das, Goldman, Garvey, Carroll, Knowles, Deaso, D'Angelo, Deo, Glahn, Gonzalez-Heydrich), Tommy Fuss Center for Neuropsychiatric Disease Research (Deo, Glahn, Gonzalez-Heydrich), and Division of Newborn Medicine (Agrawal), Boston Children's Hospital, Boston; Department of Pediatrics (Brownstein, Smith, Genetti, Agrawal, Beggs, Deo) and Department of Psychiatry (Mollon, Carroll, Knowles, D'Angelo, Deo, Glahn, Gonzalez-Heydrich), Harvard Medical School, Boston; Department of Pediatrics (Jacquemont) and Department of Neuroscience (Douard, Moreau), Université de Montréal, Montreal; Sainte-Justine Hospital Research Center, Montreal (Douard, Saci, Moreau, Huguet, Jacquemont); Department of Biomedical and Health Informatics (Almasy) and Department of Psychiatry (Alexander-Bloch), Children's Hospital of Philadelphia, Philadelphia; Department of Psychiatry, Rutgers-Robert Wood Johnson Medical School, Piscataway, N.J. (Deo); Rutgers University Behavioral Health Care, Piscataway, N.J. (Deo). Lifespan Brain Institute, Children's Hospital of Philadelphia, Philadelphia (Almasy); Department of Genetics, University of Pennsylvania, Philadelphia (Almasy); Department of Pharmacology, Feinberg School of Medicine, Northwestern University, Chicago (Smith)
| | - Kristin Cabral
- Early Psychosis Investigation Center (Brownstein, Mollon, Smith, Hojlo, Knowles, Deaso, D'Angelo, Deo, Glahn, Gonzalez-Heydrich), Division of Genetics and Genomics (Brownstein, Smith, Cabral, Li, Bowen, Rao, Genetti, Agrawal, Beggs, Glahn), Manton Center for Orphan Disease Research (Brownstein, Smith, Cabral, Li, Bowen, Genetti, Agrawal, Beggs, Glahn), Department of Psychiatry and Behavioral Sciences (Mollon, Hojlo, Das, Goldman, Garvey, Carroll, Knowles, Deaso, D'Angelo, Deo, Glahn, Gonzalez-Heydrich), Tommy Fuss Center for Neuropsychiatric Disease Research (Deo, Glahn, Gonzalez-Heydrich), and Division of Newborn Medicine (Agrawal), Boston Children's Hospital, Boston; Department of Pediatrics (Brownstein, Smith, Genetti, Agrawal, Beggs, Deo) and Department of Psychiatry (Mollon, Carroll, Knowles, D'Angelo, Deo, Glahn, Gonzalez-Heydrich), Harvard Medical School, Boston; Department of Pediatrics (Jacquemont) and Department of Neuroscience (Douard, Moreau), Université de Montréal, Montreal; Sainte-Justine Hospital Research Center, Montreal (Douard, Saci, Moreau, Huguet, Jacquemont); Department of Biomedical and Health Informatics (Almasy) and Department of Psychiatry (Alexander-Bloch), Children's Hospital of Philadelphia, Philadelphia; Department of Psychiatry, Rutgers-Robert Wood Johnson Medical School, Piscataway, N.J. (Deo); Rutgers University Behavioral Health Care, Piscataway, N.J. (Deo). Lifespan Brain Institute, Children's Hospital of Philadelphia, Philadelphia (Almasy); Department of Genetics, University of Pennsylvania, Philadelphia (Almasy); Department of Pharmacology, Feinberg School of Medicine, Northwestern University, Chicago (Smith)
| | - Jianqiao Li
- Early Psychosis Investigation Center (Brownstein, Mollon, Smith, Hojlo, Knowles, Deaso, D'Angelo, Deo, Glahn, Gonzalez-Heydrich), Division of Genetics and Genomics (Brownstein, Smith, Cabral, Li, Bowen, Rao, Genetti, Agrawal, Beggs, Glahn), Manton Center for Orphan Disease Research (Brownstein, Smith, Cabral, Li, Bowen, Genetti, Agrawal, Beggs, Glahn), Department of Psychiatry and Behavioral Sciences (Mollon, Hojlo, Das, Goldman, Garvey, Carroll, Knowles, Deaso, D'Angelo, Deo, Glahn, Gonzalez-Heydrich), Tommy Fuss Center for Neuropsychiatric Disease Research (Deo, Glahn, Gonzalez-Heydrich), and Division of Newborn Medicine (Agrawal), Boston Children's Hospital, Boston; Department of Pediatrics (Brownstein, Smith, Genetti, Agrawal, Beggs, Deo) and Department of Psychiatry (Mollon, Carroll, Knowles, D'Angelo, Deo, Glahn, Gonzalez-Heydrich), Harvard Medical School, Boston; Department of Pediatrics (Jacquemont) and Department of Neuroscience (Douard, Moreau), Université de Montréal, Montreal; Sainte-Justine Hospital Research Center, Montreal (Douard, Saci, Moreau, Huguet, Jacquemont); Department of Biomedical and Health Informatics (Almasy) and Department of Psychiatry (Alexander-Bloch), Children's Hospital of Philadelphia, Philadelphia; Department of Psychiatry, Rutgers-Robert Wood Johnson Medical School, Piscataway, N.J. (Deo); Rutgers University Behavioral Health Care, Piscataway, N.J. (Deo). Lifespan Brain Institute, Children's Hospital of Philadelphia, Philadelphia (Almasy); Department of Genetics, University of Pennsylvania, Philadelphia (Almasy); Department of Pharmacology, Feinberg School of Medicine, Northwestern University, Chicago (Smith)
| | - Joshua Bowen
- Early Psychosis Investigation Center (Brownstein, Mollon, Smith, Hojlo, Knowles, Deaso, D'Angelo, Deo, Glahn, Gonzalez-Heydrich), Division of Genetics and Genomics (Brownstein, Smith, Cabral, Li, Bowen, Rao, Genetti, Agrawal, Beggs, Glahn), Manton Center for Orphan Disease Research (Brownstein, Smith, Cabral, Li, Bowen, Genetti, Agrawal, Beggs, Glahn), Department of Psychiatry and Behavioral Sciences (Mollon, Hojlo, Das, Goldman, Garvey, Carroll, Knowles, Deaso, D'Angelo, Deo, Glahn, Gonzalez-Heydrich), Tommy Fuss Center for Neuropsychiatric Disease Research (Deo, Glahn, Gonzalez-Heydrich), and Division of Newborn Medicine (Agrawal), Boston Children's Hospital, Boston; Department of Pediatrics (Brownstein, Smith, Genetti, Agrawal, Beggs, Deo) and Department of Psychiatry (Mollon, Carroll, Knowles, D'Angelo, Deo, Glahn, Gonzalez-Heydrich), Harvard Medical School, Boston; Department of Pediatrics (Jacquemont) and Department of Neuroscience (Douard, Moreau), Université de Montréal, Montreal; Sainte-Justine Hospital Research Center, Montreal (Douard, Saci, Moreau, Huguet, Jacquemont); Department of Biomedical and Health Informatics (Almasy) and Department of Psychiatry (Alexander-Bloch), Children's Hospital of Philadelphia, Philadelphia; Department of Psychiatry, Rutgers-Robert Wood Johnson Medical School, Piscataway, N.J. (Deo); Rutgers University Behavioral Health Care, Piscataway, N.J. (Deo). Lifespan Brain Institute, Children's Hospital of Philadelphia, Philadelphia (Almasy); Department of Genetics, University of Pennsylvania, Philadelphia (Almasy); Department of Pharmacology, Feinberg School of Medicine, Northwestern University, Chicago (Smith)
| | - Abhijit S Rao
- Early Psychosis Investigation Center (Brownstein, Mollon, Smith, Hojlo, Knowles, Deaso, D'Angelo, Deo, Glahn, Gonzalez-Heydrich), Division of Genetics and Genomics (Brownstein, Smith, Cabral, Li, Bowen, Rao, Genetti, Agrawal, Beggs, Glahn), Manton Center for Orphan Disease Research (Brownstein, Smith, Cabral, Li, Bowen, Genetti, Agrawal, Beggs, Glahn), Department of Psychiatry and Behavioral Sciences (Mollon, Hojlo, Das, Goldman, Garvey, Carroll, Knowles, Deaso, D'Angelo, Deo, Glahn, Gonzalez-Heydrich), Tommy Fuss Center for Neuropsychiatric Disease Research (Deo, Glahn, Gonzalez-Heydrich), and Division of Newborn Medicine (Agrawal), Boston Children's Hospital, Boston; Department of Pediatrics (Brownstein, Smith, Genetti, Agrawal, Beggs, Deo) and Department of Psychiatry (Mollon, Carroll, Knowles, D'Angelo, Deo, Glahn, Gonzalez-Heydrich), Harvard Medical School, Boston; Department of Pediatrics (Jacquemont) and Department of Neuroscience (Douard, Moreau), Université de Montréal, Montreal; Sainte-Justine Hospital Research Center, Montreal (Douard, Saci, Moreau, Huguet, Jacquemont); Department of Biomedical and Health Informatics (Almasy) and Department of Psychiatry (Alexander-Bloch), Children's Hospital of Philadelphia, Philadelphia; Department of Psychiatry, Rutgers-Robert Wood Johnson Medical School, Piscataway, N.J. (Deo); Rutgers University Behavioral Health Care, Piscataway, N.J. (Deo). Lifespan Brain Institute, Children's Hospital of Philadelphia, Philadelphia (Almasy); Department of Genetics, University of Pennsylvania, Philadelphia (Almasy); Department of Pharmacology, Feinberg School of Medicine, Northwestern University, Chicago (Smith)
| | - Casie Genetti
- Early Psychosis Investigation Center (Brownstein, Mollon, Smith, Hojlo, Knowles, Deaso, D'Angelo, Deo, Glahn, Gonzalez-Heydrich), Division of Genetics and Genomics (Brownstein, Smith, Cabral, Li, Bowen, Rao, Genetti, Agrawal, Beggs, Glahn), Manton Center for Orphan Disease Research (Brownstein, Smith, Cabral, Li, Bowen, Genetti, Agrawal, Beggs, Glahn), Department of Psychiatry and Behavioral Sciences (Mollon, Hojlo, Das, Goldman, Garvey, Carroll, Knowles, Deaso, D'Angelo, Deo, Glahn, Gonzalez-Heydrich), Tommy Fuss Center for Neuropsychiatric Disease Research (Deo, Glahn, Gonzalez-Heydrich), and Division of Newborn Medicine (Agrawal), Boston Children's Hospital, Boston; Department of Pediatrics (Brownstein, Smith, Genetti, Agrawal, Beggs, Deo) and Department of Psychiatry (Mollon, Carroll, Knowles, D'Angelo, Deo, Glahn, Gonzalez-Heydrich), Harvard Medical School, Boston; Department of Pediatrics (Jacquemont) and Department of Neuroscience (Douard, Moreau), Université de Montréal, Montreal; Sainte-Justine Hospital Research Center, Montreal (Douard, Saci, Moreau, Huguet, Jacquemont); Department of Biomedical and Health Informatics (Almasy) and Department of Psychiatry (Alexander-Bloch), Children's Hospital of Philadelphia, Philadelphia; Department of Psychiatry, Rutgers-Robert Wood Johnson Medical School, Piscataway, N.J. (Deo); Rutgers University Behavioral Health Care, Piscataway, N.J. (Deo). Lifespan Brain Institute, Children's Hospital of Philadelphia, Philadelphia (Almasy); Department of Genetics, University of Pennsylvania, Philadelphia (Almasy); Department of Pharmacology, Feinberg School of Medicine, Northwestern University, Chicago (Smith)
| | - Devon Carroll
- Early Psychosis Investigation Center (Brownstein, Mollon, Smith, Hojlo, Knowles, Deaso, D'Angelo, Deo, Glahn, Gonzalez-Heydrich), Division of Genetics and Genomics (Brownstein, Smith, Cabral, Li, Bowen, Rao, Genetti, Agrawal, Beggs, Glahn), Manton Center for Orphan Disease Research (Brownstein, Smith, Cabral, Li, Bowen, Genetti, Agrawal, Beggs, Glahn), Department of Psychiatry and Behavioral Sciences (Mollon, Hojlo, Das, Goldman, Garvey, Carroll, Knowles, Deaso, D'Angelo, Deo, Glahn, Gonzalez-Heydrich), Tommy Fuss Center for Neuropsychiatric Disease Research (Deo, Glahn, Gonzalez-Heydrich), and Division of Newborn Medicine (Agrawal), Boston Children's Hospital, Boston; Department of Pediatrics (Brownstein, Smith, Genetti, Agrawal, Beggs, Deo) and Department of Psychiatry (Mollon, Carroll, Knowles, D'Angelo, Deo, Glahn, Gonzalez-Heydrich), Harvard Medical School, Boston; Department of Pediatrics (Jacquemont) and Department of Neuroscience (Douard, Moreau), Université de Montréal, Montreal; Sainte-Justine Hospital Research Center, Montreal (Douard, Saci, Moreau, Huguet, Jacquemont); Department of Biomedical and Health Informatics (Almasy) and Department of Psychiatry (Alexander-Bloch), Children's Hospital of Philadelphia, Philadelphia; Department of Psychiatry, Rutgers-Robert Wood Johnson Medical School, Piscataway, N.J. (Deo); Rutgers University Behavioral Health Care, Piscataway, N.J. (Deo). Lifespan Brain Institute, Children's Hospital of Philadelphia, Philadelphia (Almasy); Department of Genetics, University of Pennsylvania, Philadelphia (Almasy); Department of Pharmacology, Feinberg School of Medicine, Northwestern University, Chicago (Smith)
| | - Emma E M Knowles
- Early Psychosis Investigation Center (Brownstein, Mollon, Smith, Hojlo, Knowles, Deaso, D'Angelo, Deo, Glahn, Gonzalez-Heydrich), Division of Genetics and Genomics (Brownstein, Smith, Cabral, Li, Bowen, Rao, Genetti, Agrawal, Beggs, Glahn), Manton Center for Orphan Disease Research (Brownstein, Smith, Cabral, Li, Bowen, Genetti, Agrawal, Beggs, Glahn), Department of Psychiatry and Behavioral Sciences (Mollon, Hojlo, Das, Goldman, Garvey, Carroll, Knowles, Deaso, D'Angelo, Deo, Glahn, Gonzalez-Heydrich), Tommy Fuss Center for Neuropsychiatric Disease Research (Deo, Glahn, Gonzalez-Heydrich), and Division of Newborn Medicine (Agrawal), Boston Children's Hospital, Boston; Department of Pediatrics (Brownstein, Smith, Genetti, Agrawal, Beggs, Deo) and Department of Psychiatry (Mollon, Carroll, Knowles, D'Angelo, Deo, Glahn, Gonzalez-Heydrich), Harvard Medical School, Boston; Department of Pediatrics (Jacquemont) and Department of Neuroscience (Douard, Moreau), Université de Montréal, Montreal; Sainte-Justine Hospital Research Center, Montreal (Douard, Saci, Moreau, Huguet, Jacquemont); Department of Biomedical and Health Informatics (Almasy) and Department of Psychiatry (Alexander-Bloch), Children's Hospital of Philadelphia, Philadelphia; Department of Psychiatry, Rutgers-Robert Wood Johnson Medical School, Piscataway, N.J. (Deo); Rutgers University Behavioral Health Care, Piscataway, N.J. (Deo). Lifespan Brain Institute, Children's Hospital of Philadelphia, Philadelphia (Almasy); Department of Genetics, University of Pennsylvania, Philadelphia (Almasy); Department of Pharmacology, Feinberg School of Medicine, Northwestern University, Chicago (Smith)
| | - Emma Deaso
- Early Psychosis Investigation Center (Brownstein, Mollon, Smith, Hojlo, Knowles, Deaso, D'Angelo, Deo, Glahn, Gonzalez-Heydrich), Division of Genetics and Genomics (Brownstein, Smith, Cabral, Li, Bowen, Rao, Genetti, Agrawal, Beggs, Glahn), Manton Center for Orphan Disease Research (Brownstein, Smith, Cabral, Li, Bowen, Genetti, Agrawal, Beggs, Glahn), Department of Psychiatry and Behavioral Sciences (Mollon, Hojlo, Das, Goldman, Garvey, Carroll, Knowles, Deaso, D'Angelo, Deo, Glahn, Gonzalez-Heydrich), Tommy Fuss Center for Neuropsychiatric Disease Research (Deo, Glahn, Gonzalez-Heydrich), and Division of Newborn Medicine (Agrawal), Boston Children's Hospital, Boston; Department of Pediatrics (Brownstein, Smith, Genetti, Agrawal, Beggs, Deo) and Department of Psychiatry (Mollon, Carroll, Knowles, D'Angelo, Deo, Glahn, Gonzalez-Heydrich), Harvard Medical School, Boston; Department of Pediatrics (Jacquemont) and Department of Neuroscience (Douard, Moreau), Université de Montréal, Montreal; Sainte-Justine Hospital Research Center, Montreal (Douard, Saci, Moreau, Huguet, Jacquemont); Department of Biomedical and Health Informatics (Almasy) and Department of Psychiatry (Alexander-Bloch), Children's Hospital of Philadelphia, Philadelphia; Department of Psychiatry, Rutgers-Robert Wood Johnson Medical School, Piscataway, N.J. (Deo); Rutgers University Behavioral Health Care, Piscataway, N.J. (Deo). Lifespan Brain Institute, Children's Hospital of Philadelphia, Philadelphia (Almasy); Department of Genetics, University of Pennsylvania, Philadelphia (Almasy); Department of Pharmacology, Feinberg School of Medicine, Northwestern University, Chicago (Smith)
| | - Pankaj B Agrawal
- Early Psychosis Investigation Center (Brownstein, Mollon, Smith, Hojlo, Knowles, Deaso, D'Angelo, Deo, Glahn, Gonzalez-Heydrich), Division of Genetics and Genomics (Brownstein, Smith, Cabral, Li, Bowen, Rao, Genetti, Agrawal, Beggs, Glahn), Manton Center for Orphan Disease Research (Brownstein, Smith, Cabral, Li, Bowen, Genetti, Agrawal, Beggs, Glahn), Department of Psychiatry and Behavioral Sciences (Mollon, Hojlo, Das, Goldman, Garvey, Carroll, Knowles, Deaso, D'Angelo, Deo, Glahn, Gonzalez-Heydrich), Tommy Fuss Center for Neuropsychiatric Disease Research (Deo, Glahn, Gonzalez-Heydrich), and Division of Newborn Medicine (Agrawal), Boston Children's Hospital, Boston; Department of Pediatrics (Brownstein, Smith, Genetti, Agrawal, Beggs, Deo) and Department of Psychiatry (Mollon, Carroll, Knowles, D'Angelo, Deo, Glahn, Gonzalez-Heydrich), Harvard Medical School, Boston; Department of Pediatrics (Jacquemont) and Department of Neuroscience (Douard, Moreau), Université de Montréal, Montreal; Sainte-Justine Hospital Research Center, Montreal (Douard, Saci, Moreau, Huguet, Jacquemont); Department of Biomedical and Health Informatics (Almasy) and Department of Psychiatry (Alexander-Bloch), Children's Hospital of Philadelphia, Philadelphia; Department of Psychiatry, Rutgers-Robert Wood Johnson Medical School, Piscataway, N.J. (Deo); Rutgers University Behavioral Health Care, Piscataway, N.J. (Deo). Lifespan Brain Institute, Children's Hospital of Philadelphia, Philadelphia (Almasy); Department of Genetics, University of Pennsylvania, Philadelphia (Almasy); Department of Pharmacology, Feinberg School of Medicine, Northwestern University, Chicago (Smith)
| | - Alan H Beggs
- Early Psychosis Investigation Center (Brownstein, Mollon, Smith, Hojlo, Knowles, Deaso, D'Angelo, Deo, Glahn, Gonzalez-Heydrich), Division of Genetics and Genomics (Brownstein, Smith, Cabral, Li, Bowen, Rao, Genetti, Agrawal, Beggs, Glahn), Manton Center for Orphan Disease Research (Brownstein, Smith, Cabral, Li, Bowen, Genetti, Agrawal, Beggs, Glahn), Department of Psychiatry and Behavioral Sciences (Mollon, Hojlo, Das, Goldman, Garvey, Carroll, Knowles, Deaso, D'Angelo, Deo, Glahn, Gonzalez-Heydrich), Tommy Fuss Center for Neuropsychiatric Disease Research (Deo, Glahn, Gonzalez-Heydrich), and Division of Newborn Medicine (Agrawal), Boston Children's Hospital, Boston; Department of Pediatrics (Brownstein, Smith, Genetti, Agrawal, Beggs, Deo) and Department of Psychiatry (Mollon, Carroll, Knowles, D'Angelo, Deo, Glahn, Gonzalez-Heydrich), Harvard Medical School, Boston; Department of Pediatrics (Jacquemont) and Department of Neuroscience (Douard, Moreau), Université de Montréal, Montreal; Sainte-Justine Hospital Research Center, Montreal (Douard, Saci, Moreau, Huguet, Jacquemont); Department of Biomedical and Health Informatics (Almasy) and Department of Psychiatry (Alexander-Bloch), Children's Hospital of Philadelphia, Philadelphia; Department of Psychiatry, Rutgers-Robert Wood Johnson Medical School, Piscataway, N.J. (Deo); Rutgers University Behavioral Health Care, Piscataway, N.J. (Deo). Lifespan Brain Institute, Children's Hospital of Philadelphia, Philadelphia (Almasy); Department of Genetics, University of Pennsylvania, Philadelphia (Almasy); Department of Pharmacology, Feinberg School of Medicine, Northwestern University, Chicago (Smith)
| | - Eugene D'Angelo
- Early Psychosis Investigation Center (Brownstein, Mollon, Smith, Hojlo, Knowles, Deaso, D'Angelo, Deo, Glahn, Gonzalez-Heydrich), Division of Genetics and Genomics (Brownstein, Smith, Cabral, Li, Bowen, Rao, Genetti, Agrawal, Beggs, Glahn), Manton Center for Orphan Disease Research (Brownstein, Smith, Cabral, Li, Bowen, Genetti, Agrawal, Beggs, Glahn), Department of Psychiatry and Behavioral Sciences (Mollon, Hojlo, Das, Goldman, Garvey, Carroll, Knowles, Deaso, D'Angelo, Deo, Glahn, Gonzalez-Heydrich), Tommy Fuss Center for Neuropsychiatric Disease Research (Deo, Glahn, Gonzalez-Heydrich), and Division of Newborn Medicine (Agrawal), Boston Children's Hospital, Boston; Department of Pediatrics (Brownstein, Smith, Genetti, Agrawal, Beggs, Deo) and Department of Psychiatry (Mollon, Carroll, Knowles, D'Angelo, Deo, Glahn, Gonzalez-Heydrich), Harvard Medical School, Boston; Department of Pediatrics (Jacquemont) and Department of Neuroscience (Douard, Moreau), Université de Montréal, Montreal; Sainte-Justine Hospital Research Center, Montreal (Douard, Saci, Moreau, Huguet, Jacquemont); Department of Biomedical and Health Informatics (Almasy) and Department of Psychiatry (Alexander-Bloch), Children's Hospital of Philadelphia, Philadelphia; Department of Psychiatry, Rutgers-Robert Wood Johnson Medical School, Piscataway, N.J. (Deo); Rutgers University Behavioral Health Care, Piscataway, N.J. (Deo). Lifespan Brain Institute, Children's Hospital of Philadelphia, Philadelphia (Almasy); Department of Genetics, University of Pennsylvania, Philadelphia (Almasy); Department of Pharmacology, Feinberg School of Medicine, Northwestern University, Chicago (Smith)
| | - Laura Almasy
- Early Psychosis Investigation Center (Brownstein, Mollon, Smith, Hojlo, Knowles, Deaso, D'Angelo, Deo, Glahn, Gonzalez-Heydrich), Division of Genetics and Genomics (Brownstein, Smith, Cabral, Li, Bowen, Rao, Genetti, Agrawal, Beggs, Glahn), Manton Center for Orphan Disease Research (Brownstein, Smith, Cabral, Li, Bowen, Genetti, Agrawal, Beggs, Glahn), Department of Psychiatry and Behavioral Sciences (Mollon, Hojlo, Das, Goldman, Garvey, Carroll, Knowles, Deaso, D'Angelo, Deo, Glahn, Gonzalez-Heydrich), Tommy Fuss Center for Neuropsychiatric Disease Research (Deo, Glahn, Gonzalez-Heydrich), and Division of Newborn Medicine (Agrawal), Boston Children's Hospital, Boston; Department of Pediatrics (Brownstein, Smith, Genetti, Agrawal, Beggs, Deo) and Department of Psychiatry (Mollon, Carroll, Knowles, D'Angelo, Deo, Glahn, Gonzalez-Heydrich), Harvard Medical School, Boston; Department of Pediatrics (Jacquemont) and Department of Neuroscience (Douard, Moreau), Université de Montréal, Montreal; Sainte-Justine Hospital Research Center, Montreal (Douard, Saci, Moreau, Huguet, Jacquemont); Department of Biomedical and Health Informatics (Almasy) and Department of Psychiatry (Alexander-Bloch), Children's Hospital of Philadelphia, Philadelphia; Department of Psychiatry, Rutgers-Robert Wood Johnson Medical School, Piscataway, N.J. (Deo); Rutgers University Behavioral Health Care, Piscataway, N.J. (Deo). Lifespan Brain Institute, Children's Hospital of Philadelphia, Philadelphia (Almasy); Department of Genetics, University of Pennsylvania, Philadelphia (Almasy); Department of Pharmacology, Feinberg School of Medicine, Northwestern University, Chicago (Smith)
| | - Aaron Alexander-Bloch
- Early Psychosis Investigation Center (Brownstein, Mollon, Smith, Hojlo, Knowles, Deaso, D'Angelo, Deo, Glahn, Gonzalez-Heydrich), Division of Genetics and Genomics (Brownstein, Smith, Cabral, Li, Bowen, Rao, Genetti, Agrawal, Beggs, Glahn), Manton Center for Orphan Disease Research (Brownstein, Smith, Cabral, Li, Bowen, Genetti, Agrawal, Beggs, Glahn), Department of Psychiatry and Behavioral Sciences (Mollon, Hojlo, Das, Goldman, Garvey, Carroll, Knowles, Deaso, D'Angelo, Deo, Glahn, Gonzalez-Heydrich), Tommy Fuss Center for Neuropsychiatric Disease Research (Deo, Glahn, Gonzalez-Heydrich), and Division of Newborn Medicine (Agrawal), Boston Children's Hospital, Boston; Department of Pediatrics (Brownstein, Smith, Genetti, Agrawal, Beggs, Deo) and Department of Psychiatry (Mollon, Carroll, Knowles, D'Angelo, Deo, Glahn, Gonzalez-Heydrich), Harvard Medical School, Boston; Department of Pediatrics (Jacquemont) and Department of Neuroscience (Douard, Moreau), Université de Montréal, Montreal; Sainte-Justine Hospital Research Center, Montreal (Douard, Saci, Moreau, Huguet, Jacquemont); Department of Biomedical and Health Informatics (Almasy) and Department of Psychiatry (Alexander-Bloch), Children's Hospital of Philadelphia, Philadelphia; Department of Psychiatry, Rutgers-Robert Wood Johnson Medical School, Piscataway, N.J. (Deo); Rutgers University Behavioral Health Care, Piscataway, N.J. (Deo). Lifespan Brain Institute, Children's Hospital of Philadelphia, Philadelphia (Almasy); Department of Genetics, University of Pennsylvania, Philadelphia (Almasy); Department of Pharmacology, Feinberg School of Medicine, Northwestern University, Chicago (Smith)
| | - Zohra Saci
- Early Psychosis Investigation Center (Brownstein, Mollon, Smith, Hojlo, Knowles, Deaso, D'Angelo, Deo, Glahn, Gonzalez-Heydrich), Division of Genetics and Genomics (Brownstein, Smith, Cabral, Li, Bowen, Rao, Genetti, Agrawal, Beggs, Glahn), Manton Center for Orphan Disease Research (Brownstein, Smith, Cabral, Li, Bowen, Genetti, Agrawal, Beggs, Glahn), Department of Psychiatry and Behavioral Sciences (Mollon, Hojlo, Das, Goldman, Garvey, Carroll, Knowles, Deaso, D'Angelo, Deo, Glahn, Gonzalez-Heydrich), Tommy Fuss Center for Neuropsychiatric Disease Research (Deo, Glahn, Gonzalez-Heydrich), and Division of Newborn Medicine (Agrawal), Boston Children's Hospital, Boston; Department of Pediatrics (Brownstein, Smith, Genetti, Agrawal, Beggs, Deo) and Department of Psychiatry (Mollon, Carroll, Knowles, D'Angelo, Deo, Glahn, Gonzalez-Heydrich), Harvard Medical School, Boston; Department of Pediatrics (Jacquemont) and Department of Neuroscience (Douard, Moreau), Université de Montréal, Montreal; Sainte-Justine Hospital Research Center, Montreal (Douard, Saci, Moreau, Huguet, Jacquemont); Department of Biomedical and Health Informatics (Almasy) and Department of Psychiatry (Alexander-Bloch), Children's Hospital of Philadelphia, Philadelphia; Department of Psychiatry, Rutgers-Robert Wood Johnson Medical School, Piscataway, N.J. (Deo); Rutgers University Behavioral Health Care, Piscataway, N.J. (Deo). Lifespan Brain Institute, Children's Hospital of Philadelphia, Philadelphia (Almasy); Department of Genetics, University of Pennsylvania, Philadelphia (Almasy); Department of Pharmacology, Feinberg School of Medicine, Northwestern University, Chicago (Smith)
| | - Clara A Moreau
- Early Psychosis Investigation Center (Brownstein, Mollon, Smith, Hojlo, Knowles, Deaso, D'Angelo, Deo, Glahn, Gonzalez-Heydrich), Division of Genetics and Genomics (Brownstein, Smith, Cabral, Li, Bowen, Rao, Genetti, Agrawal, Beggs, Glahn), Manton Center for Orphan Disease Research (Brownstein, Smith, Cabral, Li, Bowen, Genetti, Agrawal, Beggs, Glahn), Department of Psychiatry and Behavioral Sciences (Mollon, Hojlo, Das, Goldman, Garvey, Carroll, Knowles, Deaso, D'Angelo, Deo, Glahn, Gonzalez-Heydrich), Tommy Fuss Center for Neuropsychiatric Disease Research (Deo, Glahn, Gonzalez-Heydrich), and Division of Newborn Medicine (Agrawal), Boston Children's Hospital, Boston; Department of Pediatrics (Brownstein, Smith, Genetti, Agrawal, Beggs, Deo) and Department of Psychiatry (Mollon, Carroll, Knowles, D'Angelo, Deo, Glahn, Gonzalez-Heydrich), Harvard Medical School, Boston; Department of Pediatrics (Jacquemont) and Department of Neuroscience (Douard, Moreau), Université de Montréal, Montreal; Sainte-Justine Hospital Research Center, Montreal (Douard, Saci, Moreau, Huguet, Jacquemont); Department of Biomedical and Health Informatics (Almasy) and Department of Psychiatry (Alexander-Bloch), Children's Hospital of Philadelphia, Philadelphia; Department of Psychiatry, Rutgers-Robert Wood Johnson Medical School, Piscataway, N.J. (Deo); Rutgers University Behavioral Health Care, Piscataway, N.J. (Deo). Lifespan Brain Institute, Children's Hospital of Philadelphia, Philadelphia (Almasy); Department of Genetics, University of Pennsylvania, Philadelphia (Almasy); Department of Pharmacology, Feinberg School of Medicine, Northwestern University, Chicago (Smith)
| | - Guillaume Huguet
- Early Psychosis Investigation Center (Brownstein, Mollon, Smith, Hojlo, Knowles, Deaso, D'Angelo, Deo, Glahn, Gonzalez-Heydrich), Division of Genetics and Genomics (Brownstein, Smith, Cabral, Li, Bowen, Rao, Genetti, Agrawal, Beggs, Glahn), Manton Center for Orphan Disease Research (Brownstein, Smith, Cabral, Li, Bowen, Genetti, Agrawal, Beggs, Glahn), Department of Psychiatry and Behavioral Sciences (Mollon, Hojlo, Das, Goldman, Garvey, Carroll, Knowles, Deaso, D'Angelo, Deo, Glahn, Gonzalez-Heydrich), Tommy Fuss Center for Neuropsychiatric Disease Research (Deo, Glahn, Gonzalez-Heydrich), and Division of Newborn Medicine (Agrawal), Boston Children's Hospital, Boston; Department of Pediatrics (Brownstein, Smith, Genetti, Agrawal, Beggs, Deo) and Department of Psychiatry (Mollon, Carroll, Knowles, D'Angelo, Deo, Glahn, Gonzalez-Heydrich), Harvard Medical School, Boston; Department of Pediatrics (Jacquemont) and Department of Neuroscience (Douard, Moreau), Université de Montréal, Montreal; Sainte-Justine Hospital Research Center, Montreal (Douard, Saci, Moreau, Huguet, Jacquemont); Department of Biomedical and Health Informatics (Almasy) and Department of Psychiatry (Alexander-Bloch), Children's Hospital of Philadelphia, Philadelphia; Department of Psychiatry, Rutgers-Robert Wood Johnson Medical School, Piscataway, N.J. (Deo); Rutgers University Behavioral Health Care, Piscataway, N.J. (Deo). Lifespan Brain Institute, Children's Hospital of Philadelphia, Philadelphia (Almasy); Department of Genetics, University of Pennsylvania, Philadelphia (Almasy); Department of Pharmacology, Feinberg School of Medicine, Northwestern University, Chicago (Smith)
| | - Anthony J Deo
- Early Psychosis Investigation Center (Brownstein, Mollon, Smith, Hojlo, Knowles, Deaso, D'Angelo, Deo, Glahn, Gonzalez-Heydrich), Division of Genetics and Genomics (Brownstein, Smith, Cabral, Li, Bowen, Rao, Genetti, Agrawal, Beggs, Glahn), Manton Center for Orphan Disease Research (Brownstein, Smith, Cabral, Li, Bowen, Genetti, Agrawal, Beggs, Glahn), Department of Psychiatry and Behavioral Sciences (Mollon, Hojlo, Das, Goldman, Garvey, Carroll, Knowles, Deaso, D'Angelo, Deo, Glahn, Gonzalez-Heydrich), Tommy Fuss Center for Neuropsychiatric Disease Research (Deo, Glahn, Gonzalez-Heydrich), and Division of Newborn Medicine (Agrawal), Boston Children's Hospital, Boston; Department of Pediatrics (Brownstein, Smith, Genetti, Agrawal, Beggs, Deo) and Department of Psychiatry (Mollon, Carroll, Knowles, D'Angelo, Deo, Glahn, Gonzalez-Heydrich), Harvard Medical School, Boston; Department of Pediatrics (Jacquemont) and Department of Neuroscience (Douard, Moreau), Université de Montréal, Montreal; Sainte-Justine Hospital Research Center, Montreal (Douard, Saci, Moreau, Huguet, Jacquemont); Department of Biomedical and Health Informatics (Almasy) and Department of Psychiatry (Alexander-Bloch), Children's Hospital of Philadelphia, Philadelphia; Department of Psychiatry, Rutgers-Robert Wood Johnson Medical School, Piscataway, N.J. (Deo); Rutgers University Behavioral Health Care, Piscataway, N.J. (Deo). Lifespan Brain Institute, Children's Hospital of Philadelphia, Philadelphia (Almasy); Department of Genetics, University of Pennsylvania, Philadelphia (Almasy); Department of Pharmacology, Feinberg School of Medicine, Northwestern University, Chicago (Smith)
| | - Sébastien Jacquemont
- Early Psychosis Investigation Center (Brownstein, Mollon, Smith, Hojlo, Knowles, Deaso, D'Angelo, Deo, Glahn, Gonzalez-Heydrich), Division of Genetics and Genomics (Brownstein, Smith, Cabral, Li, Bowen, Rao, Genetti, Agrawal, Beggs, Glahn), Manton Center for Orphan Disease Research (Brownstein, Smith, Cabral, Li, Bowen, Genetti, Agrawal, Beggs, Glahn), Department of Psychiatry and Behavioral Sciences (Mollon, Hojlo, Das, Goldman, Garvey, Carroll, Knowles, Deaso, D'Angelo, Deo, Glahn, Gonzalez-Heydrich), Tommy Fuss Center for Neuropsychiatric Disease Research (Deo, Glahn, Gonzalez-Heydrich), and Division of Newborn Medicine (Agrawal), Boston Children's Hospital, Boston; Department of Pediatrics (Brownstein, Smith, Genetti, Agrawal, Beggs, Deo) and Department of Psychiatry (Mollon, Carroll, Knowles, D'Angelo, Deo, Glahn, Gonzalez-Heydrich), Harvard Medical School, Boston; Department of Pediatrics (Jacquemont) and Department of Neuroscience (Douard, Moreau), Université de Montréal, Montreal; Sainte-Justine Hospital Research Center, Montreal (Douard, Saci, Moreau, Huguet, Jacquemont); Department of Biomedical and Health Informatics (Almasy) and Department of Psychiatry (Alexander-Bloch), Children's Hospital of Philadelphia, Philadelphia; Department of Psychiatry, Rutgers-Robert Wood Johnson Medical School, Piscataway, N.J. (Deo); Rutgers University Behavioral Health Care, Piscataway, N.J. (Deo). Lifespan Brain Institute, Children's Hospital of Philadelphia, Philadelphia (Almasy); Department of Genetics, University of Pennsylvania, Philadelphia (Almasy); Department of Pharmacology, Feinberg School of Medicine, Northwestern University, Chicago (Smith)
| | - David C Glahn
- Early Psychosis Investigation Center (Brownstein, Mollon, Smith, Hojlo, Knowles, Deaso, D'Angelo, Deo, Glahn, Gonzalez-Heydrich), Division of Genetics and Genomics (Brownstein, Smith, Cabral, Li, Bowen, Rao, Genetti, Agrawal, Beggs, Glahn), Manton Center for Orphan Disease Research (Brownstein, Smith, Cabral, Li, Bowen, Genetti, Agrawal, Beggs, Glahn), Department of Psychiatry and Behavioral Sciences (Mollon, Hojlo, Das, Goldman, Garvey, Carroll, Knowles, Deaso, D'Angelo, Deo, Glahn, Gonzalez-Heydrich), Tommy Fuss Center for Neuropsychiatric Disease Research (Deo, Glahn, Gonzalez-Heydrich), and Division of Newborn Medicine (Agrawal), Boston Children's Hospital, Boston; Department of Pediatrics (Brownstein, Smith, Genetti, Agrawal, Beggs, Deo) and Department of Psychiatry (Mollon, Carroll, Knowles, D'Angelo, Deo, Glahn, Gonzalez-Heydrich), Harvard Medical School, Boston; Department of Pediatrics (Jacquemont) and Department of Neuroscience (Douard, Moreau), Université de Montréal, Montreal; Sainte-Justine Hospital Research Center, Montreal (Douard, Saci, Moreau, Huguet, Jacquemont); Department of Biomedical and Health Informatics (Almasy) and Department of Psychiatry (Alexander-Bloch), Children's Hospital of Philadelphia, Philadelphia; Department of Psychiatry, Rutgers-Robert Wood Johnson Medical School, Piscataway, N.J. (Deo); Rutgers University Behavioral Health Care, Piscataway, N.J. (Deo). Lifespan Brain Institute, Children's Hospital of Philadelphia, Philadelphia (Almasy); Department of Genetics, University of Pennsylvania, Philadelphia (Almasy); Department of Pharmacology, Feinberg School of Medicine, Northwestern University, Chicago (Smith)
| | - Joseph Gonzalez-Heydrich
- Early Psychosis Investigation Center (Brownstein, Mollon, Smith, Hojlo, Knowles, Deaso, D'Angelo, Deo, Glahn, Gonzalez-Heydrich), Division of Genetics and Genomics (Brownstein, Smith, Cabral, Li, Bowen, Rao, Genetti, Agrawal, Beggs, Glahn), Manton Center for Orphan Disease Research (Brownstein, Smith, Cabral, Li, Bowen, Genetti, Agrawal, Beggs, Glahn), Department of Psychiatry and Behavioral Sciences (Mollon, Hojlo, Das, Goldman, Garvey, Carroll, Knowles, Deaso, D'Angelo, Deo, Glahn, Gonzalez-Heydrich), Tommy Fuss Center for Neuropsychiatric Disease Research (Deo, Glahn, Gonzalez-Heydrich), and Division of Newborn Medicine (Agrawal), Boston Children's Hospital, Boston; Department of Pediatrics (Brownstein, Smith, Genetti, Agrawal, Beggs, Deo) and Department of Psychiatry (Mollon, Carroll, Knowles, D'Angelo, Deo, Glahn, Gonzalez-Heydrich), Harvard Medical School, Boston; Department of Pediatrics (Jacquemont) and Department of Neuroscience (Douard, Moreau), Université de Montréal, Montreal; Sainte-Justine Hospital Research Center, Montreal (Douard, Saci, Moreau, Huguet, Jacquemont); Department of Biomedical and Health Informatics (Almasy) and Department of Psychiatry (Alexander-Bloch), Children's Hospital of Philadelphia, Philadelphia; Department of Psychiatry, Rutgers-Robert Wood Johnson Medical School, Piscataway, N.J. (Deo); Rutgers University Behavioral Health Care, Piscataway, N.J. (Deo). Lifespan Brain Institute, Children's Hospital of Philadelphia, Philadelphia (Almasy); Department of Genetics, University of Pennsylvania, Philadelphia (Almasy); Department of Pharmacology, Feinberg School of Medicine, Northwestern University, Chicago (Smith)
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Mandal AS, Gandal M, Seidlitz J, Alexander-Bloch A. A Critical Appraisal of Imaging Transcriptomics. Biol Psychiatry Glob Open Sci 2022; 2:311-313. [PMID: 36324661 PMCID: PMC9616265 DOI: 10.1016/j.bpsgos.2022.08.001] [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] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2022] [Accepted: 08/01/2022] [Indexed: 11/07/2022] Open
Affiliation(s)
- Ayan S. Mandal
- Lifespan Brain Institute, Children’s Hospital of Philadelphia and University of Pennsylvania, Philadelphia, Pennsylvania,Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania,Address correspondence to Ayan S. Mandal, Ph.D.
| | - Michael Gandal
- Lifespan Brain Institute, Children’s Hospital of Philadelphia and University of Pennsylvania, Philadelphia, Pennsylvania,Department of Genetics, University of Pennsylvania, Philadelphia, Pennsylvania,Department of Psychiatry, University of Pennsylvania, Philadelphia, Pennsylvania
| | - Jakob Seidlitz
- Lifespan Brain Institute, Children’s Hospital of Philadelphia and University of Pennsylvania, Philadelphia, Pennsylvania,Department of Genetics, University of Pennsylvania, Philadelphia, Pennsylvania,Department of Psychiatry, University of Pennsylvania, Philadelphia, Pennsylvania
| | - Aaron Alexander-Bloch
- Lifespan Brain Institute, Children’s Hospital of Philadelphia and University of Pennsylvania, Philadelphia, Pennsylvania,Department of Genetics, University of Pennsylvania, Philadelphia, Pennsylvania,Department of Psychiatry, University of Pennsylvania, Philadelphia, Pennsylvania,Department of Child and Adolescent Psychiatry and Behavioral Science, Children’s Hospital of Philadelphia, Philadelphia, Pennsylvania,Aaron Alexander-Bloch, M.D., Ph.D., M.Phil.
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14
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Shanmugan S, Seidlitz J, Cui Z, Adebimpe A, Bassett DS, Bertolero MA, Davatzikos C, Fair DA, Gur RE, Gur RC, Larsen B, Li H, Pines A, Raznahan A, Roalf DR, Shinohara RT, Vogel J, Wolf DH, Fan Y, Alexander-Bloch A, Satterthwaite TD. Sex differences in the functional topography of association networks in youth. Proc Natl Acad Sci U S A 2022; 119:e2110416119. [PMID: 35939696 PMCID: PMC9388107 DOI: 10.1073/pnas.2110416119] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [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: 06/07/2021] [Accepted: 07/15/2022] [Indexed: 01/16/2023] Open
Abstract
Prior work has shown that there is substantial interindividual variation in the spatial distribution of functional networks across the cerebral cortex, or functional topography. However, it remains unknown whether there are sex differences in the topography of individualized networks in youth. Here, we leveraged an advanced machine learning method (sparsity-regularized non-negative matrix factorization) to define individualized functional networks in 693 youth (ages 8 to 23 y) who underwent functional MRI as part of the Philadelphia Neurodevelopmental Cohort. Multivariate pattern analysis using support vector machines classified participant sex based on functional topography with 82.9% accuracy (P < 0.0001). Brain regions most effective in classifying participant sex belonged to association networks, including the ventral attention, default mode, and frontoparietal networks. Mass univariate analyses using generalized additive models with penalized splines provided convergent results. Furthermore, transcriptomic data from the Allen Human Brain Atlas revealed that sex differences in multivariate patterns of functional topography were spatially correlated with the expression of genes on the X chromosome. These results highlight the role of sex as a biological variable in shaping functional topography.
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Affiliation(s)
- Sheila Shanmugan
- Penn Lifespan Informatics and Neuroimaging Center, University of Pennsylvania, Philadelphia, PA 19104
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA 19104
- Penn-Children's Hospital of Philadelphia Lifespan Brain Institute, University of Pennsylvania, Philadelphia, PA 19104
| | - Jakob Seidlitz
- Penn Lifespan Informatics and Neuroimaging Center, University of Pennsylvania, Philadelphia, PA 19104
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA 19104
- Penn-Children's Hospital of Philadelphia Lifespan Brain Institute, University of Pennsylvania, Philadelphia, PA 19104
| | - Zaixu Cui
- Penn Lifespan Informatics and Neuroimaging Center, University of Pennsylvania, Philadelphia, PA 19104
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA 19104
- Penn-Children's Hospital of Philadelphia Lifespan Brain Institute, University of Pennsylvania, Philadelphia, PA 19104
- Chinese Institute for Brain Research, Beijing,102206, China
| | - Azeez Adebimpe
- Penn Lifespan Informatics and Neuroimaging Center, University of Pennsylvania, Philadelphia, PA 19104
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA 19104
- Penn-Children's Hospital of Philadelphia Lifespan Brain Institute, University of Pennsylvania, Philadelphia, PA 19104
| | - Danielle S. Bassett
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA 19104
- Department of Bioengineering, University of Pennsylvania, Philadelphia, PA 19104
- Department of Neurology, University of Pennsylvania, Philadelphia, PA 19104
- Department of Electrical and Systems Engineering, University of Pennsylvania, Philadelphia, PA 19104
- Department of Physics and Astronomy, University of Pennsylvania, Philadelphia, PA 19104
- Santa Fe Institute, Santa Fe, NM 87501
| | - Maxwell A. Bertolero
- Penn Lifespan Informatics and Neuroimaging Center, University of Pennsylvania, Philadelphia, PA 19104
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA 19104
- Penn-Children's Hospital of Philadelphia Lifespan Brain Institute, University of Pennsylvania, Philadelphia, PA 19104
| | - Christos Davatzikos
- Department of Bioengineering, University of Pennsylvania, Philadelphia, PA 19104
- Department of Electrical and Systems Engineering, University of Pennsylvania, Philadelphia, PA 19104
- Department of Radiology, University of Pennsylvania, Philadelphia, PA 19104
- Center for Biomedical Image Computation and Analytics, University of Pennsylvania, Philadelphia, PA 19104
| | - Damien A. Fair
- Department of Behavioral Neuroscience, Department of Psychiatry, Advanced Imaging Research Center, Oregon Health and Science University, Portland, OR 97239
| | - Raquel E. Gur
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA 19104
- Penn-Children's Hospital of Philadelphia Lifespan Brain Institute, University of Pennsylvania, Philadelphia, PA 19104
- Department of Neurology, University of Pennsylvania, Philadelphia, PA 19104
- Department of Radiology, University of Pennsylvania, Philadelphia, PA 19104
- Center for Biomedical Image Computation and Analytics, University of Pennsylvania, Philadelphia, PA 19104
| | - Ruben C. Gur
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA 19104
- Penn-Children's Hospital of Philadelphia Lifespan Brain Institute, University of Pennsylvania, Philadelphia, PA 19104
- Department of Neurology, University of Pennsylvania, Philadelphia, PA 19104
- Center for Biomedical Image Computation and Analytics, University of Pennsylvania, Philadelphia, PA 19104
| | - Bart Larsen
- Penn Lifespan Informatics and Neuroimaging Center, University of Pennsylvania, Philadelphia, PA 19104
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA 19104
- Penn-Children's Hospital of Philadelphia Lifespan Brain Institute, University of Pennsylvania, Philadelphia, PA 19104
| | - Hongming Li
- Department of Radiology, University of Pennsylvania, Philadelphia, PA 19104
- Center for Biomedical Image Computation and Analytics, University of Pennsylvania, Philadelphia, PA 19104
| | - Adam Pines
- Penn Lifespan Informatics and Neuroimaging Center, University of Pennsylvania, Philadelphia, PA 19104
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA 19104
- Penn-Children's Hospital of Philadelphia Lifespan Brain Institute, University of Pennsylvania, Philadelphia, PA 19104
| | - Armin Raznahan
- Section on Developmental Neurogenomics Unit, Intramural Research Program, National Institutes of Mental Health, Bethesda, MD 20892
| | - David R. Roalf
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA 19104
- Penn-Children's Hospital of Philadelphia Lifespan Brain Institute, University of Pennsylvania, Philadelphia, PA 19104
| | - Russell T. Shinohara
- Center for Biomedical Image Computation and Analytics, University of Pennsylvania, Philadelphia, PA 19104
- Penn Statistics in Imaging and Visualization Center, Department of Biostatistics, Epidemiology, and Informatics, University of Pennsylvania, Philadelphia, PA 19104
| | - Jacob Vogel
- Penn Lifespan Informatics and Neuroimaging Center, University of Pennsylvania, Philadelphia, PA 19104
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA 19104
- Penn-Children's Hospital of Philadelphia Lifespan Brain Institute, University of Pennsylvania, Philadelphia, PA 19104
| | - Daniel H. Wolf
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA 19104
- Penn-Children's Hospital of Philadelphia Lifespan Brain Institute, University of Pennsylvania, Philadelphia, PA 19104
- Center for Biomedical Image Computation and Analytics, University of Pennsylvania, Philadelphia, PA 19104
| | - Yong Fan
- Department of Radiology, University of Pennsylvania, Philadelphia, PA 19104
- Center for Biomedical Image Computation and Analytics, University of Pennsylvania, Philadelphia, PA 19104
| | - Aaron Alexander-Bloch
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA 19104
- Penn-Children's Hospital of Philadelphia Lifespan Brain Institute, University of Pennsylvania, Philadelphia, PA 19104
| | - Theodore D. Satterthwaite
- Penn Lifespan Informatics and Neuroimaging Center, University of Pennsylvania, Philadelphia, PA 19104
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA 19104
- Penn-Children's Hospital of Philadelphia Lifespan Brain Institute, University of Pennsylvania, Philadelphia, PA 19104
- Center for Biomedical Image Computation and Analytics, University of Pennsylvania, Philadelphia, PA 19104
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15
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Alexander-Bloch A, Huguet G, Schultz LM, Huffnagle N, Jacquemont S, Seidlitz J, Saci Z, Moore TM, Bethlehem RAI, Mollon J, Knowles EK, Raznahan A, Merikangas A, Chaiyachati BH, Raman H, Schmitt JE, Barzilay R, Calkins ME, Shinohara RT, Satterthwaite TD, Gur RC, Glahn DC, Almasy L, Gur RE, Hakonarson H, Glessner J. Copy Number Variant Risk Scores Associated With Cognition, Psychopathology, and Brain Structure in Youths in the Philadelphia Neurodevelopmental Cohort. JAMA Psychiatry 2022; 79:699-709. [PMID: 35544191 PMCID: PMC9096695 DOI: 10.1001/jamapsychiatry.2022.1017] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/21/2021] [Accepted: 03/16/2022] [Indexed: 12/23/2022]
Abstract
Importance Psychiatric and cognitive phenotypes have been associated with a range of specific, rare copy number variants (CNVs). Moreover, IQ is strongly associated with CNV risk scores that model the predicted risk of CNVs across the genome. But the utility of CNV risk scores for psychiatric phenotypes has been sparsely examined. Objective To determine how CNV risk scores, common genetic variation indexed by polygenic scores (PGSs), and environmental factors combine to associate with cognition and psychopathology in a community sample. Design, Setting, and Participants The Philadelphia Neurodevelopmental Cohort is a community-based study examining genetics, psychopathology, neurocognition, and neuroimaging. Participants were recruited through the Children's Hospital of Philadelphia pediatric network. Participants with stable health and fluency in English underwent genotypic and phenotypic characterization from November 5, 2009, through December 30, 2011. Data were analyzed from January 1 through July 30, 2021. Exposures The study examined (1) CNV risk scores derived from models of burden, predicted intolerance, and gene dosage sensitivity; (2) PGSs from genomewide association studies related to developmental outcomes; and (3) environmental factors, including trauma exposure and neighborhood socioeconomic status. Main Outcomes and Measures The study examined (1) neurocognition, with the Penn Computerized Neurocognitive Battery; (2) psychopathology, with structured interviews based on the Schedule for Affective Disorders and Schizophrenia for School-Age Children; and (3) brain volume, with magnetic resonance imaging. Results Participants included 9498 youths aged 8 to 21 years; 4906 (51.7%) were female, and the mean (SD) age was 14.2 (3.7) years. After quality control, 18 185 total CNVs greater than 50 kilobases (10 517 deletions and 7668 duplications) were identified in 7101 unrelated participants genotyped on Illumina arrays. In these participants, elevated CNV risk scores were associated with lower overall accuracy on cognitive tests (standardized β = 0.12; 95% CI, 0.10-0.14; P = 7.41 × 10-26); lower accuracy across a range of cognitive subdomains; increased overall psychopathology; increased psychosis-spectrum symptoms; and higher deviation from a normative developmental model of brain volume. Statistical models of developmental outcomes were significantly improved when CNV risk scores were combined with PGSs and environmental factors. Conclusions and Relevance In this study, elevated CNV risk scores were associated with lower cognitive ability, higher psychopathology including psychosis-spectrum symptoms, and greater deviations from normative magnetic resonance imaging models of brain development. Together, these results represent a step toward synthesizing rare genetic, common genetic, and environmental factors to understand clinically relevant outcomes in youth.
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Affiliation(s)
- Aaron Alexander-Bloch
- Department of Child and Adolescent Psychiatry and Behavioral Science, Children’s Hospital of Philadelphia, Philadelphia, Pennsylvania
- The Lifespan Brain Institute, Children’s Hospital of Philadelphia and Penn Medicine, University of Pennsylvania, Philadelphia
- Neurodevelopment and Psychosis Section, Department of Psychiatry, University of Pennsylvania, Philadelphia
| | - Guillaume Huguet
- Department of Pediatrics, University of Montreal, Montreal, Quebec, Canada
- Research Center of the Sainte-Justine University Hospital, Montreal, Quebec, Canada
| | - Laura M. Schultz
- The Lifespan Brain Institute, Children’s Hospital of Philadelphia and Penn Medicine, University of Pennsylvania, Philadelphia
- Department of Biomedical and Health Informatics, Children’s Hospital of Philadelphia, Philadelphia, Pennsylvania
| | - Nicholas Huffnagle
- Department of Child and Adolescent Psychiatry and Behavioral Science, Children’s Hospital of Philadelphia, Philadelphia, Pennsylvania
- The Lifespan Brain Institute, Children’s Hospital of Philadelphia and Penn Medicine, University of Pennsylvania, Philadelphia
| | - Sebastien Jacquemont
- Department of Pediatrics, University of Montreal, Montreal, Quebec, Canada
- Research Center of the Sainte-Justine University Hospital, Montreal, Quebec, Canada
| | - Jakob Seidlitz
- Department of Child and Adolescent Psychiatry and Behavioral Science, Children’s Hospital of Philadelphia, Philadelphia, Pennsylvania
- The Lifespan Brain Institute, Children’s Hospital of Philadelphia and Penn Medicine, University of Pennsylvania, Philadelphia
- Neurodevelopment and Psychosis Section, Department of Psychiatry, University of Pennsylvania, Philadelphia
| | - Zohra Saci
- Research Center of the Sainte-Justine University Hospital, Montreal, Quebec, Canada
| | - Tyler M. Moore
- The Lifespan Brain Institute, Children’s Hospital of Philadelphia and Penn Medicine, University of Pennsylvania, Philadelphia
- Neurodevelopment and Psychosis Section, Department of Psychiatry, University of Pennsylvania, Philadelphia
| | | | - Josephine Mollon
- Department of Psychiatry, Boston Children’s Hospital, Harvard Medical School, Boston, Massachusetts
| | - Emma K. Knowles
- Department of Psychiatry, Boston Children’s Hospital, Harvard Medical School, Boston, Massachusetts
| | - Armin Raznahan
- Section on Developmental Neurogenomics, National Institute of Mental Health, Bethesda, Maryland
| | - Alison Merikangas
- The Lifespan Brain Institute, Children’s Hospital of Philadelphia and Penn Medicine, University of Pennsylvania, Philadelphia
- Department of Biomedical and Health Informatics, Children’s Hospital of Philadelphia, Philadelphia, Pennsylvania
- Department of Genetics, University of Pennsylvania, Philadelphia
| | - Barbara H. Chaiyachati
- The Lifespan Brain Institute, Children’s Hospital of Philadelphia and Penn Medicine, University of Pennsylvania, Philadelphia
- Center for Applied Genomics, Children’s Hospital of Philadelphia, Philadelphia, Pennsylvania
- Department of Pediatrics, University of Pennsylvania, Philadelphia
| | | | - J. Eric Schmitt
- Department of Radiology, University of Pennsylvania, Philadelphia, Pennsylvania
| | - Ran Barzilay
- Department of Child and Adolescent Psychiatry and Behavioral Science, Children’s Hospital of Philadelphia, Philadelphia, Pennsylvania
- The Lifespan Brain Institute, Children’s Hospital of Philadelphia and Penn Medicine, University of Pennsylvania, Philadelphia
- Neurodevelopment and Psychosis Section, Department of Psychiatry, University of Pennsylvania, Philadelphia
| | - Monica E. Calkins
- The Lifespan Brain Institute, Children’s Hospital of Philadelphia and Penn Medicine, University of Pennsylvania, Philadelphia
- Neurodevelopment and Psychosis Section, Department of Psychiatry, University of Pennsylvania, Philadelphia
| | - Russel T. Shinohara
- Penn Statistics in Imaging and Visualization Center, University of Pennsylvania, Philadelphia
- Department of Biostatistics, Epidemiology, and Informatics, University of Pennsylvania, Philadelphia
- Penn Center for Biomedical Image Computing and Analytics, University of Pennsylvania, Philadelphia
| | - Theodore D. Satterthwaite
- The Lifespan Brain Institute, Children’s Hospital of Philadelphia and Penn Medicine, University of Pennsylvania, Philadelphia
- Neurodevelopment and Psychosis Section, Department of Psychiatry, University of Pennsylvania, Philadelphia
- Penn Lifespan Informatics and Neuroimaging Center, University of Pennsylvania, Philadelphia
| | - Ruben C. Gur
- The Lifespan Brain Institute, Children’s Hospital of Philadelphia and Penn Medicine, University of Pennsylvania, Philadelphia
- Neurodevelopment and Psychosis Section, Department of Psychiatry, University of Pennsylvania, Philadelphia
| | - David C. Glahn
- Department of Psychiatry, Boston Children’s Hospital, Harvard Medical School, Boston, Massachusetts
| | - Laura Almasy
- The Lifespan Brain Institute, Children’s Hospital of Philadelphia and Penn Medicine, University of Pennsylvania, Philadelphia
- Department of Biomedical and Health Informatics, Children’s Hospital of Philadelphia, Philadelphia, Pennsylvania
- Department of Genetics, University of Pennsylvania, Philadelphia
| | - Raquel E. Gur
- Department of Child and Adolescent Psychiatry and Behavioral Science, Children’s Hospital of Philadelphia, Philadelphia, Pennsylvania
- The Lifespan Brain Institute, Children’s Hospital of Philadelphia and Penn Medicine, University of Pennsylvania, Philadelphia
- Neurodevelopment and Psychosis Section, Department of Psychiatry, University of Pennsylvania, Philadelphia
| | - Hakon Hakonarson
- Center for Applied Genomics, Children’s Hospital of Philadelphia, Philadelphia, Pennsylvania
- Department of Pediatrics, University of Pennsylvania, Philadelphia
| | - Joseph Glessner
- Center for Applied Genomics, Children’s Hospital of Philadelphia, Philadelphia, Pennsylvania
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16
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Larsen B, Cui Z, Adebimpe A, Pines A, Alexander-Bloch A, Bertolero M, Calkins ME, Gur RE, Gur RC, Mahadevan AS, Moore TM, Roalf DR, Seidlitz J, Sydnor VJ, Wolf DH, Satterthwaite TD. A developmental reduction of the excitation:inhibition ratio in association cortex during adolescence. Sci Adv 2022; 8:eabj8750. [PMID: 35119918 PMCID: PMC8816330 DOI: 10.1126/sciadv.abj8750] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/07/2021] [Accepted: 12/13/2021] [Indexed: 06/14/2023]
Abstract
Adolescence is hypothesized to be a critical period for the development of association cortex. A reduction of the excitation:inhibition (E:I) ratio is a hallmark of critical period development; however, it has been unclear how to assess the development of the E:I ratio using noninvasive neuroimaging techniques. Here, we used pharmacological fMRI with a GABAergic benzodiazepine challenge to empirically generate a model of E:I ratio based on multivariate patterns of functional connectivity. In an independent sample of 879 youth (ages 8 to 22 years), this model predicted reductions in the E:I ratio during adolescence, which were specific to association cortex and related to psychopathology. These findings support hypothesized shifts in E:I balance of association cortices during a neurodevelopmental critical period in adolescence.
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Affiliation(s)
- Bart Larsen
- Penn Lifespan Neuroinformatics Center, University of Pennsylvania, Philadelphia, PA 19104, USA
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA 19104, USA
- Lifespan Brain Institute (LiBI) of Penn Medicine and CHOP, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Zaixu Cui
- Penn Lifespan Neuroinformatics Center, University of Pennsylvania, Philadelphia, PA 19104, USA
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA 19104, USA
- Lifespan Brain Institute (LiBI) of Penn Medicine and CHOP, University of Pennsylvania, Philadelphia, PA 19104, USA
- Chinese Institute for Brain Research, Beijing 102206, China
| | - Azeez Adebimpe
- Penn Lifespan Neuroinformatics Center, University of Pennsylvania, Philadelphia, PA 19104, USA
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA 19104, USA
- Lifespan Brain Institute (LiBI) of Penn Medicine and CHOP, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Adam Pines
- Penn Lifespan Neuroinformatics Center, University of Pennsylvania, Philadelphia, PA 19104, USA
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA 19104, USA
- Lifespan Brain Institute (LiBI) of Penn Medicine and CHOP, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Aaron Alexander-Bloch
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA 19104, USA
- Lifespan Brain Institute (LiBI) of Penn Medicine and CHOP, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Max Bertolero
- Penn Lifespan Neuroinformatics Center, University of Pennsylvania, Philadelphia, PA 19104, USA
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA 19104, USA
- Lifespan Brain Institute (LiBI) of Penn Medicine and CHOP, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Monica E. Calkins
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA 19104, USA
- Lifespan Brain Institute (LiBI) of Penn Medicine and CHOP, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Raquel E. Gur
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA 19104, USA
- Lifespan Brain Institute (LiBI) of Penn Medicine and CHOP, University of Pennsylvania, Philadelphia, PA 19104, USA
- Department of Radiology, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Ruben C. Gur
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA 19104, USA
- Lifespan Brain Institute (LiBI) of Penn Medicine and CHOP, University of Pennsylvania, Philadelphia, PA 19104, USA
- Department of Radiology, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Arun S. Mahadevan
- Department of Bioengineering, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Tyler M. Moore
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA 19104, USA
- Lifespan Brain Institute (LiBI) of Penn Medicine and CHOP, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - David R. Roalf
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA 19104, USA
- Lifespan Brain Institute (LiBI) of Penn Medicine and CHOP, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Jakob Seidlitz
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA 19104, USA
- Lifespan Brain Institute (LiBI) of Penn Medicine and CHOP, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Valerie J. Sydnor
- Penn Lifespan Neuroinformatics Center, University of Pennsylvania, Philadelphia, PA 19104, USA
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA 19104, USA
- Lifespan Brain Institute (LiBI) of Penn Medicine and CHOP, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Daniel H. Wolf
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA 19104, USA
- Lifespan Brain Institute (LiBI) of Penn Medicine and CHOP, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Theodore D. Satterthwaite
- Penn Lifespan Neuroinformatics Center, University of Pennsylvania, Philadelphia, PA 19104, USA
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA 19104, USA
- Lifespan Brain Institute (LiBI) of Penn Medicine and CHOP, University of Pennsylvania, Philadelphia, PA 19104, USA
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17
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Rodrigue AL, Mastrovito D, Esteban O, Durnez J, Koenis MMG, Janssen R, Alexander-Bloch A, Knowles EM, Mathias SR, Mollon J, Pearlson GD, Frangou S, Blangero J, Poldrack RA, Glahn DC. Searching for Imaging Biomarkers of Psychotic Dysconnectivity. Biol Psychiatry Cogn Neurosci Neuroimaging 2021; 6:1135-1144. [PMID: 33622655 PMCID: PMC8206251 DOI: 10.1016/j.bpsc.2020.12.002] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [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] [Received: 06/29/2020] [Revised: 12/08/2020] [Accepted: 12/09/2020] [Indexed: 11/19/2022]
Abstract
BACKGROUND Progress in precision psychiatry is predicated on identifying reliable individual-level diagnostic biomarkers. For psychosis, measures of structural and functional connectivity could be promising biomarkers given consistent reports of dysconnectivity across psychotic disorders using magnetic resonance imaging. METHODS We leveraged data from four independent cohorts of patients with psychosis and control subjects with observations from approximately 800 individuals. We used group-level analyses and two supervised machine learning algorithms (support vector machines and ridge regression) to test within-, between-, and across-sample classification performance of white matter and resting-state connectivity metrics. RESULTS Although we replicated group-level differences in brain connectivity, individual-level classification was suboptimal. Classification performance within samples was variable across folds (highest area under the curve [AUC] range = 0.30) and across datasets (average support vector machine AUC range = 0.50; average ridge regression AUC range = 0.18). Classification performance between samples was similarly variable or resulted in AUC values of approximately 0.65, indicating a lack of model generalizability. Furthermore, collapsing across samples (resting-state functional magnetic resonance imaging, N = 888; diffusion tensor imaging, N = 860) did not improve model performance (maximal AUC = 0.67). Ridge regression models generally outperformed support vector machine models, although classification performance was still suboptimal in terms of clinical relevance. Adjusting for demographic covariates did not greatly affect results. CONCLUSIONS Connectivity measures were not suitable as diagnostic biomarkers for psychosis as assessed in this study. Our results do not negate that other approaches may be more successful, although it is clear that a systematic approach to individual-level classification with large independent validation samples is necessary to properly vet neuroimaging features as diagnostic biomarkers.
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Affiliation(s)
- Amanda L Rodrigue
- Department of Psychiatry, Boston Children's Hospital, Harvard Medical School, Boston, Massachusetts.
| | - Dana Mastrovito
- Department of Psychology, Stanford University, Stanford, California.
| | - Oscar Esteban
- Department of Psychology, Stanford University, Stanford, California
| | - Joke Durnez
- Department of Psychology, Stanford University, Stanford, California
| | - Marinka M G Koenis
- Department of Psychiatry, Yale University School of Medicine, New Haven, Connecticut; Olin Neuropsychiatry Research Center, Institute of Living, Hartford, Connecticut
| | - Ronald Janssen
- Olin Neuropsychiatry Research Center, Institute of Living, Hartford, Connecticut
| | - Aaron Alexander-Bloch
- Department of Psychiatry, Yale University School of Medicine, New Haven, Connecticut
| | - Emma M Knowles
- Department of Psychiatry, Boston Children's Hospital, Harvard Medical School, Boston, Massachusetts
| | - Samuel R Mathias
- Department of Psychiatry, Boston Children's Hospital, Harvard Medical School, Boston, Massachusetts
| | - Josephine Mollon
- Department of Psychiatry, Boston Children's Hospital, Harvard Medical School, Boston, Massachusetts
| | - Godfrey D Pearlson
- Department of Psychiatry, Yale University School of Medicine, New Haven, Connecticut; Olin Neuropsychiatry Research Center, Institute of Living, Hartford, Connecticut
| | - Sophia Frangou
- Department of Psychiatry, Icahn School of Medicine, Mount Sinai, New York, New York; Centre for Brain Health, University of British Columbia, Vancouver, British Columbia, Canada
| | - John Blangero
- Department of Human Genetics and South Texas Diabetes and Obesity Institute, School of Medicine, University of Texas of the Rio Grande Valley, Brownsville, Texas
| | | | - David C Glahn
- Department of Psychiatry, Boston Children's Hospital, Harvard Medical School, Boston, Massachusetts; Olin Neuropsychiatry Research Center, Institute of Living, Hartford, Connecticut
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18
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Mandal A, Romero-Garcia R, Seidlitz J, Hart M, Alexander-Bloch A, Suckling J. NIMG-31. PROPOSED ORIGINS AND PATHWAYS OF DIFFUSE GLIOMAS REVEALED BY LESION COVARIANCE NETWORKS. Neuro Oncol 2021. [DOI: 10.1093/neuonc/noab196.531] [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] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Abstract
Abstract
Diffuse gliomas have been hypothesized to originate from neural stem cells in the subventricular zone and develop along previously healthy brain networks. Here, we evaluated these hypotheses by mapping independent sources of glioma localization and determining their relationships with neurogenic niches, genetic markers, and large-scale connectivity networks. Using lesion data from a total of 410 patients with high- and low-grade glioma, we identified – and replicated in an independent sample – three lesion covariance networks (LCNs), which reflect clusters of frequent glioma localization. These three LCNs overlapped with the anterior, posterior, and inferior horns of the lateral ventricles respectively, extending into the frontal, parietal, and temporal cortices. The first LCN, which overlapped with the anterior horn, was associated with low-grade, IDH-mutated/1p19q-codeleted tumors, as well as a neural transcriptomic signature and improved overall survival. Each LCN significantly coincided with multiple structural and functional connectivity networks, with LCN1 bearing an especially strong relationship with brain connectivity, consistent with its neural transcriptomic profile. Finally, we identified subcortical, periventricular structures with functional connectivity patterns to the cortex that significantly matched each LCN. These results build upon prior reports of glioma growth along white matter pathways, as well as evidence for the coordination of glioma stem cell proliferation by neuronal activity. Cumulatively, our findings support a model wherein periventricular brain connectivity guides glioma development from the subventricular zone into distributed brain regions.
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19
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Sydnor VJ, Larsen B, Bassett DS, Alexander-Bloch A, Fair DA, Liston C, Mackey AP, Milham MP, Pines A, Roalf DR, Seidlitz J, Xu T, Raznahan A, Satterthwaite TD. Neurodevelopment of the association cortices: Patterns, mechanisms, and implications for psychopathology. Neuron 2021; 109:2820-2846. [PMID: 34270921 PMCID: PMC8448958 DOI: 10.1016/j.neuron.2021.06.016] [Citation(s) in RCA: 191] [Impact Index Per Article: 63.7] [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: 03/08/2021] [Revised: 05/24/2021] [Accepted: 06/11/2021] [Indexed: 12/11/2022]
Abstract
The human brain undergoes a prolonged period of cortical development that spans multiple decades. During childhood and adolescence, cortical development progresses from lower-order, primary and unimodal cortices with sensory and motor functions to higher-order, transmodal association cortices subserving executive, socioemotional, and mentalizing functions. The spatiotemporal patterning of cortical maturation thus proceeds in a hierarchical manner, conforming to an evolutionarily rooted, sensorimotor-to-association axis of cortical organization. This developmental program has been characterized by data derived from multimodal human neuroimaging and is linked to the hierarchical unfolding of plasticity-related neurobiological events. Critically, this developmental program serves to enhance feature variation between lower-order and higher-order regions, thus endowing the brain's association cortices with unique functional properties. However, accumulating evidence suggests that protracted plasticity within late-maturing association cortices, which represents a defining feature of the human developmental program, also confers risk for diverse developmental psychopathologies.
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Affiliation(s)
- Valerie J Sydnor
- Penn Lifespan Informatics and Neuroimaging Center (PennLINC), Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA; Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Bart Larsen
- Penn Lifespan Informatics and Neuroimaging Center (PennLINC), Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA; Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Danielle S Bassett
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA; Department of Bioengineering, School of Engineering & Applied Science, University of Pennsylvania, Philadelphia, PA 19104, USA; Department of Electrical & Systems Engineering, School of Engineering & Applied Science, University of Pennsylvania, Philadelphia, PA 19104, USA; Department of Physics & Astronomy, College of Arts & Sciences, University of Pennsylvania, Philadelphia, PA 19104, USA; Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA; Santa Fe Institute, Santa Fe, NM 87501, USA
| | - Aaron Alexander-Bloch
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA; Department of Child and Adolescent Psychiatry and Behavioral Science, The Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA
| | - Damien A Fair
- Masonic Institute for the Developing Brain, Institute of Child Development, College of Education and Human Development, Department of Pediatrics, Medical School, University of Minnesota, Minneapolis, MN 55414, USA
| | - Conor Liston
- Department of Psychiatry and Brain and Mind Research Institute, Weill Cornell Medicine, New York, NY 10065, USA
| | - Allyson P Mackey
- Department of Psychology, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Michael P Milham
- Center for the Developing Brain, Child Mind Institute, New York, NY 10022, USA; Center for Biomedical Imaging and Neuromodulation, Nathan Kline Institute, Orangeburg, NY 10962, USA
| | - Adam Pines
- Penn Lifespan Informatics and Neuroimaging Center (PennLINC), Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA; Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - David R Roalf
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Jakob Seidlitz
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA; Department of Child and Adolescent Psychiatry and Behavioral Science, The Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA
| | - Ting Xu
- Center for the Developing Brain, Child Mind Institute, New York, NY 10022, USA
| | - Armin Raznahan
- Section on Developmental Neurogenomics, NIMH Intramural Research Program, NIH, Bethesda, MD 20892, USA
| | - Theodore D Satterthwaite
- Penn Lifespan Informatics and Neuroimaging Center (PennLINC), Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA; Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA; Center for Biomedical Image Computing and Analytics, University of Pennsylvania, Philadelphia, PA 19104, USA.
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20
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Xenophontos A, Seidlitz J, Liu S, Clasen LS, Blumenthal JD, Giedd JN, Alexander-Bloch A, Raznahan A. Altered Sex Chromosome Dosage Induces Coordinated Shifts in Cortical Anatomy and Anatomical Covariance. Cereb Cortex 2021; 30:2215-2228. [PMID: 31828307 DOI: 10.1093/cercor/bhz235] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [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: 01/08/2023] Open
Abstract
Sex chromosome dosage (SCD) variation increases risk for neuropsychiatric impairment, which may reflect direct SCD effects on brain organization. Here, we 1) map cumulative X- and Y-chromosome dosage effects on regional cortical thickness (CT) and investigate potential functional implications of these effects using Neurosynth, 2) test if this map is organized by patterns of CT covariance that are evident in health, and 3) characterize SCD effects on CT covariance itself. We modeled SCD effects on CT and CT covariance for 308 equally sized regions of the cortical sheet using structural neuroimaging data from 301 individuals with varying numbers of sex chromosomes (169 euploid, 132 aneuploid). Mounting SCD increased CT in the rostral frontal cortex and decreased CT in the lateral temporal cortex, bilaterally. Regions targeted by SCD were associated with social functioning, language processing, and comprehension. Cortical regions with a similar degree of SCD-sensitivity showed heightened CT covariance in health. Finally, greater SCD also increased covariance among regions similarly affected by SCD. Our study both 1) develops novel methods for comparing typical and disease-related structural covariance networks in the brain and 2) uses these techniques to resolve and identify organizing principles for SCD effects on regional cortical anatomy and anatomical covariance.
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Affiliation(s)
- Anastasia Xenophontos
- Developmental Neurogenomics Unit, Human Genetics Branch, National Institute of Mental Health, Bethesda, MD 20892, USA
| | - Jakob Seidlitz
- Developmental Neurogenomics Unit, Human Genetics Branch, National Institute of Mental Health, Bethesda, MD 20892, USA.,Department of Psychiatry, University of Cambridge, Cambridge CB2 1TN, UK
| | - Siyuan Liu
- Developmental Neurogenomics Unit, Human Genetics Branch, National Institute of Mental Health, Bethesda, MD 20892, USA
| | - Liv S Clasen
- Developmental Neurogenomics Unit, Human Genetics Branch, National Institute of Mental Health, Bethesda, MD 20892, USA
| | - Jonathan D Blumenthal
- Developmental Neurogenomics Unit, Human Genetics Branch, National Institute of Mental Health, Bethesda, MD 20892, USA
| | - Jay N Giedd
- Department of Psychiatry, University of California, La Jolla, CA 92093, USA
| | - Aaron Alexander-Bloch
- Department of Child and Adolescent Psychiatry and Behavioral Science, Children's Hospital of Philadelphia, Philadelphia, PA 19104.,Department of Psychiatry, University of Pennsylvania, Philadelphia, PA 19104
| | - Armin Raznahan
- Developmental Neurogenomics Unit, Human Genetics Branch, National Institute of Mental Health, Bethesda, MD 20892, USA
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21
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Abstract
The development of executive function is linked to maturation of prefrontal cortex (PFC) in childhood. Childhood obesity has been associated with changes in brain structure, particularly in PFC, as well as deficits in executive functions. We aimed to determine whether differences in cortical structure mediate the relationship between executive function and childhood obesity. We analyzed MR-derived measures of cortical thickness for 2700 children between the ages of 9 and 11 years, recruited as part of the NIH Adolescent Brain and Cognitive Development (ABCD) study. We related our findings to measures of executive function and body mass index (BMI). In our analysis, increased BMI was associated with significantly reduced mean cortical thickness, as well as specific bilateral reduced cortical thickness in prefrontal cortical regions. This relationship remained after accounting for age, sex, race, parental education, household income, birth-weight, and in-scanner motion. Increased BMI was also associated with lower executive function. Reduced thickness in the rostral medial and superior frontal cortex, the inferior frontal gyrus, and the lateral orbitofrontal cortex partially accounted for reductions in executive function. These results suggest that childhood obesity is associated with compromised executive function. This relationship may be partly explained by BMI-associated reduced cortical thickness in the PFC.
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Affiliation(s)
- Lisa Ronan
- Department of Psychiatry, University of Cambridge, Cambridge CB2 8HA UK
| | - Aaron Alexander-Bloch
- Department of Child and Adolescent Psychiatry and Behavioral Science, Children's Hospital of Philadelphia, PA 19104, USA
| | - Paul C Fletcher
- Department of Psychiatry, University of Cambridge, Cambridge CB2 8HA UK.,Cambridgeshire and Peterborough NHS Foundation Trust, Cambridge CB21 5EF, UK.,The Wellcome-MRC Institute of Metabolic Science-Metabolic Research Laboratories (IMS-MRL), University of Cambridge, Cambridge CB2 0QQ, UK
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22
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Gur RE, Roalf DR, Alexander-Bloch A, McDonald-McGinn DM, Gur RC. Pathways to understanding psychosis through rare - 22q11.2DS - and common variants. Curr Opin Genet Dev 2021; 68:35-40. [PMID: 33571729 PMCID: PMC8728946 DOI: 10.1016/j.gde.2021.01.007] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/14/2020] [Revised: 01/09/2021] [Accepted: 01/14/2021] [Indexed: 12/17/2022]
Abstract
The 22q11.2 Deletion Syndrome has significant impact on brain and behavior, with about 25% of individuals developing schizophrenia. The condition offers a model for prospective studies on the emergence of psychosis and advancing mechanistic hypotheses on gene-environment interactions, with magnified power for examining genome-phenome association. Here, we highlight findings that build on the International 22q11.2 Brain and Behavior Consortium and relate to several key domains in the study of psychosis-risk and schizophrenia. We examine neurocognition, olfaction and neuroimaging data that indicate similar impairment patterns in this rare syndrome and idiopathic presentation of schizophrenia. We conclude that the converging paradigms, studying psychosis dimensionally in rare and common variants samples, provide complementary approaches that will propel precision medicine in psychiatry.
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Affiliation(s)
- Raquel E Gur
- Lifespan Brain Institute, Penn Medicine and Children's Hospital of Philadelphia, the Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, and the Department of Child and Adolescent Psychiatry and Behavioral Sciences, Children's Hospital of Philadelphia, Philadelphia, PA, USA.
| | - David R Roalf
- Lifespan Brain Institute, Penn Medicine and Children's Hospital of Philadelphia, the Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, and the Department of Child and Adolescent Psychiatry and Behavioral Sciences, Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Aaron Alexander-Bloch
- Lifespan Brain Institute, Penn Medicine and Children's Hospital of Philadelphia, the Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, and the Department of Child and Adolescent Psychiatry and Behavioral Sciences, Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Donna M McDonald-McGinn
- Division of Human Genetics and 22q and You Center, Children's Hospital of Philadelphia, Department of Pediatrics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Ruben C Gur
- Lifespan Brain Institute, Penn Medicine and Children's Hospital of Philadelphia, the Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, and the Department of Child and Adolescent Psychiatry and Behavioral Sciences, Children's Hospital of Philadelphia, Philadelphia, PA, USA
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23
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Taylor JH, Appel S, Eli M, Alexander-Bloch A, Maayan L, Gur RE, Bloch MH. Time to Clinical Response in the Treatment of Early Onset Schizophrenia Spectrum Disorders Study. J Child Adolesc Psychopharmacol 2021; 31:46-52. [PMID: 32633541 PMCID: PMC7891207 DOI: 10.1089/cap.2020.0030] [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] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
Objectives: We investigated the time course of clinical response in the Treatment of Early Onset Schizophrenia Spectrum Disorders Study (TEOSS). Methods: TEOSS randomized 119 predominantly outpatient youth ages 8-19 years with schizophrenia or schizoaffective disorder to 8 weeks of treatment with molindone, risperidone, or olanzapine. We used proportional hazards regression to determine whether these three antipsychotics differed in the time until clinical response, defined as the time from treatment initiation to the point of achieving a Clinical Global Impressions-Improvement (CGI-I) scale score of 1 ("very much improved") or 2 ("much improved") that was maintained until week 8. Results: Of the 116 youth who initiated treatment, 56 (48%) achieved clinical response. Among clinical responders, the median (±interquartile range) time until clinical response was 4.0 (±4.0) weeks for olanzapine, 4.5 (±4.0) weeks for risperidone, and 6.0 (±4.0) weeks for molindone. There were no significant differences in time course for clinical response between medications (p = 0.84). Youth without symptom improvement (CGI-I ≥ 4) after 3 weeks were more likely to be clinical nonresponders at week 8 (relative risk ratio = 1.98, 95% confidence interval 1.29-3.05), compared with youth with at-least-minimal symptom improvement after 3 weeks when looking at all antipsychotics combined. Conclusion: To our knowledge, our study is the first to investigate medication differences in treatment response timing in early onset schizophrenia spectrum disorders. Clinical response times for molindone, risperidone, and olanzapine were not significantly different. Furthermore, while lack of early improvement predicted clinical nonresponse, whether or not to continue antipsychotic treatment after 3 or more weeks without symptom improvement should be based on clinical judgment after weighing potential risks, benefits, and alternatives. ClinicalTrials.gov Identifier: NCT00053703.
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Affiliation(s)
- Jerome H. Taylor
- Department of Child and Adolescent Psychiatry and Behavioral Sciences, Children's Hospital of Philadelphia, Philadelphia, Pennsylvania, USA.,Department of Psychiatry, University of Pennsylvania, Philadelphia, Pennsylvania, USA.,Address correspondence to: Jerome H. Taylor, MD, Department of Child and Adolescent Psychiatry and Behavioral Sciences, Children's Hospital of Philadelphia, 3440 Market Street, Suite 201, Philadelphia, PA 19104, USA
| | - Scott Appel
- Center for Clinical Epidemiology and Biostatistics, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Matthew Eli
- Department of Child and Adolescent Psychiatry and Behavioral Sciences, Children's Hospital of Philadelphia, Philadelphia, Pennsylvania, USA.,Department of Psychiatry, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Aaron Alexander-Bloch
- Department of Child and Adolescent Psychiatry and Behavioral Sciences, Children's Hospital of Philadelphia, Philadelphia, Pennsylvania, USA.,Department of Psychiatry, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Lawrence Maayan
- Department of Child and Adolescent Psychiatry and Behavioral Sciences, Children's Hospital of Philadelphia, Philadelphia, Pennsylvania, USA
| | - Raquel E. Gur
- Department of Child and Adolescent Psychiatry and Behavioral Sciences, Children's Hospital of Philadelphia, Philadelphia, Pennsylvania, USA.,Department of Psychiatry, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Michael H. Bloch
- Department of Psychiatry, Child Study Center, Yale University, New Haven, Connecticut, USA
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24
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Williams JC, Balasuriya L, Alexander-Bloch A, Qayyum Z. Comparing the Effectiveness of a Guide Booklet to Simulation-Based Training for Management of Acute Agitation. Psychiatr Q 2019; 90:861-869. [PMID: 31463735 DOI: 10.1007/s11126-019-09670-z] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [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] [Indexed: 01/13/2023]
Abstract
Simulation-based training may be an effective teaching modality for psychiatry residents; however, simulation-based training is an unstudied and underutilized aspect of psychiatry resident training. The objective of this study was to compare the teaching effectiveness of a simulation-based training to reading a resident on-call psychiatry guide booklet in improving the self-confidence and knowledge of residents that is necessary for managing acutely agitated patients. Pre-intervention self-confidence and knowledge were measured for all residents using a Likert scale questionnaire and a clinical vignette questionnaire, respectively. Residents (n = 23) were randomly assigned to either the simulation group (n = 12) or the guide booklet group (n = 11). Residents in the simulation group completed the simulation-based training, and residents in the guide booklet group were instructed to read the corresponding pages of the booklet regarding management of acute agitation. The comparative teaching effectiveness of the guide booklet and simulation-based training was measured with a post-intervention self-confidence questionnaire and a clinical vignette questionnaire. The study spanned approximately one academic year (July 2016- Sept 2017). Residents who participated in the simulation-based training showed significantly greater improvement in self-confidence (simulation median improvement = 1.458 vs. guide median improvement = 0.033, p = 0.002) and knowledge (simulation median improvement = 0.135 vs. guide median improvement = 0.021, p = 0.0124). Simulation-based training was more effective at improving residents' self-confidence and knowledge compared to the on-call psychiatry booklet for the management of acutely agitated patients. Though simulation is being used in other specialties, it is a very underutilized tool in the field of psychiatry. This finding underscores the potential for simulation-based training in residency programs to improve resident learning.
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Affiliation(s)
- J Corey Williams
- The Children's Hospital of Philadelphia, Department of Child & Adolescent Psychiatry and Behavioral Sciences, Philadelphia, PA, USA.
| | | | | | - Zheala Qayyum
- School of Medicine, Harvard University, Boston, MA, USA
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25
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Fineberg SK, Leavitt J, Stahl DS, Kronemer S, Landry CD, Alexander-Bloch A, Hunt LT, Corlett PR. Differential Valuation and Learning From Social and Nonsocial Cues in Borderline Personality Disorder. Biol Psychiatry 2018; 84:838-845. [PMID: 30041970 PMCID: PMC6218635 DOI: 10.1016/j.biopsych.2018.05.020] [Citation(s) in RCA: 20] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/26/2018] [Revised: 05/12/2018] [Accepted: 05/24/2018] [Indexed: 11/27/2022]
Abstract
BACKGROUND Volatile interpersonal relationships are a core feature of borderline personality disorder (BPD) and lead to devastating disruption of patients' personal and professional lives. Quantitative models of social decision making and learning hold promise for defining the underlying mechanisms of this problem. In this study, we tested BPD and control subject weighting of social versus nonsocial information and their learning about choices under stable and volatile conditions. We compared behavior using quantitative models. METHODS Subjects (n = 20 BPD, n = 23 control subjects) played an extended reward learning task with a partner (confederate) that requires learning about nonsocial and social cue reward probability (the social valuation task). Task experience was measured using language metrics: explicit emotions/beliefs, talk about the confederate, and implicit distress (using the previously established marker self-referentiality). Subjects' weighting of social and nonsocial cues was tested in mixed-effect regression models. Subjects' learning rates under stable and volatile conditions were modeled (Rescorla-Wagner approach) and group × condition interactions tested. RESULTS Compared to control subjects, BPD subject debriefings included more mentions of the confederate and less distress language. BPD subjects also weighted social cues more heavily but had blunted learning responses to (nonsocial and social) volatility. CONCLUSIONS This is the first report of patient behavior in the social valuation task. The results suggest that BPD subjects expect higher volatility than control subjects. These findings lay the groundwork for a neurocomputational dissection of social and nonsocial belief updating in BPD, which holds promise for the development of novel clinical interventions that more directly target pathophysiology.
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Affiliation(s)
- Sarah K. Fineberg
- Department of Psychiatry, Yale University, New Haven, Connecticut,Address correspondence to Sarah K. Fineberg, M.D., Ph.D., Connecticut Mental Health Center Room 518, 34 Park Street, New Haven, CT 06519.
| | - Jacob Leavitt
- Department of Psychology, University of Houston, Houston, Texas
| | - Dylan S. Stahl
- Yale Child Study Center, Yale University, New Haven, Connecticut
| | - Sharif Kronemer
- Department of Neurology, Yale University, New Haven, Connecticut
| | - Christopher D. Landry
- Columbia University College of Physicians and Surgeons, Columbia University, New York, New York
| | | | - Laurence T. Hunt
- Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, United Kingdom,Oxford Health National Health Service Foundation Trust, Oxford, United Kingdom
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26
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Akiki TJ, Averill CL, Wrocklage KM, Scott JC, Averill LA, Schweinsburg B, Alexander-Bloch A, Martini B, Southwick SM, Krystal JH, Abdallah CG. Topology of brain functional connectivity networks in posttraumatic stress disorder. Data Brief 2018; 20:1658-1675. [PMID: 30364328 PMCID: PMC6195053 DOI: 10.1016/j.dib.2018.08.198] [Citation(s) in RCA: 4] [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] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/03/2018] [Accepted: 08/23/2018] [Indexed: 12/26/2022] Open
Abstract
Here we present functional neuroimaging-based network data (focused on the default mode network) collected from a cohort of US Veterans with history of combat exposure, combined with clinical assessments for PTSD and other psychiatric comorbidities. The data has been processed and analyzed using several network construction methods (signed, thresholded, normalized to phase-randomized and rewired surrogates, functional and multimodal parcellation). An interpretation and discussion of the data can be found in the main NeuroImage article by Akiki et al. [51].
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Affiliation(s)
- Teddy J Akiki
- National Center for PTSD - Clinical Neurosciences Division, US Department of Veterans Affairs, West Haven, CT, United States.,Department of Psychiatry, Yale University School of Medicine, New Haven, CT, United States
| | - Christopher L Averill
- National Center for PTSD - Clinical Neurosciences Division, US Department of Veterans Affairs, West Haven, CT, United States.,Department of Psychiatry, Yale University School of Medicine, New Haven, CT, United States
| | - Kristen M Wrocklage
- National Center for PTSD - Clinical Neurosciences Division, US Department of Veterans Affairs, West Haven, CT, United States.,Department of Psychiatry, Yale University School of Medicine, New Haven, CT, United States.,Gaylord Specialty Healthcare, Department of Psychology, Wallingford, CT, United States
| | - J Cobb Scott
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States.,VISN4 Mental Illness Research, Education, and Clinical Center at the Philadelphia VA Medical Center, Philadelphia, PA, United States
| | - Lynnette A Averill
- National Center for PTSD - Clinical Neurosciences Division, US Department of Veterans Affairs, West Haven, CT, United States.,Department of Psychiatry, Yale University School of Medicine, New Haven, CT, United States
| | - Brian Schweinsburg
- National Center for PTSD - Clinical Neurosciences Division, US Department of Veterans Affairs, West Haven, CT, United States.,Department of Psychiatry, Yale University School of Medicine, New Haven, CT, United States
| | - Aaron Alexander-Bloch
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT, United States
| | - Brenda Martini
- National Center for PTSD - Clinical Neurosciences Division, US Department of Veterans Affairs, West Haven, CT, United States.,Department of Psychiatry, Yale University School of Medicine, New Haven, CT, United States
| | - Steven M Southwick
- National Center for PTSD - Clinical Neurosciences Division, US Department of Veterans Affairs, West Haven, CT, United States.,Department of Psychiatry, Yale University School of Medicine, New Haven, CT, United States
| | - John H Krystal
- National Center for PTSD - Clinical Neurosciences Division, US Department of Veterans Affairs, West Haven, CT, United States.,Department of Psychiatry, Yale University School of Medicine, New Haven, CT, United States
| | - Chadi G Abdallah
- National Center for PTSD - Clinical Neurosciences Division, US Department of Veterans Affairs, West Haven, CT, United States.,Department of Psychiatry, Yale University School of Medicine, New Haven, CT, United States
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27
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Váša F, Seidlitz J, Romero-Garcia R, Whitaker KJ, Rosenthal G, Vértes PE, Shinn M, Alexander-Bloch A, Fonagy P, Dolan RJ, Jones PB, Goodyer IM, Sporns O, Bullmore ET. Adolescent Tuning of Association Cortex in Human Structural Brain Networks. Cereb Cortex 2018; 28:281-294. [PMID: 29088339 PMCID: PMC5903415 DOI: 10.1093/cercor/bhx249] [Citation(s) in RCA: 144] [Impact Index Per Article: 24.0] [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: 04/19/2017] [Indexed: 12/27/2022] Open
Abstract
Motivated by prior data on local cortical shrinkage and intracortical myelination, we predicted age-related changes in topological organization of cortical structural networks during adolescence. We estimated structural correlation from magnetic resonance imaging measures of cortical thickness at 308 regions in a sample of N = 297 healthy participants, aged 14–24 years. We used a novel sliding-window analysis to measure age-related changes in network attributes globally, locally and in the context of several community partitions of the network. We found that the strength of structural correlation generally decreased as a function of age. Association cortical regions demonstrated a sharp decrease in nodal degree (hubness) from 14 years, reaching a minimum at approximately 19 years, and then levelling off or even slightly increasing until 24 years. Greater and more prolonged age-related changes in degree of cortical regions within the brain network were associated with faster rates of adolescent cortical myelination and shrinkage. The brain regions that demonstrated the greatest age-related changes were concentrated within prefrontal modules. We conclude that human adolescence is associated with biologically plausible changes in structural imaging markers of brain network organization, consistent with the concept of tuning or consolidating anatomical connectivity between frontal cortex and the rest of the connectome.
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Affiliation(s)
- František Váša
- Brain Mapping Unit, Department of Psychiatry, University of Cambridge, Cambridge CB2 0SZ, UK
| | - Jakob Seidlitz
- Brain Mapping Unit, Department of Psychiatry, University of Cambridge, Cambridge CB2 0SZ, UK.,Developmental Neurogenomics Unit, National Institute of Mental Health, Bethesda, MD 20892, USA
| | - Rafael Romero-Garcia
- Brain Mapping Unit, Department of Psychiatry, University of Cambridge, Cambridge CB2 0SZ, UK
| | - Kirstie J Whitaker
- Brain Mapping Unit, Department of Psychiatry, University of Cambridge, Cambridge CB2 0SZ, UK.,The Alan Turing Institute for Data Science, British Library, London NW1 2DB, UK
| | - Gideon Rosenthal
- Department of Brain and Cognitive Sciences, Ben-Gurion University of the Negev, PO Box 653, Beer-Sheva 8410501, Israel
| | - Petra E Vértes
- Brain Mapping Unit, Department of Psychiatry, University of Cambridge, Cambridge CB2 0SZ, UK
| | - Maxwell Shinn
- Brain Mapping Unit, Department of Psychiatry, University of Cambridge, Cambridge CB2 0SZ, UK
| | - Aaron Alexander-Bloch
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT 06511, USA
| | - Peter Fonagy
- Research Department of Clinical, Educational and Health Psychology, University College London, London WC1E 6BT, UK
| | - Raymond J Dolan
- Wellcome Trust Centre for Neuroimaging, UCL Institute of Neurology, University College London, London WC1N 3BG, UK.,Max Planck University College London Centre for Computational Psychiatry and Ageing Research, University College London, London WC1B 5EH, UK
| | - Peter B Jones
- Brain Mapping Unit, Department of Psychiatry, University of Cambridge, Cambridge CB2 0SZ, UK.,Cambridgeshire & Peterborough NHS Foundation Trust, Huntingdon PE29 3RJ, UK
| | - Ian M Goodyer
- Brain Mapping Unit, Department of Psychiatry, University of Cambridge, Cambridge CB2 0SZ, UK.,Cambridgeshire & Peterborough NHS Foundation Trust, Huntingdon PE29 3RJ, UK
| | | | - Olaf Sporns
- Department of Psychological and Brain Sciences, Indiana University, Bloomington, IN 47405, USA
| | - Edward T Bullmore
- Brain Mapping Unit, Department of Psychiatry, University of Cambridge, Cambridge CB2 0SZ, UK.,Cambridgeshire & Peterborough NHS Foundation Trust, Huntingdon PE29 3RJ, UK.,Immunology & Inflammation Therapeutic Area Unit, GlaxoSmithKline R&D, Stevenage SG1 2NY, UK
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28
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Reardon PK, Seidlitz J, Vandekar S, Liu S, Patel R, Park MTM, Alexander-Bloch A, Clasen LS, Blumenthal JD, Lalonde FM, Giedd JN, Gur RC, Gur RE, Lerch JP, Chakravarty MM, Satterthwaite TD, Shinohara RT, Raznahan A. Normative brain size variation and brain shape diversity in humans. Science 2018; 360:1222-1227. [PMID: 29853553 DOI: 10.1126/science.aar2578] [Citation(s) in RCA: 117] [Impact Index Per Article: 19.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2017] [Accepted: 04/09/2018] [Indexed: 01/09/2023]
Abstract
Brain size variation over primate evolution and human development is associated with shifts in the proportions of different brain regions. Individual brain size can vary almost twofold among typically developing humans, but the consequences of this for brain organization remain poorly understood. Using in vivo neuroimaging data from more than 3000 individuals, we find that larger human brains show greater areal expansion in distributed frontoparietal cortical networks and related subcortical regions than in limbic, sensory, and motor systems. This areal redistribution recapitulates cortical remodeling across evolution, manifests by early childhood in humans, and is linked to multiple markers of heightened metabolic cost and neuronal connectivity. Thus, human brain shape is systematically coupled to naturally occurring variations in brain size through a scaling map that integrates spatiotemporally diverse aspects of neurobiology.
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Affiliation(s)
- P K Reardon
- Developmental Neurogenomics Unit, National Institute of Mental Health, NIH, Bethesda, MD, USA.,Department of Physiology, Anatomy and Genetics, Oxford University, UK.,Vagelos College of Physicians and Surgeons, New York, NY, USA
| | - Jakob Seidlitz
- Developmental Neurogenomics Unit, National Institute of Mental Health, NIH, Bethesda, MD, USA.,Department of Psychiatry, Cambridge University, Cambridge, UK
| | - Simon Vandekar
- Department of Biostatistics, Epidemiology, and Informatics, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Siyuan Liu
- Developmental Neurogenomics Unit, National Institute of Mental Health, NIH, Bethesda, MD, USA
| | - Raihaan Patel
- Cerebral Imaging Center, Douglas Mental Health University Institute, Montreal, Quebec, Canada.,Department of Biological and Biomedical Engineering, McGill University, Montreal, Quebec, Canada
| | - Min Tae M Park
- Cerebral Imaging Center, Douglas Mental Health University Institute, Montreal, Quebec, Canada.,Schulich School of Medicine and Dentistry, Western University, London, Ontario, Canada
| | | | - Liv S Clasen
- Developmental Neurogenomics Unit, National Institute of Mental Health, NIH, Bethesda, MD, USA
| | - Jonathan D Blumenthal
- Developmental Neurogenomics Unit, National Institute of Mental Health, NIH, Bethesda, MD, USA
| | - Francois M Lalonde
- Developmental Neurogenomics Unit, National Institute of Mental Health, NIH, Bethesda, MD, USA
| | - Jay N Giedd
- Department of Psychiatry, University of California-San Diego, La Jolla, CA, USA
| | - Ruben C Gur
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Raquel E Gur
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Jason P Lerch
- Mouse Imaging Center, Hospital for Sick Children, Toronto, ON, Canada
| | - M Mallar Chakravarty
- Cerebral Imaging Center, Douglas Mental Health University Institute, Montreal, Quebec, Canada.,Department of Biological and Biomedical Engineering, McGill University, Montreal, Quebec, Canada
| | | | - Russell T Shinohara
- Department of Biostatistics, Epidemiology, and Informatics, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Armin Raznahan
- Developmental Neurogenomics Unit, National Institute of Mental Health, NIH, Bethesda, MD, USA.
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29
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Akiki TJ, Averill CL, Wrocklage KM, Scott JC, Averill LA, Schweinsburg B, Alexander-Bloch A, Martini B, Southwick SM, Krystal JH, Abdallah CG. Default mode network abnormalities in posttraumatic stress disorder: A novel network-restricted topology approach. Neuroimage 2018; 176:489-498. [PMID: 29730491 DOI: 10.1016/j.neuroimage.2018.05.005] [Citation(s) in RCA: 106] [Impact Index Per Article: 17.7] [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: 02/05/2018] [Revised: 04/15/2018] [Accepted: 05/01/2018] [Indexed: 01/23/2023] Open
Abstract
Disruption in the default mode network (DMN) has been implicated in numerous neuropsychiatric disorders, including posttraumatic stress disorder (PTSD). However, studies have largely been limited to seed-based methods and involved inconsistent definitions of the DMN. Recent advances in neuroimaging and graph theory now permit the systematic exploration of intrinsic brain networks. In this study, we used resting-state functional magnetic resonance imaging (fMRI), diffusion MRI, and graph theoretical analyses to systematically examine the DMN connectivity and its relationship with PTSD symptom severity in a cohort of 65 combat-exposed US Veterans. We employed metrics that index overall connectivity strength, network integration (global efficiency), and network segregation (clustering coefficient). Then, we conducted a modularity and network-based statistical analysis to identify DMN regions of particular importance in PTSD. Finally, structural connectivity analyses were used to probe whether white matter abnormalities are associated with the identified functional DMN changes. We found decreased DMN functional connectivity strength to be associated with increased PTSD symptom severity. Further topological characterization suggests decreased functional integration and increased segregation in subjects with severe PTSD. Modularity analyses suggest a spared connectivity in the posterior DMN community (posterior cingulate, precuneus, angular gyrus) despite overall DMN weakened connections with increasing PTSD severity. Edge-wise network-based statistical analyses revealed a prefrontal dysconnectivity. Analysis of the diffusion networks revealed no alterations in overall strength or prefrontal structural connectivity. DMN abnormalities in patients with severe PTSD symptoms are characterized by decreased overall interconnections. On a finer scale, we found a pattern of prefrontal dysconnectivity, but increased cohesiveness in the posterior DMN community and relative sparing of connectivity in this region. The DMN measures established in this study may serve as a biomarker of disease severity and could have potential utility in developing circuit-based therapeutics.
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Affiliation(s)
- Teddy J Akiki
- National Center for PTSD - Clinical Neurosciences Division, US Department of Veterans Affairs, West Haven, CT, USA; Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA
| | - Christopher L Averill
- National Center for PTSD - Clinical Neurosciences Division, US Department of Veterans Affairs, West Haven, CT, USA; Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA
| | - Kristen M Wrocklage
- National Center for PTSD - Clinical Neurosciences Division, US Department of Veterans Affairs, West Haven, CT, USA; Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA; Gaylord Specialty Healthcare, Department of Psychology, Wallingford, CT, USA
| | - J Cobb Scott
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA; VISN4 Mental Illness Research, Education, and Clinical Center at the Philadelphia VA Medical Center, Philadelphia, PA, USA
| | - Lynnette A Averill
- National Center for PTSD - Clinical Neurosciences Division, US Department of Veterans Affairs, West Haven, CT, USA; Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA
| | - Brian Schweinsburg
- National Center for PTSD - Clinical Neurosciences Division, US Department of Veterans Affairs, West Haven, CT, USA; Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA
| | | | - Brenda Martini
- National Center for PTSD - Clinical Neurosciences Division, US Department of Veterans Affairs, West Haven, CT, USA; Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA
| | - Steven M Southwick
- National Center for PTSD - Clinical Neurosciences Division, US Department of Veterans Affairs, West Haven, CT, USA; Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA
| | - John H Krystal
- National Center for PTSD - Clinical Neurosciences Division, US Department of Veterans Affairs, West Haven, CT, USA; Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA
| | - Chadi G Abdallah
- National Center for PTSD - Clinical Neurosciences Division, US Department of Veterans Affairs, West Haven, CT, USA; Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA.
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Vijayakumar N, Mills KL, Alexander-Bloch A, Tamnes CK, Whittle S. Structural brain development: A review of methodological approaches and best practices. Dev Cogn Neurosci 2017; 33:129-148. [PMID: 29221915 PMCID: PMC5963981 DOI: 10.1016/j.dcn.2017.11.008] [Citation(s) in RCA: 76] [Impact Index Per Article: 10.9] [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: 02/16/2017] [Revised: 06/05/2017] [Accepted: 11/16/2017] [Indexed: 11/26/2022] Open
Abstract
Continued advances in neuroimaging technologies and statistical modelling capabilities have improved our knowledge of structural brain development in children and adolescents. While this has provided an increasingly nuanced understanding of brain development, the field is still plagued by inconsistent findings. This review highlights the methodological diversity in existing longitudinal magnetic resonance imaging (MRI) studies on structural brain development during childhood and adolescence, and addresses how such variation might contribute to inconsistencies in the literature. We discuss the impact of method choices at multiple decision points across the research process, from study design and sample selection, to image processing and statistical analysis. We also highlight the extent to which different methodological considerations have been empirically examined, drawing attention to specific areas that would benefit from future investigation. Where appropriate, we recommend certain best practices that would be beneficial for the field to adopt, including greater completeness and transparency in reporting methods, in order to ultimately develop an accurate and detailed understanding of normative child and adolescent brain development.
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Affiliation(s)
| | | | | | | | - Sarah Whittle
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne and Melbourne Health, Melbourne, Australia; Melbourne School of Psychological Sciences, The University of Melbourne, Melbourne, Australia
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Alexander-Bloch A, Clasen L, Stockman M, Ronan L, Lalonde F, Giedd J, Raznahan A. Subtle in-scanner motion biases automated measurement of brain anatomy from in vivo MRI. Hum Brain Mapp 2016; 37:2385-97. [PMID: 27004471 DOI: 10.1002/hbm.23180] [Citation(s) in RCA: 103] [Impact Index Per Article: 12.9] [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: 04/13/2015] [Revised: 02/29/2016] [Accepted: 03/01/2016] [Indexed: 11/07/2022] Open
Abstract
While the potential for small amounts of motion in functional magnetic resonance imaging (fMRI) scans to bias the results of functional neuroimaging studies is well appreciated, the impact of in-scanner motion on morphological analysis of structural MRI is relatively under-studied. Even among "good quality" structural scans, there may be systematic effects of motion on measures of brain morphometry. In the present study, the subjects' tendency to move during fMRI scans, acquired in the same scanning sessions as their structural scans, yielded a reliable, continuous estimate of in-scanner motion. Using this approach within a sample of 127 children, adolescents, and young adults, significant relationships were found between this measure and estimates of cortical gray matter volume and mean curvature, as well as trend-level relationships with cortical thickness. Specifically, cortical volume and thickness decreased with greater motion, and mean curvature increased. These effects of subtle motion were anatomically heterogeneous, were present across different automated imaging pipelines, showed convergent validity with effects of frank motion assessed in a separate sample of 274 scans, and could be demonstrated in both pediatric and adult populations. Thus, using different motion assays in two large non-overlapping sets of structural MRI scans, convergent evidence showed that in-scanner motion-even at levels which do not manifest in visible motion artifact-can lead to systematic and regionally specific biases in anatomical estimation. These findings have special relevance to structural neuroimaging in developmental and clinical datasets, and inform ongoing efforts to optimize neuroanatomical analysis of existing and future structural MRI datasets in non-sedated humans. Hum Brain Mapp 37:2385-2397, 2016. © 2016 Wiley Periodicals, Inc.
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Affiliation(s)
- Aaron Alexander-Bloch
- Developmental Neurogenomics Unit, Child Psychiatry Branch, National Institute of Mental Health, Bethesda, Maryland.,Department of Psychiatry, Yale University School of Medicine, New Haven, Connecticut
| | - Liv Clasen
- Developmental Neurogenomics Unit, Child Psychiatry Branch, National Institute of Mental Health, Bethesda, Maryland
| | - Michael Stockman
- Developmental Neurogenomics Unit, Child Psychiatry Branch, National Institute of Mental Health, Bethesda, Maryland
| | - Lisa Ronan
- Brain Mapping Unit, University of Cambridge, Cambridge, United Kingdom
| | - Francois Lalonde
- Developmental Neurogenomics Unit, Child Psychiatry Branch, National Institute of Mental Health, Bethesda, Maryland
| | - Jay Giedd
- Department of Psychiatry, UCSD, San Diego, California
| | - Armin Raznahan
- Developmental Neurogenomics Unit, Child Psychiatry Branch, National Institute of Mental Health, Bethesda, Maryland
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Giedd JN, Raznahan A, Alexander-Bloch A, Schmitt E, Gogtay N, Rapoport JL. Child psychiatry branch of the National Institute of Mental Health longitudinal structural magnetic resonance imaging study of human brain development. Neuropsychopharmacology 2015; 40:43-9. [PMID: 25195638 PMCID: PMC4262916 DOI: 10.1038/npp.2014.236] [Citation(s) in RCA: 188] [Impact Index Per Article: 20.9] [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: 05/01/2014] [Revised: 08/14/2014] [Accepted: 08/22/2014] [Indexed: 12/17/2022]
Abstract
The advent of magnetic resonance imaging, which safely allows in vivo quantification of anatomical and physiological features of the brain, has revolutionized pediatric neuroscience. Longitudinal studies are useful for the characterization of developmental trajectories (ie, changes in imaging measures by age). Developmental trajectories (as opposed to static measures) have proven to have greater power in discriminating healthy from clinical groups and in predicting cognitive/behavioral measures, such as IQ. Here we summarize results from an ongoing longitudinal pediatric neuroimaging study that has been conducted at the Child Psychiatry Branch of the National Institute of Mental Health since 1989. Developmental trajectories of structural MRI brain measures from healthy youth are compared and contrasted with trajectories in attention-deficit/hyperactivity disorder (ADHD) and childhood-onset schizophrenia. Across ages 5-25 years, in both healthy and clinical populations, white matter volumes increase and gray matter volumes follow an inverted U trajectory, with peak size occurring at different times in different regions. At a group level, differences related to psychopathology are seen for gray and white matter volumes, rates of change, and for interconnectedness among disparate brain regions.
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Affiliation(s)
- Jay N Giedd
- Child Psychiatry Branch, NIMH, National Institutes of Mental Health, Bethesda, MD, USA,Child Psychiatry Branch, NIMH, National Institutes of Mental Health, 10 Center Drive, MSC 1367, Building 10, Room 4C110, Bethesda, MD 20892, USA, Tel: +1 301 435 4517, Fax: +1 301 480 8898, E-mail:
| | - Armin Raznahan
- Child Psychiatry Branch, NIMH, National Institutes of Mental Health, Bethesda, MD, USA
| | - Aaron Alexander-Bloch
- Child Psychiatry Branch, NIMH, National Institutes of Mental Health, Bethesda, MD, USA
| | - Eric Schmitt
- Child Psychiatry Branch, NIMH, National Institutes of Mental Health, Bethesda, MD, USA
| | - Nitin Gogtay
- Child Psychiatry Branch, NIMH, National Institutes of Mental Health, Bethesda, MD, USA
| | - Judith L Rapoport
- Child Psychiatry Branch, NIMH, National Institutes of Mental Health, Bethesda, MD, USA
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Vértes PE, Alexander-Bloch A, Bullmore ET. Generative models of rich clubs in Hebbian neuronal networks and large-scale human brain networks. Philos Trans R Soc Lond B Biol Sci 2014; 369:20130531. [PMID: 25180309 PMCID: PMC4150306 DOI: 10.1098/rstb.2013.0531] [Citation(s) in RCA: 35] [Impact Index Per Article: 3.5] [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] [Indexed: 12/13/2022] Open
Abstract
Rich clubs arise when nodes that are 'rich' in connections also form an elite, densely connected 'club'. In brain networks, rich clubs incur high physical connection costs but also appear to be especially valuable to brain function. However, little is known about the selection pressures that drive their formation. Here, we take two complementary approaches to this question: firstly we show, using generative modelling, that the emergence of rich clubs in large-scale human brain networks can be driven by an economic trade-off between connection costs and a second, competing topological term. Secondly we show, using simulated neural networks, that Hebbian learning rules also drive the emergence of rich clubs at the microscopic level, and that the prominence of these features increases with learning time. These results suggest that Hebbian learning may provide a neuronal mechanism for the selection of complex features such as rich clubs. The neural networks that we investigate are explicitly Hebbian, and we argue that the topological term in our model of large-scale brain connectivity may represent an analogous connection rule. This putative link between learning and rich clubs is also consistent with predictions that integrative aspects of brain network organization are especially important for adaptive behaviour.
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Affiliation(s)
- Petra E Vértes
- Behavioural and Clinical Neuroscience Institute, Department of Psychiatry, University of Cambridge, Cambridge, UK
| | - Aaron Alexander-Bloch
- Behavioural and Clinical Neuroscience Institute, Department of Psychiatry, University of Cambridge, Cambridge, UK Child Psychiatry Branch, National Institute of Mental Health, Bethesda, MD, USA David Geffen School of Medicine at UCLA, Los Angeles, CA, USA
| | - Edward T Bullmore
- Behavioural and Clinical Neuroscience Institute, Department of Psychiatry, University of Cambridge, Cambridge, UK Cambridgeshire and Peterborough NHS Foundation Trust, Cambridge, UK GlaxoSmithKline, Immuno Psychiatry, Alternative Discovery and Development, Stevenage, UK
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34
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Ronan L, Voets N, Rua C, Alexander-Bloch A, Hough M, Mackay C, Crow TJ, James A, Giedd JN, Fletcher PC. Differential tangential expansion as a mechanism for cortical gyrification. Cereb Cortex 2014; 24:2219-28. [PMID: 23542881 PMCID: PMC4089386 DOI: 10.1093/cercor/bht082] [Citation(s) in RCA: 104] [Impact Index Per Article: 10.4] [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] [Indexed: 02/02/2023] Open
Abstract
Gyrification, the developmental buckling of the cortex, is not a random process-the forces that mediate expansion do so in such a way as to generate consistent patterns of folds across individuals and even species. Although the origin of these forces is unknown, some theories have suggested that they may be related to external cortical factors such as axonal tension. Here, we investigate an alternative hypothesis, namely, whether the differential tangential expansion of the cortex alone can account for the degree and pattern-specificity of gyrification. Using intrinsic curvature as a measure of differential expansion, we initially explored whether this parameter and the local gyrification index (used to quantify the degree of gyrification) varied in a regional-specific pattern across the cortical surface in a manner that was replicable across independent datasets of neurotypicals. Having confirmed this consistency, we further demonstrated that within each dataset, the degree of intrinsic curvature of the cortex was predictive of the degree of cortical folding at a global and regional level. We conclude that differential expansion is a plausible primary mechanism for gyrification, and propose that this perspective offers a compelling mechanistic account of the co-localization of cytoarchitecture and cortical folds.
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Affiliation(s)
- Lisa Ronan
- Brain Mapping Unit, Department of Psychiatry, University of Cambridge, Cambridge CB2 3EB, UK,,Address correspondence to Dr Lisa Ronan, Brain Mapping Unit, University of Cambridge, Sir William Hardy Building, Downing Site, Downing Street, Cambridge CB2 3EB, UK.
| | - Natalie Voets
- FMRIB Centre, Nuffield Department of Clinical Neurosciences, University of Oxford, OX3 9DU, UK
| | - Catarina Rua
- Brain Mapping Unit, Department of Psychiatry, University of Cambridge, Cambridge CB2 3EB, UK,
| | - Aaron Alexander-Bloch
- Brain Mapping Unit, Department of Psychiatry, University of Cambridge, Cambridge CB2 3EB, UK,,Child Psychiatry Branch, NIH, Bethesda MD, 20892, USA
| | - Morgan Hough
- FMRIB Centre, Nuffield Department of Clinical Neurosciences, University of Oxford, OX3 9DU, UK
| | - Clare Mackay
- FMRIB Centre, Nuffield Department of Clinical Neurosciences, University of Oxford, OX3 9DU, UK
| | - Tim J. Crow
- SANE POWIC, Department of Psychiatry, Warneford Hospital, University of Oxford, OX3 7JX
| | - Anthony James
- Highfield Adolescent Unit, Warneford Hospital, Oxford OX3 7JX, UK and
| | - Jay N. Giedd
- Child Psychiatry Branch, NIH, Bethesda MD, 20892, USA
| | - Paul C. Fletcher
- Brain Mapping Unit, Department of Psychiatry, University of Cambridge, Cambridge CB2 3EB, UK,
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Abstract
Brain structure varies between people in a markedly organized fashion. Communities of brain regions co-vary in their morphological properties. For example, cortical thickness in one region influences the thickness of structurally and functionally connected regions. Such networks of structural co-variance partially recapitulate the functional networks of healthy individuals and the foci of grey matter loss in neurodegenerative disease. This architecture is genetically heritable, is associated with behavioural and cognitive abilities and is changed systematically across the lifespan. The biological meaning of this structural co-variance remains controversial, but it appears to reflect developmental coordination or synchronized maturation between areas of the brain. This Review discusses the state of current research into brain structural co-variance, its underlying mechanisms and its potential value in the understanding of various neurological and psychiatric conditions.
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Affiliation(s)
- Aaron Alexander-Bloch
- Child Psychiatry Branch, National Institute of Mental Health, Bethesda, Maryland 20892, USA.
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Alexander-Bloch A, Raznahan A, Bullmore E, Giedd J. The convergence of maturational change and structural covariance in human cortical networks. J Neurosci 2013; 33:2889-99. [PMID: 23407947 PMCID: PMC3711653 DOI: 10.1523/jneurosci.3554-12.2013] [Citation(s) in RCA: 333] [Impact Index Per Article: 30.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/25/2012] [Revised: 10/06/2012] [Accepted: 12/12/2012] [Indexed: 01/14/2023] Open
Abstract
Large-scale covariance of cortical thickness or volume in distributed brain regions has been consistently reported by human neuroimaging studies. The mechanism of this population covariance of regional cortical anatomy has been hypothetically related to synchronized maturational changes in anatomically connected neuronal populations. Brain regions that grow together, i.e., increase or decrease in volume at the same rate over the course of years in the same individual, are thus expected to demonstrate strong structural covariance or anatomical connectivity across individuals. To test this prediction, we used a structural MRI dataset on healthy young people (N = 108; aged 9-22 years at enrollment), comprising 3-6 longitudinal scans on each participant over 6-12 years of follow-up. At each of 360 regional nodes, and for each participant, we estimated the following: (1) the cortical thickness in the median scan and (2) the linear rate of change in cortical thickness over years of serial scanning. We constructed structural and maturational association matrices and networks from these measurements. Both structural and maturational networks shared similar global and nodal topological properties, as well as mesoscopic features including a modular community structure, a relatively small number of highly connected hub regions, and a bias toward short distance connections. Using resting-state functional magnetic resonance imaging data on a subset of the sample (N = 32), we also demonstrated that functional connectivity and network organization was somewhat predictable by structural/maturational networks but demonstrated a stronger bias toward short distance connections and greater topological segregation. Brain structural covariance networks are likely to reflect synchronized developmental change in distributed cortical regions.
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Affiliation(s)
- Aaron Alexander-Bloch
- Behavioural and Clinical Neuroscience Institute, Department of Psychiatry, University of Cambridge, Cambridge CB2 3EB, United Kingdom
- Child Psychiatry Branch, National Institute of Mental Health, Bethesda, Maryland 20892
- David Geffen School of Medicine at University of California, Los Angeles, Los Angeles, California 90024
| | - Armin Raznahan
- Child Psychiatry Branch, National Institute of Mental Health, Bethesda, Maryland 20892
| | - Ed Bullmore
- Behavioural and Clinical Neuroscience Institute, Department of Psychiatry, University of Cambridge, Cambridge CB2 3EB, United Kingdom
- GlaxoSmithKline, Clinical Unit Cambridge, Addenbrooke's Hospital, Cambridge CB2 2GG, United Kingdom, and
- Cambridgeshire and Peterborough NHS Foundation Trust, Cambridge CB21 5EF, United Kingdom
| | - Jay Giedd
- Child Psychiatry Branch, National Institute of Mental Health, Bethesda, Maryland 20892
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Alexander-Bloch A, Lambiotte R, Roberts B, Giedd J, Gogtay N, Bullmore E. The discovery of population differences in network community structure: new methods and applications to brain functional networks in schizophrenia. Neuroimage 2012; 59:3889-900. [PMID: 22119652 PMCID: PMC3478383 DOI: 10.1016/j.neuroimage.2011.11.035] [Citation(s) in RCA: 131] [Impact Index Per Article: 10.9] [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: 08/22/2011] [Revised: 10/27/2011] [Accepted: 11/08/2011] [Indexed: 02/02/2023] Open
Abstract
The modular organization of the brain network can vary in two fundamental ways. The amount of inter- versus intra-modular connections between network nodes can be altered, or the community structure itself can be perturbed, in terms of which nodes belong to which modules (or communities). Alterations have previously been reported in modularity, which is a function of the proportion of intra-modular edges over all modules in the network. For example, we have reported that modularity is decreased in functional brain networks in schizophrenia: There are proportionally more inter-modular edges and fewer intra-modular edges. However, despite numerous and increasing studies of brain modular organization, it is not known how to test for differences in the community structure, i.e., the assignment of regional nodes to specific modules. Here, we introduce a method based on the normalized mutual information between pairs of modular networks to show that the community structure of the brain network is significantly altered in schizophrenia, using resting-state fMRI in 19 participants with childhood-onset schizophrenia and 20 healthy participants. We also develop tools to show which specific nodes (or brain regions) have significantly different modular communities between groups, a subset that includes right insular and perisylvian cortical regions. The methods that we propose are broadly applicable to other experimental contexts, both in neuroimaging and other areas of network science.
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Affiliation(s)
- Aaron Alexander-Bloch
- Behavioural & Clinical Neuroscience Institute, Department of Psychiatry, University of Cambridge, Cambridge, UK.
| | | | - Ben Roberts
- Statistical Laboratory, University of Cambridge, Cambridge UK
| | - Jay Giedd
- Child Psychiatry Branch, National Institute of Mental Health, Bethesda, MD, USA
| | - Nitin Gogtay
- Child Psychiatry Branch, National Institute of Mental Health, Bethesda, MD, USA
| | - Ed Bullmore
- Behavioural & Clinical Neuroscience Institute, Department of Psychiatry, University of Cambridge, Cambridge UK,Corresponding authors at: Herchel Smith Building for Brain and Mind Sciences, Cambridge Biomedical Campus, Cambridge CB2 0SZ, UK. Fax: +44 1223 336581
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38
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Alexander-Bloch A, Lambiotte R, Roberts B, Giedd J, Gogtay N, Bullmore E. The discovery of population differences in network community structure: new methods and applications to brain functional networks in schizophrenia. Neuroimage 2011. [PMID: 22119652 DOI: 10.1016/jneuroimage.2011.11.035] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/08/2023] Open
Abstract
The modular organization of the brain network can vary in two fundamental ways. The amount of inter- versus intra-modular connections between network nodes can be altered, or the community structure itself can be perturbed, in terms of which nodes belong to which modules (or communities). Alterations have previously been reported in modularity, which is a function of the proportion of intra-modular edges over all modules in the network. For example, we have reported that modularity is decreased in functional brain networks in schizophrenia: There are proportionally more inter-modular edges and fewer intra-modular edges. However, despite numerous and increasing studies of brain modular organization, it is not known how to test for differences in the community structure, i.e., the assignment of regional nodes to specific modules. Here, we introduce a method based on the normalized mutual information between pairs of modular networks to show that the community structure of the brain network is significantly altered in schizophrenia, using resting-state fMRI in 19 participants with childhood-onset schizophrenia and 20 healthy participants. We also develop tools to show which specific nodes (or brain regions) have significantly different modular communities between groups, a subset that includes right insular and perisylvian cortical regions. The methods that we propose are broadly applicable to other experimental contexts, both in neuroimaging and other areas of network science.
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Affiliation(s)
- Aaron Alexander-Bloch
- Behavioural & Clinical Neuroscience Institute, Department of Psychiatry, University of Cambridge, Cambridge, UK.
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